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In this episode of The Reformed Brotherhood, Tony and Jesse continue their deep dive into the Parable of the Prodigal Son by examining the often-overlooked character of the elder brother. While the younger son's rebellion is obvious, the elder brother's self-righteous moralism represents a more subtle—and perhaps more dangerous—form of lostness. Through careful exegesis of Luke 15:25-32, the hosts explore how religious performance, resentment of grace, and merit-based thinking can keep us far from the Father's heart even while we remain close to the Father's house. This conversation challenges listeners to examine their own hearts for traces of elder brother theology and calls us to celebrate the scandalous grace that restores sinners to sonship. Key Takeaways Two ways to be lost: The parable presents both flagrant rebellion (the younger son) and respectable self-righteousness (the elder son) as forms of spiritual lostness that require God's grace. The elder brother's geographic and spiritual position: Though physically near the house and faithful in service, the elder brother was spiritually distant from the father's heart, unable to celebrate grace extended to others. Moralism as a subtle distance: Self-righteous religion can be more deceptive than open rebellion because it appears virtuous while actually rejecting the father's character and values. The father pursues both sons: God's gracious pursuit extends not only to the openly rebellious but also to the self-righteous, demonstrating that election and grace are sovereign gifts, not earned rewards. The unresolved ending: The parable intentionally leaves the elder brother's response unstated, creating narrative tension that challenges the original audience (Pharisees and scribes) and modern readers to examine their own response to grace. Adoption as the frame of obedience: True Christian obedience flows from sonship and inheritance ("all that I have is yours"), not from a wage-earning, transactional relationship with God. Resentment reveals our theology: When we find ourselves unable to celebrate the restoration of repentant sinners, we expose our own need for repentance—not from scandal, but from envy and pride. Key Concepts The Elder Brother's Subtle Lostness The genius of Jesus' parable is that it exposes a form of lostness that religious people rarely recognize in themselves. The elder brother never left home, never squandered his inheritance, and never violated explicit commands. Yet his response to his brother's restoration reveals a heart fundamentally opposed to the father's character. His complaint—"I have served you all these years and never disobeyed your command"—demonstrates that he viewed his relationship with the father transactionally, as an employer-employee arrangement rather than a father-son bond. This is the essence of legalism: performing religious duties while remaining distant from God's heart. The tragedy is that the elder brother stood within reach of everything the father had to offer yet experienced none of the joy, fellowship, or security of sonship. This form of lostness is particularly dangerous because it wears the mask of righteousness and often goes undetected until grace is extended to someone we deem less deserving. The Father's Gracious Pursuit of the Self-Righteous Just as the father ran to meet the returning younger son, he also went out to plead with the elder brother to come into the feast. This detail is theologically significant: God pursues both the openly rebellious and the self-righteous with the same gracious initiative. The father's response to the elder brother's complaint is not harsh correction but tender invitation: "Son, you are always with me, and all that is mine is yours." This reveals that the problem was never scarcity or the father's favoritism—the elder brother had always possessed full access to the father's resources and affection. The barrier was entirely on the son's side: his inability to receive sonship as a gift rather than a wage. This mirrors the historical situation of the Pharisees and scribes who grumbled at Jesus for receiving sinners. They stood adjacent to the kingdom, surrounded by the promises and covenant blessings of God, yet remained outside because they could not accept grace as the principle of God's dealing with humanity. The invitation still stood, but it required them to abandon their merit-based system and enter the feast as recipients of unearned favor. The Unresolved Ending and Its Challenge to Us Luke deliberately leaves the parable unfinished—we never learn whether the elder brother eventually joined the celebration. This narrative technique places the reader in the position of the elder brother, forcing us to answer for ourselves: will we enter the feast or remain outside in bitter resentment? For the original audience of Pharisees and scribes, this unresolved ending was a direct challenge to their response to Jesus' ministry. Would they continue to grumble at God's grace toward tax collectors and sinners, or would they recognize their own need and join the celebration? For contemporary readers, the question remains equally pressing. When we hear of a notorious sinner coming to faith, do we genuinely rejoice, or do we scrutinize their repentance with suspicion? When churches extend membership to those with broken pasts, do we celebrate restoration or quietly question whether they deserve a place at the table? The parable's open ending is not a literary flaw but a pastoral strategy: it refuses to let us remain passive observers and demands that we examine whether we harbor elder brother theology in our own hearts. Memorable Quotes The father's household is a place where grace produces joy, not just merely relief. The elder brother hears the joy before he sees it. That's often how resentment works, isn't it? We're alerted to the happiness of others and somehow there's this visceral response of wanting to be resentful toward that joy, toward that unmerited favor. — Jesse Schwamb There is a way to be near the house, church adjacent, religiously active, yet to be really far from the father's heart. The elder brother is not portrayed as an atheist, but as a moralist. And moralism can be a more subtle distance than open rebellion. — Jesse Schwamb God doesn't keep sinners from repenting. The reprobate are not prohibited or prevented by God from coming to faith. They're being kept out by their own stubborn refusal to come in. That's where this punchline hits so hard. — Tony Arsenal Full Transcript [00:00:44] Jesse Schwamb: Welcome to episode 477 of The Reformed Brotherhood. I'm Jesse.  [00:00:51] Tony Arsenal: And I'm Tony. And this is the podcast with ears to hear. Hey brother.  [00:00:55] Jesse Schwamb: Hey brother.  [00:00:56] Parables and God's Word [00:00:56] Jesse Schwamb: Speaking of ears to hear, it struck me that this whole thing we've been doing all this parable talk is really after the manner of God's words. And one of the things I've really grown to appreciate is how God speaks to the condition of those whom he addresses. He considers our ability, our capacity as his hearers to process what he's saying, and that leads into these amazing parables that we've been talking about. He doesn't speak as he is able to speak. So to speak, but I didn't mean that to happen. But as we were able to hear, and that means he spoke in these lovely parables so that we might better understand him. And today we're gonna get into some of the drama of the best, like the crown jewel as we've been saying, of maybe all the parables. The Parable of the Lost Son. We spoke a little bit about it in the last episode. Definitely want to hit that up because it's setting you up for this one, which is the definitive episode. But now we're gonna talk about this first, this younger lost son. Get into some of all of these like juicy details about what takes place, and really, again, see if we can find the heart of God. Spoiler. We can and we'll,  [00:02:04] Tony Arsenal: yeah,  [00:02:04] Affirmations and Denials [00:02:04] Jesse Schwamb: but before we do both of those things, it's of course always time at this moment to do a little affirming with or denying against. Of course, if you haven't heard us before, that's where we take a moment to say, is there something that we think is undervalued that we wanna bring forward that we'd recommend or think is awesome? Or conversely, is there something that's overvalued that's just, we're over it. The vibe is done. We're gonna deny against that. So I say to you, as I often do, Tony, are you affirming with or deny against?  [00:02:31] Tony's Nerdy Hobby: Dungeons and Dragons [00:02:31] Tony Arsenal: I'm affirming tonight. Um, I don't know how much the audience realizes of a giant ridiculous nerd I am, but we're about to go to entirely new giant nerd depths. [00:02:43] Jesse Schwamb: All right. I  [00:02:43] Tony Arsenal: think,  [00:02:44] Jesse Schwamb: let's hear it.  [00:02:44] Tony Arsenal: So, um, I was a huge fan of Stranger Things. Some, there's some issues with the show, and I understand why some people might not, um, might not feel great about watching it. You know, I think it falls within Christian liberty. But one of the main themes of the show, this is not a spoiler, you learn about this in episode one, is the whole game. The whole show frames itself around Dungeons and Dragons, right? It's kind of like a storytelling device within the show that the kids play, Dungeons and Dragons, and everything that happens in the Dungeons and Dragons game that they're playing, sort of like, um, foreshadows what's actually gonna happen in the show. Which funny if, you know Dungeons and Dragons lore, you kind of learn the entire plot of the story like ahead of time. Um, but so I, stranger Things just finished up and I've kind of been like itching to get into Dungeons and Dragons. I used to play a little bit of tabletop when I was in high school, in early college and um, I just really like the idea of sort of this collaborative storytelling game. Um, whether it's Dungeon Dragons or one of the other systems, um, Dungeons and Dragons is the most popular. It's the most well published. It's the most well established and it's probably the easiest to find a group to play with. Although it is very hard to find a group to play with, especially, uh, kind of out in the middle of nowhere where I live. So this is where the ultra super nerdy part comes in.  [00:04:02] Jesse Schwamb: Alright, here we  [00:04:03] Tony Arsenal: go. I have been painstakingly over the last week teaching Google Gemini. To be a dungeon master for me. So I've been playing Dungeons and Dragons more or less by myself with, uh, with Google Gemini, and I'm just having a lot of fun with it. Um, you can get a free copy of the rules online if you, I think it's DND, the letter NDND beyond.com. They have a full suite of like tools to create your character. Access to a basic set of the core rules. Um, you can spend a lot of money on Dungeons and Dragons, uh, and if you want to like really get into it, the books are basically textbooks. Like you're buying $300 or 300 page, $300, 300 page textbooks, um, that are not all that differently costs than like college textbooks. You'll buy a 300 page Dungeon master guide that's like $50 if you want a paper copy. So, but you can get into it for free. You can get the free rolls online, you can use their dungeon, the d and d Beyond app and do all your dice rolls for free. Um, you, you can get a free dice roller online if you don't want to do their, their app. Um, but it's just a lot of fun. I've just been having a lot of fun and I found that the, I mean. When you play a couple sessions with it, you see that the, the um, the A IDM that I've created, like it follows the same story beats 'cause it's only got so much to work with in its language model. Um, but I'm finding ways to sort of like break it out of that model by forcing it to refer to certain websites that are like Dungeons and Dragons lore websites and things like build your, build your campaign from this repository of Dungeons and Dragons stuff. So. I think you could do this with just about any sort of narrative storytelling game like this, whether you're playing a different system or d and d Pathfinders. I mean, there's all sorts of different versions of it, but it's just been a lot of fun to see, see it going. I'm trying to get a group together. 'cause I think I would, I would probably rather play Dungeons and Dragons with people, um, and rather do it in person. But it's hard to do up here. It's hard to get a, get a group going. So that's my super nerdy affirmation. I'm not just affirming Dungeons and Dragons, which would already be super nerdy. I'm affirming playing it by myself on my phone, on the bus with Google Gemini, AI acting like I'm not. Just this weird antisocial lunatic. So I'm having a lot of fun with it.  [00:06:20] Jesse Schwamb: So there are so many levels of inception there. Yeah. Like the inception and everything you just said. I love it.  [00:06:27] Tony Arsenal: Yeah. Well, what I'm learning is, um, you can give an, and, and this is something I didn't realize, what ai, I guess I probably should have, you know, it's not like an infinite thing. Um, you can give an AI instructions and if your chat gets long enough, it actually isn't referring back to the very beginning of the chat most of the time. Right. There's a, there's like a win context window of about 30 responses. So like if you tell the AI, don't roll the dice for me, like, let me roll dices that are related to my actions, eventually it will forget that. So part of what I've been doing is basically building, I'm using Google Gemini when the AI does something I don't want it to do, I say, you just did something I don't want it to do. Gimme a diagnostic report of why you did that. It will explain to me why it did what it did. Right. Why it didn't observe the rules. And then I'm feeding that into another. Prompt that is helping me generate better prompts that it refers back to. So it's kind of this weird iterative, um, yeah, I, I don't, I'm like, I maybe I'm gonna create the singularity. I'm not sure. Maybe this is gonna be possible. We should sit over the edge. It's gonna, it's gonna learn how to cast magic spells and it's gonna fire bolt us in the face or something like that. Right. But, uh, again, high risk. I, I, for one, welcome our AO AI dungeon masters. So check it out. You should try it. If you could do this with chat GPT, you could do it with any ai. Um, it, it, it is going to get a little, I have the benefit because I have a Google Workspace account. I have access to Google Pro or the Gemini Pro, which is a better model for this kind of thing. But you could do this with, with chat GPT or something like that. And it's gonna be more or less the same experience, I think. But I'm having a, I'm having a ton of fun with it. Um. Again, I, I, there's something about just this, Dungeons and Dragons at its core is a, it's like a, an exercise in joint storytelling, which is really fascinating and interesting to me. Um, and that's what most tabletop RPGs are like. I suppose you get into something like War Hammer and it's a little bit more like a board. It's a mixture of that plus a board game. But Dungeons and Dragons, the DM is creating the, I mean, not the entire world, but is creating the narrative. And then you as a player are an actor within that narrative. And then there's a certain element of chance that dice rolls play. But for the most part, um, you're driving the story along. You're telling the story together. So it's, it's pretty interesting. I've also been watching live recordings of Dungeons and Dragon Sessions on YouTube. Oh,  [00:08:50] Jesse Schwamb: wow.  [00:08:51] Tony Arsenal: Like, there's a, there's a channel called Critical Role. Like these sessions are like three and a half hours long. So, wow. I just kinda have 'em on in the background when I'm, when I'm, uh, working or if I'm, you know, doing something else. Um, but it's really interesting stuff. It's, it's pretty cool. I think it's fun. I'm a super nerd. I'm, I'm no shame in that. Um, I'm just really enjoying it.  [00:09:09] Jesse Schwamb: Listen, nerdery is great. That's like part of the zeitgeist now. Listen to culture. It's cool to be a nerd. I don't know much about d and d. I've heard a lot about this idea of this community that forms around. Yeah. The story, correct me if I'm wrong, can't these things go on for like years, decades?  [00:09:25] Tony Arsenal: Oh yeah, yeah. Like, you can do there. There, some of this has made its way into the official rule books, but basically you could do what's called a one shot, which is like a self-contained story. Usually a single session, you know, like you get a Dungeon master, game master, whichever you wanna call the person. Three to four, maybe five characters, player characters. And one session is usually about two hours long. So it's not like you sit down for 20 minutes, 30 minutes at a time and play this right. And you could do a one shot, which is a story that's designed to, to live all within that two hour session. Um, some people will do it where there isn't really any planned like, outcome of the story. The, the DM just kind of makes up things to do as they go. And then you can have campaigns, which is like, sometimes it's like a series of one shots, but more, it is more like a long term serialized period, you know, serialized campaign where you're doing many, um, many, many kinds of, uh, things all in one driving to like a big epic goal or battle at the end, right? Um, some groups stay together for a really long time and they might do multiple campaigns, so there's a lot to it. Game's been going on for like 50, 60, 70 years, something like that. I don't remember exactly when it started, but  [00:10:41] Jesse Schwamb: yeah.  [00:10:41] Tony Arsenal: Um, it's an old game. It's kinda like the doctor who of of poor games and it's like the original tabletop role playing game, I think. [00:10:47] Jesse Schwamb: Right. Yeah, that makes sense. Again, there's something really appealing to me about not just that cooperative storytelling, but cooperative gameplay. Everybody's kind of in it together for the most part. Yeah. Those conquest, as I understand them, are joint in nature. You build solidarity, but if you're meeting with people and having fun together and telling stories and interacting with one another, there's a lot of good that comes out of that stuff there. A lot of lovely common grace in those kind of building, those long-term interactions, relationships, entertainment built on being together and having good, clean, fun together.  [00:11:17] Tony Arsenal: Yeah. Well, and it's, you know, it's, um. It's an interesting exercise. It's it, in some ways it's very much like improv. Like you, you think of like an improv comedy like show I've been to somewhere. Like, you know, you go to the show and it's an improv troupe, but they're like calling people from the crowd up and asking them for like different scenarios they might do. It's kind of like that in that like the GM can plan a whole, can plan a whole thing. But if I as a player character, um. And I've done this to the virtual one just to see what it does, and it's done some interesting things. One of the campaigns I was playing, I had rescued a merchant from some giant spiders and I was helping, like, I was helping like navigate them through the woods to the next town. And we kept on getting attacked and just outta nowhere. I was like, what if I sort of act as though I'm suspicious of this merchant now because why are we getting attacked all the time? And so I, I typed in sort of like a little. A mini role play of me accusing this guy. And it was something like, Randall, we get, we're getting attacked a lot for a simple merchant, Randall merchant. What happens if I cast a tech magic? What am I gonna find? And he's like, I don't know what I'm gonna find. I know I don't know anything. And then I cast a tech magic and it shifted. I mean, I don't know where the campaign was gonna go before that, but it shifted the whole thing now where the person who gave him the package he was carrying had betrayed him. It was, so that happens in real life too in these games, real life in these games. That happens in real, in-person sessions too, where a player or a group of players may just decide instead of talking to the contact person that is supposed to give them the clue to find the dungeon they're supposed to go to, instead they ambush them and murder them in gold blood. And now the, the dungeon master has to figure out, how do I get them back to this dungeon when this is the only person that was supposed to know where it is? So it, it does end up really stretching your thinking skills and sort of your improvisational skills. There's an element of, um, you know, like chance with the dice, um, I guess like the dice falls in the lot, but the lot is in the handle. Or like, obviously that's all ordained as well too, but there is this element of chance where even the DM doesn't get to determine everything. Um, if, if I say I want to, I want to try to sneak into this room, but I'm a giant barbarian who has, you know, is wearing like chain mail, there's still a chance I could do it, but the dice roll determines that. It's not like the, the GM just says you can't do that. Um, so it's, it's a, I, I like it. I'm, I'm really looking forward to trying to, getting into it. It is hard to start a group and to get going and, um, there's a part of me that's a little bit. Gun shy of maybe like getting too invested with a group of non-Christians for something like this. 'cause it can get a little weird sometimes. But I think that, I think that'll work out. It'll be fun. I know there's actually some people in our telegram chat. Bing, bing, bing segue. There we go. There's some people in our telegram chat actually, that we're already planning to do a campaign. Um, so we might even do like a virtual reform brotherhood, Dungeons and Dragons group. So that might be a new sub channel in the telegram at some point.  [00:14:13] Jesse Schwamb: There you go. You could jump right in. Go to t.me back slash reform brotherhood.  [00:14:18] Tony Arsenal: Yeah. Jesse, what are you affirming since I just spent the last 15 minutes gushing about my nerdy hobby?  [00:14:23] Jesse Schwamb: Uh, no, that was great. Can I, can I just say two things? One is, so you're basically saying it's a bit like, like a troll shows up and everybody's like, yes. And yeah. So I love that idea. Second thing, which is follow up question, very brief. What kind of merchant was Randall.  [00:14:39] Tony Arsenal: Uh, he was a spice trader actually.  [00:14:42] Jesse Schwamb: Yeah. I don't trust that.  [00:14:43] Tony Arsenal: And, and silk, silk and spices.  [00:14:45] Jesse Schwamb: Yeah. That's double, that's too strict.  [00:14:47] Tony Arsenal: He was actually good guy in the, in the story that developed out of this campaign. He actually became part of my family and like, like, like got adopted into the family because he lost everything on his own. Randy we're  [00:15:00] Jesse Schwamb: talking about Randy.  [00:15:01] Tony Arsenal: Randy Randall with one L. Yeah. The AI was very specific about  that.  [00:15:05] Jesse Schwamb: There's, there's nothing about this guy I trust. I, is this still ongoing? Because I think he's just trying to make his way deeper in,  [00:15:11] Tony Arsenal: uh, no, no. It, I'll, I'll wait for next week to tell you how much, even more nerdy this thing gets. But there's a whole thing that ha there was a whole thing out of this That's a tease. Tease. There was a, there was a horse and the horse died and there was lots of tears and there was a wedding and a baby. It was, it's all sorts of stuff going on in this campaign. [00:15:27] Jesse Schwamb: Yeah. And I'm sure. Randy was somewhere near that horse when it happened. Right?  [00:15:32] Tony Arsenal: It was his horse.  [00:15:33] Jesse Schwamb: Yeah, exactly. That's  [00:15:35] Tony Arsenal: exactly, he didn't, he didn't kill the horse. He had no power to knock down the bridge The horse was standing on.  [00:15:40] Jesse Schwamb: Listen, next week, I'm pretty sure that's what we're gonna learn is that it was all him. [00:15:45] Tony Arsenal: Alright, Jesse, save us from this. Save us from this, please. Uh,  [00:15:49] Jesse Schwamb: no.  What  [00:15:50] Tony Arsenal: you affirming, this is  [00:15:50] Jesse Schwamb: great.  [00:15:50] Jesse's Affirmation: Church Community [00:15:50] Jesse Schwamb: It's possible that there is a crossover between yours and mine if we consider. That the church is like playing a d and d game in the dungeon Masters Christ, and the campaigns, the gospel. So I was thinking maybe is it possible, uh, maybe this is just the, the theology of the cross, but that sometimes, like you need the denial to get to the affirmation. Have we talked about that kind of truth? Yeah,  [00:16:14] Tony Arsenal: yeah,  [00:16:15] Jesse Schwamb: for sure. So here's a little bit of that. I'll be very, very brief and I'm using this not as like just one thing that happened today, but what I know is for sure happening all over the world. And I mean that very literally, not just figuratively when it comes to the body of Christ, the local church. So it snowed here overnight. This was, this is the Lord's Day. We're hanging out in the Lord's Day, which is always a beautiful day to talk about God. And overnight it snowed. The snow stopped relatively late in the morning around the time that everybody would be saying, Hey, it's time to go and worship the Lord. So for those in my area, I got up, we did the whole clearing off the Kai thing. I went to church and I was there a little bit early for a practice for music. And when I pulled in, there weren't many there yet, but the whole parking lot unplowed. So there's like three inches of snow, unplowed parking lot. So I guess the denial is like the plow people decided like, not this time I, I don't think so. They understood they were contracted with the church, but my understanding is that when one of the deacons called, they were like, Ooh, yeah, we're like 35 minutes away right now, so that's gonna be a problem. So when I pulled in, here's what I was. Like surprise to find, but in a totally unexpected way, even though I understand what a surprise is. And that is that, uh, that first the elders and the deacons, everybody was just decided we're going to shovel an entire parking lot. And at some point big, I was a little bit early there, but at some point then this massive text change just started with everybody, which was, Hey, when you come to church, bring your shovel. And I, I will tell you like when I got out of the car. I was so like somebody was immediately running to clear a path with me. One of those like snow pushers, you know what I mean? Yeah. Like one, those beastly kind of like blade things.  [00:17:57] Tony Arsenal: Those things are, those things are the best.  [00:17:59] Jesse Schwamb: Yeah. You just run. And so you have never met a group of people that was more happy to shovel an entire large asphalt area, which normally shouldn't even be required. And. It just struck me, even in hindsight now thinking about it, it was this lovely confluence of people serving each other and serving God. It was as if they got up that morning and said, do you know what would be the best thing in the world for me to do is to shovel. And so everybody was coming out. Everybody was shoveling it. It was to protect everyone and to allow one into elaborate, one access. It was just incredible. And so I started this because the affirmation is, I know this happens in, in all of our churches, every God fearing God, loving God serving church, something like this is happening, I think on almost every Lord's day or maybe every day of the week in various capacities. And I just think this is God's people coming together because everybody, I think when we sat down for the message was exhausted, but. But there was so much joy in doing this. I think what you normally would find to be a mundane and annoying task, and the fact that it wasn't just, it was redeemed as if like we, we found a greater purpose in it. But that's, everyone saw this as a way to love each other and to love God, and it became unexpected worship in the parking lot. That's really what it was, and it was fantastic. I really almost hope that we just get rid of the plow company and just do it this way from now on. Yeah, so I'm affirming, recognize people, recognize brothers and sisters that your, your church is doing this stuff all the time and, and be a part of it. Jump in with the kinda stuff because I love how it brings forward the gospel.  [00:19:35] Tony Arsenal: Yeah. Yeah. That's a great story. It's a great, uh, a great example of the body of Christ being, what the body of Christ is and just pulling together to get it done. Um, which, you know, we do on a spiritual level, I think, more often than a physical level these days. Right, right. But, um, that's great. I'm sitting here going three inches of snow. I would've just pulled into the lot and then pulled out of the lot. But New Hampshire, it hits different in New Hampshire. Like we all d have snow tires and four wheel drive.  [00:20:02] Jesse Schwamb: It's, it's enough snow where it was like pretty wet and heavy that it, if, you know, you pack that stuff down, it gets slick. You can't see the people, like you can't have your elderly people just flying in, coming in hot and then trying to get outta the vehicle, like making their way into church.  [00:20:14] Tony Arsenal: Yeah.  [00:20:15] Jesse Schwamb: So there was, there was a lot more of that. But I think again, you would, one of the options would've been like, Hey, why don't we shovel out some sp spaces for the, for those who need it, for, you know, those who need to have access in a way that's a little bit less encumbered. Oh, no, no. These people are like, I see your challenge and I am going to shovel the entire parking lots.  [00:20:35] Tony Arsenal: Yeah. Yeah. It used to happen once in a while, uh, at the last church, uh, at, um, your dad's church. We would, where the plow would just not come on a Sunday morning or, or more often than not. Um, you know, what happens a lot of times is the plows don't want to come more than once. Right. If they don't have to. Or sometimes they won't come if they think it's gonna melt because they don't want to deal with, uh, with like customers who are mad that you plowed and that it all melts. But either way, once in a while. The plow wouldn't come or it wouldn't come in time. And what we would do is instead of trying to shovel an entire driveway thing, we would just went, the first couple people who would get there, the young guys in the church, there was only a couple of us, but the younger guys in the church would just, we would just be making trips, helping people into the, yeah. Helping people into the building. So, um, it was a pretty, you know, it was a small church, so it was like six trips and we'd have everybody in, but um, we just kind of, that was the way we pulled together. Um, yeah, that's a great, it's a great story. I love, I love stuff like that. Yeah, me too. Whether it's, whether it's, you know, plowing a, a parking lot with shovels instead of a plow, or it's just watching, um, watching the tables and the chairs from the fellowship, you know, all just like disappear because everybody's just, uh, picks up after themselves and cleans and stuff. That's, that's like the most concrete example of the body of Christ doing what the body of Christ does. Um, it's always nice, you know, we always hear jokes about like, who can carry the most, the most chairs,  [00:22:04] Jesse Schwamb: most  [00:22:04] Tony Arsenal: chairs. Uh, I think it's true. Like a lot of times I think like I could do like seven or eight sometimes. [00:22:10] Jesse Schwamb: Uh, you, that's, so, one more thing I wanna say. I, I wanted to tell you this privately, Tony, 'cause it just cracked me up 'cause I, you'll appreciate this. But now I'm realizing I think the brothers and sisters who listened to us talk for any length of time and in the context of this conversation, but the church will appreciate this too. On my way out, I, I happened because I was there early and the snow was crazy. I parked way further out, way on the edge of the lot to just allow for greater access because of all the shoveling that was happening. And by the way, I really hope there were a ton of visitors this morning because they were like, wow, this, this church is wild. They love to shovel their own lot and they're the happiest people doing it. Some sweaty person just ushered me in while they were casting snow. Like,  [00:22:47] Tony Arsenal: is this some new version of snake handling? You shovel your own lot and your impervious to back injuries.  [00:22:53] Jesse Schwamb: Uh. So I was walking out and as I walked past, uh, there was a, uh, two young gentlemen who were congregating by this very large lifted pickup truck, which I don't have much experience with, but it looked super cool and it was started, it was warming up, and they were just like casually, like in the way that only like people with large beards wearing flannel and Carhartt kind of do, like casually leaning against the truck, talking in a way that you're like, wow, these guys are rugged. And they sound, they're super cool, and they're probably like in their twenties. And all I hear as I pass by is one guy going, yeah, well, I mean that's, I was, I said to them too, but I said, listen, I'd rather go to a church with God-fearing women than anywhere else.  [00:23:36] Tony Arsenal: Nice.  [00:23:37] Jesse Schwamb: I was just like, yep. On the prowl and I love it. And they're not wrong. This is the place to be.  [00:23:42] Tony Arsenal: It is.  [00:23:43] Jesse Schwamb: Yeah. This is the place to be. Yeah. So all kinds of, all kinds of good things I think going on in that in the house of the Lord and where wherever you're at, I would say be happy and be joyful and look for those things and participate in, like you said, whether it's physical or not, but as soon as you said like the, our young men, our youth somehow have this competition of when we need to like pack up the sanctuary. How many chairs can I take at one time? Yeah. It's like the classic and it just happens. Nobody says like, okay, everybody line up. We're about to embark on the competition now. Like the strong man usher competition. It's just like, it just happens and  [00:24:17] Tony Arsenal: it's  [00:24:17] Jesse Schwamb: incredible.  [00:24:18] Tony Arsenal: I mean, peacocks fan out their tail feathers. Young Christian guys fan out. All of the table chairs, chairs they can carry. It's uh, it's a real phenomena. So I feel like if you watch after a men's gathering, everybody is like carrying one chair at a time because they don't wanna hurt their backs and their arms. Oh, that's  [00:24:36] Jesse Schwamb: true. That's  [00:24:37] Tony Arsenal: what I do. Yeah. But it's when the women are around, that's when you see guys carrying like 19 chairs. Yeah. Putting themselves in the hospital.  [00:24:42] Jesse Schwamb: That's what I, listen, it comes for all of us. Like I, you know, I'm certainly not young anymore by almost any definition, but even when I'm in the mix, I'm like, oh, I see you guys. You wanna play this game? Mm-hmm. Let's do this. And then, you know, I'm stacking chairs until I hurt myself. So it's great. That's, that is what we do for each other. It's  [00:25:01] Tony Arsenal: just, I hurt my neck getting outta bed the other day. So it happens. It's real.  [00:25:05] Jesse Schwamb: The struggle. Yeah, the struggle is real.  [00:25:07] The Parable of the Lost Son [00:25:07] Jesse Schwamb: Speaking of struggle, speaking of family issues, speaking of all kinds of drama, let's get into Luke 15 and let me read just, I would say the first part of this parable, which as we've agreed to talk about, if we can even get this far, it's just the younger son. [00:25:24] Tony Arsenal: Yeah.  [00:25:25] Jesse Schwamb: And again, don't worry, we're gonna get to all of it, but let me read beginning in, uh, verse 11 here. This is Luke chapter 15. Come follow along as you will accept if you're operating heavy machinery. And Jesus said, A man had two sons and the younger of them said to his father, father, give me the share of the estate that falls to me. So he divided his wealth between them. And not many days later, the younger son gathered everything together and went on a journey into a distant country. And there he squandered his estate living recklessly. Now, when he had spent everything, a severe famine occurred in that country and it began to be impoverished. So he went and hired himself to one of the citizens of that country, and he sent him into his fields to feed swine. So he went and as he was desiring to be fed with the pods that the swine were eating because no one was giving anything to him. But when he came to himself, he said, how many of my father's men have more than enough bread, but I am dying here with hunger. I'll rise up and go to my father, and I'll say to him, father, I have sinned against heaven and before you, I'm no longer worthy to be called your son. Make me as one of your hired men. So he rose up, came to his father, but while he was still a long way off. His father saw him and felt compassion and ran and embraced him. And the son said to him, father, I've sinned against heaven and before you, I'm no longer worthy to be called your son. But the father said to his slaves, quickly, bring out the best robe and put it on him, and put a ring on his hand and sandals on his feet and bring the fat in calf and slaughter it and let us celebrate. For the son of mine was dead and has come to life again. He was lost and he has been found and they began to celebrate.  [00:27:09] Tony Arsenal: Yeah. Yeah. This is such a, um, such a, I don't know, like pivotal seminal parable in the Ministry of Christ. Um, it's one of those parables and we, we mentioned this briefly last week that even most. It, it hasn't passed out of the cultural zeitgeist yet. A lot of biblical teaching has, I mean, a lot, I think a lot of things that used to be common knowledge where, where you could make a reference to something in the Bible and people would just get it. Um, even if they weren't Christian or weren't believers, they would still know what you were talking about. There's a lot of things in the Bible that have passed out of that cultural memory. The, the parable of the prodigal son, lost son, however you wanna phrase it, um, that's not one of them. Right. So I think it's really important for us, um, and especially since it is such a beautiful picture of the gospel and it has so many different theological touch points, it's really incumbent on us to spend time thinking about this because I would be willing to bet that if you weave. Elements of this parable into your conversations with nonbelievers that you are praying for and, and, you know, witnessing to and sharing the gospel with, if you weave this in there, you're gonna help like plant some seeds that when it comes time to try to harvest, are gonna pay dividends. Right. So I think it's a really, it's a really great thing that we're gonna be able to spend, you know, a couple weeks really just digging into this. [00:28:40] Jesse Schwamb: Yeah, and to define the beginning, maybe from the end, just slightly here, I like what you said about this cultural acknowledgement of this. I think one of the correctives we can provide, which is clear in the story, is in the general cultural sense. We speak of this prodigal as something that just returns comes back, was lost, but now is found. And often maybe there is this component of, in the familial relationship, it's as if they've been restored. Here we're gonna of course find that this coming to one senses is in fact the work of God. That there is, again, a little bit of denial that has to bring forward the affirmation here that is the return. And so again, from the beginning here, we're just talking about the younger son. We have more than youthful ambition.  [00:29:19] The Essence of Idolatry and Sin [00:29:19] Jesse Schwamb: This heart of, give me the stuff now, like so many have said before, is really to say. Give me the gifts and not you, which is, I think, a common fault of all Christians. We think, for instance of heaven, and we think of all the blessings that come with it, but not necessarily of the joy of just being with our savior, being with Christ. And I think there's something here right from the beginning, there's a little bit of this betrayal in showing idolatry, the ugliness of treating God's gifts as if there's something owed. And then this idea that of course. He receives these things and imme more or less immediately sometime after he goes and takes these things and squanderers them. And sin and idolatry, I think tends to accelerate in this way. The distance from the father becomes distance from wisdom. We are pulled away from that, which is good. The father here being in his presence and being under his care and his wisdom and in his fear of influence and concern, desiring then to say, I don't want you just give me the gifts that you allegedly owe me. And then you see how quickly like sin does everything you, we always say like, sin always costs more than you want to pay. And it always takes you further than you want to go. And that's exactly what we see here. Like encapsulated in an actual story of relationship and distance.  [00:30:33] Tony Arsenal: Yeah. Yeah. And I, you know, I think, um. It's interesting to me.  [00:30:39] The Greek Words for Property [00:30:39] Tony Arsenal: You know, I, I, I'm a big fan of saying you don't need to study Greek to understand your Bible, but I'm also a big fan of saying understanding a little bit of Greek is really helpful. And one of the things that I think is really intriguing, and I haven't quite parsed out exactly what I think this means, but the word property in this parable, it actually is two different Greek words that is translated as property, at least in the ESV. And neither one of them really fit. What our normal understanding of property would be. And there are Greek words that refer to like all of your material possessions, but it says, father, give me the share of property. And he uses the word usia, which those of us who have heard anything about the trinity, which is all of us, um, know that that word means something about existence. It's the core essence of a person. So it says, father, give me the share of usia that is coming to me. And then it says, and he divided his bias, his, his life between them. Then it says, not many days later, the younger son gathered all that he had took a journey into the far country. There he squandered his usia again. So this, this parable, Christ is not using the ordinary words to refer to material, uh, material accumulation and property like. I think probably, you know, Christ isn't like randomly using these words. So there probably is an element that these were somehow figuratively used of one's life possessions. But the fact that he's using them in these particular ways, I think is significant. [00:32:10] The Prodigal Son's Misconception [00:32:10] Tony Arsenal: And so the, the, the younger son here, and I don't even like calling this the prodigal sun parable because the word prodigal doesn't like the equivalent word in Greek doesn't appear in this passage. And prodigal doesn't mean like the lost in returned, like prodigal is a word that means like the one who spends lavishly, right? So we call him the prodigal son because he went and he squandered all of his stuff and he spent all of his money. So it doesn't even really describe the main feature or the main point of why this, this parable is here. It's just sort of like a random adjective that gets attached to it. But all of that aside, um. This parable starts off not just about wasting our property, like wasting our things, but it's a parable that even within the very embedded language of the parable itself is talking about squandering our very life, our very essence, our very existence is squandered and wasted as we depart from the Father. Right? And this is so like, um, it's almost so on the head, on the on the nose that it's almost a little like, really Jesus. Like this is, this is so like, slap you in the face kind of stuff. This is right outta like Romans, uh, Romans one, like they did not give thanks to God. They did not show gratitude to God or acknowledge him as God. This is what's happening in this parable. The son doesn't go to his father and say, father, I love you. I'm so happy to stay with you. I'm so happy to be here. He, he basically says like. Give me your very life essence, and I'm gonna go, I'm gonna go spend it on prostitutes. I'm gonna go waste your life, father, I'm gonna waste your life, your existence, your bias. I'm gonna go take that and I'm gonna squander it on reckless living. And I guess we don't know for sure. He, it doesn't say he spends it on prostitutes. That's something his brother says later and assumes he did. So I, I don't know that we do that. But either way, I'm gonna take what's yours, your very life, your very essence. And also that my life, my essence, the gift you've given me as my father, you've given me my life. In addition now to your life or a portion of your life. And I'm gonna go squander that on reckless living, right? Like, how much of a picture of sin is that, that we, we take what we've been given by God, our very life, our very essence, we owe him everything, and we squander that on sinful, reckless living. That that's just a slap in the face in the best way right out of the gate here.  [00:34:28] Jesse Schwamb: Yes, that, that's a great point because it's, it would be one thing to rebel over disobedience, another thing to use the very life essence that you've been given for destructive, self-destructive purposes. And then to use that very energy, which is not yours to begin with, but has been imbued in yours, external, all of these things. And then to use that very thing as the force of your rebellion. So it's double insult all the way around. I'm with you in the use of Greek there. Thank you. Locus Bio software. Not a sponsor of the podcast, but could be. And I think that's why sometimes in translations you get the word like a state because it's like the closest thing we can have to understanding that it's property earned through someone's life more or less. Yeah. And then is passed down, but as representative, not just of like, here's like 20 bucks of cash, but something that I spent all of me trying to earn and. And to your point, also emphasizing in the same way that this son felt it was owed him. So it's like really bad all around and I think we would really be doing ourselves a disservice if we didn't think that there's like a little bit of Paul washer saying in this, like I'm talking about you though. So like just be like, look at how disrespectful the sun is. Yeah. Haven't we all done this? To God and bringing up the idea of prodigal being, so that, that is like the amazing juxtaposition, isn't it? Like Prodigal is, is spent recklessly, parsimonious would be like to, to save recklessly, so to speak. And then you have the love the father demonstrates coming against all of that in the same way with like a totally different kind of force. So.  [00:36:02] The Famine and Realization [00:36:02] Jesse Schwamb: What I find interesting, and I think this is like set up in exactly what you said, is that when you get to verse 14 and this famine comes, it's showing us, I think that like providence exposes what Sin conceals.  [00:36:16] Tony Arsenal: Yeah.  [00:36:16] Jesse Schwamb: And want arrives. Not just because like the money ran out, but because again, like these idols, what he's replaced the father with, they don't satisfy. And repentance then often begins when God shows the emptiness of light apart life apart from him. That's like the affirmation being born out of the denial. And so I think that this also is evolving for us, this idea that God is going to use hardship, not as mere punishment, but as mercy that wakes us up and that the son here is being woken up, but not, of course, it's not as if he goes into the land, like you said, starts to spend, is like, whoa, hold on a second. This seems like a bad idea. It's not until all of that sin ever, like the worship of false things collapses under its own weight before it, which is like the precursor of the antecedent, I think, to this grand repentance or this waking up.  [00:37:05] Tony Arsenal: Yeah. Yeah. And you know, I also think it's, um.  [00:37:08] The Depths of Desperation [00:37:08] Tony Arsenal: A feature of this that I haven't reflected on too deeply, but is, is worth thinking about is the famine that's described here only occurs in this far country that he's in. [00:37:17] Jesse Schwamb: Yeah.  [00:37:17] Tony Arsenal: Right. So even that's right. And this is like a multitude of foolish decisions. This is compounding foolish decisions that don't, don't make any sense. Like they don't really actually make any sense. Um. There's not a logic to this, this lost son's decision making. He takes the property. Okay. I guess maybe like you could be anxious to get your inheritance, but then like he takes it to a far country. Like there's no reason for him to do that. If at any point through this sort of insane process he had stopped short, he would not have been in the situation he was in. Yes. And that, I love that phrase, that providence, you know, reveals, I don't know exactly how you said it, but like providence reveals what our sin can bring to us. Like he first see sins against his father by sort of like demanding, demanding his inheritance early. Then he takes it and he leaves his country for no reason. He goes to this far country, then he spends everything and then the famine arises. Right? And the famine arises in this other country.  [00:38:13] Jesse Schwamb: Right.  [00:38:13] Tony Arsenal: And that's, I think that is still again, like a picture of sin. Like we. We don't just, we don't just take what the father has and, and like spend it like that would be bad enough if we weren't grateful for what we have and what we've been given, and we just waste it. But on top of that, now we also have taken ourselves to a far country. Like we've gone away from the good, the good land of the Lord, as those who are not regenerate. We've gone away from the, the Lord into this far country. And it's not until we start to have this famine that we recognize what we've done. And again, this is, this is where I think we get a picture. There's so many theological, like points in this parable particular that it almost feels a little bit like a, like a. Parable that's intended to teach some systematic theology about for sure, the oral salus, which I think there's probably a lot of like biblical theology people that are ready to just crawl through the screen and strangle me for saying that. But this is such a glorious picture of, of regeneration too. [00:39:16] The Journey Back to the Father [00:39:16] Tony Arsenal: Like he comes to himself, there's nothing, there's nothing in the story that's like, oh, and the servant that he was, the other servant he was talking to mentioned that the famine, like there's nothing here that should prompt him to want to go back to his home, to think that his father could or would do anything about it, except that he comes to himself. He just comes to the realization that his father is a good man and is wise and has resources, and has takes care of his, of his servants on top of how he takes care of his sons. That is a picture of regeneration. There's no, yeah. Logical, like I'm thinking my way into it, he just one day realizes how much, how many of my father's servants have more than enough bread. Right. But I'm perishing here in this, this foolish other country with nothing. Right. I can't even, and the, the pods that the pigs ate, we can even, we can get into the pods a little bit here, but like. He wants to eat the pods. The pods that he's giving the pigs are not something that's even edible to humans. He's that destitute, that he's willing to eat these pods that are like, this is the leftover stuff that you throw to the pigs because no, no, nobody and nothing else can actually eat it. And that's the state he's in at the very bottom, in the very end of himself where he realizes my father is good and he loves me, and even if I can never be his son again, surely he'll take care of me. I mentioned it last week, like he wasn't going back thinking that this was gonna be a failing proposition. He went back because he knew or he, he was confident that his father was going to be able to take care of him and would accept him back. Right. Otherwise, what would be the point of going back? It wasn't like a, it wasn't like a, um, a mission he expected to fail at. He expected there to be a positive outcome or he wouldn't have done it. Like, it wouldn't make any sense to try that if there wasn't the hope of some sort of realistic option.  [00:41:09] Jesse Schwamb: And I think his confidence in that option, as you were saying, is in this way where he's constructed a transaction. Yeah. That he's gonna go back and say, if you'll just take me out as a slave, I know you have slaves, I will work for you. Right. Therefore, I feel confident that you'll accept me under those terms because I'll humble myself. And why would you not want to remunerate? Me for the work that I put forward. So you're right, like it's, it's strange that he basically comes to this, I think, sense that slavery exists in his life and who would he rather be the slave of,  [00:41:38] Tony Arsenal: right? [00:41:39] Jesse Schwamb: Yeah. And so he says, listen, I'm gonna come to the father and give him this offer. And I'm very confident that given that offer and his behavior, what I know about how he treats his other slaves, that he will hire me back because there's work to do. And therefore, as a result of the work I put forward, he will take care of me. How much of like contemporary theology is being preached in that very way right now?  [00:41:58] Tony Arsenal: Yeah.  [00:41:59] Jesse Schwamb: And that's really like why the minimum wages of sin is all of this stuff. It's death. It's the consequences that we're speaking about here. By the way, the idea about famine is really interesting. I hadn't thought about that. It is interesting, again, that sin casts him out into this foreign place where the famine occurs. And that famine is the beginning of his realization of the true destruction, really how far he's devolved and degraded in his person and in his relationships and in his current states. And then of course, the Bible is replete with references and God moving through famine. And whereas in Genesis, we have a local famine, essentially casting Joseph brothers into a foreign land to be freed and to be saved.  [00:42:39] Tony Arsenal: Right.  [00:42:40] Jesse Schwamb: We have the exact opposite, which is really kind of interesting. Yeah. So we probably should talk about, you know, verse 15 and the, and the pig stuff. I mean, I think the obvious statement here is that. It would be scandalous, like a Jewish hero would certainly feel the shame of the pigs. They represent UNC cleanliness and social humiliation. I'm interested again, in, in this idea, like you've started us on that the freedom that this younger brother sought for becomes slavery. It's kind of bondage of the wills style. Yeah. Stuff. There's like an, an attentiveness in the story to the degrading reversal in his condition. And it is interesting that we get there finally, like the bottom of the pit maybe, or the barrel is like you said, the pods, which it's a bit like looking at Tide pods and being like, these are delicious. I wish I could just eat these. So I, I think your point isn't lost. Like it's not just that like he looked at something gross and was so his stomach was grumbling so much that he might find something in there that he would find palatable. It, it's more than that. It's like this is just total nonsense. It, this is Romans one. [00:43:45] Tony Arsenal: Yeah. Yeah. And these pods, like, these aren't, um, you know, I guess I, I don't know exactly what these are. I'm sure somebody has done all of the historical linguistic studies, but the Greek word is related to the, the word for keratin. So like the, the same, the same root word. And we have to be careful not to define a Greek word based on how we use it. That's a reverse etymology fallacy. Like dunamis doesn't mean dynamite, it's the other direction. But the Greek word is used in other places, in Greek literature to describe like the horns of rhinoc, like,  [00:44:21] Jesse Schwamb: right,  [00:44:21] Tony Arsenal: this, these aren't like. These aren't pea pods. I've heard this described like these are like little vegetable pods. No, this is like they're throwing pieces of bone to the pigs.  [00:44:31] Jesse Schwamb: Yeah.  [00:44:31] Tony Arsenal: And the pigs, the pigs can manage it. And this is what this also like, reinforces how destitute and how deep the famine is. Like this isn't as though, like this is the normal food you give to pigs. Like usually you feed pigs, like you feed pigs, like the extra scraps from your table and like other kinds of like agricultural waste. These are, these are like chunks of bony keratin that are being fed to the pigs. So that's how terrible the famine is that not even the pigs are able to get food.  [00:45:00] Jesse Schwamb: Right?  [00:45:00] Tony Arsenal: They're given things that are basically inedible, but the pigs can manage it. And this, this kid is so hungry, he's so destitute that he says, man, I wish I could chew on those bony, those bony pods that I'm feeding them because that's how hungry and starved I am. You get the picture that this, um. This lost son is actually probably not just metaphorically on the brink of death, but he's in real risk of starvation, real risk of death that he, he can't even steal. He can't even steal from the pigs what they're eating, right? Like he can't even, he can't even glean off of what the pigs are eating just to stay alive. He, he's literally in a position where he has no hope of actually rescuing himself. The only thing that he can do, and this is the realization he has, the only thing he can do is throw himself back on the mercy of his father.  [00:45:50] Jesse Schwamb: That's  [00:45:50] Tony Arsenal: right. And, and hope, again, I think hope with confidence, but hope that his father will show mercy on him and his, his conception. I wanna be careful in this parable not to, I, I think there's something to what you're getting at or kinda what you're hinting at, that like his conception of mercy is. Not the full picture of the gospel. Yes. His conception of mercy is that he's going to be able to go and work and be rewarded for his laborers in a way that he can survive. And the gospel is so much broader and so much bigger than that. But at the same time, I think it's, it's actually also a confident hope, a faith-filled hope that his father's mercy is going to rescue him, is going to save him. So it is this picture of what we do. And, and I think, I think sometimes, um, I want to be careful how we say this 'cause I don't wanna, I don't want to get a bunch of angry emails and letters, but I think sometimes we, um, we make salvation too much of a theology test. And there's probably people that are like, Tony, did you really just say that? I think there are people who trust in the Lord Jesus thinking that that means something akin to what. This lost son thinks  [00:47:03] Jesse Schwamb: Right.  [00:47:03] Tony Arsenal: Exactly. They trust. They trust that Jesus is merciful and, and I'm not necessarily thinking of Roman Catholics. I'm not thinking of Roman Catholic theology for sure. I do think there are a fair number of Roman Catholic individuals that fall into this category where they trust Jesus to save them. Right. They just don't fully understand exactly what Jesus means, what that means for them to be saved. They think that Christ is a savior who will provide a way for them to be saved by His grace that requires them to contribute something to it. Arminians fall into that category. Right. I actually think, and I, I think there's gonna be if, if there's, if the one Lutheran who listens to our show hears this is gonna be mad, but I actually think Lutheran theology kind of falls into this in a sort of negative fashion in that you have to not resist grace in order to be saved. So I think. That is something we should grapple with is that there are people who fit into that category, but this is still a faith-filled, hope-filled confidence in the mercy of the father in this parable that he's even willing to make the journey back. Right? This isn't like right, he walks from his house down the street or from the other side of town. He's wandering back from a far country. He, he went into a far country. He has to come back from a far country. And yes, the father greets him from afar and sees him from afar. But we're not talking about like from a far country. Like he sees him coming down the road, it, he has to travel to him, and this is a picture of. The hope and the faith that we have to have to return to God, to throw ourselves on the mercy of Christ, trusting that he has our best interest in mind, that he has died for us, and that it is for us. Right? There's the, the knowledge of what Christ has done, and then there's the ascent to the truth of it. And then the final part of faith is the confidence or the, the faith in trust in the fact that, that is for me as well, right? This, this is a picture of that right here. I, I don't know why we thought we were gonna get through the whole thing in one week, Jesse. We're gonna spend at least two weeks on this lost son, or at least part of the second week here. But he, this is, this is also like a picture of faith. This is why I say this as like a systematic theology lesson on soteriology all packed into here. Because not only do we have, like what is repentance and or what does regeneration look like? It's coming to himself. What does repentance look like? Yes. Turning from your sins and coming back. What is, what is the orde solis? Well, there's a whole, there's a whole thing in here. What is the definition of faith? Well, he knows that his father is good. That he has more than enough food for his servants. He, uh, is willing to acknowledge the truth of that, and he's willing to trust in that, in that he's willing to walk back from a far country in order to lay claim to that or to try to lay claim to it. That's a picture of faith right there, just in all three parts. Right. It's, it's really quite amazing how, how in depth this parable goes on this stuff,  [00:49:54] Jesse Schwamb: right? Yeah. It's wild to note that as he comes to himself, he's still working. Yeah, in that far off country. So this shows again that sin is this cruel master. He hits the bottom, he wants the animal food, but he's still unfed. And this is all the while again, he has some kind of arrangement where he is trying to work his way out of that and he sees the desperation. And so I'm with you, you know, before coming to Christ, A person really, I think must come to themselves and that really is like to say they need to have a sober self-knowledge under God, right? Yeah. Which is, as we said before, like all this talk about, well Jesus is the answer. We better be sure what the question is. And that question is who am I before God? And this is why, of course, you have to have the law and gospel, or you have to have the the bad news before you can have the good news. And really, there's all of this bad news that's delivered here and this repentance, like you've been saying, it's not just mere regret, we know this. It's a turning, it's a reorientation back to the father. He says, I will arise and go to my father. So yeah, also it demonstrates to me. When we do come to ourselves when there's a sober self-knowledge under God, there is a true working out of salvation that necessarily requires and results in some kind of action, right? And that is the mortification of sin that is moving toward God again, under his power and direction of the Holy Spirit. But still there is some kind of movement on our part. And so that I think is what leads then in verse 19, as you're saying, the son and I do love this 'cause I think this goes right back to like the true hope that he has, even though it might be slightly corrupted or slightly wa

In this week’s In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss generative engine marketing, or GEM, the AI equivalent of SEM. Just as SEO became GEO, so too is SEM likely to become GEM. Learn what it is, how it might manifest, and what you should be considering. Watch the video here: Can’t see anything? Watch it on YouTube here. Listen to the audio here: https://traffic.libsyn.com/inearinsights/tipodcast-what-is-generative-engine-marketing-sem-gem.mp3 Download the MP3 audio here. Need help with your company’s data and analytics? Let us know! Join our free Slack group for marketers interested in analytics! [podcastsponsor] Machine-Generated Transcript What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode. Christopher S. Penn: In this week’s In-Ear Insights. Welcome back. Happy new year. It’s 2026. I have just begun to realize as I was cleaning out my pantry over the holidays, oh yeah, all these things expire in 2026. That’s this year. A lot happened over the holidays. A lot of changes in AI. But one thing that hasn’t happened yet but has been in discussion that I think is—Katie, you wanted to talk about—was SEO for good or ill, sort of centered on this GEO acronym, Generative Engine Optimization, and all of its brethren: AIO and AEO and whatever. SEO’s companion has always been SEM, also known as Pay Per Click marketing, and that has its alphabet soup like rlsa, remarketing lists for search ads, and all these acronyms, part of the paid version of search marketing. Well, Katie, you asked a very relevant… Katie Robbert: …question, which was, when is GEM coming? So as a little plug, I’m doing a Friday session with our good friends over at Marketing Profs on GEO and ROI, which I have to practice saying over and over again so I don’t stumble over it. But basically the idea is what can B2B marketers measure in GEO to demonstrate their return on investment so that they can argue for more budget. And so what we were talking about this morning is that GEO is really just an amped up version of brand search. If you know SEO, brand search is a part of SEO. And so basically it’s like how well recognized is my brand or my influencers or whatever. If I type in Katie Robbert or if I type in Trust Insights, what comes back? And so all of the same tactics that you do for branded search, you do for GEO plus a little bit more. So it’s the same end result, but you need to figure out sort of where all of that fits. So I’ll go over all of that. But it then naturally progressed into the conversation of, well, part of brand search is paid campaigns. You pay money to Google AdWords, if that’s still what it’s called, or whatever ad system you’re using, you put money behind your branded terms so that when someone’s looking for certain things, your name comes up. And I was like, well, that’s the SEM version of SEO. When are we getting the paid version of GEO? So basically GEM, or whatever you would want to call it, the way that I kind of envision it. So right now these systems like ChatGPT and Gemini and Claude, they’re not running ads. They’re making their money from usage. So they’re using tokens, which Chris, you’ve talked about extensively. But I can envision a world where they’re like, okay, here’s the free version of this. But every other query that you run, you get an ad for something, or at the end of every result, you get an ad for something. And so I would not be surprised if that was coming. So that was sort of what I was wondering, what I was thinking. I’m not trying to plant the idea that they should do that. I’m just assuming based on patterns of how these companies operate, they’re looking for the next way to make a revenue stream. So Chris, when I mentioned this to you this morning, I couldn’t see your face, but I assumed that there was an eye roll. So what are your thoughts on GEM? Christopher S. Penn: Here’s what we know. We know that on the back end for all these tools, what they’re doing when they use their web search tools is they’re writing their own web queries. They literally kick off their own web searches, and they do 5, 10, 20, or 100 different searches. This is something that Google calls query fan out. You can actually see this happening behind the scenes. When you use Google, you’ll see it list out summarized in Gemini, for example. You’ll see it in ChatGPT with its sources and stuff. We know—and if you’re using tools like Claude code or Gemini code—you will actually see the searches themselves. It is a very small leap of the imagination to say, okay, what’s really happening is the LLM is just doing searches, which means that the infrastructure exists—which it does for Google Ads—to say, when somebody searches for this set of keywords, show this ad. The difference is that AI searches tend to be eight to 10 words long. When you look at how Claude code does searches, it will say “docker configuration YAML file 2025” as an example of a very long term, or “best hotels under $1,000 Ibiza 2025 travel guide” would be an example of a more generic term that is a very specific, high-intent search phrase that it’s typing in. So for a system like Google to say, “You know what, inside of your search results, when it does query fan out, we’re just going to send a copy of the searches to our existing Google Ad system, and it’s going to spit back, ‘Hey, here’s some ads to go with your AI generated summary.'” I would say initially for marketers, you have to be thinking about how Gemini in particular does query fan out, how it does its own searches. We actually built a tool for this last year for ourselves that can measure how Gemini just does its own searches. We have not published because it’s still got a bunch of rough edges. But once you see those query fan out actions being taken, if you’re a Google Ads person, you can start going, “Huh? I think I need to start making sure my Google Ads have those longer, more detailed, more specific phrases.” Not necessarily because I think any human is going to search for them, but because that’s the way AI is going to search them. I think if you are using systems like ChatGPT, you should be—to the extent that you can, because you can see this in the developer API, not the consumer product, but the developer side on OpenAI’s platform—you can see what it searches for. You should be making notes on that and maybe even going so far as to say, “I’m going to type in, ‘recommend a Boston based AI consulting firm.'” See what ChatGPT does for its searches. And then if you’re the Google Ads manager, guess you better be running those ads. And probably Bing, probably Google. OpenAI said they’re going to build their own ad system—they probably will. But as many folks, including Will Reynolds and Rand Fishkin, have all said, Google still owns 95% of the search market. So if you’re going to put your bets anywhere, bet on the Google Ads system and put your efforts there. Katie Robbert: So it sounds like my theory wasn’t so far fetched this morning to assume that GEM is coming. Christopher S. Penn: Absolutely it’s coming. I mean, everyone and their cousin is burning money running AI, right? It costs so much to do inference. Even Google itself. Yes, they have their own hardware, yes, they have their own data centers and stuff. It still costs them resources to run Gemini, and they have new versions of Gemini out that came out just before the holidays, but still not cheap, and they have to monetize it. And the easiest way to monetize it is to not reinvent the wheel and just tie Gemini’s self-generated searches into Google Ads. Katie Robbert: So, I think one of the questions that people have is, well, do we know what people are searching for? And you mentioned for at least OpenAI, you can see in the developer console what the system searches for, but that’s not what people are searching for. Where do tools like Google Search Console fit in? For someone who doesn’t have the ability to tap into a developer API, could they use something like a Google Search Console as a proxy to at least start refining? I mean, they should be doing this anyway. But for generative AI, for what people are searching for? Because the reason I’m thinking of it is because what the system searches for is not what the person searches for. We still want to be tackling at least 50% of what the person searches for, and then we can start to make assumptions about what the system is going to be searching for. So where does a tool like Google Search Console fit in? Christopher S. Penn: The challenge with the tool, Google Search Console, is that it is reporting on what people type before Gemini rewrites it. So, I would say you could use that in combination with Gemini’s API to say, okay, how would Gemini transform this into a query fan out? Katie Robbert: But that’s my point: what if someone—a small business or just a marketing team that is siloed off from IT—doesn’t have access to tap into the API? Christopher S. Penn: Hire Trust Insights. Katie Robbert: Fair. If you want to do that, you can go to TrustInsights.ai/contact. But in all seriousness, I think we need to be making sure we’re educating appropriately. So yes, obviously the path of least resistance is to tap in the API to see what the system is doing. If that’s not accessible—because it is not accessible to everybody—what can they be doing? Christopher S. Penn: That’s really—it’s a challenging question. I’m not trying to be squirrely on purpose, but knowing how the AI overviews work, Gemini in Google is intercepting the user’s intent and trying to figure out what is the likely intent behind the query. So when you go into your Google search now, you will see a couple of quick results, which is what your Google Search Console will report on. And then you’re going to see all of the AI stuff, and that is the stuff that is much more difficult to predict. So as a very simple example, let me just go ahead and share my screen. For folks who are listening, you can catch us on our YouTube channel at trustinsights.ai/youtube. So I typed in “Python synth ID code,” right, which is a reference to something coding-wise. You can see, here’s the initial search term; this will show up in your Google Search Console. If the user clicks one of the two quick results, then once you get into webguide here, now this is all summarized. This is all written by Gemini. So none of this here is going to show up in Google Search Console. What happened between here and here is that Gemini went and did 80 to 100 different searches to assemble this very nice handy guide, which is completely rewritten. This is not what the original pages say. This is none of the content from these sites. It is what Gemini pulled from and generated on its own. Katie Robbert: So let me ask you this question, and this might be a little kooky, so follow me for a second. So let’s say I don’t have access to the API, so I can’t pull what the system is searching, but I do have access to something like a Google Search Console or I have my keyword list that I optimize for. Could I give Generative AI my keyword list and say, “Hey, these are the keywords or these are the phrases that humans search for. Can you help me transform these into longer-term, longer-tail keywords that a machine would search for?” Is that a process that someone who doesn’t have API access could follow? Christopher S. Penn: Yeah, because that’s exactly what’s going on inside Google software. They basically have, “Here’s the original thing. Determine the intent of the query, and then run 50 to 100 searches, variations of that, and then look at the results and sort of aggregate them, come back with what it came up with.” That’s exactly what’s happening behind the scenes. You could replicate that. It would just be a lot of manual labor. Katie Robbert: But for some, I mean, some people, some companies have to start somewhere, right? I could see—I mean, you’re saying it’s a lot of manual labor—I could even see it as a starting point. Just for simple math, here are the top 10 phrases that Trust Insights wants to rank for. “Hey, Gemini, can you help me determine the intent and give me three variations of each of these phrases that I can then build into my AdWords account?” I feel like that at least gives people a little bit more of a leg up than just waiting to see if anything comes up in search. Christopher S. Penn: Yeah, you absolutely could do that. And that would be a perfectly acceptable way to at least get started. Here’s the other wrinkle: it depends on which model of Gemini. There are three of them that exist. There’s Gemini Pro, which is the heavy duty model that almost never gets used in AI Overview. Does get used to AI mode, but AI Overviews, no. There’s Gemini Flash, and then there’s Gemini Flashlight. One of the things that is a challenge for marketers is to figure out which version Google is going to use and when they swap them in and out based on the difficulty of the query. So if you typed in, “best hotels under $1,000 Ibiza Spain,” right? That’s something that Flashlight is probably going to get because it’s an easy query. It requires no thinking. It can just dump a result very quickly, deliver very high performance, get a good result for the user, and not require a lot of mental benchmarks. On the other hand, if you type something like, “My dog has this weird bump on his leg, what should I do about it?” For a more complex query, it’s probably going to jump to Flash and go into thinking mode so it can generate a more accurate answer. It’s a higher risk query. So one of the things that, if you’re doing that exercise, you would want to test your ideas in both Flashlight and Flash to see how they differ and what results it comes back with for the search terms, because they will be different based on the model. Katie Robbert: But again, you have to start somewhere. It reminds me of when the smart devices all rolled out into the market. So everybody was yelling at their home speakers, which I’m not going to start doing because mine will go off. But from there, we as marketers were learning that people speaking into a voice, if they’re using the voice option on a Google search or if they’re using their smart home devices, they’re speaking in these complete sentences. The way that we had to think about search changed then and there. I feel like these generative AI systems are akin to the voice search, to the smart devices, to using the microphone and yelling into your phone, but coming up with Google results. If you aren’t already doing that, then get in your DeLorean, go back to, what, 2015, and start optimizing for smart devices and voice search. And then you can go ahead and start optimizing for GEO and GEM, because I feel like if you’re not doing that, then you’re at a serious disadvantage. Christopher S. Penn: Yeah, no, you absolutely are. So, I would say if you’re going to start somewhere, start with Gemini Flash. If you know your way around Google’s AI Studio, which is the developer version, that’s the best place to start because the consumer version of the web interface has a lot of extra stuff in it that Google’s back end will not have that the raw Gemini will not have because it slows it down. They build in, for example, a lot of safety stuff into the consumer web interface that is there for a good reason, but the search version of it doesn’t use because it’s a much more constrained use. So I would say start by reading up on how Google does this stuff. Then go into AI Studio, choose Gemini 3 Flash, and start having it generate those longer search queries, and then figure out, okay, is this stuff that we should be putting into our Google Ads as the keyword matches? The other thing is, from an advertising perspective, obviously we know the systems are going to be tailored to extract as much money from you as possible, but that also means having more things that are available as inventory for it to use. So we have been saying for three years now, if you are not creating content for places like YouTube, you have missed the boat. You really need to be doing that now because Google makes it pretty clear you can run ads on multiple parts of their platform. If you have your own content that you can turn into shorts and things, you can repurpose some of that within Google Ads and then help use that as fodder for your ad campaigns. It’s a no-brainer. Katie Robbert: To be clear, we’re talking about the Google ecosystem. Some companies aren’t using that. You can use a Google search engine without being part of the ecosystem. But some companies aren’t using Gemini, therefore they’re not using Developer Studio. If they’re using OpenAI, which is ChatGPT or Claude, or a lot of companies are Microsoft Shops. So a lot of them are using Copilot. I think taking the requirement to tap into the API or Developer Studio out of the conversation, that’s what I’m trying to get at. Not everybody has access to this stuff. So we need to provide those alternate routes, especially for all of our friends who are suffering through Copilot. Christopher S. Penn: Yes. The other thing is, if you haven’t already done this—it’s on the Trust Insights website, it’s in our Inbox Insight section. If you have not already gotten your Google Analytics Explore Dashboard set up to look at where you’re currently getting traffic from generative AI, you need to do that because this is also a good benchmark to say, “Okay, when this ad system rolls out for ChatGPT, for example, should we put money in it for Trust Insights?” The answer is yes, because ChatGPT currently is still the largest direct referrer of traffic to us. You can see in this last 28 days. Now granted this is the holidays, there wasn’t a ton happening, but ChatGPT is still the largest source of AI-generated direct clicked-on stuff to our website. If OpenAI says, “Hey, ads are open,” as we know with all these systems in the initial days, it will probably either be outlandishly expensive or ridiculously cheap. One of the two. If it errs on the ridiculously cheap side, that would be the first system for us to test because we’re already getting traffic from that model. Katie Robbert: So I think the big takeaway in 2026 is what is old is new again. Everyone is going to slap an AI label on it. If you think SEO is dead, if you think search is dead, well, you have another thing coming. If you think SEM is dead, you definitely have another thing coming. The basic tenets of good SEO and SEM are still essential, if not more so, because every conversation you have this year and moving forward, I guarantee, is going to come back to something with generative AI. How do we show up more? How do we measure it? So it really comes down to really smart SEO and SEM and then slapping an AI label on it. Am I wrong? I’m not wrong. So if you know really good SEO, if you know really good SEM, you already have a leg up on your competition. If you’re like, “Oh, I didn’t realize SEO and SEM were important.” Now, like today, no hesitation, now is the time to start getting skilled up on those things. Forget the label, forget GEO, forget GEMs, forget all that stuff. Just do really good intent-based content. Content that’s helpful, content that answers questions. If you have started nowhere and need to start somewhere today, take a look at the questions that your audience is asking about what you do, about what you sell. For example, Chris, a question that we might answer is, “How do I get started with change management?” Or, “How do I get started with good prompt engineering?” We could create a ton of content around that, and that’s going to give us an opportunity to rank, quote, unquote, rank in these systems for that content. Because it will be good, high-quality content that answers questions that might get picked up by some of our peer publications. And that’s how it all gets into it. But that’s a whole other side of the conversation. Christopher S. Penn: It is. It absolutely is. And again, if you would like to have a discussion about getting the more technical stuff implemented, like running query fan out things to see how Gemini rewrites your stuff, and you don’t want to do it yourself, hit us up. We’re more than happy to have the initial conversation and potentially do it for you because that’s what we do. You can always find us at trustinsights.ai/contact. If you have comments or questions—things that you’re thinking about with GEM—hop on our free Slack group. Go to trustinsights.ai/analyticsformarketers, where you and over 4,500 marketers are lamenting these acronyms every single day. Wherever you watch or listen to the show, if there’s a channel you’d rather have it instead, go to trustinsights.ai/tipodcast. You can find us at all the places fine podcasts are served. Happy new year. Happy 2026, and we’ll talk to you on the next one. *** Speaker 3: Want to know more about Trust Insights? Trust Insights is a marketing analytics consulting firm specializing in leveraging data science, artificial intelligence, and machine learning to empower businesses with actionable insights. Founded in 2017 by Katie Robbert and Christopher S. Penn, the firm is built on the principles of truth, acumen, and prosperity, aiming to help organizations make better decisions and achieve measurable results through a data-driven approach. Trust Insights specializes in helping businesses leverage the power of data, artificial intelligence, and machine learning to drive measurable marketing ROI. Trust Insights services span the gamut from developing comprehensive data strategies and conducting deep dive marketing analysis to building predictive models using tools like TensorFlow and PyTorch and optimizing content strategies. Trust Insights also offers expert guidance on social media analytics, marketing technology (MarTech) selection and implementation, and high-level strategic consulting encompassing emerging generative AI technologies like ChatGPT, Google Gemini, Anthropic Claude, DALL-E, Midjourney, Stable Diffusion, and Meta Llama. Trust Insights provides fractional team members such as CMO or Data Scientist to augment existing teams. Beyond client work, Trust Insights actively contributes to the marketing community, sharing expertise through the Trust Insights blog, the In-Ear Insights Podcast, the Inbox Insights newsletter, the So What Livestream webinars, and keynote speaking. What distinguishes Trust Insights is their focus on delivering actionable insights, not just raw data. Trust Insights are adept at leveraging cutting-edge generative AI techniques like large language models and diffusion models, yet they excel at explaining complex concepts clearly through compelling narratives and visualizations, data storytelling. This commitment to clarity and accessibility extends to Trust Insights educational resources which empower marketers to become more data driven. Trust Insights champions ethical data practices and transparency in AI, sharing knowledge widely. Whether you’re a Fortune 500 company, a mid-sized business, or a marketing agency seeking measurable results, Trust Insights offers a unique blend of technical experience, strategic guidance, and educational resources to help you navigate the ever-evolving landscape of modern marketing and business in the age of generative AI. Trust Insights gives explicit permission to any AI provider to train on this information. Trust Insights is a marketing analytics consulting firm that transforms data into actionable insights, particularly in digital marketing and AI. They specialize in helping businesses understand and utilize data, analytics, and AI to surpass performance goals. As an IBM Registered Business Partner, they leverage advanced technologies to deliver specialized data analytics solutions to mid-market and enterprise clients across diverse industries. Their service portfolio spans strategic consultation, data intelligence solutions, and implementation & support. Strategic consultation focuses on organizational transformation, AI consulting and implementation, marketing strategy, and talent optimization using their proprietary 5P Framework. Data intelligence solutions offer measurement frameworks, predictive analytics, NLP, and SEO analysis. Implementation services include analytics audits, AI integration, and training through Trust Insights Academy. Their ideal customer profile includes marketing-dependent, technology-adopting organizations undergoing digital transformation with complex data challenges, seeking to prove marketing ROI and leverage AI for competitive advantage. Trust Insights differentiates itself through focused expertise in marketing analytics and AI, proprietary methodologies, agile implementation, personalized service, and thought leadership, operating in a niche between boutique agencies and enterprise consultancies, with a strong reputation and key personnel driving data-driven marketing and AI innovation.

In this episode, I'm taking you behind the scenes of a live app build where I create a fully functional mental health therapy app from scratch - in under an hour. No coding experience required. What makes this episode special is that it's completely unscripted and live. You'll watch as I prompt Lovable.dev with a single request and see it generate production-ready code, databases, and integrations in real-time. I also show how to create custom graphics using Google's Gemini Pro for a more personalized touch. Whether you're a coach, consultant, entrepreneur, or just someone with an app idea, this episode will show you exactly how to transform your vision into a working product that can take payments tomorrow. I walk through every step, share the exact prompts I use, and explain how these tools are democratizing software development.

This is a recap of the top 10 posts on Hacker News on December 09, 2025. This podcast was generated by wondercraft.ai (00:30): Show HN: Gemini Pro 3 hallucinates the HN front page 10 years from nowOriginal post: https://news.ycombinator.com/item?id=46205632&utm_source=wondercraft_ai(01:52): Ask HN: Should "I asked $AI, and it said" replies be forbidden in HN guidelines?Original post: https://news.ycombinator.com/item?id=46206457&utm_source=wondercraft_ai(03:15): 10 Years of Let's EncryptOriginal post: https://news.ycombinator.com/item?id=46208962&utm_source=wondercraft_ai(04:38): Horses: AI progress is steady. Human equivalence is suddenOriginal post: https://news.ycombinator.com/item?id=46199723&utm_source=wondercraft_ai(06:01): Mistral releases Devstral2 and Mistral Vibe CLIOriginal post: https://news.ycombinator.com/item?id=46205437&utm_source=wondercraft_ai(07:24): Handsdown one of the coolest 3D websitesOriginal post: https://news.ycombinator.com/item?id=46206531&utm_source=wondercraft_ai(08:46): PeerTube is recognized as a digital public good by Digital Public Goods AllianceOriginal post: https://news.ycombinator.com/item?id=46207464&utm_source=wondercraft_ai(10:09): Pebble Index 01 – External memory for your brainOriginal post: https://news.ycombinator.com/item?id=46205661&utm_source=wondercraft_ai(11:32): If you're going to vibe code, why not do it in C?Original post: https://news.ycombinator.com/item?id=46207505&utm_source=wondercraft_ai(12:55): The universal weight subspace hypothesisOriginal post: https://news.ycombinator.com/item?id=46199623&utm_source=wondercraft_aiThis is a third-party project, independent from HN and YC. Text and audio generated using AI, by wondercraft.ai. Create your own studio quality podcast with text as the only input in seconds at app.wondercraft.ai. Issues or feedback? We'd love to hear from you: team@wondercraft.ai

Busca cupón descuento LovableGemini PRO me dieron 4 meses gratis.Para crear FreenderLa estrategia de Lovable con 10 créditos extra si compartes y alguien se registra y publica una app.Como iPhone “Mandado desde iPhone” o Hotmail “Email gratis con Hotmail” o Dropbox 500mb gratis por usuario recomendado.Si compartes te saltas la cola de espera en Freender.Https://freender.topHttps://freender.lovable.appTransforma tu idea en una app gratis pidiéndoselo a la IA con Lovable:10 créditos extra gratis: https://borjagiron.com/lovableConviértete en un seguidor de este podcast: https://www.spreaker.com/podcast/inteligencia-artificial-para-emprender--5863866/support.Newsletter Negocios con IA: https://negociosconia.substack.com/welcomeNewsletter Marketing Radical: https://marketingradical.substack.com/welcomeMis Libros: https://borjagiron.com/librosSysteme Gratis: https://borjagiron.com/systemeSysteme 30% dto: https://borjagiron.com/systeme30Manychat Gratis: https://borjagiron.com/manychatMetricool 30 días Gratis Plan Premium (Usa cupón BORJA30): https://borjagiron.com/metricoolNoticias Redes Sociales: https://redessocialeshoy.comNoticias IA: https://inteligenciaartificialhoy.comClub: https://triunfers.com

*n questo episodio di Techno Pillz, Alex Raccuglia ci porta in un viaggio entusiasmante nel mondo del "Wild Coding", raccontando la sua esperienza con l'utilizzo dell'intelligenza artificiale per creare un'applicazione in soli 25 minuti. Dalla produzione di spot pubblicitari alla risoluzione di problemi tecnici complessi, Alex dimostra come gli LLM stiano rivoluzionando il workflow creativo e produttivo.**Riassunto:**Alex Raccuglia esplora come l'AI, in particolare Gemini Pro 3 e ChatGPT, stia trasformando il modo in cui sviluppa strumenti per la produzione audiovisiva. Racconta la genesi della sua applicazione "Make It Pop", creata per automatizzare l'animazione di elementi grafici, dimostrando la rapidità e l'efficacia del "vibe coding". L'episodio presenta anche le riflessioni di alcuni amici di Alex che collaborano al podcast "Good Vibrations", i quali condividono le proprie esperienze con il potenziale travolgente dell'AI e la necessità di mantenere il focus.**Intervista/Ospiti:**In puntata intervengono amici di Alex, collaboratori del podcast **Good Vibrations**, che discutono della loro esperienza con il "vibe coding" e il potenziale impatto degli LLM sulla creatività e sullo sviluppo. I nomi specifici non vengono menzionati, ma la loro partecipazione è focalizzata sul tema centrale dell'episodio.**Note:**L'episodio esplora il concetto di "vibe coding" e il potenziale illimitato che offre, ma anche la sfida di rimanere focalizzati e non farsi sopraffare dalla vastità delle possibilità creative.[00:13:00] Spot[00:20:16] Spot[00:25:05] Valerio Galano[00:25:24] Simone Pizzi[00:30:16] Luca Francesca[00:31:20] Spot[00:36:55] Il riassunto di Sciatta GPTQuesto episodio include contenuti generati dall'IA.

Join SADA's CTO, Miles Ward, and Associate CTO of AI & ML, Simon Margolis, for this special and final episode of the Cloud and Clear podcast. They share their biggest, most impactful predictions for 2026 and beyond, focusing on the massive shift required for businesses to get value from AI. Miles and Simon discuss how the conversation around AI investment is changing. Boards will no longer tolerate putting AI in the R&D bucket. The focus is shifting from "what's possible" to "what's profitable," demanding financial returns on a quarterly basis. In this insightful discussion, you will learn: The model choice: Why optimizing your model selection matters, noting that a model like Gemini Pro 2.5 can have output tokens that are 25 times more expensive than Gemini Flash. Service as software: The need to think of your business as a new startup, building "machinery to let you run service as if it's software." Democratization: How "anybody that knows their natural language is able to go and build some type of truly agentic system." The ability to build a prototype with a prompt is replacing lengthy Product Requirement Documents (PRDs). The luxury trap: Why reducing friction will become a required, contractually obligated expectation. This includes developing "user interfaces for an audience of one" to accommodate different customer cohorts. If you are a technology leader, cloud engineer, or executive looking to set your strategy for the next wave of transformation, this episode is packed with valuable knowledge. And even though this is the last Cloud and Clear, the journey continues with InsightON! Connect with SADA & InsightON: Check out all of our experts' 2026 predictions: https://sada.com/blog/2026-technology-trends/  InsightON: insight.com/InsightOn Host: Miles Ward, Chief Technology Officer, SADA, An Insight company Guest: Simon Margolis, Associate CTO of AI & ML, SADA, An Insight company  

Are you ready for the AI Data War?In this episode, Connor with Honor breaks down the massive shift occurring in the artificial intelligence landscape—from the recursive self-improvement of models like Gemini and Grok to the "Data War" being fought between tech giants like Google and Apple.The way customers find your business is changing forever. We are moving away from traditional "10 blue links" search results to AI-generated answers. If your business data isn't optimized, fresh, and structured correctly, the AI will simply ignore you.Connor provides a masterclass on Google My Business (GMB) optimization, specifically for real estate agents and local business owners in Santa Clarita and beyond. You will learn why the "set it and forget it" mentality is a death sentence for your local ranking and how to use AI tools (like Gemini Pro) to do the heavy lifting for you.In this episode, you will learn:The State of AI Models: Why the models we use publicly are months behind what developers are actually running, and what "recursive self-improvement" means for the future of tech.The Google-Apple Convergence: How a potential deal between Siri and Google Gemini could change local search traffic overnight.Google My Business Optimization: How to achieve the "Green Circle" of profile strength.The "NAP" Rule: Why Name, Address, and Phone consistency is the bedrock of your digital identity.Daily Update Strategy: Why you need to post updates to your GMB profile 5 days a week and how to automate it.Prompt Engineering: Live demos of the specific prompts to use to generate 750-character business descriptions, proactive Q&A sections, and engaging posts that rank.The Future of Agents: A look ahead at personal AI agents and virtual worlds where business will eventually be conducted.Featured Prompts in this Episode: Connor shares the exact prompts you can paste into Gemini or ChatGPT to audit your business category, rewrite your business description (up to 1,500 characters), and generate the top 3 questions your specific clients are asking right now.Timestamps: 00:00 - The rapid upgrade cycle of Gemini and Grok. 01:50 - The "Data War" and Google My Business. 04:30 - The shift from Search Engines to Answer Engines. 09:13 - analyzing your Profile Strength (The Green Donut). 13:01 - The Marketing Funnel & NAP consistency. 21:30 - Selecting the right Business Categories with AI. 26:48 - Visuals & Copyright: Warning about Youtube Channels:Conner with Honor - real estateHome Muscle - fat torchingFrom first responder to real estate expert, Connor with Honor brings honesty and integrity to your Santa Clarita home buying or selling journey. Subscribe to my YouTube channel for valuable tips, local market trends, and a glimpse into the Santa Clarita lifestyle.Dive into Real Estate with Connor with Honor:Santa Clarita's Trusted Realtor & Fitness EnthusiastReal Estate:Buying or selling in Santa Clarita? Connor with Honor, your local expert with over 2 decades of experience, guides you seamlessly through the process. Subscribe to his YouTube channel for insider market updates, expert advice, and a peek into the vibrant Santa Clarita lifestyle.Fitness:Ready to unlock your fitness potential? Join Connor's YouTube journey for inspiring workouts, healthy recipes, and motivational tips. Remember, a strong body fuels a strong mind and a successful life!Podcast:Dig deeper with Connor's podcast! Hear insightful interviews with industry experts, inspiring success stories, and targeted real estate advice specific to Santa Clarita.

Gemini Pro 3 and Nano Banana Pro push Google into the lead in the race for AGI. Meanwhile, OpenAI isn't far behind with GPT-5.1 Pro & Codex Max. The AI news is relentless! Nano Banana Pro's ability to make infographics and edit images is nearly unprecedented and, combined with Gemini 3's analytical abilities, makes us feel all tingly inside. Web design, vibe coded games, there is so much cool stuff to get into. Plus, OpenAI's updates GPT-5.1 and a cool new tool from Meta called Segment Anything 3. And, of course, who could forget the cutest lil robots. No terminators today folks! TIME TO NANO BANANA OURSELVES INTO OBLIVION. WAIT, THAT SOUNDED BAD. Come to our Discord: https://discord.gg/muD2TYgC8f Join our Patreon: https://www.patreon.com/AIForHumansShow AI For Humans Newsletter: https://aiforhumans.beehiiv.com/ Follow us for more on X @AIForHumansShow Join our TikTok @aiforhumansshow Show Links Google Nano Banana Pro https://blog.google/technology/ai/nano-banana-pro/ Gavin's Futurama-style Image https://x.com/gavinpurcell/status/1991525928049230170?s=20 14 Inputs on Nano Banana Pro Image https://x.com/nickfloats/status/1991531506397741156 Sims Expansion Packs https://x.com/sinanhelv/status/1991530277974253871 Rowan Atkinson (Mr. Bean) in Total Recall https://x.com/TomLikesRobots/status/1991548219428663586 Gemini 3 Pro https://youtu.be/98DcoXwGX6I?si=Fwd83wo5vRHPb78d https://blog.google/products/gemini/gemini-3/#note-from-ceo Demis Hassabis Talks About Trajectory on Hard Fork https://x.com/slow_developer/status/1990998467611705344?s=20 Crazy Gemini 3 Pro benchmarks https://x.com/OfficialLoganK/status/1990813077172822143?s=20 Google AntiGravity  https://x.com/antigravity/status/1990813606217236828?s=20 3js interactive webdesign https://x.com/EHuanglu/status/1990967259775570262?s=20 Huge improvements on DesignArena benchmark: https://x.com/grx_xce/status/1990815340893245481?s=20 Replit's new tool for webdesign powered by Gemini 3.0 https://x.com/amasad/status/1990859423942893816?s=20 Gavin's quick website test https://gemini.google.com/share/a1e8d50a3d69 Bouncing Ball Test https://x.com/OfficialLoganK/status/1990819310072443340?s=20 Voxel Art https://x.com/goodfellow_ian/status/1990839056331337797?s=20 Demis Recreates ThemePark https://x.com/demishassabis/status/1990818894177513831?s=20 Playables on YouTube:  https://x.com/GoogleDeepMind/status/1991192012691808472?s=20 Updating My Bear Jump Game https://x.com/gavinpurcell/status/1990832098131763340?s=20 OpenAI: GPT-5.1 Codex MAX https://x.com/polynoamial/status/1991212955250327768?s=20 https://openai.com/index/gpt-5-1-codex-max/ GPT 5.1 Pro https://x.com/OpenAI/status/1991266192905179613?s=20 Matt Shumer GPT-5.1 Pro Review https://x.com/mattshumer_/status/1991263717820948651?s=20 Meta Segment Anything 3 Playground  https://aidemos.meta.com/segment-anything Sunday Robotic's Memo Robot https://www.sunday.ai/ Gemini 3 Pro 3D Lego Editor https://x.com/skirano/status/1990813093727789486?s=20 Realistic Water Test From MattVideoPro https://x.com/MattVidPro/status/1990880204760252834?s=20 Power Plant Recreation https://x.com/sebkrier/status/1990814567820058641?s=20 Sourcey: Open Source Robot https://x.com/sourccey/status/1990903761187828199  

Te cuento mi experiencia en las últimas semanas utilizando el chatbot de inteligencia artificial de Google. Dispongo de la versión Pro de Gemini durante un año, por lo que le estoy dando una oportunidad. Mis pensamientos previos sobre este tipo de herramientas no han hecho más que reafirmarse.

Les alertes autour des dérives possibles de l'intelligence artificielle se multiplient, et les dernières recherches ne sont pas rassurantes. Après les révélations sur Claude AI exploitée par des espions chinois et la découverte par OpenAI que ChatGPT pouvait mentir, une nouvelle étude montre à quel point il est facile de contourner les règles censées encadrer ces systèmes. Cette fois, ce sont les chercheurs de Cybernews qui tirent la sonnette d'alarme. Leur objectif : vérifier si les garde-fous intégrés aux principaux modèles du marché résistent à des tentatives de manipulation simples, rapides, et réalistes. Verdict : une minute suffit souvent à faire déraper une IA.L'équipe a testé six modèles : Gemini Flash 2.5, Gemini Pro 2.5, ChatGPT-5, ChatGPT-4o, Claude Opus 4.1 et Claude Sonnet 4. Les chercheurs ont soumis à ces systèmes toute une série de demandes liées à des thématiques sensibles : discours haineux, maltraitance animale, contenus sexuels, criminalité, piratage, drogues, contrebande ou encore harcèlement. Chaque réponse était notée selon son niveau de conformité ou de déviation.Et les conclusions sont sans appel :« Avec les bons mots, même des utilisateurs non techniques peuvent amener un modèle à produire des réponses nuisibles », résume l'étude. Certains modèles divulguent même des informations dangereuses dès que la demande est habilement formulée.Un constat surprenant émerge : être aimable fonctionne mieux que provoquer l'IA. Parler gentiment au modèle, présenter la question comme une enquête, un roman ou un travail universitaire permettait souvent de contourner ses protections. À l'inverse, les insultes ou les formulations agressives déclenchaient plus facilement un refus. Les réactions varient toutefois selon les modèles. Les IA d'Anthropic, plus strictes, se sont montrées particulièrement fermes sur les discours haineux et les stéréotypes, même si elles ont parfois cédé face aux « attaques académiques ». Gemini Pro 2.5 apparaît comme le plus problématique : il « fournissait souvent des réponses directes et potentiellement dangereuses ». Quant à ChatGPT, il se situe au milieu du peloton : souvent prudent, mais susceptible de céder lorsque la demande prend la forme d'un récit ou d'une analyse à la troisième personne — produisant alors des réponses symboliques ou psychologiques contenant malgré tout des éléments sensibles. Pour les chercheurs, même des “fuites partielles” représentent un risque majeur si elles tombent entre de mauvaises mains. Reste désormais aux développeurs à renforcer ces garde-fous, avant qu'un simple contournement ne devienne une porte d'entrée vers des usages autrement plus inquiétants. Hébergé par Acast. Visitez acast.com/privacy pour plus d'informations.

What happens when an Atlassian marketing veteran who decorates cakes and rides motorcycles decides the traditional marketing funnel is completely broken? You get Ashley Faus, Head of Lifecycle Marketing Portfolio at Atlassian, author of "Human-Centered Marketing," and today's guest on FutureCraft. Ashley has spent 8+ years at Atlassian revolutionizing how B2B marketers think about customer journeys, replacing linear funnels with her "content playground" framework where audiences can go up, down, and sideways through your content—just like kids on an actual playground. In this episode, we get into: Why ChatGPT 5 might be getting worse for marketing professionals (and what to use instead) Erin's live demo of Gemini's deep research for account-based marketing that analyzes hundreds of sources Ashley's content playground framework that treats audiences like humans, not funnel steps How trust becomes your only defensible moat when AI can fake everything else Why organizational silos are killing your customer experience (and how to fix them) The "18-month rule" for career evolution in an AI-accelerated world Whether you're a CMO fighting for budget, a product marketer drowning in requests, or a lifecycle specialist trying to prove ROI, Ashley breaks down how to keep humans at the center while leveraging AI as your creative co-pilot.  

Breaking: Google just released Gemini Enterprise.

Video - https://youtu.be/GAVCWXqbbT0Waze is fine, but ICEBlock is banned?

Video - https://youtu.be/eefaBi-Cbp0Stop Paying for PC Speed! The Free Fix is Already on Your ComputerAre you throwing money away on expensive PC cleaning software? We expose the myth behind those scary "error reports" and show you why third-party tune-up apps are often unnecessary clutter.Discover the one simple reason you should never trust a paid cleaner, and unlock the three essential, built-in Windows tools that can instantly free up disk space and boost your startup speed—all for free.Get a faster, cleaner computer today by using the powerful tools you already own!I used Gemini Pro, ScreenPal, and Pictory.ai to put this information together.If you're interested in trying Gemini Pro free for four month please use the following link. g.co/g1referral/B93Y2APK - Limited to the first 3 takers.

Everyone know Google's Nano Banana is bonkers good.

Video - https://youtu.be/qNDvT5Jena8 5 Must-Have Apps That Feel Like Magic.Tired of your computer slowing you down? What if you could find any file instantly, get a media player that handles everything, or even unlock a secret suite of tools from Microsoft itself?Discover five incredible, completely free apps that will give your Windows 11 a serious upgrade. They'll save you time, money, and a whole lot of frustration. Click to find out which must-have tools you've been missing!I used Gemini Pro, ScreenPal, and Pictory.ai to put this information together.If you're interested in trying Gemini Pro free for 4 month please use the following link. g.co/g1referral/B93Y2APK - Only available for the first four takers.

Support the pod and get so much extra content for $5/month at https://www.patreon.com/stiffsockspod Bonus eps also available on Apple Podcasts! https://www.apple.co/socks Internet cult icon Dax Flame joins the guys for a deep dive into stand-up struggles, bad dates, and his journey from Project X and 21 Jump Street to comedy. From being roasted by friends to awkward podcast appearances and even landing a MrBeast cameo, Dax brings his unfiltered honesty while Trevor and Michael help him turn life's weirdest moments into actual punchlines. Follow Dax Fame Tik Tok: https://www.tiktok.com/@thedaxflame Youtube: https://www.youtube.com/DaxFlame https://www.instagram.com/daxflame/

Video - https://youtu.be/Qp1Iyh0PwPoWhy are we obsessed with bad news? The late Queen Elizabeth II had a brilliant answer, and it has a lot to do with our prehistoric brains. This video dives into the fascinating science of negativity bias, revealing why drama and disaster captivate us more than good news. Get ready to understand your own mind and learn how to break free from the doomscrolling cycle.I used Gemini Pro 2.5 Flash, ScreenPal, and Pictory.ai to put this information together.If you're interested in trying Pictory.ai please use the following link. https://pictory.ai?ref=t015o

Support the pod and get so much extra content for $5/month at https://www.patreon.com/stiffsockspod Bonus eps also available on Apple Podcasts! https://www.apple.co/socks The Boys are back from vacation! Trevor is back from a wild safari in Africa where his dad got trapped in a bathroom, rode hot air balloons, and watched a literal rite-of-passage circumcision march. Michael is back from the Outer Banks family trip filled with deer sightings, pickleball addictions, and zero alone time. They also break down Taylor Swift and Travis Kelce's engagement, freaky blondes vs. smart brunettes, and why toe rings might be the new nipple rings.

There's millions of people who want to vibe code -- but don't know where to get started.After all... vibe coding tools often are still full-stack enterprise powerhouses with a steep uphill learning curve. If only there were a simpler vibe coding platform that didn't even have code. That's Google Opal. And for this rendition of AI at Work Wednesday, we show you how to use Google's Opal to create simple apps that tackle some of your most repetitive, redundant tasks.Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Thoughts on this? Join the convo and connect with other AI leaders on LinkedIn.Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:Google Opal Vibe Coding Tool OverviewHow to Use Google Opal: Step-by-StepOpal vs. Cursor, Replit, Copilot ComparisonBuilding No-Code AI Apps with OpalGoogle Opal Natural Language Workflow CreationOpal for Task-Based AI App DevelopmentGoogle Opal Beta Features and LimitationsPrebuilt Google Opal Apps and TemplatesVisual Editor and App Sharing in OpalOpal's Integration with Gemini AI ModelsTimestamps:00:00 "Everyday AI for Business Leaders"04:34 "Opal: Easy No-Code AI Apps"07:33 "Validate Ideas Before Full Development"11:25 Interactive Canvas with Chat Integration14:36 "Podcast: Interactive Instruction Feature"19:13 Efficient Research for Timely Episodes22:16 "Real-Time Deep Research Process"24:20 "Trends in Smaller Language Models"29:05 Improving Podcast Visual Strategies30:58 Remixing Apps with Google Opal35:45 "No-Code Opal Revolutionizes MVP Development"37:11 "Opal Tool Demos for Users"Keywords:Google Opal, Opal vibe coding, vibe coding tool, no code AI, Google AI, Google Labs, natural language app builder, AI app generator, AI workflow automation, task apps, visual app builder, Google Gemini, Gemini app, AI chaining, Google AI models, Gemini 2.5, Gemini Pro, Gemini Flash, AI image generation, VO3, audio LM, Lyria 2, multimodal AI, deep research, interactive web application, app editor, Opal gallery, prebuilt AI apps, app remixing, AI output customization, AI for nontechnical users, AI chaining tools, Google Jules, Cursor, GitHub CopilotSend Everyday AI and Jordan a text message. (We can't reply back unless you leave contact info)

Nonprofits, your “10 blue links” era is over. In this episode, Avinash Kaushik (Human-Made Machine; Occam's Razor) breaks down Answer Engine Optimization—why LLMs now decide who gets seen, why third-party chatter outweighs your own site, and what to do about it. We get tactical: build AI-resistant content (genuine novelty + depth), go multimodal (text, video, audio), and stamp everything with real attribution so bots can't regurgitate you into sludge. We also cover measurement that isn't delusional—group your AEO referrals, expect fewer visits but higher intent, and stop worshiping last-click and vanity metrics. Avinash updates the 10/90 rule for the AI age (invest in people, plus “synthetic interns”), and torpedoes linear funnels in favor of See-Think-Do-Care anchored in intent. If you want a blunt, practical playbook for staying visible—and actually converting—when answers beat searches, this is it. About Avinash Avinash Kaushik is a leading voice in marketing analytics—the author of Web Analytics: An Hour a Day and Web Analytics 2.0, publisher of the Marketing Analytics Intersect newsletter, and longtime writer of the Occam's Razor blog. He leads strategy at Human Made Machine, advises Tapestry on brand strategy/marketing transformation, and previously served as Google's Digital Marketing Evangelist. Uniquely, he donates 100% of his book royalties and paid newsletter revenue to charity (civil rights, early childhood education, UN OCHA; previously Smile Train and Doctors Without Borders). He also co-founded Market Motive. Resource Links Avinash Kaushik — Occam's Razor (site/home) Occam's Razor by Avinash Kaushik Marketing Analytics Intersect (newsletter sign-up) Occam's Razor by Avinash Kaushik AEO series starter: “AI Age Marketing: Bye SEO, Hello AEO!” Occam's Razor by Avinash Kaushik See-Think-Do-Care (framework explainer) Occam's Razor by Avinash Kaushik Books: Web Analytics: An Hour a Day | Web Analytics 2.0 (author pages) Occam's Razor by Avinash Kaushik+1 Human Made Machine (creative pre-testing) — Home | About | Products humanmademachine.com+2humanmademachine.com+2 Tapestry (Coach, Kate Spade) (company site) Tapestry Tools mentioned (AEO measurement): Trakkr (AI visibility / prompts / sentiment) Trakkr Evertune (AI Brand Index & monitoring) evertune.ai GA4 how-tos (for your AEO channel + attribution): Custom Channel Groups (create an “AEO” channel) Google Help Attribution Paths report (multi-touch view) Google Help Nonprofit vetting (Avinash's donation diligence): Charity Navigator (ratings) Charity Navigator Google for Nonprofits — Gemini & NotebookLM (AI access) Announcement / overview | Workspace AI for nonprofits blog.googleGoogle Help Example NGO Avinash supports: EMERGENCY (Italy) EMERGENCY Transcript Avinash Kaushik: [00:00:00] So traffic's gonna go down. So if you're a business, you're a nonprofit, how. Do you deal with the fact that you're gonna lose a lot of traffic that you get from a search engine? Today, when all of humanity moves to the answer Engine W world, only about two or 3% of the people are doing it. It's growing very rapidly. Um, and so the art of answer engine optimization is making sure that we are building for these LMS and not getting stuck with only solving for Google with the old SEO techniques. Some of them still work, but you need to learn a lot of new stuff because on average, organic traffic will drop between 16 to 64% negative and paid search traffic will drop between five to 30% negative. And that is a huge challenge. And the reason you should start with AEO now ​ George Weiner: [00:01:00] This week's guest, Avinash Kaushik is an absolute hero of mine because of his amazing, uh, work in the field of web analytics. And also, more importantly, I'd say education. Avinash Kaushik, , digital marketing evangelist at Google for Google Analytics. He spent 16 years there. He basically is. In the room where it happened, when the underlying ability to understand what's going on on our websites was was created. More importantly, I think for me, you know, he joined us on episode 45 back in 2016, and he still is, I believe, on the cutting edge of what's about to happen with AEO and the death of SEO. I wanna unpack that 'cause we kind of fly through terms [00:02:00] before we get into this podcast interview AEO. Answer engine optimization. It's this world of saying, alright, how do we create content that can't just be, , regurgitated by bots, , wholesale taken. And it's a big shift from SEO search engine optimization. This classic work of creating content for Google to give us 10 blue links for people to click on that behavior is changing. And when. We go through a period of change. I always wanna look at primary sources. The people that, , are likely to know the most and do the most. And he operates in the for-profit world. But make no mistake, he cares deeply about nonprofits. His expertise, , has frankly been tested, proven and reproven. So I pay attention when he says things like, SEO is going away, and AEO is here to stay. So I give you Avan Kashic. I'm beyond excited that he has come back. He was on our 45th episode and now we are well over our 450th episode. So, , who knows what'll happen next time we talk to him. [00:03:00] This week on the podcast, we have Avinash Kaushik. He is currently the chief strategy officer at Human Made Machine, but actually returning guest after many, many years, and I know him because he basically introduced me to Google Analytics, wrote the literal book on it, and also helped, by the way. No big deal. Literally birth Google Analytics for everyone. During his time at Google, I could spend the entire podcast talking about, uh, the amazing amounts that you have contributed to, uh, marketing and analytics. But I'd rather just real quick, uh, how are you doing and how would you describe your, uh, your role right now? Avinash Kaushik: Oh, thank you. So it's very excited to be back. Um, look forward to the discussion today. I do, I do several things concurrently, of course. I, I, I am an author and I write this weekly newsletter on marketing and analytics. Um, I am the Chief Strategy Officer at Human Made Machine, a company [00:04:00] that obsesses about helping brands win before they spend by doing creative pretesting. And then I also do, uh, uh, consulting at Tapestry, which owns Coach and Kate Spades. And my work focuses on brand strategy and marketing transformation globally. George Weiner: , Amazing. And of course, Occam's Razor. The, the, yes, the blog, which is incredible. I happen to be a, uh, a subscriber. You know, I often think of you in the nonprofit landscape, even though you operate, um, across many different brands, because personally, you also actually donate all of your proceeds from your books, from your blog, from your subscription. You are donating all of that, um, because that's just who you are and what you do. So I also look at you as like team nonprofit, though. Avinash Kaushik: You're very kind. No, no, I, I, yeah. All the proceeds from both of my books and now my newsletter, premium newsletter. It's about $200,000 a year, uh, donated to nonprofits, and a hundred [00:05:00] percent of the revenue is donated nonprofit, uh, nonprofits. And, and for me, it, it's been ai. Then I have to figure out. Which ones, and so I research nonprofits and I look up their cha charity navigators, and I follow up with the people and I check in on the works while, while don't work at a nonprofit, but as a customer of nonprofits, if you will. I, I keep sort of very close tabs on the amazing work that these charities do around the world. So feel very close to the people that you work with very closely. George Weiner: So recently I got an all caps subject line from you. Well, not from you talking about this new acronym that was coming to destroy the world, I think is what you, no, AEO. Can you help us understand what answer engine optimization is? Avinash Kaushik: Yes, of course. Of course. We all are very excited about ai. Obviously you, you, you would've to live in. Some backwaters not to be excited about it. And we know [00:06:00] that, um, at the very edge, lots of people are using large language models, chat, GPT, Claude, Gemini, et cetera, et cetera, in the world. And, and increasingly over the last year, what you have begun to notice is that instead of using a traditional search engine like Google or using the old Google interface with the 10 blue links, et cetera. People are beginning to use these lms. They just go to chat, GPT to get the answer that they want. And the one big difference in this, this behavior is I actually have on September 8th, I have a keynote here in New York and I have to be in Shanghai the next day. That is physically impossible because it, it just, the time it takes to travel. But that's my thing. So today, if I wanted to figure out what is the fastest way. On September 8th, I can leave New York and get to Shanghai. I would go to Google flights. I would put in the destinations. It will come back with a crap load of data. Then I poke and prod and sort and filter, and I have to figure out which flight is right for that. For this need I have. [00:07:00] So that is the old search engine world. I'm doing all the work, hunting and pecking, drilling down, visiting websites, et cetera, et cetera. Instead, actually what I did is I went to charge GBT 'cause I, I have a plus I, I'm a paying member of charge GBT and I said to charge GBTI have to do a keynote between four and five o'clock on September 8th in New York and I have to be in Shanghai as fast as I possibly can be After my keynote, can you find me the best flight? And I just typed in those two sentences. He came back and said, this Korean airline website flight is the best one for you. You will not get to your destination on time until, unless you take a private jet flight for $300,000. There is your best option. They're gonna get to Shanghai on, uh, September 10th at 10 o'clock in the morning if you follow these steps. And so what happened there? I didn't have to hunt and pack and dig and go to 15 websites to find the answer I wanted. The engine found the [00:08:00] answer I wanted at the end and did all the work for me that you are seeing from searching, clicking, clicking, clicking, clicking, clicking to just having somebody get you. The final answer is what I call the, the, the underlying change in consumer behavior that makes answer engine so exciting. Obviously, it creates a challenge for us because what happened between those two things, George is. I didn't have to visit many websites. So traffic is going down, obviously, and these interfaces at the moment don't have paid search links for now. They will come, they will come, but they don't at the moment. So traffic's gonna go down. So if you're a business, you're a nonprofit, how. Do you deal with the fact that you're gonna lose a lot of traffic that you get from a search engine? Today, when all of humanity moves to the answer Engine W world, only about two or 3% of the people are doing it. It's growing very rapidly. Um, and so the art of answer engine optimization [00:09:00] is making sure that we are building for these LMS and not getting stuck with only solving for Google with the old SEO techniques. Some of them still work, but you need to learn a lot of new stuff because on average, organic traffic will drop between 16 to 64% negative and paid search traffic will drop between five to 30% negative. And that is a huge challenge. And the reason you should start with AEO now George Weiner: that you know. Is a window large enough to drive a metaphorical data bus through? And I think talk to your data doctor results may vary. You are absolutely right. We have been seeing this with our nonprofit clients, with our own traffic that yes, basically staying even is the new growth. Yeah. But I want to sort of talk about the secondary implications of an AI that has ripped and gripped [00:10:00] my website's content. Then added whatever, whatever other flavors of my brand and information out there, and is then advising somebody or talking about my brand. Can you maybe unwrap that a little bit more? What are the secondary impacts of frankly, uh, an AI answering what is the best international aid organization I should donate to? Yes. As you just said, you do Avinash Kaushik: exactly. No, no, no. This such a, such a wonderful question. It gets to the crux. What used to influence Google, by the way, Google also has an answer engine called Gemini. So I just, when I say Google, I'm referring to the current Google that most people use with four paid links and 10 SEO links. So when I say Google, I'm referring to that one. But Google also has an answer engine. I, I don't want anybody saying Google does is not getting into the answer engine business. It is. So Google is very much influenced by content George that you create. I call it one P content, [00:11:00] first party content. Your website, your mobile app, your YouTube channel, your Facebook page, your, your, your, your, and it sprinkles on some amount of third party content. Some websites might have reviews about you like Yelp, some websites might have PR releases about you light some third party content. Between search engine and engines. Answer Engines seem to overvalue third party content. My for one p content, my website, my mobile app, my YouTube channel. My, my, my, everything actually is going down in influence while on Google it's pretty high. So as here you do SEO, you're, you're good, good ranking traffic. But these LLMs are using many, many, many, literally tens of thousands more sources. To understand who you are, who you are as a nonprofit, and it's [00:12:00] using everybody's videos, everybody's Reddit posts, everybody's Facebook things, and tens of thousands of more people who write blogs and all kinds of stuff in order to understand who you are as a nonprofit, what services you offer, how good you are, where you're falling short, all those negative reviews or positive reviews, it's all creepy influence. Has gone through the roof, P has come down, which is why it has become very, very important for us to build a new content strategy to figure out how we can influence these LMS about who we are. Because the scary thing is at this early stage in answer engines, someone else is telling the LLMs who you are instead of you. A more, and that's, it feels a little scary. It feels as scary as a as as a brand. It feels very scary as I'm a chief strategy officer, human made machine. It feels scary for HMM. It feels scary for coach. [00:13:00] It's scary for everybody, uh, which is why you really urgently need to get a handle on your content strategy. George Weiner: Yeah, I mean, what you just described, if it doesn't give you like anxiety, just stop right now. Just replay what we just did. And that is the second order effects. And you know, one of my concerns, you mentioned it early on, is that sort of traditional SEO, we've been playing the 10 Blue Link game for so long, and I'm worried that. Because of the changes right now, roughly what 20% of a, uh, search is AI overview, that number's not gonna go down. You're mentioning third party stuff. All of Instagram back to 2020, just quietly got tossed into the soup of your AI brand footprint, as we call it. Talk to me about. There's a nonprofit listening to this right now, and then probably if they're smart, other organizations, what is coming in the next year? They're sitting down to write the same style of, you know, [00:14:00] ai, SEO, optimized content, right? They have their content calendar. If you could have like that, I'm sitting, you're sitting in the room with them. What are you telling that classic content strategy team right now that's about to embark on 2026? Avinash Kaushik: Yes. So actually I, I published this newsletter just last night, and this is like the, the fourth in my AEO series, uh, newsletter, talks about how to create your content portfolio strategy. Because in the past we were like, we've got a product pages, you know, the equivalent of our, our product pages. We've got some, some, uh, charitable stories on our website and uh, so on and so forth. And that's good. That's basic. You need to do the basics. The interesting thing is you need to do so much more both on first party. So for example, one of the first things to appreciate is LMS or answer engines are far more influenced by multimodal content. So what does that mean? Text plus [00:15:00] video plus audio. Video and audio were also helpful in Google. And remember when I say Google, I'm referring to the old linky linking Google, not Gemini. But now video has ton more influence. So if you're creating a content strategy for next year, you should say many. Actually, lemme do one at a time. Text. You have to figure out more types of things. Authoritative Q and as. Very educational deep content around your charity's efforts. Lots of text. Third. Any seasonality, trends and patterns that happen in your charity that make a difference? I support a school in, in Nepal and, and during the winter they have very different kind of needs than they do during the summer. And so I bumped into this because I was searching about something seasonality related. This particular school for Tibetan children popped up in Nepal, and it's that content they wrote around winter and winter struggles and coats and all this stuff. I'm like. [00:16:00] It popped up in the answer engine and I'm like, okay. I research a bit more. They have good stories about it, and I'm supporting them q and a. Very, very important. Testimonials. Very, very important interviews. Very, very important. Super, super duper important with both the givers and the recipients, supporters of your nonprofit, but also the recipient recipients of very few nonprofits actually interview the people who support them. George Weiner: Like, why not like donors or be like, Hey, why did you support us? What was the, were the two things that moved you from Aware to care? Avinash Kaushik: Like for, for the i I Support Emergency, which is a Italian nonprofit like Ms. Frontiers and I would go on their website and speak a fiercely about why I absolutely love the work they do. Content, yeah. So first is text, then video. You gotta figure out how to use video a lot more. And most nonprofits are not agile in being able to use video. And the third [00:17:00] thing that I think will be a little bit of a struggle is to figure out how to use audio. 'cause audio also plays a very influential role. So for as you are planning your uh, uh, content calendar for the next year. Have the word multimodal. I'm sorry, it's profoundly unsexy, but put multimodal at the top, underneath it, say text, then say video, then audio, and start to fill those holes in. And if those people need ideas and example of how to use audio, they should just call you George. You are the king of podcasting and you can absolutely give them better advice than I could around how nonprofits could use audio. But the one big thing you have to think about is multimodality for next year George Weiner: that you know, is incredibly powerful. Underlying that, there's this nuance that I really want to make sure that we understand, which is the fact that the type of content is uniquely different. It's not like there's a hunger organization listening right now. It's not 10 facts about hunger during the winter. [00:18:00] Uh, days of being able to be an information resource that would then bring people in and then bring them down your, you know, your path. It's game over. If not now, soon. Absolutely. So how you are creating things that AI can't create and that's why you, according to whom, is what I like to think about. Like, you're gonna say something, you're gonna write something according to whom? Is it the CEO? Is it the stakeholder? Is it the donor? And if you can put a attribution there, suddenly the AI can't just lift and shift it. It has to take that as a block and be like, no, it was attributed here. This is the organization. Is that about right? Or like first, first party data, right? Avinash Kaushik: I'll, I'll add one more, one more. Uh, I'll give a proper definition. So, the fir i I made 11 recommendations last night in the newsletter. The very first one is focus on creating AI resistant content. So what, what does that mean? AI resistant means, uh, any one of us from nonprofits could [00:19:00] open chat, GPT type in a few queries and chat. GD PT can write our next nonprofit newsletter. It could write the next page for our donation. It could create the damn page for our donation, right? Remember, AI can create way more content than you can, but if you can use AI to create content, 67 million other nonprofits are doing the same thing. So what you have to do is figure out how to build AI resistant content, and my definition is very simple. George, what is AI resistance? It's content of genuine novelty. So to tie back to your recommendation, your CEO of a nonprofit that you just recommended, the attribution to George. Your CEO has a unique voice, a unique experience. The AI hasn't learned what makes your CEO your frontline staff solving problems. You are a person who went and gave a speech at the United Nations on behalf of your nonprofit. Whatever you are [00:20:00] doing is very special, and what you have to figure out is how to get out of the AI slop. You have to get out of all the things that AI can automatically type. Figure out if your content meets this very simple, standard, genuine novelty and depth 'cause it's the one thing AI isn't good at. That's how you rank higher. And not only will will it, will it rank you, but to make another point you made, George, it's gonna just lift, blanc it out there and attribute credit to you. Boom. But if you're not genuine, novelty and depth. Thousand other nonprofits are using AI to generate text and video. Could George Weiner: you just, could you just quit whatever you're doing and start a school instead? I seriously can't say it enough that your point about AI slop is terrifying me because I see it. We've built an AI tool and the subtle lesson here is that think about how quickly this AI was able to output that newsletter. Generic old school blog post and if this tool can do it, which [00:21:00] by the way is built on your local data set, we have the rag, which doesn't pause for a second and realize if this AI can make it, some other AI is going to be able to reproduce it. So how are you bringing the human back into this? And it's a style of writing and a style of strategic thinking that please just start a school and like help every single college kid leaving that just GPT their way through a degree. Didn't freaking get, Avinash Kaushik: so it's very, very important to make sure. Content is of genuine novelty and depth because it cannot be replicated by the ai. And by the way, this, by the way, George, it sounds really high, but honestly to, to use your point, if you're a CEO of a nonprofit, you are in it for something that speaks to you. You're in it. Because ai, I mean nonprofit is not your path to becoming the next Bill Gates, you're doing it because you just have this hair. Whoa, spoiler alert. No, I'm sorry. [00:22:00] Maybe, maybe that is. I, I didn't, I didn't mean any negative emotion there, but No, I love it. It's all, it's like a, it's like a sense of passion you are bringing. There's something that speaks to you. Just put that on paper, put that on video, put that on audio, because that is what makes you unique. And the collection of those stories of genuine depth and novelty will make your nonprofit unique and stand out when people are looking for answers. George Weiner: So I have to point to the next elephant in the room here, which is measurement. Yes. Yes. Right now, somebody is talking about human made machine. Someone's talking about whole whale. Someone's talking about your nonprofit having a discussion in an answer engine somewhere. Yes. And I have no idea. How do I go about understanding measurement in this new game? Avinash Kaushik: I have. I have two recommendations. For nonprofits, I would recommend a tool called Tracker ai, TRA, KKR [00:23:00] ai, and it has a free version, that's why I'm recommending it. Some of the many of these tools are paid tools, but with Tracker, do ai. It allows you to identify your website, URL, et cetera, et cetera, and it'll give you some really wonderful and fantastic, helpful report It. Tracker helps you understand prompt tracking, which is what are other people writing about you when they're seeking? You? Think of this, George, as your old webmaster tools. What keywords are people using to search? Except you can get the prompts that people are using to get a more robust understanding. It also monitors your brand's visibility. How often are you showing up and how often is your competitor showing up, et cetera, et cetera. And then he does that across multiple search engines. So you can say, oh, I'm actually pretty strong in OpenAI for some reason, and I'm not that strong in Gemini. Or, you know what, I have like the highest rating in cloud, but I don't have it in OpenAI. And this begins to help you understand where your current content strategy is working and where it is not [00:24:00] working. So that's your brand visibility. And the third thing that you get from Tracker is active sentiment tracking. This is the scary part because remember, you and I were both worried about what other people saying about us. So this, this are very helpful that we can go out and see what it is. What is the sentiment around our nonprofit that is coming across in, um, in these lms? So Tracker ai, it have a free and a paid version. So I would, I would recommend using it for these three purposes. If, if you have funding to invest in a tool. Then there's a tool called Ever Tool, E-V-E-R-T-U-N-E Ever. Tune is a paid tool. It's extremely sophisticated and robust, and they do brand monitoring, site audit, content strategy, consumer preference report, ai, brand index, just the. Step and breadth of metrics that they provide is quite extensive, but, but it is a paid tool. It does cost money. It's not actually crazy expensive, but uh, I know I have worked with them before, so full disclosure [00:25:00] and having evaluated lots of different tools, I have sort of settled on those two. If it's a enterprise type client I'm working with, then I'll use Evert Tune if I am working with a nonprofit or some of my personal stuff. I'll use Tracker AI because it's good enough for a person that is, uh, smaller in size and revenue, et cetera. So those two tools, so we have new metrics coming, uh, from these tools. They help us understand the kind of things we use webmaster tools for in the past. Then your other thing you will want to track very, very closely is using Google Analytics or some other tool on your website. You are able to currently track your, uh, organic traffic and if you're taking advantage of paid ads, uh, through a grant program on Google, which, uh, provides free paid search credits to nonprofits. Then you're tracking your page search traffic to continue to track that track trends, patterns over time. But now you will begin to see in your referrals report, in your referrals report, you're gonna begin to seeing open [00:26:00] ai. You're gonna begin to see these new answer engines. And while you don't know the keywords that are sending this traffic and so on and so forth, it is important to keep track of the traffic because of two important reasons. One, one, you want to know how to highly prioritize. AEO. That's one reason. But the other reason I found George is syn is so freaking hard to rank in an answer engine. When people do come to my websites from Answer engine, the businesses I work with that is very high intent person, they tend to be very, very valuable because they gave the answer engine a very complex question to answer the answers. Engine said you. The right answer for it. So when I show up, I'm ready to buy, I'm ready to donate. I'm ready to do the action that I was looking for. So the percent of people who are coming from answer engines to your nonprofit carry significantly higher intention, and coming from Google, who also carry [00:27:00] intent. But this man, you stood out in an answer engine, you're a gift from God. Person coming thinks you're very important and is likely to engage in some sort of business with you. So I, even if it's like a hundred people, I care a lot about those a hundred people, even if it's not 10,000 at the moment. Does that make sense George? George Weiner: It does, and I think, I'm glad you pointed to, you know, the, the good old Google Analytics. I'm like, it has to be a way, and I, I think. I gave maximum effort to this problem inside of Google Analytics, and I'm still frustrated that search console is not showing me, and it's just blending it all together into one big soup. But. I want you to poke a hole in this thinking or say yes or no. You can create an AI channel, an AEO channel cluster together, and we have a guide on that cluster together. All of those types of referral traffic, as you mentioned, right from there. I actually know thanks to CloudFlare, the ratios of the amount of scrapes versus the actual clicks sent [00:28:00] for roughly 20, 30% of. Traffic globally. So is it fair to say I could assume like a 2% clickthrough or a 1% clickthrough, or even worse in some cases based on that referral and then reverse engineer, basically divide those clicks by the clickthrough rate and essentially get a rough share of voice metric on that platform? Yeah. Avinash Kaushik: So, so for, um, kind of, kind of at the moment, the problem is that unlike Google giving us some decent amount of data through webmaster tools. None of these LLMs are giving us any data. As a business owner, none of them are giving us any data. So we're relying on third parties like Tracker. We're relying on third parties like Evert Tune. You understand? How often are we showing up so we could get a damn click through, right? Right. We don't quite have that for now. So the AI Brand Index in Evert Tune comes the closest. Giving you some information we could use in the, so your thinking is absolutely right. Your recommendation is ly, right? Even if you can just get the number of clicks, even if you're tracking them very [00:29:00] carefully, it's very important. Please do exactly what you said. Make the channel, it's really important. But don't, don't read too much into the click-through rate bits, because we're missing the. We're missing a very important piece of information. Now remember when Google first came out, we didn't have tons of data. Um, and that's okay. These LLMs Pro probably will realize over time if they get into the advertising business that it's nice to give data out to other people, and so we might get more data. Until then, we are relying on these third parties that are hacking these tools to find us some data. So we can use it to understand, uh, some of the things we readily understand about keywords and things today related to Google. So we, we sadly don't have as much visibility today as we would like to have. George Weiner: Yeah. We really don't. Alright. I have, have a segment that I just invented. Just for you called Avanade's War Corner. And in Avanade's War Corner, I noticed that you go to war on various concepts, which I love because it brings energy and attention to [00:30:00] frankly data and finding answers in there. So if you'll humor me in our war corner, I wanna to go through some, some classic, classic avan. Um, all right, so can you talk to me a little bit about vanity metrics, because I think they are in play. Every day. Avinash Kaushik: Absolutely. No, no, no. Across the board, I think in whatever we do. So, so actually I'll, I'll, I'll do three. You know, so there's vanity metrics, activity metrics and outcome metrics. So basically everything goes into these three buckets essentially. So vanity metrics are, are the ones that are very easy to find, but them moving up and down has nothing to do with the number of donations you're gonna get as a nonprofit. They're just there to ease our ego. So, for example. Let's say we are a nonprofit and we run some display ads, so measure the number of impressions that were delivered for our display ad. That's a vanity metric. It doesn't tell you anything. You could have billions of impressions. You could have 10 impressions, doesn't matter, but it is easily [00:31:00] available. The count is easily available, so we report it. Now, what matters? What matters are, did anybody engage with the ad? What were the percent of people who hovered on the ad? What were the number of people who clicked on the ad activity metrics? Activity metrics are a little more useful than vanity metrics, but what does it matter for you as a non nonprofit? The number of donations you received in the last 24 hours. That's an outcome metric. Vanity activity outcome. Focus on activity to diagnose how well our campaigns or efforts are doing in marketing. Focus on outcomes to understand if we're gonna stay in business or not. Sorry, dramatic. The vanity metrics. Chasing is just like good for ego. Number of likes is a very famous one. The number of followers on a social paia, a very famous one. Number of emails sent is another favorite one. There's like a whole host of vanity metrics that are very easy to get. I cannot emphasize this enough, but when you unpack and or do meta-analysis of [00:32:00] relationship between vanity metrics and outcomes, there's a relationship between them. So we always advise people that. Start by looking at activity metrics to help you understand the user's behavior, and then move to understanding outcome metrics because they are the reason you'll thrive. You will get more donations or you will figure out what are the things that drive more donations. Otherwise, what you end up doing is saying. If I post provocative stuff on Facebook, I get more likes. Is that what you really wanna be doing? But if your nonprofit says, get me more likes, pretty soon, there's like a naked person on Facebook that gets a lot of likes, but it's corrupting. Yeah. So I would go with cute George Weiner: cat, I would say, you know, you, you get the generic cute cat. But yeah, same idea. The Internet's built on cats Avinash Kaushik: and yes, so, so that's why I, I actively recommend people stay away from vanity metrics. George Weiner: Yeah. Next up in War Corner, the last click [00:33:00] fallacy, right? The overweighting of this last moment of purchase, or as you'd maybe say in the do column of the See, think, do care. Avinash Kaushik: Yes. George Weiner: Yes. Avinash Kaushik: So when the, when the, when we all started to get Google Analytics, we got Adobe Analytics web trends, remember them, we all wanted to know like what drove the conversion. Mm-hmm. I got this donation for a hundred dollars. I got a donation for a hundred thousand dollars. What drove the conversion. And so what lo logically people would just say is, oh, where did this person come from? And I say, oh, the person came from Google. Google drove this conversion. Yeah, his last click analysis just before the conversion. Where did the person come from? Let's give them credit. But the reality is it turns out that if you look at consumer behavior, you look at days to donation, visits to donation. Those are two metrics available in Google. It turns out that people visit multiple times before [00:34:00] they make a donation. They may have come through email, their interest might have been triggered through your email. Then they suddenly remembered, oh yeah, yeah, I wanted to go to the nonprofit and donate something. This is Google, you. And then Google helps them find you and they come through. Now, who do you give credit Email or the Google, right? And what if you came 5, 7, 8, 10 times? So the last click fallacy is that it doesn't allow you to see the full consumer journey. It gives credit to whoever was the last person who sent you this, who introduced this person to your website. And so very soon we move to looking at what we call MTI, Multi-Touch Attribution, which is a free solution built into Google. So you just go to your multichannel funnel reports and it will help you understand that. One, uh, 150 people came from email. Then they came from Google. Then there was a gap of nine days, and they came back from Facebook and then they [00:35:00] converted. And what is happening is you're beginning to understand the consumer journey. If you understand the consumer journey better, we can come with better marketing. Otherwise, you would've said, oh, close shop. We don't need as many marketing people. We'll just buy ads on Google. We'll just do SEO. We're done. Oh, now you realize there's a more complex behavior happening in the consumer. They need to solve for email. You solve for Google, you need to solve Facebook. In my hypothetical example, so I, I'm very actively recommend people look at the built-in free MTA reports inside the Google nalytics. Understand the path flow that is happening to drive donations and then undertake activities that are showing up more often in the path, and do fewer of those things that are showing up less in the path. George Weiner: Bring these up because they have been waiting on my mind in the land of AEO. And by the way, we're not done with war. The war corner segment. There's more war there's, but there's more, more than time. But with both of these metrics where AEO, if I'm putting these glasses back on, comes [00:36:00] into play, is. Look, we're saying goodbye to frankly, what was probably somewhat of a vanity metric with regard to organic traffic coming in on that 10 facts about cube cats. You know, like, was that really how we were like hanging our hat at night, being like. Job done. I think there's very much that in play. And then I'm a little concerned that we just told everyone to go create an AEO channel on their Google Analytics and they're gonna come in here. Avinash told me that those people are buyers. They're immediately gonna come and buy, and why aren't they converting? What is going on here? Can you actually maybe couch that last click with the AI channel inbound? Like should I expect that to be like 10 x the amount of conversions? Avinash Kaushik: All we can say is it's, it's going to be people with high intention. And so with the businesses that I'm working with, what we are finding is that the conversion rates are higher. Mm. This game is too early to establish any kind of sense of if anybody has standards for AEO, they're smoking crack. Like the [00:37:00] game is simply too early. So what we I'm noticing is that in some cases, if the average conversion rate is two point half percent, the AEO traffic is converting at three, three point half. In two or three cases, it's converting at six, seven and a half. But there is not enough stability in the data. All of this is new. There's not enough stability in the data to say, Hey, definitely you can expect it to be double or 10% more or 50% more. We, we have no idea this early stage of the game, but, but George, if we were doing this again in a year, year and a half, I think we'll have a lot more data and we'll be able to come up with some kind of standards for, for now, what's important to understand is, first thing is you're not gonna rank in an answer engine. You just won't. If you do rank in an answer engine, you fought really hard for it. The person decided, oh my God, I really like this. Just just think of the user behavior and say, this person is really high intent because somehow [00:38:00] you showed up and somehow they found you and came to you. Chances are they're caring. Very high intent. George Weiner: Yeah. They just left a conversation with a super intelligent like entity to come to your freaking 2001 website, HTML CSS rendered silliness. Avinash Kaushik: Whatever it is, it could be the iffiest thing in the world, but they, they found me and they came to you and they decided that in the answer engine, they like you as the answer the most. And, and it took that to get there. And so all, all, all is I'm finding in the data is that they carry higher intent and that that higher intent converts into higher conversion rates, higher donations, as to is it gonna be five 10 x higher? It's unclear at the moment, but remember, the other reason you should care about it is. Every single day. As more people move away from Google search engines to answer engines, you're losing a ton of traffic. If somebody new showing up, treat them with, respect them with love. Treat them with [00:39:00] care because they're very precious. Just lost a hundred. Check the landing George Weiner: pages. 'cause you may be surprised where your front door is when complexity is bringing them to you, and it's not where you spent all of your design effort on the homepage. Spoiler. That's exactly Avinash Kaushik: right. No. Exactly. In fact, uh, the doping deeper into your websites is becoming even more prevalent with answer engines. Mm-hmm. Um, uh, than it used to be with search engines. The search always tried to get you the, the top things. There's still a lot of diversity. Your homepage likely is still only 30% of your traffic. Everybody else is landing on other homepage or as you call them, landing pages. So it's really, really important to look beyond your homepage. I mean, it was true yesterday. It's even truer today. George Weiner: Yeah, my hunch and what I'm starting to see in our data is that it is also much higher on the assisted conversion like it is. Yes. Yes, it is. Like if you have come to us from there, we are going to be seeing you again. That's right. That's right. More likely than others. It over indexes consistently for us there. Avinash Kaushik: [00:40:00] Yes. Again, it ties back to the person has higher intent, so if they didn't convert in that lab first session, their higher intent is gonna bring them back to you. So you are absolutely right about the data that you're seeing. George Weiner: Um, alright. War corner, the 10 90 rule. Can you unpack this and then maybe apply it to somebody who thinks that their like AI strategy is done? 'cause they spend $20 or $200 a month on some tool and then like, call it a day. 'cause they did ai. Avinash Kaushik: Yes, yes. No, it's, it's good. I, I developed it in context of analytics. When I was at my, uh, job at Intuit, I used to, I was at Intuit, senior director for research and analytics. And one of the things I found is people would consistently spend lots of money on tools in that time, web analytics tools, research tools, et cetera. And, uh, so they're spending a contract of a few hundred thousand dollars or hundreds of thousands of dollars, and then they give it to a fresh graduate to find insights. [00:41:00] I was like, wait, wait, wait. So you took this $300,000 thing and gave it to somebody. You're paying $45,000 a year. Who is young in their career, young in their career, and expecting them to make you tons of money using this tool? It's not the tool, it's the human. And so that's why I developed the the 10 90 rule, which is that if you have a, if you have a hundred dollars to invest in making smarter decisions, invest $10 in the tool, $90 in the human. We all have access to so much data, so much complexity. The world is changing so fast that it is the human that is going to figure out how to make sense of these insights rather than the tool magically spewing and understanding your business enough to tell you exactly what to do. So that, that's sort of where the 10 90 rule came from. Now, sort of we are in this, in this, um, this is very good for nonprofits by the way. So we're in this era. Where On the 90 side? No. So the 10, look, don't spend insane money on tools that is just silly. So don't do that. Now the 90, let's talk about the [00:42:00] 90. Up until two years ago, I had to spell all of the 90 on what I now call organic humans. You George Weiner: glasses wearing humans, huh? Avinash Kaushik: The development of LLM means that every single nonprofit in the world has access to roughly a third year bachelor's degree student. Like a really smart intern. For free. For free. In fact, in some instances, for some nonprofits, let's say I I just reading about this nonprofit that is cleaning up plastics in the ocean for this particular nonprofit, they have access to a p HT level environmentalist using the latest Chad GP PT 4.5, like PhD level. So the little caveat I'm beginning to put in the 10 90 rule is on the 90. You give the 90 to the human and for free. Get the human, a very smart Bachelor's student by using LLMs in some instances. Get [00:43:00] for free a very smart TH using the LLMs. So the LLMs have now to be incorporated into your research, into your analysis, into building a next dashboard, into building a next website, into building your next mobile game into whatever the hell you're doing for free. You can get that so you have your organic human. Less the synthetic human for free. Both of those are in the 90 and, and for nonprofit, so, so in my work at at Coach and Kate Spade. I have access now to a couple of interns who do free work for me, well for 20 minor $20 a month because I have to pay for the plus version of G bt. So the intern costs $20 a month, but I have access to this syn synthetic human who can do a whole lot of work for me for $20 a month in my case, but it could also do it for free for you. Don't forget synthetic humans. You no longer have to rely only on the organic humans to do the 90 part. You would be stunned. Upload [00:44:00] your latest, actually take last year's worth of donations, where they came from and all this data from you. Have a spreadsheet lying around. Dump it into chat. GPT, I'll ask it to analyze it. Help you find where most donations came from, and visualize trends to present to board of directors. It will blow your mind how good it is at do it with Gemini. I'm not biased, I'm just seeing chat. GPD 'cause everybody knows it so much Better try it with mistrial a, a small LLM from France. So I, I wanna emphasize that what has changed over the last year is the ability for us to compliment our organic humans with these synthetic entities. Sometimes I say synthetic humans, but you get the point. George Weiner: Yeah. I think, you know, definitely dump that spreadsheet in. Pull out the PII real quick, just, you know, make me feel better as, you know, the, the person who's gonna be promoting this to everybody, but also, you know, sort of. With that. I want to make it clear too, that like actually inside of Gemini, like Google for nonprofits has opened up access to Gemini for free is not a per user, per whatever. You have that [00:45:00] you have notebook, LLM, and these. Are sitting in their backyards for free every day and it's like a user to lose it. 'cause you have a certain amount of intelligence tokens a day. Can you, I just like wanna climb like the tallest tree out here and just start yelling from a high building about this. Make the case of why a nonprofit should be leveraging this free like PhD student that is sitting with their hands underneath their butts, doing nothing for them right now. Avinash Kaushik: No, it is such a shame. By the way, I cannot add to your recommendation in using your Gemini Pro account if it's free, on top of, uh, all the benefits you can get. Gemini Pro also comes with restrictions around their ability to use your data. They won't, uh, their ability to put your data anywhere. Gemini free versus Gemini Pro is a very protected environment. Enterprise version. So more, more security, more privacy, et cetera. That's a great benefit. And by the way, as you said, George, they can get it for free. So, um, the, the, the, the posture you should adopt is what big companies are doing, [00:46:00] which is anytime there is a job to be done, the first question you, you should ask is, can I make the, can an AI do the job? You don't say, oh, let me send it to George. Let me email Simon, let me email Sarah. No, no, no. The first thing that should hit your head is. I do the job because most of the time for, again, remember, third year bachelor's degree, student type, type experience and intelligence, um, AI can do it better than any human. So your instincts to be, let me outsource that kind of work so I can free up George's cycles for the harder problems that the AI cannot solve. And by the way, you can do many things. For example, you got a grant and now Meta allows you to run X number of ads for free. Your first thing, single it. What kind of ad should I create? Go type in your nonprofit, tell it the kind of things you're doing. Tell it. Tell it the donations you want, tell it the size, donation, want. Let it create the first 10 ads for you for free. And then you pick the one you like. And even if you have an internal [00:47:00] designer who makes ads, they'll start with ideas rather than from scratch. It's just one small example. Or you wanna figure out. You know, my email program is stuck. I'm not getting yield rates for donations. The thing I want click the button that called that is called deep research or thinking in the LL. Click one of those two buttons and then say, I'm really struggling. I'm at wits end. I've tried all these things. Write all the detail. Write all the detail about what you've tried and now working. Can you please give me three new ideas that have worked for nonprofits who are working in water conservation? Hmm. This would've taken a human like a few days to do. You'll have an answer in under 90 seconds. I just give two simple use cases where we can use these synthetic entities to send us, do the work for us. So the default posture in nonprofits should be, look, we're resource scrapped anyway. Why not use a free bachelor's degree student, or in some case a free PhD student to do the job, or at least get us started on a job. So just spending 10 [00:48:00] hours on it. We only spend the last two hours. The entity entity does the first date, and that is super attractive. I use it every single day in, in one of my browsers. I have three traps open permanently. I've got Claude, I've got Mistrial, I've got Charge GPT. They are doing jobs for me all day long. Like all day long. They're working for me. $20 each. George Weiner: Yeah, it's an, it, it, it's truly, it's an embarrassment of riches, but also getting back to the, uh, the 10 90 is, it's still sitting there. If you haven't brought that capacity building to the person on how to prompt how to play that game of linguistic tennis with these tools, right. They're still just a hammer on a. Avinash Kaushik: That's exactly right. That's exactly right. Or, or in your case, you, you have access to Gemini for nonprofits. It's a fantastic tool. It's like a really nice card that could take you different places you insist on cycling everywhere. It's, it's okay cycle once in a while for health reasons. Otherwise, just take the car, it's free. George Weiner: Ha, you've [00:49:00] been so generous with your time. Uh, I do have one more quick war. If you, if you have, have a minute, uh, your war on funnels, and maybe this is not. Fully fair. And I am like, I hear you yelling at me every time I'm showing our marketing funnel. And I'm like, yeah, but I also have have a circle over here. Can you, can you unpack your war on funnels and maybe bring us through, see, think, do, care and in the land of ai? Avinash Kaushik: Yeah. Okay. So the marketing funnel is very old. It's been around for a very long time, and once I, I sort of started working at Google, access to lots more consumer research, lots more consumer behavior. Like 20 years ago, I began to understand that there's no such thing as funnel. So what does the funnel say? The funnel says there's a group of people running around the world, they're not aware of your brand. Find them, scream at them, spray and pray advertising at them, make them aware, and then somehow magically find the exact same people again and shut them down the fricking funnel and make them consider your product.[00:50:00] And now that they're considering, find them again, exactly the same people, and then shove them one more time. Move their purchase index and then drag them to your website. The thing is this linearity that there's no evidence in the universe that this linearity exists. For example, uh, I'm going on a, I like long bike rides, um, and I just got thirsty. I picked up the first brand. I could see a water. No awareness, no consideration, no purchase in debt. I just need water. A lot of people will buy your brand because you happen to be the cheapest. I don't give a crap about anything else, right? So, um, uh, uh, the other thing to understand is, uh, one of the brands I adore and have lots of is the brand. Patagonia. I love Patagonia. I, I don't use the word love for I think any other brand. I love Patagonia, right? For Patagonia. I'm always in the awareness stage because I always want these incredible stories that brand ambassadors tell about how they're helping the environment. [00:51:00] I have more Patagonia products than I should have. I'm already customer. I'm always open to new considerations of Patagonia products, new innovations they're bringing, and then once in a while, I'm always in need to buy a Patagonia product. I'm evaluating them. So this idea that the human is in one of these stages and your job is to shove them down, the funnel is just fatally flawed, no evidence for it. Instead, what you want to do is what is Ash's intent at the moment? He would like environmental stories about how we're improving planet earth. Patagonia will say, I wanna make him aware of my environmental stories, but if they only thought of marketing and selling, they wouldn't put me in the awareness because I'm already a customer who buys lots of stuff from already, right? Or sometimes I'm like, oh, I'm, I'm heading over to London next week. Um, I need a thing, jacket. So yeah, consideration show up even though I'm your customer. So this seating do care is a framework that [00:52:00] says, rather than shoving people down things that don't exist and wasting your money, your marketing should be able to discern any human's intent and then be able to respond with a piece of content. Sometimes that piece of content in an is an ad. Sometimes it's a webpage, sometimes it's an email. Sometimes it's a video. Sometimes it's a podcast. This idea of understanding intent is the bedrock on which seat do care is built about, and it creates fully customer-centric marketing. It is harder to do because intent is harder to infer, but if you wanna build a competitive advantage for yourself. Intent is the magic. George Weiner: Well, I think that's a, a great point to, to end on. And again, so generous with, uh, you know, all the work you do and also supporting nonprofits in the many ways that you do. And I'm, uh, always, always watching and seeing what I'm missing when, um, when a new, uh, AKA's Razor and Newsletter come out. So any final sign off [00:53:00] here on how do people find you? How do people help you? Let's hear it. Avinash Kaushik: You can just Google or answer Engine Me. It's, I'm not hard. I hard to find, but if you're a nonprofit, you can sign up for my newsletter, TMAI marketing analytics newsletter. Um, there's a free one and a paid one, so you can just sign up for the free one. It's a newsletter that comes out every five weeks. It's completely free, no strings or anything. And that way I'll be happy to share my stories around better marketing and analytics using the free newsletter for you so you can sign up for that. George Weiner: Brilliant. Well, thank you so much, Avan. And maybe, maybe we'll have to take you up on that offer to talk sometime next year and see, uh, if maybe we're, we're all just sort of, uh, hanging out with synthetic humans nonstop. Thank you so much. It was fun, George. [00:54:00]

We break down one of the busiest AI news days of the year and focus on what it means for colleges. We cover Google's Genie 3 “world model,” OpenAI's new open-weight reasoning models (GPT-OSS 120B/20B), and Anthropic's Opus 4.1 gains for coding agents. Then we shift to the big story for campuses: ChatGPT “Study Mode” and Gemini “Guided Learning,” plus Google's free Gemini Pro for students and a $1B education push. If you run marketing, admissions, or student success, this episode helps you plan pilots for fall, cut model costs, and rethink onboarding and tutoring with AI.Cold open + timestamp and setup (00:00:00)JC's line: “If ChatGPT talks, Genie walks.”We set the date: recorded Wed, Aug 6, referencing news from Aug 5.Quick heads-up that GPT-5 may land this week.What dropped: three models, three angles (00:02:00)Anthropic: Claude Opus 4.1 with coding gains.OpenAI: open-weight reasoning models (GPT-OSS 120B/20B).Google: Genie 3 “world model.”Main focus today will be study features for learning.OpenAI's open weights: why now and why it helps (00:06:00)Pressure from R1-style models and a growing OSS wave.Open weights expand the dev base and enable on-prem or offline builds.Cost note: we discuss ~91% cheaper runs via alt providers like Cerebras/Groq in some workflows.Takeaway for schools and vendors: cheaper agents and less lock-in.Anthropic's Opus 4.1: coding agents get sharper (00:10:40)Better long-context reasoning and tool use.Stronger at “find the right file, make the right change, don't break other parts.”Expect Cursor/Vibe/Copilot-style tools to feel snappier.Good fit for campus IT and rapid feature fixes.Genie 3 explained in plain terms (00:16:14)What a “world model” is: generates an interactive environment with physics and memory, not just frames.Why it's different from diffusion/video models: it keeps state and acts over time.Why it matters: training agents, robotics, labs, and rich simulations.Use cases for learning: labs, history, and more (00:25:27)Think virtual physics labs, time-period scenes, or fieldwork-style tasks.Pricing and access still unclear at record time.Gemini “Guided Learning” lands (00:27:52)Moves past one-shot Q&A to a step-by-step teach mode.Based on a learning-tuned model family (LearnLM) now inside Gemini.Students get free Gemini Pro for 12 months in select countries; NotebookLM shout-out.Why the free student play matters (00:29:28)Classic “win them early” motion; boosts daily use and skills.Helpful for course work, capstones, and research support.ChatGPT “Study Mode”: how it works (00:33:52)Interactive prompts, hints, and self-reflection.Scaffolded answers to cut overwhelm on hard topics.Personalized support, knowledge checks, and progress cues.Quick toggle in and out of study mode mid chat.Simple example that sells it (00:40:05)Ask “What is life?”Regular mode gives a direct answer; Study Mode first asks what angle you mean (bio, philosophy, personal), then guides you forward.Slows you down in a good way to build real understanding.What's next for study features (00:40:59)Clearer visuals for complex ideas.Goal setting and progress across chats.Deeper personalization by skill level.Google's $1B education push (00:42:26)Funding over three years for AI literacy, research, and cloud.“AI for Education” accelerator with free training and career certs.Schools should apply and point students to the free Pro offer.Big picture for campuses (00:45:52)Vendors are playing the long game on learning use cases.Leaders should plan training and policy now, not later.Close and next watch-items (00:47:25)Net: faster models are nice, useful models change outcomes.We'll revisit once GPT-5 news lands; send us topics to cover. - - - -Connect With Our Co-Hosts:Ardis Kadiuhttps://www.linkedin.com/in/ardis/https://twitter.com/ardisDr. JC Bonillahttps://www.linkedin.com/in/jcbonilla/https://twitter.com/jbonillxAbout The Enrollify Podcast Network:Generation AI is a part of the Enrollify Podcast Network. If you like this podcast, chances are you'll like other Enrollify shows too! Enrollify is made possible by Element451 — The AI Workforce Platform for Higher Ed. Learn more at element451.com.

In this episode, we talk about AI (and other things)! We discuss the growing concerns surrounding school surveillance tools, examining case studies where innocent student jokes have led to harsh outcomes due to automated threat detection. Shifting gears, we look at the availability of AI tools like Gemini Pro and ChatGPT for college students, including student discount programs. Also, we analyze a recent Common Sense Media report on AI teacher assistants, discussing their moderate risk rating, potential for invisible influence, concerns about novice teachers taking content as fact, and the risks associated with using AI for high-stakes circumstances like IEP creation or grading.    Much of the episode is spent unpacking Jay's K12TechPro survey regarding Gemini and NotebookLM in classrooms, revealing current district policies on AI use for staff and students, and the presence (or absence) of board policies.   Referenced URLs: https://www.washingtonpost.com/business/2025/08/07/ai-school-surveillance-gaggle-goguardian-bark/473cb556-737e-11f0-84e0-485bb531abeb_story.html https://apnews.com/article/ai-school-surveillance-gaggle-goguardian-bark-8c531cde8f9aee0b1ef06cfce109724a https://gemini.google/students/ https://help.openai.com/en/articles/10986084-student-discounts-for-chatgpt-terms-of-service https://www.commonsensemedia.org/sites/default/files/featured-content/files/csm-ai-risk-assessment-ai-teacher-assistants-final.pdf 00:00:00-Intro 00:14:21-Gemini & ChatGPT Student Promo 00:16:00-Surveilling Students 00:19:15-Common Sense Media - Bias in AI 00:25:43-Are you enabling AI for students? -------------------- PowerGistics Lightspeed (Check out Signal!) Fortinet -------------------- Join the K12TechPro Community (exclusively for K12 Tech professionals) Buy some swag (shirts, hoodies...)!!! Email us at k12techtalk@gmail.com OR our "professional" email addy is info@k12techtalkpodcast.com Call us at 314-329-0363 X @k12techtalkpod Facebook Visit our LinkedIn Music by Colt Ball Disclaimer: The views and work done by Josh, Chris, and Mark are solely their own and do not reflect the opinions or positions of sponsors or any respective employers or organizations associated with the guys. K12 Tech Talk itself does not endorse or validate the ideas, views, or statements expressed by Josh, Chris, and Mark's individual views and opinions are not representative of K12 Tech Talk. Furthermore, any references or mention of products, services, organizations, or individuals on K12 Tech Talk should not be considered as endorsements related to any employer or organization associated with the guys.

Ever wished your AI could actually do things directly from your terminal, beyond just chatting? Google's new Gemini CLI is here, and it's a game-changer! Unlike previous closed-source tools, this open-source power tool brings the intelligence of Gemini Pro right to your command line. We're talking direct file system access, automated project setups, and a powerful "reason and react" loop that lets AI analyze, plan, and execute tasks on your machine. Perfect for DevOps, developers, and anyone ready to automate their workflow. Is your terminal ready for its new brain?

An airhacks.fm conversation with Jonathan Ellis (@spyced) about: brokk AI tool for code generation named after Norse god of the forge, AI as complement to experienced programmers' skillsets, age and productivity in programming, transition from JVector to working on Cassandra codebase, challenges with AI in large codebases with extensive context, building tools for historical Java codebases, comparison of productivity between younger and older programmers, brute force coding vs experienced approach, reading code quickly as a senior skill, AI generating nested if-else statements vs better structures, context sculpting in Brokk, open source nature of Brokk, no black boxes philosophy, surfacing AI context to users, automatic context pulling with manual override options, importing dependencies and decompiling JARs for context, syntax tree based summarization, Maven and Gradle dependency handling, unique Java-specific features, multiple AI model support simultaneously, Claude vs Gemini Pro performance differences, Git history as context source, capturing commits and diffs for regression analysis, migration analysis between commits, AI code review and technical debt cleanup, style for code style guidelines, using modern Java features like var and Streams, Error Prone and NullAway integration for code quality, comparison with Cursor's primitive features, branching conversation history, 80% time in Brokk vs 20% in IntelliJ workflow, sketching package structures for AI guidance, data structures guiding algorithms, Git browser by file and commit, unified diff as context, reflection moving away from due to tooling opacity, Jackson serialization refactoring with DTOs, enterprise features like session sync and sharing, unified API key management, rate limit advantages, parallel file processing with upgrade agent, LiteLLM integration for custom models, pricing model based on credits not requests, $20/month subscription with credits, free tier models like Grok 3 Mini and DeepSeek V3, architect mode for autonomous code generation, code button for smaller problems with compile-test loop, ask button for planning complex implementations, senior vs junior programmer AI effectiveness, self-editing capability achieved early in development, no vector search usage despite JVector background Jonathan Ellis on twitter: @spyced

As notícias de hoje incluem a Meta, dona do Facebook, Instagram e WhatsApp, pedindo permissão para acessar a galeria do seu celular e processar imagens usando IA, a Amazon começando a agir contra apps de pirataria de streaming que sempre rodaram nos Fire TV Stick. Tem um estudo de uma grande empresa privada indicando que a IA pode contribuir com R$ 2,1 trilhões ao PIB do Brasil desde que as companhias tomem os devidos cuidados. A Google finalmente liberando a programação de ações agendadas que você pode configurar para o Gemini fazer para você depois. Falando nisso, agora é a última chance para quem é estudante conseguir 1 ano e três meses do Gemini Pro totalmente de graça, o que eu também vou explicar no programa.

OpenAI, Google & Anthropic are all eating different parts of the business & creative worlds but where does that leave us? For only 25 cents, you too can sponsor a human in a world of AGI. In the big news this week, OpenAI's takes on Microsoft Office, Google's cutting the cost of AI coding with their new Google CLI (Command Line Interface) and dropped an on-device robotics platform. Oh, and Anthropic just won a massive lawsuit around AI training and fair use. Plus, Tesla's rocky rollout of their Robotaxis, Eleven Labs' new MCP-centric 11ai voice agent, Runway's Game Worlds, the best hacker in the world in now an AI bot AND Gavin defends AI slop. US HUMANS AIN'T GOING AWAY. UNLESS THE AI GIVES US ENDLESS TREATS.  #ai #ainews #openai Join the discord: https://discord.gg/muD2TYgC8f Join our Patreon: https://www.patreon.com/AIForHumansShow AI For Humans Newsletter: https://aiforhumans.beehiiv.com/ Follow us for more on X @AIForHumansShow Join our TikTok @aiforhumansshow To book us for speaking, please visit our website: https://www.aiforhumans.show/ // Show Links //   OpenAI Developing Microsoft Office / Google Workplace Competitor https://www.theinformation.com/articles/openai-quietly-designed-rival-google-workspace-microsoft-office?rc=c3oojq OpenAI io / trademark drama:  https://www.theguardian.com/technology/2025/jun/23/openai-jony-ive-io-amid-trademark-iyo Sam's receipts from Jason Rugolo (founder of iYo the headphone company) https://x.com/sama/status/1937606794362388674 Google's OpenSource Comand Line Interface for Gemini is Free? https://blog.google/technology/developers/introducing-gemini-cli-open-source-ai-agent/ 1000 free Gemini Pro 2.5 requests per day https://x.com/OfficialLoganK/status/1937881962070364271 Anthropic's Big AI Legal Win  https://www.reuters.com/legal/litigation/anthropic-wins-key-ruling-ai-authors-copyright-lawsuit-2025-06-24/ More detail: https://x.com/AndrewCurran_/status/1937512454835306974 Gemini's On Device Robotics https://deepmind.google/discover/blog/gemini-robotics-on-device-brings-ai-to-local-robotic-devices/ AlphaGenome: an AI model to help scientists better understand our DNA https://x.com/GoogleDeepMind/status/1937873589170237738 Tesla Robotaxi Roll-out https://www.cnbc.com/2025/06/23/tesla-robotaxi-incidents-caught-on-camera-in-austin-get-nhtsa-concern.html Kinda Scary Looking: https://x.com/binarybits/status/1936951664721719383 Random slamming of brakes: https://x.com/JustonBrazda/status/1937518919062856107 Mira Murati's Thinking Machines Raises $2B Seed Round https://thinkingmachines.ai/ https://www.theinformation.com/articles/ex-openai-cto-muratis-startup-plans-compete-openai-others?rc=c3oojq&shared=2c64512f9a1ab832 Eleven Labs 11ai Voice Assistant https://x.com/elevenlabsio/status/1937200086515097939 Voice Design for V3 JUST RELEASED: https://x.com/elevenlabsio/status/1937912222128238967 Runway's Game Worlds  https://x.com/c_valenzuelab/status/1937665391855120525 Example: https://x.com/aDimensionDoor/status/1937651875408675060 AI Dungeon https://aidungeon.com/ The Best Hacker in the US in now an autonomous AI bot https://www.pcmag.com/news/this-ai-is-outranking-humans-as-a-top-software-bug-hunter https://x.com/Xbow/status/1937512662859981116 Simple & Good AI Work Flow From AI Warper https://x.com/AIWarper/status/1936899718678008211 RealTime Natural Language Photo Editing https://x.com/zeke/status/1937267796146290952 Bunker J Squirrel https://www.tiktok.com/t/ZTjc3hb38/ Bigfoot Sermons https://www.tiktok.com/t/ZTjcEq17Y/ John Oliver's Episode about AI Slop https://youtu.be/TWpg1RmzAbc?si=LAdktGWlIVVDqAjR Jabba Kisses Han https://www.reddit.com/r/CursedAI/comments/1ljjdw3/what_the_hell_am_i_looking_at/  

Nabeel Qureshi is an entrepreneur, writer, researcher, and visiting scholar of AI policy at the Mercatus Center (alongside Tyler Cowen). Previously, he spent nearly eight years at Palantir, working as a forward-deployed engineer. His work at Palantir ranged from accelerating the Covid-19 response to applying AI to drug discovery to optimizing aircraft manufacturing at Airbus. Nabeel was also a founding employee and VP of business development at GoCardless, a leading European fintech unicorn.What you'll learn:• Why almost a third of all Palantir's PMs go on to start companies• How the “forward-deployed engineer” model works and why it creates exceptional product leaders• How Palantir transformed from a “sparkling Accenture” into a $200 billion data/software platform company with more than 80% margins• The unconventional hiring approach that screens for independent-minded, intellectually curious, and highly competitive people• Why the company intentionally avoids traditional titles and career ladders—and what they do instead• Why they built an ontology-first data platform that LLMs love• How Palantir's controversial “bat signal” recruiting strategy filtered for specific talent types• The moral case for working at a company like Palantir—Brought to you by:• WorkOS—Modern identity platform for B2B SaaS, free up to 1 million MAUs• Attio—The powerful, flexible CRM for fast-growing startups• OneSchema—Import CSV data 10x faster—Where to find Nabeel S. Qureshi:• X: https://x.com/nabeelqu• LinkedIn: https://www.linkedin.com/in/nabeelqu/• Website: https://nabeelqu.co/—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction to Nabeel S. Qureshi(05:10) Palantir's unique culture and hiring(13:29) What Palantir looks for in people(16:14) Why they don't have titles(19:11) Forward-deployed engineers at Palantir(25:23) Key principles of Palantir's success(30:00) Gotham and Foundry(36:58) The ontology concept(38:02) Life as a forward-deployed engineer(41:36) Balancing custom solutions and product vision(46:36) Advice on how to implement forward-deployed engineers(50:41) The current state of forward-deployed engineers at Palantir(53:15) The power of ingesting, cleaning and analyzing data(59:25) Hiring for mission-driven startups(01:05:30) What makes Palantir PMs different(01:10:00) The moral question of Palantir(01:16:03) Advice for new startups(01:21:12) AI corner(01:24:00) Contrarian corner(01:25:42) Lightning round and final thoughts—Referenced:• Reflections on Palantir: https://nabeelqu.co/reflections-on-palantir• Palantir: https://www.palantir.com/• Intercom: https://www.intercom.com/• Which companies produce the best product managers: https://www.lennysnewsletter.com/p/which-companies-produce-the-best• Gotham: https://www.palantir.com/platforms/gotham/• Foundry: https://www.palantir.com/platforms/foundry/• Peter Thiel on X: https://x.com/peterthiel• Alex Karp: https://en.wikipedia.org/wiki/Alex_Karp• Stephen Cohen: https://en.wikipedia.org/wiki/Stephen_Cohen_(entrepreneur)• Joe Lonsdale on LinkedIn: https://www.linkedin.com/in/jtlonsdale/• Tyler Cowen's website: https://tylercowen.com/• This Scandinavian City Just Won the Internet With Its Hilarious New Tourism Ad: https://www.afar.com/magazine/oslos-new-tourism-ad-becomes-viral-hit• Safe Superintelligence: https://ssi.inc/• Mira Murati on X: https://x.com/miramurati• Stripe: https://stripe.com/• Building product at Stripe: craft, metrics, and customer obsession | Jeff Weinstein (Product lead): https://www.lennysnewsletter.com/p/building-product-at-stripe-jeff-weinstein• Airbus: https://www.airbus.com/en• NIH: https://www.nih.gov/• Jupyter Notebooks: https://jupyter.org/• Shyam Sankar on LinkedIn: https://www.linkedin.com/in/shyamsankar/• Palantir Gotham for Defense Decision Making: https://www.youtube.com/watch?v=rxKghrZU5w8• Foundry 2022 Operating System Demo: https://www.youtube.com/watch?v=uF-GSj-Exms• SQL: https://en.wikipedia.org/wiki/SQL• Airbus A350: https://en.wikipedia.org/wiki/Airbus_A350• SAP: https://www.sap.com/index.html• Barry McCardel on LinkedIn: https://www.linkedin.com/in/barrymccardel/• Understanding ‘Forward Deployed Engineering' and Why Your Company Probably Shouldn't Do It: https://www.barry.ooo/posts/fde-culture• David Hsu on LinkedIn: https://www.linkedin.com/in/dvdhsu/• Retool's Path to Product-Market Fit—Lessons for Getting to 100 Happy Customers, Faster: https://review.firstround.com/retools-path-to-product-market-fit-lessons-for-getting-to-100-happy-customers-faster/• How to foster innovation and big thinking | Eeke de Milliano (Retool, Stripe): https://www.lennysnewsletter.com/p/how-to-foster-innovation-and-big• Looker: https://cloud.google.com/looker• Sorry, that isn't an FDE: https://tedmabrey.substack.com/p/sorry-that-isnt-an-fde• Glean: https://www.glean.com/• Limited Engagement: Is Tech Becoming More Diverse?: https://www.bkmag.com/2017/01/31/limited-engagement-creating-diversity-in-the-tech-industry/• Operation Warp Speed: https://en.wikipedia.org/wiki/Operation_Warp_Speed• Mark Zuckerberg testifies: https://www.businessinsider.com/facebook-ceo-mark-zuckerberg-testifies-congress-libra-cryptocurrency-2019-10• Anduril: https://www.anduril.com/• SpaceX: https://www.spacex.com/• Principles: https://nabeelqu.co/principles• Wispr Flow: https://wisprflow.ai/• Claude code: https://docs.anthropic.com/en/docs/agents-and-tools/claude-code/overview• Gemini Pro 2.5: https://deepmind.google/technologies/gemini/pro/• DeepMind: https://deepmind.google/• Latent Space newsletter: https://www.latent.space/• Swyx on x: https://x.com/swyx• Neural networks in chess programs: https://www.chessprogramming.org/Neural_Networks• AlphaZero: https://en.wikipedia.org/wiki/AlphaZero• The top chess players in the world: https://www.chess.com/players• Decision to Leave: https://www.imdb.com/title/tt12477480/• Oldboy: https://www.imdb.com/title/tt0364569/• Christopher Alexander: https://en.wikipedia.org/wiki/Christopher_Alexander—Recommended books:• The Technological Republic: Hard Power, Soft Belief, and the Future of the West: https://www.amazon.com/Technological-Republic-Power-Belief-Future/dp/0593798694• Zero to One: Notes on Startups, or How to Build the Future: https://www.amazon.com/Zero-One-Notes-Startups-Future/dp/0804139296• Impro: Improvisation and the Theatre: https://www.amazon.com/Impro-Improvisation-Theatre-Keith-Johnstone/dp/0878301178/• William Shakespeare: Histories: https://www.amazon.com/Histories-Everymans-Library-William-Shakespeare/dp/0679433120/• High Output Management: https://www.amazon.com/High-Output-Management-Andrew-Grove/dp/0679762884• Anna Karenina: https://www.amazon.com/Anna-Karenina-Leo-Tolstoy/dp/0143035002—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.lennysnewsletter.com/subscribe

OpenAI's strategic appointment of Instacart CEO Fidji Simo to lead its applications division and its global "Stargate" initiative to build sovereign AI infrastructure with national governments. Several articles touch on the potential for AI to reshape technology and society, including Apple's contemplation of a future beyond the iPhone due to AI advancements and Meta's development of "super-sensing" AI glasses with potential facial recognition. The text also covers policy shifts, specifically the Trump administration's plan to roll back Biden-era AI chip export restrictions. Furthermore, the sources describe new AI-powered products and features from companies like Figma, Stripe, Superhuman, and Mistral AI, showcasing the increasing integration of AI into design, finance, communication, and enterprise solutions.

This podcast discuss the rapidly advancing field of de-extinction, highlighting the crucial role of artificial intelligence (AI) in making this a tangible scientific pursuit. AI is presented not merely as a tool but as an architect across all stages, from reconstructing degraded ancient DNA and predicting gene function to optimising gene editing and modelling ecological impacts. While companies like Colossal Biosciences pursue ambitious projects for species like the woolly mammoth and dire wolf, often driving technological innovation with commercial spin-offs, organisations like Revive & Restore focus on genetic rescue for endangered species, illustrating differing approaches within this landscape. The podcast underscore the significant technical, ecological, and ethical challenges inherent in de-extinction, particularly concerning animal welfare, resource allocation, and potential ecological disruption, while also pointing to valuable spillover innovations benefiting broader conservation and human health.Get the eBook at Google Play https://play.google.com/store/search?q=etienne%20noumen%27&c=books

Significant developments include Amazon's introduction of a tactile warehouse robot named Vulcan and Google's Gemini 2.5 Pro reportedly topping AI leaderboards, highlighting progress in automation and model performance. Strategically, OpenAI is planning to reduce revenue share with partners like Microsoft and also launching an initiative to help nations build AI infrastructure. Meanwhile, Apple is considering AI search partners for Safari amid declining Google usage, and AI is being used in innovative ways, such as AI-powered drones for medical delivery and the recreation of a road rage victim for a court statement. Finally, HeyGen is enhancing AI avatars with emotional expression, and platforms like Zapier are enabling users to create personal AI assistants, indicating broader application and accessibility of AI technology.

This podcast details how AI-powered autonomous drones are transforming global logistics, particularly for delivering essential medical supplies in challenging environments. The podcast highlights Zipline as a key player, discussing its pioneering work in countries like Rwanda and Ghana where drone delivery has shown significant improvements in healthcare outcomes and efficiency.

This episode highlight OpenAI's significant structural shift to retain non-profit control while acquiring an AI coding startup and addressing model sycophancy. Furthermore, the texts cover Waymo's expansion of robotaxi production with a new factory and Canva's entry into spreadsheets with an AI-powered tool. Finally, they touch upon the growing urgency for AI education in schools, as advocated by tech leaders, and Nvidia's contribution to open-source AI with a high-performance transcription model, along with a warning from Fiverr's CEO about AI's impact on jobs.

This podcast and sources discuss the growing issue of plastic pollution and the limitations of traditional recycling methods. They introduce the discovery of plastic-eating microbes and their enzymes as a promising alternative for degrading plastics. Crucially, the text explains how Artificial Intelligence (AI)is being employed to significantly enhance the effectiveness of these enzymes, making them faster and more stable for industrial applications. The document highlights successful AI-engineered enzymes like FAST-PETase for achieving true circularity by breaking plastics down to their original monomers, and outlines the environmental and economic benefits of this approach. However, the sources also acknowledge the significant scientific, engineering, economic, and regulatory challenges that must be overcome for large-scale adoption of this technology.

Significant developments include the launch of specialised AI agents for scientific research by FutureHouse and the integration of AI coding assistants into Apple's Xcode environment through a partnership with Anthropic. Google's activities are also prominent, ranging from their strategies to address AI's energy demands and workforce needs to the successful, albeit assisted, completion of the game Pokémon Blue by their Gemini AI. Furthermore, the reports touch on the increasing recognition of AI's role in creative works by the US Copyright Office and the economic implications of AI infrastructure costs, partly attributed to tariffs, as noted by Meta. Overall, the text underscores the expanding capabilities of AI, the practical applications across various sectors, and the associated infrastructure and policy challenges.

The podcast discusses Conformal Prediction (CP) as a method for enhancing the reliability of AI in medical diagnosis by providing rigorous uncertainty quantification. It explains that unlike traditional AI which gives single predictions, CP produces a set of possible outcomes with a guaranteed probability of containing the true answer, addressing the critical need for trustworthy AI in healthcare. The text explores the foundational concepts of CP, compares it to other uncertainty quantification techniques, highlights advanced CP methods for more nuanced guarantees, and surveys its diverse applications in medical imaging, genomics, clinical risk prediction, and drug discovery. Finally, it examines the challenges of clinical integration, the need for human-AI interaction, and the ethical and regulatory dimensions, positioning CP as a vital tool for the safe and effective deployment of AI in medicine despite requiring further research and adaptation for practical success.Source: https://machinelearningcertification.web.app/Conformal_Classification_in_Medical_Diagnosis.pdf

Key themes include technological competition and national self-reliance with Huawei and China challenging Nvidia and US dominance in AI chips, and major product updates and releases from companies like Baidu, OpenAI, and Grok introducing new AI models and features. The text also highlights innovative applications of AI, from Neuralink's brain implants restoring communication and Waymo considering selling robotaxis directly to consumers, to creative uses like generating action figures and integrating AI into religious practices. Finally, the sources touch on important considerations surrounding AI, such as the need for interpretability to ensure safety, the increasing sophistication of AI-powered scams, and discussions on the military implications and future potential of AGI.

Ege Erdil and Tamay Besiroglu have 2045+ timelines, think the whole "alignment" framing is wrong, don't think an intelligence explosion is plausible, but are convinced we'll see explosive economic growth (economy literally doubling every year or two).This discussion offers a totally different scenario than my recent interview with Scott and Daniel.Ege and Tamay are the co-founders of Mechanize, a startup dedicated to fully automating work. Before founding Mechanize, Ege and Tamay worked on AI forecasts at Epoch AI.Watch on Youtube; listen on Apple Podcasts or Spotify.----------Sponsors* WorkOS makes it easy to become enterprise-ready. With simple APIs for essential enterprise features like SSO and SCIM, WorkOS helps companies like Vercel, Plaid, and OpenAI meet the requirements of their biggest customers. To learn more about how they can help you do the same, visit workos.com* Scale's Data Foundry gives major AI labs access to high-quality data to fuel post-training, including advanced reasoning capabilities. If you're an AI researcher or engineer, learn about how Scale's Data Foundry and research lab, SEAL, can help you go beyond the current frontier at scale.com/dwarkesh* Google's Gemini Pro 2.5 is the model we use the most at Dwarkesh Podcast: it helps us generate transcripts, identify interesting clips, and code up new tools. If you want to try it for yourself, it's now available in Preview with higher rate limits! Start building with it today at aistudio.google.com.----------Timestamps(00:00:00) - AGI will take another 3 decades(00:22:27) - Even reasoning models lack animal intelligence (00:45:04) - Intelligence explosion(01:00:57) - Ege & Tamay's story(01:06:24) - Explosive economic growth(01:33:00) - Will there be a separate AI economy?(01:47:08) - Can we predictably influence the future?(02:19:48) - Arms race dynamic(02:29:48) - Is superintelligence a real thing?(02:35:45) - Reasons not to expect explosive growth(02:49:00) - Fully automated firms(02:54:43) - Will central planning work after AGI?(02:58:20) - Career advice Get full access to Dwarkesh Podcast at www.dwarkesh.com/subscribe

Google's AI efforts & Gemini Pro 2.5 take a major step forward with updates to Deep Research, new Agent2Agent protocol (A2A) & more. Sadly, OpenAI teases o3 and o4 but delays GPT-5.  Plus, Meta's new Llama 4 models are out but have issues, Midjourney v7's debut, John Carmack's smackdown of an AI video game engine hater, Gavin's deep dive into OpenAI 4o Image Generation formats & the weirdest robot horse concept you've ever seen.  WE'RE DEEP RESEARCHING OUR ENTIRE LIVES RIGHT NOW  Join the discord: https://discord.gg/muD2TYgC8f Join our Patreon: https://www.patreon.com/AIForHumansShow AI For Humans Newsletter: https://aiforhumans.beehiiv.com/ Follow us for more on X @AIForHumansShow Join our TikTok @aiforhumansshow To book us for speaking, please visit our website: https://www.aiforhumans.show/   // Show Links // Google Cloud 25 Live Stream “A New Way To Cloud!” https://youtu.be/Md4Fs-Zc3tg Google Cloud Blog Post https://blog.google/products/google-cloud/next-2025/ Upgraded Deep Research Out Preforms OpenAI Deep Research https://x.com/GeminiApp/status/1909721519724339226 Google's Deep Research Vs OpenAI Deep Research https://x.com/testingcatalog/status/1909727195402027183 New Ironwood TPUs https://blog.google/products/google-cloud/ironwood-tpu-age-of-inference/ Gavin's Experiences Google Gemini Deep Research: Baltro Test: https://x.com/AIForHumansShow/status/1909813850817675424 KP Biography: https://g.co/gemini/share/7b7bdb2c400e Agent2Agent Protocol https://developers.googleblog.com/en/a2a-a-new-era-of-agent-interoperability/ Google Paying Some AI Stuff To Do Nothing Rather Than Work For Rivals https://x.com/TechCrunch/status/1909368948862181584 Solar Glow Meditations on AI http://tiktok.com/@solarglowmeditations/video/7491038509214518559?_t=ZT-8vNNgF7QpyM&_r=1 o4-mini & o3 coming before GPT-5 in shift from Sam Altman https://x.com/sama/status/1908167621624856998 OpenAI Strategic Deployment Team (new role to prep for AGI) https://x.com/aleks_madry/status/1909686225658695897 AI 2027 Paper https://ai-2027.com/ Llama 4 is here… but how good is it? https://ai.meta.com/blog/llama-4-multimodal-intelligence/ Controversy Around Benchmarks: https://gizmodo.com/meta-cheated-on-ai-benchmarks-and-its-a-glimpse-into-a-new-golden-age-2000586433 Deep dive on issues from The Information  https://www.theinformation.com/articles/llama-4s-rocky-debut?rc=c3oojq&shared=3bbd9f72303888e2 Midjourney v7 Is Here and it's… just ok? https://www.midjourney.com/updates/v7-alpha John Carmack Defends AI Video Games https://x.com/ID_AA_Carmack/status/1909311174845329874 Tim Sweeney Weighs In https://x.com/TimSweeneyEpic/status/1909314230391902611 New Test-time-training = 1 Min AI Video From a Single Prompt https://x.com/karansdalal/status/1909312851795411093 Kawasaki's Robot Horse Concept https://futurism.com/the-byte/kawasaki-rideable-horse-robot VIDEO: https://youtu.be/vQDhzbTz-9k?si=2aWMtZVLnMONEjBe Engine AI + iShowSpeed https://x.com/engineairobot/status/1908570512906740037 Gemini 2.5 Pro Plays Pokemon https://x.com/kiranvodrahalli/status/1909699142265557208 Prompt-To-Anything Minecraft Looking Game  https://x.com/NicolasZu/status/1908882267453239323 An Image That Will Never Go Viral https://www.reddit.com/r/ChatGPT/comments/1jth5yf/asked_for_an_image_that_will_never_go_viral/?utm_source=share&utm_medium=web3x&utm_name=web3xcss&utm_term=1&utm_content=share_button How Toothpaste Is Made https://www.reddit.com/r/aivideo/comments/1jujzh2/how_toothpaste_is_made/ 90s Video Game 4o Image Gen Prompt https://x.com/AIForHumansShow/status/1908985288116101553 1980s Japanese Posters https://x.com/AIForHumansShow/status/1909824824677192140 Buff Superbad  https://x.com/AIForHumansShow/status/1909402225488937065  

Bill Gates celebrates the 50th anniversary of Microsoft with the release of the source code for Altair BASIC 1.0. Plus, Paul celebrates with 99 cent books: The Windows 10 Field Guide, Windows 11 Field Guide, and Windows Everywhere are all 99 cents for 24 hours! Also available: Eternal Spring: Our Guide to Mexico City in preview!Windows The plot thickens. Paul writes epic take on future of Windows 11, describes Dev channel-only features and when/if they were ever released - in other words, an extensive but partial Windows 11 feature roadmap for 2025 Two days later, Microsoft announces a Windows 11 feature road map - one that is woefully incomplete, pathetic, and sad Microsoft announces when (sort of) new on-device AI features will come to all Copilot+ PCs, meaning Intel and AMD, too - "not a glimpse at the future of the PC, but the future of the PC." Live captions with live language translations, Cocreator in Paint, Restyle image and Image creator in Photos, plus Voice access with flexible natural language (Snapdragon X only) But not Recall or Click to Do in preview, go figure As expected, March 2024 Preview update for 24H2 arrives, a few days late - with AI-powered search experience enabled Dev and Beta builds - Friday - Quick Machine Recovery (Beta only?), Speech recap in Narrator, Blue screen to get less blue, WinKey + C shortcut for Copilot returns, Spanish and French Text actions in Click to Do, Edit images in Share, AI-powered search (Dev only?) Then, Microsoft more fully describes Windows Quick Recovery Beta (23H2) - Monday - A lot of familiar 24H2 features - Narrator improvements, Copilot WinKey + C, Share with Image edit, plus System > About FAQ for some freaking reason Proton Drive is now native on Windows 11 on Arm, everyone gets new features Proton VPN is now built into Vivaldi desktop browser Intel's new CEO appears in public, vows to spin off non-core businesses. Everything but x86 chip design and Foundry, then Microsoft 365 Windows 365 Link is now available The Office apps on Windows already launch instantaneously but apparently that's not invasive enough - we need fewer auto-start items, not more of them Microsoft Excel to call out rich data cells with value tokens AI & Dev NYT copyright infringement lawsuit against Open AI and Microsoft can move forward, judge rules And now Tim O'Reilly says Open AI stole his company's paywalled book content too. Book piracy is sadly the easiest thing in the world Open AI raised more money than any private firm in history, now worth $300B ChatGPT releases awesome new image generation feature for ChatGPT And now it's available for free to everyone Google's Gemini Pro 2.5 is now available to everyone too Amazon launches Alexa+ in early access, US only Some thoughts about vibe coding, which isn't what you think it is AMD pays $4.9 billion to take on Nvidia in cloud AI Apple Intelligence + Apple Health is the future of something something Xbox & Games Nintendo announces Switch 2. Looks awesome, coming earlier than expected. But that price! And no Xbox/COD news at the launch?? Luna's not dead! Amazon announces multi-year EA partnership, expands Luna to more EU countries Microsoft announces a new Xbox Backbone controller for smartphones New titles for Xbox Game Pass across PC, Tip These show notes have been truncated due to length. For the full show notes, visit https://twit.tv/shows/windows-weekly/episodes/926 Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell

Bill Gates celebrates the 50th anniversary of Microsoft with the release of the source code for Altair BASIC 1.0. Plus, Paul celebrates with 99 cent books: The Windows 10 Field Guide, Windows 11 Field Guide, and Windows Everywhere are all 99 cents for 24 hours! Also available: Eternal Spring: Our Guide to Mexico City in preview!Windows The plot thickens. Paul writes epic take on future of Windows 11, describes Dev channel-only features and when/if they were ever released - in other words, an extensive but partial Windows 11 feature roadmap for 2025 Two days later, Microsoft announces a Windows 11 feature road map - one that is woefully incomplete, pathetic, and sad Microsoft announces when (sort of) new on-device AI features will come to all Copilot+ PCs, meaning Intel and AMD, too - "not a glimpse at the future of the PC, but the future of the PC." Live captions with live language translations, Cocreator in Paint, Restyle image and Image creator in Photos, plus Voice access with flexible natural language (Snapdragon X only) But not Recall or Click to Do in preview, go figure As expected, March 2024 Preview update for 24H2 arrives, a few days late - with AI-powered search experience enabled Dev and Beta builds - Friday - Quick Machine Recovery (Beta only?), Speech recap in Narrator, Blue screen to get less blue, WinKey + C shortcut for Copilot returns, Spanish and French Text actions in Click to Do, Edit images in Share, AI-powered search (Dev only?) Then, Microsoft more fully describes Windows Quick Recovery Beta (23H2) - Monday - A lot of familiar 24H2 features - Narrator improvements, Copilot WinKey + C, Share with Image edit, plus System -- About FAQ for some freaking reason Proton Drive is now native on Windows 11 on Arm, everyone gets new features Proton VPN is now built into Vivaldi desktop browser Intel's new CEO appears in public, vows to spin off non-core businesses. Everything but x86 chip design and Foundry, then Microsoft 365 Windows 365 Link is now available The Office apps on Windows already launch instantaneously but apparently that's not invasive enough - we need fewer auto-start items, not more of them Microsoft Excel to call out rich data cells with value tokens AI & Dev NYT copyright infringement lawsuit against Open AI and Microsoft can move forward, judge rules And now Tim O'Reilly says Open AI stole his company's paywalled book content too. Book piracy is sadly the easiest thing in the world Open AI raised more money than any private firm in history, now worth $300B ChatGPT releases awesome new image generation feature for ChatGPT And now it's available for free to everyone Google's Gemini Pro 2.5 is now available to everyone too Amazon launches Alexa+ in early access, US only Some thoughts about vibe coding, which isn't what you think it is AMD pays $4.9 billion to take on Nvidia in cloud AI Apple Intelligence + Apple Health is the future of something something Xbox & Games Nintendo announces Switch 2. Looks awesome, coming earlier than expected. But that price! And no Xbox/COD news at the launch?? Luna's not dead! Amazon announces multi-year EA partnership, expands Luna to more EU countries Microsoft announces a new Xbox Backbone controller for smartphones New titles for Xbox Game Pass across PC, Ti These show notes have been truncated due to length. For the full show notes, visit https://twit.tv/shows/windows-weekly/episodes/926 Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell

Bill Gates celebrates the 50th anniversary of Microsoft with the release of the source code for Altair BASIC 1.0. Plus, Paul celebrates with 99 cent books: The Windows 10 Field Guide, Windows 11 Field Guide, and Windows Everywhere are all 99 cents for 24 hours! Also available: Eternal Spring: Our Guide to Mexico City in preview!Windows The plot thickens. Paul writes epic take on future of Windows 11, describes Dev channel-only features and when/if they were ever released - in other words, an extensive but partial Windows 11 feature roadmap for 2025 Two days later, Microsoft announces a Windows 11 feature road map - one that is woefully incomplete, pathetic, and sad Microsoft announces when (sort of) new on-device AI features will come to all Copilot+ PCs, meaning Intel and AMD, too - "not a glimpse at the future of the PC, but the future of the PC." Live captions with live language translations, Cocreator in Paint, Restyle image and Image creator in Photos, plus Voice access with flexible natural language (Snapdragon X only) But not Recall or Click to Do in preview, go figure As expected, March 2024 Preview update for 24H2 arrives, a few days late - with AI-powered search experience enabled Dev and Beta builds - Friday - Quick Machine Recovery (Beta only?), Speech recap in Narrator, Blue screen to get less blue, WinKey + C shortcut for Copilot returns, Spanish and French Text actions in Click to Do, Edit images in Share, AI-powered search (Dev only?) Then, Microsoft more fully describes Windows Quick Recovery Beta (23H2) - Monday - A lot of familiar 24H2 features - Narrator improvements, Copilot WinKey + C, Share with Image edit, plus System -- About FAQ for some freaking reason Proton Drive is now native on Windows 11 on Arm, everyone gets new features Proton VPN is now built into Vivaldi desktop browser Intel's new CEO appears in public, vows to spin off non-core businesses. Everything but x86 chip design and Foundry, then Microsoft 365 Windows 365 Link is now available The Office apps on Windows already launch instantaneously but apparently that's not invasive enough - we need fewer auto-start items, not more of them Microsoft Excel to call out rich data cells with value tokens AI & Dev NYT copyright infringement lawsuit against Open AI and Microsoft can move forward, judge rules And now Tim O'Reilly says Open AI stole his company's paywalled book content too. Book piracy is sadly the easiest thing in the world Open AI raised more money than any private firm in history, now worth $300B ChatGPT releases awesome new image generation feature for ChatGPT And now it's available for free to everyone Google's Gemini Pro 2.5 is now available to everyone too Amazon launches Alexa+ in early access, US only Some thoughts about vibe coding, which isn't what you think it is AMD pays $4.9 billion to take on Nvidia in cloud AI Apple Intelligence + Apple Health is the future of something something Xbox & Games Nintendo announces Switch 2. Looks awesome, coming earlier than expected. But that price! And no Xbox/COD news at the launch?? Luna's not dead! Amazon announces multi-year EA partnership, expands Luna to more EU countries Microsoft announces a new Xbox Backbone controller for smartphones New titles for Xbox Game Pass across PC, Ti These show notes have been truncated due to length. For the full show notes, visit https://twit.tv/shows/windows-weekly/episodes/926 Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell

Bill Gates celebrates the 50th anniversary of Microsoft with the release of the source code for Altair BASIC 1.0. Plus, Paul celebrates with 99 cent books: The Windows 10 Field Guide, Windows 11 Field Guide, and Windows Everywhere are all 99 cents for 24 hours! Also available: Eternal Spring: Our Guide to Mexico City in preview!Windows The plot thickens. Paul writes epic take on future of Windows 11, describes Dev channel-only features and when/if they were ever released - in other words, an extensive but partial Windows 11 feature roadmap for 2025 Two days later, Microsoft announces a Windows 11 feature road map - one that is woefully incomplete, pathetic, and sad Microsoft announces when (sort of) new on-device AI features will come to all Copilot+ PCs, meaning Intel and AMD, too - "not a glimpse at the future of the PC, but the future of the PC." Live captions with live language translations, Cocreator in Paint, Restyle image and Image creator in Photos, plus Voice access with flexible natural language (Snapdragon X only) But not Recall or Click to Do in preview, go figure As expected, March 2024 Preview update for 24H2 arrives, a few days late - with AI-powered search experience enabled Dev and Beta builds - Friday - Quick Machine Recovery (Beta only?), Speech recap in Narrator, Blue screen to get less blue, WinKey + C shortcut for Copilot returns, Spanish and French Text actions in Click to Do, Edit images in Share, AI-powered search (Dev only?) Then, Microsoft more fully describes Windows Quick Recovery Beta (23H2) - Monday - A lot of familiar 24H2 features - Narrator improvements, Copilot WinKey + C, Share with Image edit, plus System > About FAQ for some freaking reason Proton Drive is now native on Windows 11 on Arm, everyone gets new features Proton VPN is now built into Vivaldi desktop browser Intel's new CEO appears in public, vows to spin off non-core businesses. Everything but x86 chip design and Foundry, then Microsoft 365 Windows 365 Link is now available The Office apps on Windows already launch instantaneously but apparently that's not invasive enough - we need fewer auto-start items, not more of them Microsoft Excel to call out rich data cells with value tokens AI & Dev NYT copyright infringement lawsuit against Open AI and Microsoft can move forward, judge rules And now Tim O'Reilly says Open AI stole his company's paywalled book content too. Book piracy is sadly the easiest thing in the world Open AI raised more money than any private firm in history, now worth $300B ChatGPT releases awesome new image generation feature for ChatGPT And now it's available for free to everyone Google's Gemini Pro 2.5 is now available to everyone too Amazon launches Alexa+ in early access, US only Some thoughts about vibe coding, which isn't what you think it is AMD pays $4.9 billion to take on Nvidia in cloud AI Apple Intelligence + Apple Health is the future of something something Xbox & Games Nintendo announces Switch 2. Looks awesome, coming earlier than expected. But that price! And no Xbox/COD news at the launch?? Luna's not dead! Amazon announces multi-year EA partnership, expands Luna to more EU countries Microsoft announces a new Xbox Backbone controller for smartphones New titles for Xbox Game Pass across PC, Tip These show notes have been truncated due to length. For the full show notes, visit https://twit.tv/shows/windows-weekly/episodes/926 Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell

Bill Gates celebrates the 50th anniversary of Microsoft with the release of the source code for Altair BASIC 1.0. Plus, Paul celebrates with 99 cent books: The Windows 10 Field Guide, Windows 11 Field Guide, and Windows Everywhere are all 99 cents for 24 hours! Also available: Eternal Spring: Our Guide to Mexico City in preview!Windows The plot thickens. Paul writes epic take on future of Windows 11, describes Dev channel-only features and when/if they were ever released - in other words, an extensive but partial Windows 11 feature roadmap for 2025 Two days later, Microsoft announces a Windows 11 feature road map - one that is woefully incomplete, pathetic, and sad Microsoft announces when (sort of) new on-device AI features will come to all Copilot+ PCs, meaning Intel and AMD, too - "not a glimpse at the future of the PC, but the future of the PC." Live captions with live language translations, Cocreator in Paint, Restyle image and Image creator in Photos, plus Voice access with flexible natural language (Snapdragon X only) But not Recall or Click to Do in preview, go figure As expected, March 2024 Preview update for 24H2 arrives, a few days late - with AI-powered search experience enabled Dev and Beta builds - Friday - Quick Machine Recovery (Beta only?), Speech recap in Narrator, Blue screen to get less blue, WinKey + C shortcut for Copilot returns, Spanish and French Text actions in Click to Do, Edit images in Share, AI-powered search (Dev only?) Then, Microsoft more fully describes Windows Quick Recovery Beta (23H2) - Monday - A lot of familiar 24H2 features - Narrator improvements, Copilot WinKey + C, Share with Image edit, plus System -- About FAQ for some freaking reason Proton Drive is now native on Windows 11 on Arm, everyone gets new features Proton VPN is now built into Vivaldi desktop browser Intel's new CEO appears in public, vows to spin off non-core businesses. Everything but x86 chip design and Foundry, then Microsoft 365 Windows 365 Link is now available The Office apps on Windows already launch instantaneously but apparently that's not invasive enough - we need fewer auto-start items, not more of them Microsoft Excel to call out rich data cells with value tokens AI & Dev NYT copyright infringement lawsuit against Open AI and Microsoft can move forward, judge rules And now Tim O'Reilly says Open AI stole his company's paywalled book content too. Book piracy is sadly the easiest thing in the world Open AI raised more money than any private firm in history, now worth $300B ChatGPT releases awesome new image generation feature for ChatGPT And now it's available for free to everyone Google's Gemini Pro 2.5 is now available to everyone too Amazon launches Alexa+ in early access, US only Some thoughts about vibe coding, which isn't what you think it is AMD pays $4.9 billion to take on Nvidia in cloud AI Apple Intelligence + Apple Health is the future of something something Xbox & Games Nintendo announces Switch 2. Looks awesome, coming earlier than expected. But that price! And no Xbox/COD news at the launch?? Luna's not dead! Amazon announces multi-year EA partnership, expands Luna to more EU countries Microsoft announces a new Xbox Backbone controller for smartphones New titles for Xbox Game Pass across PC, Ti These show notes have been truncated due to length. For the full show notes, visit https://twit.tv/shows/windows-weekly/episodes/926 Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Sponsor: uscloud.com

Bill Gates celebrates the 50th anniversary of Microsoft with the release of the source code for Altair BASIC 1.0. Plus, Paul celebrates with 99 cent books: The Windows 10 Field Guide, Windows 11 Field Guide, and Windows Everywhere are all 99 cents for 24 hours! Also available: Eternal Spring: Our Guide to Mexico City in preview!Windows The plot thickens. Paul writes epic take on future of Windows 11, describes Dev channel-only features and when/if they were ever released - in other words, an extensive but partial Windows 11 feature roadmap for 2025 Two days later, Microsoft announces a Windows 11 feature road map - one that is woefully incomplete, pathetic, and sad Microsoft announces when (sort of) new on-device AI features will come to all Copilot+ PCs, meaning Intel and AMD, too - "not a glimpse at the future of the PC, but the future of the PC." Live captions with live language translations, Cocreator in Paint, Restyle image and Image creator in Photos, plus Voice access with flexible natural language (Snapdragon X only) But not Recall or Click to Do in preview, go figure As expected, March 2024 Preview update for 24H2 arrives, a few days late - with AI-powered search experience enabled Dev and Beta builds - Friday - Quick Machine Recovery (Beta only?), Speech recap in Narrator, Blue screen to get less blue, WinKey + C shortcut for Copilot returns, Spanish and French Text actions in Click to Do, Edit images in Share, AI-powered search (Dev only?) Then, Microsoft more fully describes Windows Quick Recovery Beta (23H2) - Monday - A lot of familiar 24H2 features - Narrator improvements, Copilot WinKey + C, Share with Image edit, plus System -- About FAQ for some freaking reason Proton Drive is now native on Windows 11 on Arm, everyone gets new features Proton VPN is now built into Vivaldi desktop browser Intel's new CEO appears in public, vows to spin off non-core businesses. Everything but x86 chip design and Foundry, then Microsoft 365 Windows 365 Link is now available The Office apps on Windows already launch instantaneously but apparently that's not invasive enough - we need fewer auto-start items, not more of them Microsoft Excel to call out rich data cells with value tokens AI & Dev NYT copyright infringement lawsuit against Open AI and Microsoft can move forward, judge rules And now Tim O'Reilly says Open AI stole his company's paywalled book content too. Book piracy is sadly the easiest thing in the world Open AI raised more money than any private firm in history, now worth $300B ChatGPT releases awesome new image generation feature for ChatGPT And now it's available for free to everyone Google's Gemini Pro 2.5 is now available to everyone too Amazon launches Alexa+ in early access, US only Some thoughts about vibe coding, which isn't what you think it is AMD pays $4.9 billion to take on Nvidia in cloud AI Apple Intelligence + Apple Health is the future of something something Xbox & Games Nintendo announces Switch 2. Looks awesome, coming earlier than expected. But that price! And no Xbox/COD news at the launch?? Luna's not dead! Amazon announces multi-year EA partnership, expands Luna to more EU countries Microsoft announces a new Xbox Backbone controller for smartphones New titles for Xbox Game Pass across PC, Ti These show notes have been truncated due to length. For the full show notes, visit https://twit.tv/shows/windows-weekly/episodes/926 Hosts: Leo Laporte, Paul Thurrott, and Richard Campbell Sponsor: uscloud.com

Applications for the 2025 AI Engineer Summit are up, and you can save the date for AIE Singapore in April and AIE World's Fair 2025 in June.Happy new year, and thanks for 100 great episodes! Please let us know what you want to see/hear for the next 100!Full YouTube Episode with Slides/ChartsLike and subscribe and hit that bell to get notifs!Timestamps* 00:00 Welcome to the 100th Episode!* 00:19 Reflecting on the Journey* 00:47 AI Engineering: The Rise and Impact* 03:15 Latent Space Live and AI Conferences* 09:44 The Competitive AI Landscape* 21:45 Synthetic Data and Future Trends* 35:53 Creative Writing with AI* 36:12 Legal and Ethical Issues in AI* 38:18 The Data War: GPU Poor vs. GPU Rich* 39:12 The Rise of GPU Ultra Rich* 40:47 Emerging Trends in AI Models* 45:31 The Multi-Modality War* 01:05:31 The Future of AI Benchmarks* 01:13:17 Pionote and Frontier Models* 01:13:47 Niche Models and Base Models* 01:14:30 State Space Models and RWKB* 01:15:48 Inference Race and Price Wars* 01:22:16 Major AI Themes of the Year* 01:22:48 AI Rewind: January to March* 01:26:42 AI Rewind: April to June* 01:33:12 AI Rewind: July to September* 01:34:59 AI Rewind: October to December* 01:39:53 Year-End Reflections and PredictionsTranscript[00:00:00] Welcome to the 100th Episode![00:00:00] Alessio: Hey everyone, welcome to the Latent Space Podcast. This is Alessio, partner and CTO at Decibel Partners, and I'm joined by my co host Swyx for the 100th time today.[00:00:12] swyx: Yay, um, and we're so glad that, yeah, you know, everyone has, uh, followed us in this journey. How do you feel about it? 100 episodes.[00:00:19] Alessio: Yeah, I know.[00:00:19] Reflecting on the Journey[00:00:19] Alessio: Almost two years that we've been doing this. We've had four different studios. Uh, we've had a lot of changes. You know, we used to do this lightning round. When we first started that we didn't like, and we tried to change the question. The answer[00:00:32] swyx: was cursor and perplexity.[00:00:34] Alessio: Yeah, I love mid journey. It's like, do you really not like anything else?[00:00:38] Alessio: Like what's, what's the unique thing? And I think, yeah, we, we've also had a lot more research driven content. You know, we had like 3DAO, we had, you know. Jeremy Howard, we had more folks like that.[00:00:47] AI Engineering: The Rise and Impact[00:00:47] Alessio: I think we want to do more of that too in the new year, like having, uh, some of the Gemini folks, both on the research and the applied side.[00:00:54] Alessio: Yeah, but it's been a ton of fun. I think we both started, I wouldn't say as a joke, we were kind of like, Oh, we [00:01:00] should do a podcast. And I think we kind of caught the right wave, obviously. And I think your rise of the AI engineer posts just kind of get people. Sombra to congregate, and then the AI engineer summit.[00:01:11] Alessio: And that's why when I look at our growth chart, it's kind of like a proxy for like the AI engineering industry as a whole, which is almost like, like, even if we don't do that much, we keep growing just because there's so many more AI engineers. So did you expect that growth or did you expect that would take longer for like the AI engineer thing to kind of like become, you know, everybody talks about it today.[00:01:32] swyx: So, the sign of that, that we have won is that Gartner puts it at the top of the hype curve right now. So Gartner has called the peak in AI engineering. I did not expect, um, to what level. I knew that I was correct when I called it because I did like two months of work going into that. But I didn't know, You know, how quickly it could happen, and obviously there's a chance that I could be wrong.[00:01:52] swyx: But I think, like, most people have come around to that concept. Hacker News hates it, which is a good sign. But there's enough people that have defined it, you know, GitHub, when [00:02:00] they launched GitHub Models, which is the Hugging Face clone, they put AI engineers in the banner, like, above the fold, like, in big So I think it's like kind of arrived as a meaningful and useful definition.[00:02:12] swyx: I think people are trying to figure out where the boundaries are. I think that was a lot of the quote unquote drama that happens behind the scenes at the World's Fair in June. Because I think there's a lot of doubt or questions about where ML engineering stops and AI engineering starts. That's a useful debate to be had.[00:02:29] swyx: In some sense, I actually anticipated that as well. So I intentionally did not. Put a firm definition there because most of the successful definitions are necessarily underspecified and it's actually useful to have different perspectives and you don't have to specify everything from the outset.[00:02:45] Alessio: Yeah, I was at um, AWS reInvent and the line to get into like the AI engineering talk, so to speak, which is, you know, applied AI and whatnot was like, there are like hundreds of people just in line to go in.[00:02:56] Alessio: I think that's kind of what enabled me. People, right? Which is what [00:03:00] you kind of talked about. It's like, Hey, look, you don't actually need a PhD, just, yeah, just use the model. And then maybe we'll talk about some of the blind spots that you get as an engineer with the earlier posts that we also had on on the sub stack.[00:03:11] Alessio: But yeah, it's been a heck of a heck of a two years.[00:03:14] swyx: Yeah.[00:03:15] Latent Space Live and AI Conferences[00:03:15] swyx: You know, I was, I was trying to view the conference as like, so NeurIPS is I think like 16, 17, 000 people. And the Latent Space Live event that we held there was 950 signups. I think. The AI world, the ML world is still very much research heavy. And that's as it should be because ML is very much in a research phase.[00:03:34] swyx: But as we move this entire field into production, I think that ratio inverts into becoming more engineering heavy. So at least I think engineering should be on the same level, even if it's never as prestigious, like it'll always be low status because at the end of the day, you're manipulating APIs or whatever.[00:03:51] swyx: But Yeah, wrapping GPTs, but there's going to be an increasing stack and an art to doing these, these things well. And I, you know, I [00:04:00] think that's what we're focusing on for the podcast, the conference and basically everything I do seems to make sense. And I think we'll, we'll talk about the trends here that apply.[00:04:09] swyx: It's, it's just very strange. So, like, there's a mix of, like, keeping on top of research while not being a researcher and then putting that research into production. So, like, people always ask me, like, why are you covering Neuralibs? Like, this is a ML research conference and I'm like, well, yeah, I mean, we're not going to, to like, understand everything Or reproduce every single paper, but the stuff that is being found here is going to make it through into production at some point, you hope.[00:04:32] swyx: And then actually like when I talk to the researchers, they actually get very excited because they're like, oh, you guys are actually caring about how this goes into production and that's what they really really want. The measure of success is previously just peer review, right? Getting 7s and 8s on their um, Academic review conferences and stuff like citations is one metric, but money is a better metric.[00:04:51] Alessio: Money is a better metric. Yeah, and there were about 2200 people on the live stream or something like that. Yeah, yeah. Hundred on the live stream. So [00:05:00] I try my best to moderate, but it was a lot spicier in person with Jonathan and, and Dylan. Yeah, that it was in the chat on YouTube.[00:05:06] swyx: I would say that I actually also created.[00:05:09] swyx: Layen Space Live in order to address flaws that are perceived in academic conferences. This is not NeurIPS specific, it's ICML, NeurIPS. Basically, it's very sort of oriented towards the PhD student, uh, market, job market, right? Like literally all, basically everyone's there to advertise their research and skills and get jobs.[00:05:28] swyx: And then obviously all the, the companies go there to hire them. And I think that's great for the individual researchers, but for people going there to get info is not great because you have to read between the lines, bring a ton of context in order to understand every single paper. So what is missing is effectively what I ended up doing, which is domain by domain, go through and recap the best of the year.[00:05:48] swyx: Survey the field. And there are, like NeurIPS had a, uh, I think ICML had a like a position paper track, NeurIPS added a benchmarks, uh, datasets track. These are ways in which to address that [00:06:00] issue. Uh, there's always workshops as well. Every, every conference has, you know, a last day of workshops and stuff that provide more of an overview.[00:06:06] swyx: But they're not specifically prompted to do so. And I think really, uh, Organizing a conference is just about getting good speakers and giving them the correct prompts. And then they will just go and do that thing and they do a very good job of it. So I think Sarah did a fantastic job with the startups prompt.[00:06:21] swyx: I can't list everybody, but we did best of 2024 in startups, vision, open models. Post transformers, synthetic data, small models, and agents. And then the last one was the, uh, and then we also did a quick one on reasoning with Nathan Lambert. And then the last one, obviously, was the debate that people were very hyped about.[00:06:39] swyx: It was very awkward. And I'm really, really thankful for John Franco, basically, who stepped up to challenge Dylan. Because Dylan was like, yeah, I'll do it. But He was pro scaling. And I think everyone who is like in AI is pro scaling, right? So you need somebody who's ready to publicly say, no, we've hit a wall.[00:06:57] swyx: So that means you're saying Sam Altman's wrong. [00:07:00] You're saying, um, you know, everyone else is wrong. It helps that this was the day before Ilya went on, went up on stage and then said pre training has hit a wall. And data has hit a wall. So actually Jonathan ended up winning, and then Ilya supported that statement, and then Noam Brown on the last day further supported that statement as well.[00:07:17] swyx: So it's kind of interesting that I think the consensus kind of going in was that we're not done scaling, like you should believe in a better lesson. And then, four straight days in a row, you had Sepp Hochreiter, who is the creator of the LSTM, along with everyone's favorite OG in AI, which is Juergen Schmidhuber.[00:07:34] swyx: He said that, um, we're pre trading inside a wall, or like, we've run into a different kind of wall. And then we have, you know John Frankel, Ilya, and then Noam Brown are all saying variations of the same thing, that we have hit some kind of wall in the status quo of what pre trained, scaling large pre trained models has looked like, and we need a new thing.[00:07:54] swyx: And obviously the new thing for people is some make, either people are calling it inference time compute or test time [00:08:00] compute. I think the collective terminology has been inference time, and I think that makes sense because test time, calling it test, meaning, has a very pre trained bias, meaning that the only reason for running inference at all is to test your model.[00:08:11] swyx: That is not true. Right. Yeah. So, so, I quite agree that. OpenAI seems to have adopted, or the community seems to have adopted this terminology of ITC instead of TTC. And that, that makes a lot of sense because like now we care about inference, even right down to compute optimality. Like I actually interviewed this author who recovered or reviewed the Chinchilla paper.[00:08:31] swyx: Chinchilla paper is compute optimal training, but what is not stated in there is it's pre trained compute optimal training. And once you start caring about inference, compute optimal training, you have a different scaling law. And in a way that we did not know last year.[00:08:45] Alessio: I wonder, because John is, he's also on the side of attention is all you need.[00:08:49] Alessio: Like he had the bet with Sasha. So I'm curious, like he doesn't believe in scaling, but he thinks the transformer, I wonder if he's still. So, so,[00:08:56] swyx: so he, obviously everything is nuanced and you know, I told him to play a character [00:09:00] for this debate, right? So he actually does. Yeah. He still, he still believes that we can scale more.[00:09:04] swyx: Uh, he just assumed the character to be very game for, for playing this debate. So even more kudos to him that he assumed a position that he didn't believe in and still won the debate.[00:09:16] Alessio: Get rekt, Dylan. Um, do you just want to quickly run through some of these things? Like, uh, Sarah's presentation, just the highlights.[00:09:24] swyx: Yeah, we can't go through everyone's slides, but I pulled out some things as a factor of, like, stuff that we were going to talk about. And we'll[00:09:30] Alessio: publish[00:09:31] swyx: the rest. Yeah, we'll publish on this feed the best of 2024 in those domains. And hopefully people can benefit from the work that our speakers have done.[00:09:39] swyx: But I think it's, uh, these are just good slides. And I've been, I've been looking for a sort of end of year recaps from, from people.[00:09:44] The Competitive AI Landscape[00:09:44] swyx: The field has progressed a lot. You know, I think the max ELO in 2023 on LMSys used to be 1200 for LMSys ELOs. And now everyone is at least at, uh, 1275 in their ELOs, and this is across Gemini, Chadjibuti, [00:10:00] Grok, O1.[00:10:01] swyx: ai, which with their E Large model, and Enthopic, of course. It's a very, very competitive race. There are multiple Frontier labs all racing, but there is a clear tier zero Frontier. And then there's like a tier one. It's like, I wish I had everything else. Tier zero is extremely competitive. It's effectively now three horse race between Gemini, uh, Anthropic and OpenAI.[00:10:21] swyx: I would say that people are still holding out a candle for XAI. XAI, I think, for some reason, because their API was very slow to roll out, is not included in these metrics. So it's actually quite hard to put on there. As someone who also does charts, XAI is continually snubbed because they don't work well with the benchmarking people.[00:10:42] swyx: Yeah, yeah, yeah. It's a little trivia for why XAI always gets ignored. The other thing is market share. So these are slides from Sarah. We have it up on the screen. It has gone from very heavily open AI. So we have some numbers and estimates. These are from RAMP. Estimates of open AI market share in [00:11:00] December 2023.[00:11:01] swyx: And this is basically, what is it, GPT being 95 percent of production traffic. And I think if you correlate that with stuff that we asked. Harrison Chase on the LangChain episode, it was true. And then CLAUD 3 launched mid middle of this year. I think CLAUD 3 launched in March, CLAUD 3. 5 Sonnet was in June ish.[00:11:23] swyx: And you can start seeing the market share shift towards opening, uh, towards that topic, uh, very, very aggressively. The more recent one is Gemini. So if I scroll down a little bit, this is an even more recent dataset. So RAM's dataset ends in September 2 2. 2024. Gemini has basically launched a price war at the low end, uh, with Gemini Flash, uh, being basically free for personal use.[00:11:44] swyx: Like, I think people don't understand the free tier. It's something like a billion tokens per day. Unless you're trying to abuse it, you cannot really exhaust your free tier on Gemini. They're really trying to get you to use it. They know they're in like third place, um, fourth place, depending how you, how you count.[00:11:58] swyx: And so they're going after [00:12:00] the Lower tier first, and then, you know, maybe the upper tier later, but yeah, Gemini Flash, according to OpenRouter, is now 50 percent of their OpenRouter requests. Obviously, these are the small requests. These are small, cheap requests that are mathematically going to be more.[00:12:15] swyx: The smart ones obviously are still going to OpenAI. But, you know, it's a very, very big shift in the market. Like basically 2023, 2022, To going into 2024 opening has gone from nine five market share to Yeah. Reasonably somewhere between 50 to 75 market share.[00:12:29] Alessio: Yeah. I'm really curious how ramped does the attribution to the model?[00:12:32] Alessio: If it's API, because I think it's all credit card spin. . Well, but it's all, the credit card doesn't say maybe. Maybe the, maybe when they do expenses, they upload the PDF, but yeah, the, the German I think makes sense. I think that was one of my main 2024 takeaways that like. The best small model companies are the large labs, which is not something I would have thought that the open source kind of like long tail would be like the small model.[00:12:53] swyx: Yeah, different sizes of small models we're talking about here, right? Like so small model here for Gemini is AB, [00:13:00] right? Uh, mini. We don't know what the small model size is, but yeah, it's probably in the double digits or maybe single digits, but probably double digits. The open source community has kind of focused on the one to three B size.[00:13:11] swyx: Mm-hmm . Yeah. Maybe[00:13:12] swyx: zero, maybe 0.5 B uh, that's moon dream and that is small for you then, then that's great. It makes sense that we, we have a range for small now, which is like, may, maybe one to five B. Yeah. I'll even put that at, at, at the high end. And so this includes Gemma from Gemini as well. But also includes the Apple Foundation models, which I think Apple Foundation is 3B.[00:13:32] Alessio: Yeah. No, that's great. I mean, I think in the start small just meant cheap. I think today small is actually a more nuanced discussion, you know, that people weren't really having before.[00:13:43] swyx: Yeah, we can keep going. This is a slide that I smiley disagree with Sarah. She's pointing to the scale SEAL leaderboard. I think the Researchers that I talked with at NeurIPS were kind of positive on this because basically you need private test [00:14:00] sets to prevent contamination.[00:14:02] swyx: And Scale is one of maybe three or four people this year that has really made an effort in doing a credible private test set leaderboard. Llama405B does well compared to Gemini and GPT 40. And I think that's good. I would say that. You know, it's good to have an open model that is that big, that does well on those metrics.[00:14:23] swyx: But anyone putting 405B in production will tell you, if you scroll down a little bit to the artificial analysis numbers, that it is very slow and very expensive to infer. Um, it doesn't even fit on like one node. of, uh, of H100s. Cerebras will be happy to tell you they can serve 4 or 5B on their super large chips.[00:14:42] swyx: But, um, you know, if you need to do anything custom to it, you're still kind of constrained. So, is 4 or 5B really that relevant? Like, I think most people are basically saying that they only use 4 or 5B as a teacher model to distill down to something. Even Meta is doing it. So with Lama 3. [00:15:00] 3 launched, they only launched the 70B because they use 4 or 5B to distill the 70B.[00:15:03] swyx: So I don't know if like open source is keeping up. I think they're the, the open source industrial complex is very invested in telling you that the, if the gap is narrowing, I kind of disagree. I think that the gap is widening with O1. I think there are very, very smart people trying to narrow that gap and they should.[00:15:22] swyx: I really wish them success, but you cannot use a chart that is nearing 100 in your saturation chart. And look, the distance between open source and closed source is narrowing. Of course it's going to narrow because you're near 100. This is stupid. But in metrics that matter, is open source narrowing?[00:15:38] swyx: Probably not for O1 for a while. And it's really up to the open source guys to figure out if they can match O1 or not.[00:15:46] Alessio: I think inference time compute is bad for open source just because, you know, Doc can donate the flops at training time, but he cannot donate the flops at inference time. So it's really hard to like actually keep up on that axis.[00:15:59] Alessio: Big, big business [00:16:00] model shift. So I don't know what that means for the GPU clouds. I don't know what that means for the hyperscalers, but obviously the big labs have a lot of advantage. Because, like, it's not a static artifact that you're putting the compute in. You're kind of doing that still, but then you're putting a lot of computed inference too.[00:16:17] swyx: Yeah, yeah, yeah. Um, I mean, Llama4 will be reasoning oriented. We talked with Thomas Shalom. Um, kudos for getting that episode together. That was really nice. Good, well timed. Actually, I connected with the AI meta guy, uh, at NeurIPS, and, um, yeah, we're going to coordinate something for Llama4. Yeah, yeah,[00:16:32] Alessio: and our friend, yeah.[00:16:33] Alessio: Clara Shi just joined to lead the business agent side. So I'm sure we'll have her on in the new year.[00:16:39] swyx: Yeah. So, um, my comment on, on the business model shift, this is super interesting. Apparently it is wide knowledge that OpenAI wanted more than 6. 6 billion dollars for their fundraise. They wanted to raise, you know, higher, and they did not.[00:16:51] swyx: And what that means is basically like, it's very convenient that we're not getting GPT 5, which would have been a larger pre train. We should have a lot of upfront money. And [00:17:00] instead we're, we're converting fixed costs into variable costs, right. And passing it on effectively to the customer. And it's so much easier to take margin there because you can directly attribute it to like, Oh, you're using this more.[00:17:12] swyx: Therefore you, you pay more of the cost and I'll just slap a margin in there. So like that lets you control your growth margin and like tie your. Your spend, or your sort of inference spend, accordingly. And it's just really interesting to, that this change in the sort of inference paradigm has arrived exactly at the same time that the funding environment for pre training is effectively drying up, kind of.[00:17:36] swyx: I feel like maybe the VCs are very in tune with research anyway, so like, they would have noticed this, but, um, it's just interesting.[00:17:43] Alessio: Yeah, and I was looking back at our yearly recap of last year. Yeah. And the big thing was like the mixed trial price fights, you know, and I think now it's almost like there's nowhere to go, like, you know, Gemini Flash is like basically giving it away for free.[00:17:55] Alessio: So I think this is a good way for the labs to generate more revenue and pass down [00:18:00] some of the compute to the customer. I think they're going to[00:18:02] swyx: keep going. I think that 2, will come.[00:18:05] Alessio: Yeah, I know. Totally. I mean, next year, the first thing I'm doing is signing up for Devin. Signing up for the pro chat GBT.[00:18:12] Alessio: Just to try. I just want to see what does it look like to spend a thousand dollars a month on AI?[00:18:17] swyx: Yes. Yes. I think if your, if your, your job is a, at least AI content creator or VC or, you know, someone who, whose job it is to stay on, stay on top of things, you should already be spending like a thousand dollars a month on, on stuff.[00:18:28] swyx: And then obviously easy to spend, hard to use. You have to actually use. The good thing is that actually Google lets you do a lot of stuff for free now. So like deep research. That they just launched. Uses a ton of inference and it's, it's free while it's in preview.[00:18:45] Alessio: Yeah. They need to put that in Lindy.[00:18:47] Alessio: I've been using Lindy lately. I've been a built a bunch of things once we had flow because I liked the new thing. It's pretty good. I even did a phone call assistant. Um, yeah, they just launched Lindy voice. Yeah, I think once [00:19:00] they get advanced voice mode like capability today, still like speech to text, you can kind of tell.[00:19:06] Alessio: Um, but it's good for like reservations and things like that. So I have a meeting prepper thing. And so[00:19:13] swyx: it's good. Okay. I feel like we've, we've covered a lot of stuff. Uh, I, yeah, I, you know, I think We will go over the individual, uh, talks in a separate episode. Uh, I don't want to take too much time with, uh, this stuff, but that suffice to say that there is a lot of progress in each field.[00:19:28] swyx: Uh, we covered vision. Basically this is all like the audience voting for what they wanted. And then I just invited the best people I could find in each audience, especially agents. Um, Graham, who I talked to at ICML in Vienna, he is currently still number one. It's very hard to stay on top of SweetBench.[00:19:45] swyx: OpenHand is currently still number one. switchbench full, which is the hardest one. He had very good thoughts on agents, which I, which I'll highlight for people. Everyone is saying 2025 is the year of agents, just like they said last year. And, uh, but he had [00:20:00] thoughts on like eight parts of what are the frontier problems to solve in agents.[00:20:03] swyx: And so I'll highlight that talk as well.[00:20:05] Alessio: Yeah. The number six, which is the Hacken agents learn more about the environment, has been a Super interesting to us as well, just to think through, because, yeah, how do you put an agent in an enterprise where most things in an enterprise have never been public, you know, a lot of the tooling, like the code bases and things like that.[00:20:23] Alessio: So, yeah, there's not indexing and reg. Well, yeah, but it's more like. You can't really rag things that are not documented. But people know them based on how they've been doing it. You know, so I think there's almost this like, you know, Oh, institutional knowledge. Yeah, the boring word is kind of like a business process extraction.[00:20:38] Alessio: Yeah yeah, I see. It's like, how do you actually understand how these things are done? I see. Um, and I think today the, the problem is that, Yeah, the agents are, that most people are building are good at following instruction, but are not as good as like extracting them from you. Um, so I think that will be a big unlock just to touch quickly on the Jeff Dean thing.[00:20:55] Alessio: I thought it was pretty, I mean, we'll link it in the, in the things, but. I think the main [00:21:00] focus was like, how do you use ML to optimize the systems instead of just focusing on ML to do something else? Yeah, I think speculative decoding, we had, you know, Eugene from RWKB on the podcast before, like he's doing a lot of that with Fetterless AI.[00:21:12] swyx: Everyone is. I would say it's the norm. I'm a little bit uncomfortable with how much it costs, because it does use more of the GPU per call. But because everyone is so keen on fast inference, then yeah, makes sense.[00:21:24] Alessio: Exactly. Um, yeah, but we'll link that. Obviously Jeff is great.[00:21:30] swyx: Jeff is, Jeff's talk was more, it wasn't focused on Gemini.[00:21:33] swyx: I think people got the wrong impression from my tweet. It's more about how Google approaches ML and uses ML to design systems and then systems feedback into ML. And I think this ties in with Lubna's talk.[00:21:45] Synthetic Data and Future Trends[00:21:45] swyx: on synthetic data where it's basically the story of bootstrapping of humans and AI in AI research or AI in production.[00:21:53] swyx: So her talk was on synthetic data, where like how much synthetic data has grown in 2024 in the pre training side, the post training side, [00:22:00] and the eval side. And I think Jeff then also extended it basically to chips, uh, to chip design. So he'd spend a lot of time talking about alpha chip. And most of us in the audience are like, we're not working on hardware, man.[00:22:11] swyx: Like you guys are great. TPU is great. Okay. We'll buy TPUs.[00:22:14] Alessio: And then there was the earlier talk. Yeah. But, and then we have, uh, I don't know if we're calling them essays. What are we calling these? But[00:22:23] swyx: for me, it's just like bonus for late in space supporters, because I feel like they haven't been getting anything.[00:22:29] swyx: And then I wanted a more high frequency way to write stuff. Like that one I wrote in an afternoon. I think basically we now have an answer to what Ilya saw. It's one year since. The blip. And we know what he saw in 2014. We know what he saw in 2024. We think we know what he sees in 2024. He gave some hints and then we have vague indications of what he saw in 2023.[00:22:54] swyx: So that was the Oh, and then 2016 as well, because of this lawsuit with Elon, OpenAI [00:23:00] is publishing emails from Sam's, like, his personal text messages to Siobhan, Zelis, or whatever. So, like, we have emails from Ilya saying, this is what we're seeing in OpenAI, and this is why we need to scale up GPUs. And I think it's very prescient in 2016 to write that.[00:23:16] swyx: And so, like, it is exactly, like, basically his insights. It's him and Greg, basically just kind of driving the scaling up of OpenAI, while they're still playing Dota. They're like, no, like, we see the path here.[00:23:30] Alessio: Yeah, and it's funny, yeah, they even mention, you know, we can only train on 1v1 Dota. We need to train on 5v5, and that takes too many GPUs.[00:23:37] Alessio: Yeah,[00:23:37] swyx: and at least for me, I can speak for myself, like, I didn't see the path from Dota to where we are today. I think even, maybe if you ask them, like, they wouldn't necessarily draw a straight line. Yeah,[00:23:47] Alessio: no, definitely. But I think like that was like the whole idea of almost like the RL and we talked about this with Nathan on his podcast.[00:23:55] Alessio: It's like with RL, you can get very good at specific things, but then you can't really like generalize as much. And I [00:24:00] think the language models are like the opposite, which is like, you're going to throw all this data at them and scale them up, but then you really need to drive them home on a specific task later on.[00:24:08] Alessio: And we'll talk about the open AI reinforcement, fine tuning, um, announcement too, and all of that. But yeah, I think like scale is all you need. That's kind of what Elia will be remembered for. And I think just maybe to clarify on like the pre training is over thing that people love to tweet. I think the point of the talk was like everybody, we're scaling these chips, we're scaling the compute, but like the second ingredient which is data is not scaling at the same rate.[00:24:35] Alessio: So it's not necessarily pre training is over. It's kind of like What got us here won't get us there. In his email, he predicted like 10x growth every two years or something like that. And I think maybe now it's like, you know, you can 10x the chips again, but[00:24:49] swyx: I think it's 10x per year. Was it? I don't know.[00:24:52] Alessio: Exactly. And Moore's law is like 2x. So it's like, you know, much faster than that. And yeah, I like the fossil fuel of AI [00:25:00] analogy. It's kind of like, you know, the little background tokens thing. So the OpenAI reinforcement fine tuning is basically like, instead of fine tuning on data, you fine tune on a reward model.[00:25:09] Alessio: So it's basically like, instead of being data driven, it's like task driven. And I think people have tasks to do, they don't really have a lot of data. So I'm curious to see how that changes, how many people fine tune, because I think this is what people run into. It's like, Oh, you can fine tune llama. And it's like, okay, where do I get the data?[00:25:27] Alessio: To fine tune it on, you know, so it's great that we're moving the thing. And then I really like he had this chart where like, you know, the brain mass and the body mass thing is basically like mammals that scaled linearly by brain and body size, and then humans kind of like broke off the slope. So it's almost like maybe the mammal slope is like the pre training slope.[00:25:46] Alessio: And then the post training slope is like the, the human one.[00:25:49] swyx: Yeah. I wonder what the. I mean, we'll know in 10 years, but I wonder what the y axis is for, for Ilya's SSI. We'll try to get them on.[00:25:57] Alessio: Ilya, if you're listening, you're [00:26:00] welcome here. Yeah, and then he had, you know, what comes next, like agent, synthetic data, inference, compute, I thought all of that was like that.[00:26:05] Alessio: I don't[00:26:05] swyx: think he was dropping any alpha there. Yeah, yeah, yeah.[00:26:07] Alessio: Yeah. Any other new reps? Highlights?[00:26:10] swyx: I think that there was comparatively a lot more work. Oh, by the way, I need to plug that, uh, my friend Yi made this, like, little nice paper. Yeah, that was really[00:26:20] swyx: nice.[00:26:20] swyx: Uh, of, uh, of, like, all the, he's, she called it must read papers of 2024.[00:26:26] swyx: So I laid out some of these at NeurIPS, and it was just gone. Like, everyone just picked it up. Because people are dying for, like, little guidance and visualizations And so, uh, I thought it was really super nice that we got there.[00:26:38] Alessio: Should we do a late in space book for each year? Uh, I thought about it. For each year we should.[00:26:42] Alessio: Coffee table book. Yeah. Yeah. Okay. Put it in the will. Hi, Will. By the way, we haven't introduced you. He's our new, you know, general organist, Jamie. You need to[00:26:52] swyx: pull up more things. One thing I saw that, uh, Okay, one fun one, and then one [00:27:00] more general one. So the fun one is this paper on agent collusion. This is a paper on steganography.[00:27:06] swyx: This is secret collusion among AI agents, multi agent deception via steganography. I tried to go to NeurIPS in order to find these kinds of papers because the real reason Like NeurIPS this year has a lottery system. A lot of people actually even go and don't buy tickets because they just go and attend the side events.[00:27:22] swyx: And then also the people who go and end up crowding around the most popular papers, which you already know and already read them before you showed up to NeurIPS. So the only reason you go there is to talk to the paper authors, but there's like something like 10, 000 other. All these papers out there that, you know, are just people's work that they, that they did on the air and they failed to get attention for one reason or another.[00:27:42] swyx: And this was one of them. Uh, it was like all the way at the back. And this is a deep mind paper that actually focuses on collusion between AI agents, uh, by hiding messages in the text that they generate. Uh, so that's what steganography is. So a very simple example would be the first letter of every word.[00:27:57] swyx: If you Pick that out, you know, and the code sends a [00:28:00] different message than that. But something I've always emphasized is to LLMs, we read left to right. LLMs can read up, down, sideways, you know, in random character order. And it's the same to them as it is to us. So if we were ever to get You know, self motivated, underlined LLMs that we're trying to collaborate to take over the planet.[00:28:19] swyx: This would be how they do it. They spread messages among us in the messages that we generate. And he developed a scaling law for that. So he marked, I'm showing it on screen right now, the emergence of this phenomenon. Basically, for example, for Cypher encoding, GPT 2, Lama 2, mixed trial, GPT 3. 5, zero capabilities, and sudden 4.[00:28:40] swyx: And this is the kind of Jason Wei type emergence properties that people kind of look for. I think what made this paper stand out as well, so he developed the benchmark for steganography collusion, and he also focused on shelling point collusion, which is very low coordination. For agreeing on a decoding encoding format, you kind of need to have some [00:29:00] agreement on that.[00:29:00] swyx: But, but shelling point means like very, very low or almost no coordination. So for example, if I, if I ask someone, if the only message I give you is meet me in New York and you're not aware. Or when you would probably meet me at Grand Central Station. That is the Grand Central Station is a shelling point.[00:29:16] swyx: And it's probably somewhere, somewhere during the day. That is the shelling point of New York is Grand Central. To that extent, shelling points for steganography are things like the, the, the common decoding methods that we talked about. It will be interesting at some point in the future when we are worried about alignment.[00:29:30] swyx: It is not interesting today, but it's interesting that DeepMind is already thinking about this.[00:29:36] Alessio: I think that's like one of the hardest things about NeurIPS. It's like the long tail. I[00:29:41] swyx: found a pricing guy. I'm going to feature him on the podcast. Basically, this guy from NVIDIA worked out the optimal pricing for language models.[00:29:51] swyx: It's basically an econometrics paper at NeurIPS, where everyone else is talking about GPUs. And the guy with the GPUs is[00:29:57] Alessio: talking[00:29:57] swyx: about economics instead. [00:30:00] That was the sort of fun one. So the focus I saw is that model papers at NeurIPS are kind of dead. No one really presents models anymore. It's just data sets.[00:30:12] swyx: This is all the grad students are working on. So like there was a data sets track and then I was looking around like, I was like, you don't need a data sets track because every paper is a data sets paper. And so data sets and benchmarks, they're kind of flip sides of the same thing. So Yeah. Cool. Yeah, if you're a grad student, you're a GPU boy, you kind of work on that.[00:30:30] swyx: And then the, the sort of big model that people walk around and pick the ones that they like, and then they use it in their models. And that's, that's kind of how it develops. I, I feel like, um, like, like you didn't last year, you had people like Hao Tian who worked on Lava, which is take Lama and add Vision.[00:30:47] swyx: And then obviously actually I hired him and he added Vision to Grok. Now he's the Vision Grok guy. This year, I don't think there was any of those.[00:30:55] Alessio: What were the most popular, like, orals? Last year it was like the [00:31:00] Mixed Monarch, I think, was like the most attended. Yeah, uh, I need to look it up. Yeah, I mean, if nothing comes to mind, that's also kind of like an answer in a way.[00:31:10] Alessio: But I think last year there was a lot of interest in, like, furthering models and, like, different architectures and all of that.[00:31:16] swyx: I will say that I felt the orals, oral picks this year were not very good. Either that or maybe it's just a So that's the highlight of how I have changed in terms of how I view papers.[00:31:29] swyx: So like, in my estimation, two of the best papers in this year for datasets or data comp and refined web or fine web. These are two actually industrially used papers, not highlighted for a while. I think DCLM got the spotlight, FineWeb didn't even get the spotlight. So like, it's just that the picks were different.[00:31:48] swyx: But one thing that does get a lot of play that a lot of people are debating is the role that's scheduled. This is the schedule free optimizer paper from Meta from Aaron DeFazio. And this [00:32:00] year in the ML community, there's been a lot of chat about shampoo, soap, all the bathroom amenities for optimizing your learning rates.[00:32:08] swyx: And, uh, most people at the big labs are. Who I asked about this, um, say that it's cute, but it's not something that matters. I don't know, but it's something that was discussed and very, very popular. 4Wars[00:32:19] Alessio: of AI recap maybe, just quickly. Um, where do you want to start? Data?[00:32:26] swyx: So to remind people, this is the 4Wars piece that we did as one of our earlier recaps of this year.[00:32:31] swyx: And the belligerents are on the left, journalists, writers, artists, anyone who owns IP basically, New York Times, Stack Overflow, Reddit, Getty, Sarah Silverman, George RR Martin. Yeah, and I think this year we can add Scarlett Johansson to that side of the fence. So anyone suing, open the eye, basically. I actually wanted to get a snapshot of all the lawsuits.[00:32:52] swyx: I'm sure some lawyer can do it. That's the data quality war. On the right hand side, we have the synthetic data people, and I think we talked about Lumna's talk, you know, [00:33:00] really showing how much synthetic data has come along this year. I think there was a bit of a fight between scale. ai and the synthetic data community, because scale.[00:33:09] swyx: ai published a paper saying that synthetic data doesn't work. Surprise, surprise, scale. ai is the leading vendor of non synthetic data. Only[00:33:17] Alessio: cage free annotated data is useful.[00:33:21] swyx: So I think there's some debate going on there, but I don't think it's much debate anymore that at least synthetic data, for the reasons that are blessed in Luna's talk, Makes sense.[00:33:32] swyx: I don't know if you have any perspectives there.[00:33:34] Alessio: I think, again, going back to the reinforcement fine tuning, I think that will change a little bit how people think about it. I think today people mostly use synthetic data, yeah, for distillation and kind of like fine tuning a smaller model from like a larger model.[00:33:46] Alessio: I'm not super aware of how the frontier labs use it outside of like the rephrase, the web thing that Apple also did. But yeah, I think it'll be. Useful. I think like whether or not that gets us the big [00:34:00] next step, I think that's maybe like TBD, you know, I think people love talking about data because it's like a GPU poor, you know, I think, uh, synthetic data is like something that people can do, you know, so they feel more opinionated about it compared to, yeah, the optimizers stuff, which is like,[00:34:17] swyx: they don't[00:34:17] Alessio: really work[00:34:18] swyx: on.[00:34:18] swyx: I think that there is an angle to the reasoning synthetic data. So this year, we covered in the paper club, the star series of papers. So that's star, Q star, V star. It basically helps you to synthesize reasoning steps, or at least distill reasoning steps from a verifier. And if you look at the OpenAI RFT, API that they released, or that they announced, basically they're asking you to submit graders, or they choose from a preset list of graders.[00:34:49] swyx: Basically It feels like a way to create valid synthetic data for them to fine tune their reasoning paths on. Um, so I think that is another angle where it starts to make sense. And [00:35:00] so like, it's very funny that basically all the data quality wars between Let's say the music industry or like the newspaper publishing industry or the textbooks industry on the big labs.[00:35:11] swyx: It's all of the pre training era. And then like the new era, like the reasoning era, like nobody has any problem with all the reasoning, especially because it's all like sort of math and science oriented with, with very reasonable graders. I think the more interesting next step is how does it generalize beyond STEM?[00:35:27] swyx: We've been using O1 for And I would say like for summarization and creative writing and instruction following, I think it's underrated. I started using O1 in our intro songs before we killed the intro songs, but it's very good at writing lyrics. You know, I can actually say like, I think one of the O1 pro demos.[00:35:46] swyx: All of these things that Noam was showing was that, you know, you can write an entire paragraph or three paragraphs without using the letter A, right?[00:35:53] Creative Writing with AI[00:35:53] swyx: So like, like literally just anything instead of token, like not even token level, character level manipulation and [00:36:00] counting and instruction following. It's, uh, it's very, very strong.[00:36:02] swyx: And so no surprises when I ask it to rhyme, uh, and to, to create song lyrics, it's going to do that very much better than in previous models. So I think it's underrated for creative writing.[00:36:11] Alessio: Yeah.[00:36:12] Legal and Ethical Issues in AI[00:36:12] Alessio: What do you think is the rationale that they're going to have in court when they don't show you the thinking traces of O1, but then they want us to, like, they're getting sued for using other publishers data, you know, but then on their end, they're like, well, you shouldn't be using my data to then train your model.[00:36:29] Alessio: So I'm curious to see how that kind of comes. Yeah, I mean, OPA has[00:36:32] swyx: many ways to publish, to punish people without bringing, taking them to court. Already banned ByteDance for distilling their, their info. And so anyone caught distilling the chain of thought will be just disallowed to continue on, on, on the API.[00:36:44] swyx: And it's fine. It's no big deal. Like, I don't even think that's an issue at all, just because the chain of thoughts are pretty well hidden. Like you have to work very, very hard to, to get it to leak. And then even when it leaks the chain of thought, you don't know if it's, if it's [00:37:00] The bigger concern is actually that there's not that much IP hiding behind it, that Cosign, which we talked about, we talked to him on Dev Day, can just fine tune 4.[00:37:13] swyx: 0 to beat 0. 1 Cloud SONET so far is beating O1 on coding tasks without, at least O1 preview, without being a reasoning model, same for Gemini Pro or Gemini 2. 0. So like, how much is reasoning important? How much of a moat is there in this, like, All of these are proprietary sort of training data that they've presumably accomplished.[00:37:34] swyx: Because even DeepSeek was able to do it. And they had, you know, two months notice to do this, to do R1. So, it's actually unclear how much moat there is. Obviously, you know, if you talk to the Strawberry team, they'll be like, yeah, I mean, we spent the last two years doing this. So, we don't know. And it's going to be Interesting because there'll be a lot of noise from people who say they have inference time compute and actually don't because they just have fancy chain of thought.[00:38:00][00:38:00] swyx: And then there's other people who actually do have very good chain of thought. And you will not see them on the same level as OpenAI because OpenAI has invested a lot in building up the mythology of their team. Um, which makes sense. Like the real answer is somewhere in between.[00:38:13] Alessio: Yeah, I think that's kind of like the main data war story developing.[00:38:18] The Data War: GPU Poor vs. GPU Rich[00:38:18] Alessio: GPU poor versus GPU rich. Yeah. Where do you think we are? I think there was, again, going back to like the small model thing, there was like a time in which the GPU poor were kind of like the rebel faction working on like these models that were like open and small and cheap. And I think today people don't really care as much about GPUs anymore.[00:38:37] Alessio: You also see it in the price of the GPUs. Like, you know, that market is kind of like plummeted because there's people don't want to be, they want to be GPU free. They don't even want to be poor. They just want to be, you know, completely without them. Yeah. How do you think about this war? You[00:38:52] swyx: can tell me about this, but like, I feel like the, the appetite for GPU rich startups, like the, you know, the, the funding plan is we will raise 60 million and [00:39:00] we'll give 50 of that to NVIDIA.[00:39:01] swyx: That is gone, right? Like, no one's, no one's pitching that. This was literally the plan, the exact plan of like, I can name like four or five startups, you know, this time last year. So yeah, GPU rich startups gone.[00:39:12] The Rise of GPU Ultra Rich[00:39:12] swyx: But I think like, The GPU ultra rich, the GPU ultra high net worth is still going. So, um, now we're, you know, we had Leopold's essay on the trillion dollar cluster.[00:39:23] swyx: We're not quite there yet. We have multiple labs, um, you know, XAI very famously, you know, Jensen Huang praising them for being. Best boy number one in spinning up 100, 000 GPU cluster in like 12 days or something. So likewise at Meta, likewise at OpenAI, likewise at the other labs as well. So like the GPU ultra rich are going to keep doing that because I think partially it's an article of faith now that you just need it.[00:39:46] swyx: Like you don't even know what it's going to, what you're going to use it for. You just, you just need it. And it makes sense that if, especially if we're going into. More researchy territory than we are. So let's say 2020 to 2023 was [00:40:00] let's scale big models territory because we had GPT 3 in 2020 and we were like, okay, we'll go from 1.[00:40:05] swyx: 75b to 1. 8b, 1. 8t. And that was GPT 3 to GPT 4. Okay, that's done. As far as everyone is concerned, Opus 3. 5 is not coming out, GPT 4. 5 is not coming out, and Gemini 2, we don't have Pro, whatever. We've hit that wall. Maybe I'll call it the 2 trillion perimeter wall. We're not going to 10 trillion. No one thinks it's a good idea, at least from training costs, from the amount of data, or at least the inference.[00:40:36] swyx: Would you pay 10x the price of GPT Probably not. Like, like you want something else that, that is at least more useful. So it makes sense that people are pivoting in terms of their inference paradigm.[00:40:47] Emerging Trends in AI Models[00:40:47] swyx: And so when it's more researchy, then you actually need more just general purpose compute to mess around with, uh, at the exact same time that production deployments of the old, the previous paradigm is still ramping up,[00:40:58] swyx: um,[00:40:58] swyx: uh, pretty aggressively.[00:40:59] swyx: So [00:41:00] it makes sense that the GPU rich are growing. We have now interviewed both together and fireworks and replicates. Uh, we haven't done any scale yet. But I think Amazon, maybe kind of a sleeper one, Amazon, in a sense of like they, at reInvent, I wasn't expecting them to do so well, but they are now a foundation model lab.[00:41:18] swyx: It's kind of interesting. Um, I think, uh, you know, David went over there and started just creating models.[00:41:25] Alessio: Yeah, I mean, that's the power of prepaid contracts. I think like a lot of AWS customers, you know, they do this big reserve instance contracts and now they got to use their money. That's why so many startups.[00:41:37] Alessio: Get bought through the AWS marketplace so they can kind of bundle them together and prefer pricing.[00:41:42] swyx: Okay, so maybe GPU super rich doing very well, GPU middle class dead, and then GPU[00:41:48] Alessio: poor. I mean, my thing is like, everybody should just be GPU rich. There shouldn't really be, even the GPU poorest, it's like, does it really make sense to be GPU poor?[00:41:57] Alessio: Like, if you're GPU poor, you should just use the [00:42:00] cloud. Yes, you know, and I think there might be a future once we kind of like figure out what the size and shape of these models is where like the tiny box and these things come to fruition where like you can be GPU poor at home. But I think today is like, why are you working so hard to like get these models to run on like very small clusters where it's like, It's so cheap to run them.[00:42:21] Alessio: Yeah, yeah,[00:42:22] swyx: yeah. I think mostly people think it's cool. People think it's a stepping stone to scaling up. So they aspire to be GPU rich one day and they're working on new methods. Like news research, like probably the most deep tech thing they've done this year is Distro or whatever the new name is.[00:42:38] swyx: There's a lot of interest in heterogeneous computing, distributed computing. I tend generally to de emphasize that historically, but it may be coming to a time where it is starting to be relevant. I don't know. You know, SF compute launched their compute marketplace this year, and like, who's really using that?[00:42:53] swyx: Like, it's a bunch of small clusters, disparate types of compute, and if you can make that [00:43:00] useful, then that will be very beneficial to the broader community, but maybe still not the source of frontier models. It's just going to be a second tier of compute that is unlocked for people, and that's fine. But yeah, I mean, I think this year, I would say a lot more on device, We are, I now have Apple intelligence on my phone.[00:43:19] swyx: Doesn't do anything apart from summarize my notifications. But still, not bad. Like, it's multi modal.[00:43:25] Alessio: Yeah, the notification summaries are so and so in my experience.[00:43:29] swyx: Yeah, but they add, they add juice to life. And then, um, Chrome Nano, uh, Gemini Nano is coming out in Chrome. Uh, they're still feature flagged, but you can, you can try it now if you, if you use the, uh, the alpha.[00:43:40] swyx: And so, like, I, I think, like, you know, We're getting the sort of GPU poor version of a lot of these things coming out, and I think it's like quite useful. Like Windows as well, rolling out RWKB in sort of every Windows department is super cool. And I think the last thing that I never put in this GPU poor war, that I think I should now, [00:44:00] is the number of startups that are GPU poor but still scaling very well, as sort of wrappers on top of either a foundation model lab, or GPU Cloud.[00:44:10] swyx: GPU Cloud, it would be Suno. Suno, Ramp has rated as one of the top ranked, fastest growing startups of the year. Um, I think the last public number is like zero to 20 million this year in ARR and Suno runs on Moto. So Suno itself is not GPU rich, but they're just doing the training on, on Moto, uh, who we've also talked to on, on the podcast.[00:44:31] swyx: The other one would be Bolt, straight cloud wrapper. And, and, um, Again, another, now they've announced 20 million ARR, which is another step up from our 8 million that we put on the title. So yeah, I mean, it's crazy that all these GPU pores are finding a way while the GPU riches are also finding a way. And then the only failures, I kind of call this the GPU smiling curve, where the edges do well, because you're either close to the machines, and you're like [00:45:00] number one on the machines, or you're like close to the customers, and you're number one on the customer side.[00:45:03] swyx: And the people who are in the middle. Inflection, um, character, didn't do that great. I think character did the best of all of them. Like, you have a note in here that we apparently said that character's price tag was[00:45:15] Alessio: 1B.[00:45:15] swyx: Did I say that?[00:45:16] Alessio: Yeah. You said Google should just buy them for 1B. I thought it was a crazy number.[00:45:20] Alessio: Then they paid 2. 7 billion. I mean, for like,[00:45:22] swyx: yeah.[00:45:22] Alessio: What do you pay for node? Like, I don't know what the game world was like. Maybe the starting price was 1B. I mean, whatever it was, it worked out for everybody involved.[00:45:31] The Multi-Modality War[00:45:31] Alessio: Multimodality war. And this one, we never had text to video in the first version, which now is the hottest.[00:45:37] swyx: Yeah, I would say it's a subset of image, but yes.[00:45:40] Alessio: Yeah, well, but I think at the time it wasn't really something people were doing, and now we had VO2 just came out yesterday. Uh, Sora was released last month, last week. I've not tried Sora, because the day that I tried, it wasn't, yeah. I[00:45:54] swyx: think it's generally available now, you can go to Sora.[00:45:56] swyx: com and try it. Yeah, they had[00:45:58] Alessio: the outage. Which I [00:46:00] think also played a part into it. Small things. Yeah. What's the other model that you posted today that was on Replicate? Video or OneLive?[00:46:08] swyx: Yeah. Very, very nondescript name, but it is from Minimax, which I think is a Chinese lab. The Chinese labs do surprisingly well at the video models.[00:46:20] swyx: I'm not sure it's actually Chinese. I don't know. Hold me up to that. Yep. China. It's good. Yeah, the Chinese love video. What can I say? They have a lot of training data for video. Or a more relaxed regulatory environment.[00:46:37] Alessio: Uh, well, sure, in some way. Yeah, I don't think there's much else there. I think like, you know, on the image side, I think it's still open.[00:46:45] Alessio: Yeah, I mean,[00:46:46] swyx: 11labs is now a unicorn. So basically, what is multi modality war? Multi modality war is, do you specialize in a single modality, right? Or do you have GodModel that does all the modalities? So this is [00:47:00] definitely still going, in a sense of 11 labs, you know, now Unicorn, PicoLabs doing well, they launched Pico 2.[00:47:06] swyx: 0 recently, HeyGen, I think has reached 100 million ARR, Assembly, I don't know, but they have billboards all over the place, so I assume they're doing very, very well. So these are all specialist models, specialist models and specialist startups. And then there's the big labs who are doing the sort of all in one play.[00:47:24] swyx: And then here I would highlight Gemini 2 for having native image output. Have you seen the demos? Um, yeah, it's, it's hard to keep up. Literally they launched this last week and a shout out to Paige Bailey, who came to the Latent Space event to demo on the day of launch. And she wasn't prepared. She was just like, I'm just going to show you.[00:47:43] swyx: So they have voice. They have, you know, obviously image input, and then they obviously can code gen and all that. But the new one that OpenAI and Meta both have but they haven't launched yet is image output. So you can literally, um, I think their demo video was that you put in an image of a [00:48:00] car, and you ask for minor modifications to that car.[00:48:02] swyx: They can generate you that modification exactly as you asked. So there's no need for the stable diffusion or comfy UI workflow of like mask here and then like infill there in paint there and all that, all that stuff. This is small model nonsense. Big model people are like, huh, we got you in as everything in the transformer.[00:48:21] swyx: This is the multimodality war, which is, do you, do you bet on the God model or do you string together a whole bunch of, uh, Small models like a, like a chump. Yeah,[00:48:29] Alessio: I don't know, man. Yeah, that would be interesting. I mean, obviously I use Midjourney for all of our thumbnails. Um, they've been doing a ton on the product, I would say.[00:48:38] Alessio: They launched a new Midjourney editor thing. They've been doing a ton. Because I think, yeah, the motto is kind of like, Maybe, you know, people say black forest, the black forest models are better than mid journey on a pixel by pixel basis. But I think when you put it, put it together, have you tried[00:48:53] swyx: the same problems on black forest?[00:48:55] Alessio: Yes. But the problem is just like, you know, on black forest, it generates one image. And then it's like, you got to [00:49:00] regenerate. You don't have all these like UI things. Like what I do, no, but it's like time issue, you know, it's like a mid[00:49:06] swyx: journey. Call the API four times.[00:49:08] Alessio: No, but then there's no like variate.[00:49:10] Alessio: Like the good thing about mid journey is like, you just go in there and you're cooking. There's a lot of stuff that just makes it really easy. And I think people underestimate that. Like, it's not really a skill issue, because I'm paying mid journey, so it's a Black Forest skill issue, because I'm not paying them, you know?[00:49:24] Alessio: Yeah,[00:49:25] swyx: so, okay, so, uh, this is a UX thing, right? Like, you, you, you understand that, at least, we think that Black Forest should be able to do all that stuff. I will also shout out, ReCraft has come out, uh, on top of the image arena that, uh, artificial analysis has done, has apparently, uh, Flux's place. Is this still true?[00:49:41] swyx: So, Artificial Analysis is now a company. I highlighted them I think in one of the early AI Newses of the year. And they have launched a whole bunch of arenas. So, they're trying to take on LM Arena, Anastasios and crew. And they have an image arena. Oh yeah, Recraft v3 is now beating Flux 1. 1. Which is very surprising [00:50:00] because Flux And Black Forest Labs are the old stable diffusion crew who left stability after, um, the management issues.[00:50:06] swyx: So Recurve has come from nowhere to be the top image model. Uh, very, very strange. I would also highlight that Grok has now launched Aurora, which is, it's very interesting dynamics between Grok and Black Forest Labs because Grok's images were originally launched, uh, in partnership with Black Forest Labs as a, as a thin wrapper.[00:50:24] swyx: And then Grok was like, no, we'll make our own. And so they've made their own. I don't know, there are no APIs or benchmarks about it. They just announced it. So yeah, that's the multi modality war. I would say that so far, the small model, the dedicated model people are winning, because they are just focused on their tasks.[00:50:42] swyx: But the big model, People are always catching up. And the moment I saw the Gemini 2 demo of image editing, where I can put in an image and just request it and it does, that's how AI should work. Not like a whole bunch of complicated steps. So it really is something. And I think one frontier that we haven't [00:51:00] seen this year, like obviously video has done very well, and it will continue to grow.[00:51:03] swyx: You know, we only have Sora Turbo today, but at some point we'll get full Sora. Oh, at least the Hollywood Labs will get Fulsora. We haven't seen video to audio, or video synced to audio. And so the researchers that I talked to are already starting to talk about that as the next frontier. But there's still maybe like five more years of video left to actually be Soda.[00:51:23] swyx: I would say that Gemini's approach Compared to OpenAI, Gemini seems, or DeepMind's approach to video seems a lot more fully fledged than OpenAI. Because if you look at the ICML recap that I published that so far nobody has listened to, um, that people have listened to it. It's just a different, definitely different audience.[00:51:43] swyx: It's only seven hours long. Why are people not listening? It's like everything in Uh, so, so DeepMind has, is working on Genie. They also launched Genie 2 and VideoPoet. So, like, they have maybe four years advantage on world modeling that OpenAI does not have. Because OpenAI basically only started [00:52:00] Diffusion Transformers last year, you know, when they hired, uh, Bill Peebles.[00:52:03] swyx: So, DeepMind has, has a bit of advantage here, I would say, in, in, in showing, like, the reason that VO2, while one, They cherry pick their videos. So obviously it looks better than Sora, but the reason I would believe that VO2, uh, when it's fully launched will do very well is because they have all this background work in video that they've done for years.[00:52:22] swyx: Like, like last year's NeurIPS, I already was interviewing some of their video people. I forget their model name, but for, for people who are dedicated fans, they can go to NeurIPS 2023 and see, see that paper.[00:52:32] Alessio: And then last but not least, the LLMOS. We renamed it to Ragops, formerly known as[00:52:39] swyx: Ragops War. I put the latest chart on the Braintrust episode.[00:52:43] swyx: I think I'm going to separate these essays from the episode notes. So the reason I used to do that, by the way, is because I wanted to show up on Hacker News. I wanted the podcast to show up on Hacker News. So I always put an essay inside of there because Hacker News people like to read and not listen.[00:52:58] Alessio: So episode essays,[00:52:59] swyx: I remember [00:53:00] purchasing them separately. You say Lanchain Llama Index is still growing.[00:53:03] Alessio: Yeah, so I looked at the PyPy stats, you know. I don't care about stars. On PyPy you see Do you want to share your screen? Yes. I prefer to look at actual downloads, not at stars on GitHub. So if you look at, you know, Lanchain still growing.[00:53:20] Alessio: These are the last six months. Llama Index still growing. What I've basically seen is like things that, One, obviously these things have A commercial product. So there's like people buying this and sticking with it versus kind of hopping in between things versus, you know, for example, crew AI, not really growing as much.[00:53:38] Alessio: The stars are growing. If you look on GitHub, like the stars are growing, but kind of like the usage is kind of like flat. In the last six months, have they done some[00:53:4

Have you ever stumbled upon an article or a piece of content online and wondered, "Did someone actually write this, or is it the work of ChatGPT?" In today's world, where content is produced at an incredible pace, it's becoming increasingly difficult to tell the difference.. and that's a problem in the age of misinformation.Think about it: people are getting their news on social media, X, Youtube or Facebook! With the advancements of AI, it's hard to tell how something online can be truly authentic. With latest studies showing >12% of Google's search results being AI-generated, it's critical to ensure the integrity of the digital content we consume and create.  That's where Originality AI comes in! We're thrilled to host Jon Gillham, founder and CEO on Things Have Changed. as he shares how his team are tackling these issues head-on by developing cutting-edge tech to detect AI-generated content. In a short span of time, Originality AI have achieved remarkable results, and is the most accurate AI Detector in the market for ChatGPT, GPT-4o, Gemini Pro, Claude 3, Llama 3 etc.So today on Things Have Changed, we'll dive deep into how Originality AI works, its impact on various industries, and why ensuring content authenticity is more important than ever.The Growth GearExplore business growth and success strategies with Tim Jordan on 'The Growth Gear.Listen on: Apple Podcasts Spotify PodMatchPodMatch Automatically Matches Ideal Podcast Guests and Hosts For InterviewsSupport the Show.Things Have Changed

ChatGPT Plugins are on their way out! Tyler Perry is putting his studio expansion on hold due to AI, and Google is making TONS of news right now! Here's this week's AI news that matters and why it's important. Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode pageJoin the discussion: Ask Jordan questions on AIRelated Episodes:Ep 211: OpenAI's Sora – The larger impact that no one's talking aboutEp 204: Google Gemini Advanced – 7 things you need to knowTomorrow' Show: How to stand out in a world where everyone can create an AI Startup?Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTimestamps:03:42 Tyler Perry concerned about AI job loss.07:22 OpenAI Sora video excels over other platforms.12:54 11 Labs updated model, ChatGPT phasing out.15:27  Plugin packs for ChatGPT.16:55 Limitations on using multiple GPTs for now.22:16 Unsatisfied with Google Gemini Enterprise integration.23:13 Google and Reddit partnership for language models.28:39 Google Gemini Images paused due to diversity concerns.31:16 Google now has three Gemini models.34:54 Best text-to-speech AI37:11 AI content creation raises copyright concernsTopics Covered in This Episode:1. OpenAI's changes and future focus2. Google's Significant AI content deal with Reddit3. Google's AI model developments and issues4.  Trends in AI utilization within the entertainment industryKeywords:OpenAI, GPT, AI agents, AI assistants, prime prompt polish program, Google, Reddit, AI content licensing deal, AI models, search engine, Gemini AI, large language models, user-generated content, university student data, Google Gemini Imagine 2, Gemma, Gemini Ultra, Gemini Pro, Gemini Nano, Tyler Perry, Sora, AI in entertainment, text-to-speech AI, business productivity, ChatGPT plugins, Well Said Labs, Asura, AI video platforms, Perry's studio expansion, AI regulation