Podcasts about deeps

He Interrupted Her Mid-Sentence and Said "I Don't Agree." She Asked: "How Many Recruitment Drives Have You Led?" CHRO Deepashri on Standing Your Ground It was her first day in a new role. The leadership team was deep into planning the launch of a major production system. She raised her hand and asked: "What about the people strategy?" Everyone looked at her like she was speaking a different language. "What does people have to do with this? It's a manufacturing system." She asked again. Still dismissed. Still polite. Still ignored. She could have let it go. Instead, she spent six months building an irrefutable business case. She spoke to the consultants. She researched the ROI. She calculated exactly what would be lost if people failed to adopt the system. She pre-worked the stakeholders she already had relationships with, one by one, so she would not be the only voice in the room when the moment came. Then she walked into a meeting with the global head of manufacturing, the global head of HR, and the other senior sponsors. She was the only woman in the room. She was a nervous wreck. She had her game face on. She got the budget. She got the resources. She built a people pillar that outlasted her, survived an acquisition, and is still running today. Deepashri is Chief Human Resources Officer at 8th Ave Food and Provisions. In this episode, she shares two very different stories of standing her ground at work — one strategic and six months in the making, one instinctive and decided in seconds — and what she learned from both. You'll learn: Why she refused to use HR buzzwords like "empathy" or "doing the right thing" when pitching to hard-nosed manufacturing executives, and what she said instead to make her idea impossible to ignore. The pre-meeting strategy she uses before any high-stakes pitch: influence the people you already have relationships with one-on-one first, so you are never the only advocate in the room. How she walked into the biggest pitch of her career feeling like a nervous wreck, knowing that if she failed, she would be "just another person on the leadership team with no voice." The investment banker who interrupted her mid-sentence and said "I don't agree." What she said back, why she still calls him a friend today, and what happened when she pulled it off. Why she thought she was being assertive in a conversation that completely failed to land, what her coach told her, and the three-part technique she developed to deliver the most difficult messages in a way that registered clearly without feeling disrespectful. Why assertiveness looks and sounds different across cultures, and how she learned to calibrate between India's indirect communication style and the blunt directness expected in U.S. corporate environments. Her best career compliment: "Deeps will tell you the most difficult things in the nicest possible way." About Deepashri: Chief Human Resources Officer at 8th Ave Food and Provisions, Deepashri has built her career across global HR, change management, and organizational transformation roles in India and the United States. She is a coach, storyteller, and advocate for assertive communication across cultures.

Fresh off raising a monster $15B, Marc Andreessen has lived through multiple computing platform shifts firsthand, from Mosaic and Netscape to cofounding A16z. In this episode, Marc joins swyx and Alessio in a16z's legendary Sand Hill Road office to argue that AI is not just another hype cycle, but the payoff of an “80-year overnight success”: from neural nets and expert systems to transformers, reasoning models, coding, agents, and recursive self-improvement. He lays out why he thinks this moment is different, why AI is finally escaping the old boom-bust pattern, and why the real bottleneck may be less about models than about the messy institutions, incentives, and social systems that struggle to absorb technological change.This episode was a dream come true for us, and many thanks to Erik Torenberg for the assist in setting this up. Full episode on YouTube!We discuss:* Marc's long view on AI: from the 1980s AI boom and expert systems to AlexNet, transformers, and why he sees today's moment as the culmination of decades of compounding technical progress* Why “this time is different”: the jump from LLMs to reasoning, coding, agents, and recursive self-improvement, and why Marc thinks these breakthroughs make AI real in a way prior cycles were not* AI winters vs. “80-year overnight success”: why the field repeatedly swings between utopianism and doom, and why Marc thinks the underlying researchers were mostly right even when the timelines were wrong* Scaling laws, Moore's Law, and what to build: why he believes AI scaling laws will continue, why the outside world is messier than lab purists assume, and how startups can still create durable value on top of rapidly improving models* The dot-com crash and AI infrastructure risk: Marc's comparison between today's AI capex boom and the fiber/data-center overbuild of 2000, plus why he thinks this cycle is different because the buyers are huge cash-rich incumbents and demand is already here* Why old NVIDIA chips may be getting more valuable: the pace of software progress, chronic capacity shortages, and the idea that even current models are “sandbagged” by supply constraints* Open source, edge inference, and the chip bottleneck: why Marc thinks local models, Apple Silicon, privacy, trust, and economics all point toward a major role for edge AI* American vs. Chinese open source AI: DeepSeek as a “gift to the world,” why open models matter not just because they're free but because they teach the world how things work, and how open source strategies may shift as the market consolidates* Why Pi and OpenClaw matter so much: Marc's claim that the combination of LLM + shell + filesystem + markdown + cron loop is one of the biggest software architecture breakthroughs in decades* Agents as the new “Unix”: how agent state living in files allows portability across models and runtimes, and why self-modifying agents that can extend themselves may redefine what software even is* The future of coding and programming languages: why Marc thinks software becomes abundant, why bots may translate freely across languages, and why “programming language” itself may stop being a salient concept* Browsers, protocols, and human readability: lessons from Mosaic and the web, why text protocols and “view source” mattered, and how similar principles may shape AI-native systems* Real-world OpenClaw use: health dashboards, sleep monitoring, smart homes, rewriting firmware on robot dogs, and why the most aggressive users are discovering both the power and danger of agents first* Proof of human vs. proof of bot: why Marc thinks the internet's bot problem is now unsolvable via detection alone, and why biometric + cryptographic proof of human becomes necessaryTimestamps* 00:00 Marc on AI's “80-Year Overnight Success”* 00:01 A Quick Message From swyx* 01:44 Inside a16z With Marc Andreessen* 02:13 The Truth About a16z's AI Pivot* 03:29 Why This AI Boom Is Not Like 2016* 06:33 Marc on AI Winters, Hype Cycles, and What's Different Now* 10:09 Reasoning, Coding, Agents, and the New AI Breakthroughs* 12:13 What Founders Should Build as Models Keep Improving* 16:33 AI Capex, GPU Shortages, and the Dot-Com Crash Analogy* 24:54 Open Source AI, Edge Inference, and Why It Matters* 33:03 Why OpenClaw and PI Could Change Software Forever* 41:37 Agents, the End of Interfaces, and Software for Bots* 46:47 Do Programming Languages Even Have a Future?* 54:19 AI Agents Need Money: Payments, Crypto, and Stablecoins* 56:59 Proof of Human, Internet Bots, and the Drone Problem* 01:06:12 AI, Management, and the Return of Founder-Led Companies* 01:12:23 Why the Real Economy May Resist AI Longer Than Expected* 01:15:53 Closing ThoughtsTranscriptMarc: Something about AI that causes the people in the field, I would say, to become both excessively utopian and excessively apocalyptic. Having said that, I think what's actually happened is an enormous amount of technical progress that built up over time. And like for, for example, we now know that neural network is the correct architecture.And I, I will tell you like there was a 60 year run where that was like a, you know, or even 70 years where that was controversial. And so, so the way I think about what's happening is basically, I think, I think about basically the, the, the period we're in right now is it's, I call it 80 year overnight success, right?Which is like, it's an overnight success ‘cause it's like bam, you know, chat GPT hits and then, and then oh one hits, and then, you know, open claw hits and like, you know, these are open, these are, these are like overnight, like radical, overnight transformative successes, but they're drawing on an 80 year sort of wellspring backlog, you know, of, of, of, of ideas and thinking it's not just that it's all brand new, it's that it's an unlock of all of these decades of like very serious, hardcore research.If I were 18, like this is a hundred, this is what I would be spending all of my time on. This is like such an incredible conceptual breakthrough.swyx: Before we get into today's episode, I just have a small message for listeners. Thank you. We will not be able to bring you the ai, engineering, science, and entertainment contents that you so clearly want if you didn't choose to also click in and tune into our content.We've been approached by sponsors on an almost daily basis, but fortunately enough of you actually subscribed to us to keep all this sustainable without ads, and we wanna keep it that way. But I just have one favor to ask all of you. The single, most powerful, completely free thing you can do is to click that subscribe button.It's the only thing I'll ever ask of you, and it means absolutely everything to me and my team that works so hard to bring the in space to you each and every week. If you do it, I promise you will never stop working to make the show even better. Now, let's get into it.Alessio: Hey everyone, welcome to the Lidian Space Pockets. This is CIO, founder Kernel Labs, and I'm joined by s Swix, editor of Lidian Space.swyx: Hello. And we're in a 16 Z with a, uh, mark G and welcome.Marc: Yes, yes. A and what, half of 16? Something like that. A one. Exactly,swyx: exactly. Uh, apparently this is the, the final few days in your, your current office.You're moving across the road.Marc: Uh, we're, yeah. We have a, we have some, we have some projects underway, but yeah, this is actually, oh, this is the original. We're in actually the original office. We're in the, we're in the, we're, we're in the whole thing.swyx: It's beautiful. Yeah. Great.Marc: Thank you.swyx: So I have to come out, uh, this is a, you know, I wanted to pick a spicy start in October, 2022.I just made friends with Roone and, uh, I wanted to give him something to sort of be spicy about. And I said, uh. Uh, it'll never not be funny. The A 16 Z was constantly going. The future is where the smart people choose to spend their time and then going deep into crypto and not in ai. And that was in October 22nd, 2022.And Ruen says there was an internal meeting in a 16 Z to reorient around Gen ai. Obviously you have, but was there a meeting? What, what was that?Marc: I mean, I don't, look, I've been doing AI since the late eighties.swyx: Yeah.Marc: So I, I don't know, like all that, as far as I'm concerned, this stuff is all Johnny cum lately.Yeah. You, I mean, look, we've been doing ar entire existence. I mean, we've been doing AI machine learning deep, you know, deeply. We've been doing this stuff way from the beginning. Obviously a AI is just core to computer science. I, I, I actually view them as like quite, uh, quite continuous. Um, you know, Ben and I both have computer science degrees.Um, you know, we, we both, Ben, Ben and I actually both are world enough to remember the actual AI boom in the 1980s. Yeah. There was like a, there was a big AI boom at the time. Um, and there was a, was names like expert systems. Um, and they of like lisp and lisp machines. Uh, I, I coded in lisp. I was coding a lisp in 1989.When that was the, the language of the AI future. Um, yeah. So this is something that we're like completely, you completely comfortable with. I've been doing the whole time and are very enthusiastic aboutswyx: is there a strong, like this time is different because, uh, my closest analog was 20 16 17. It was an AI boom.Mm-hmm. And it petered out very, very quickly. Um, we, it just, it just in terms of investingMarc: sort of, sort of,swyx: yeah. Investment, investment excitement.Marc: Although that's really when the, the, the Nvidia phenomenon really, it was, I would say it was in that period when it was very clear that at, at the time it, the vocabulary was more machine learning, but it, it was very clear at that time that machine learning was hitting some sort of takeoff point.Alessio: Yeah.Marc: Well, and as you guys, you guys have talked about this at length on, on your thing, but, you know, if you really track what happened, I think the real story is, it was, it was the Alex net, uh, basically breakthrough in like 2013. That was the, that was the real knee in the curve. Um, and then it was obviously the transformer breakthrough in 17.Alessio: Yeah.Marc: Um, and then everything that followed. But, but, you know, look, machine learning, you know, there were, you know, look, uh, I mean look, I've been working, you know, I've been working with, uh, one of my, you know, kind of projects working with Facebook since 2004. Um, and on the board since 2007, and of course, you know, they, they started using machine learning very early, um, and, you know, have used it basically, you know, for like 20 years for, you know, content, you know, feed optimization and advertising optimization.And obviously many, you know, financial services. You know, many, many, many companies, many different sectors have been doing this. And so it's like one of these things, it's like, it's not a, it's not a single thing. Like it's, it's like, it's like layers, right? Yeah. Um, and, and the layers arrive at different paces and, but they kind of build up.swyx: Yeah.Marc: Uh, they kind of build up over time and then, and then, yeah. And then look, in retrospect, it was 2017 was kind of the, you know, the key, the key point with the trans transformer and then. And then as you guys know, there was this really weird like four year period where it's like the, the transformer existed and then it was just like,swyx: let's go.Yeah.Marc: Well, but, but it was just, but, but between 2020, but between 2017 and 2021, I mean, that was the era of which like companies like Google had internal chat Botts, but they weren't letting anybody use them.swyx: Yeah.Marc: Right. And then, you know, and then OpenAI developed Chat GT or GPT two, and then they told everybody, this is way too dangerous to deploy.Right. Yeah. You know, we can't possibly let normal people, normal people use this thing. And then you, you guys, I'm sure remember AI Dungeon, um mm-hmm. So the o for, there was like a year where like the only way for a normal person to use GP T three was in, in AI dungeon.Alessio: Yeah.Marc: And so you, you, we would do this, you'd go in there and you'd pretend to play Dungeons and Dragons.In reality, you're just trying to talk to talk to GPT. And so there was this, you know, there was this long, you know, and I, you know, the big, big companies, you know, big companies are cautious and, you know, the big companies were cautious. It, it, by the way, it took open ai. You know, they, they, they talk about this, it took open AI time to actually adjust, you know, kind of re redirect their researchswyx: path.I, I think, uh, let say Rosewood, right? Uh, the, the dinner that founded OpenAI was right there.Marc: Right, right. But that, that dinner would've taken place in 20swyx: 18Marc: 19. The formation of OpenAI Uhhuh as late as 2018.swyx: Uh, uh, sorry. Uh, no, I'm, I'm, I'm, I'm wrong. Probably It should be 20. Yeah. They just celebrated a 10 year anniversary, so it it is 2025.Yeah, so, so 2015?Marc: Yeah. 2015. Yeah. 2015. But then, uh, um, Alec Radford did G PT one in what, probablyswyx: mm-hmm. 17, 18,Marc: yeah. 17, 18. So it, yeah. For, and then, and then they didn't really, and then GPT three was what? 2020? 2020.swyx: 2020.Marc: Because that became copilot immediately. Even open ai, which has been, you know, the leader of, of this thing in the last decade, you know, e even they had to adapt and, and, and lean into the new thing.And so. Um, yeah, I, I think it's just this process of basically sort of wave after wave layer after layer, you know, building on itself. And then you kind of get these catalytic moments where, where the whole thing pops and, and obviously that's what's happening now.swyx: Is it useful to think about will there be any ai, winter?‘cause there's always these patterns. Like, is this, in the summer is something I constantly think about because do I get, do I just like. Just get endlessly hyped and just trust that I will only be early and never wrong or right. Well, are we, will there be a winter?Marc: So there's something about, say the following.There's something about AI that has led to this repeated pattern. Um, and, and, and you guys know this,swyx: it's summer, winter, summer,Marc: winter, summer, winter, summer, winter. And it goes back 80 years. Yeah. 80 years. Uh, so the original neural network paper was 1943. Right. Which is, which is amazing. Uh, that it was, it was far back that long.And then there was you, if you guys have ever talked about this on your show, but there was this, uh, there was a big, uh, there was an a GI conference at Dartmouth University in 1950. 55. 55, yeah. And they got a NSF grant to, uh, for the, all the AI experts at the time to spend the summer together. And they figured if they had 10 weeks together, they could get a GI, uh, at the other end.And they got their, by the way, they got the grant, they got the 10 weeks and then, you know, 1955, you know. No, no. A GI. And like I said, I, I lived through the eighties version of this where there was a big, a big boom and a crash. And so, so there is this thing, and there, there is something about AI that causes the people in the field, I would say, to become both excessively utopian and excessively apocalyptic.Um, and, and it's probably on both sides of like the, the, the boom bus cycle. You, you kind of see that play out. Having said that, I think what's actually happened is like just, and you know, and we now know in retrospect like an enormous amount of technical progress that built up over time. And like for, for example, we now know that neural network is the correct architecture.And I, I will tell you like there was a 60 year run where that was like a, you know, or even 70 years or that was controversial. And, and we now know that that's the case. And so we, we now, you know, everything we're building on today just sort of derives from the original idea in 1943. And so, so in retrospect, we, we now know that like, these, these guys are right.They, they, you know, they would get the timing wrong and they thought, you know, capabilities would arrive faster, or they were, it could be turned into businesses sooner or whatever, but like, they were fundamentally, the, the scientists who worked on this over the course of decades were fundamentally correct about what they were doing.And, and the, and the payoff from, from, from all their work is happening now. And so, so the way I think about what's happening is basically, I think, I think about basically the, the, the period we're in right now is it's, I call it 80 year overnight success, right? Which is like, it's an overnight success.‘cause it's like bam, you know, chat, GPT hits and then, and then oh one hits, and then, you know, open claw hits and like, you know, these are open, these are, these are like overnight, like radical, overnight transformative successes, but they're drawing on an 80 year sort of wellspring backlog, you know, of, of, of, of ideas and thinking it's not just that it's all brand new, it's that it's an unlock of all of these decades of like very serious, hardcore research.Um, and thinking, and look, there were AI researchers who spent their entire lives. They got their PhD. They, they worked for, they've researched for 40 years. They retired in a lot of cases, they passed away and they never actually saw it work.swyx: Yeah. It's all sad.Marc: It is. It is sad. It's sad. Knewswyx: Jeff Hinton was like the last guy.Marc: Yeah. Yeah. Well, there were the guys, uh, was a guy, Alan Newell. I mean, there's tons of John McCarthy. You know, John McCarthy was like one of the inventors in the field. He's one of the guys who organized the Dartmouth Conference and you know, he taught at Stanford for 40 years. Wow. And passed, you know, passed away, I don't know, whatever, 10, 10 years ago or something.Never, never actually go. Got to see it happen. But like, it is amazing in retrospect, like, these guys were incredibly smart and they worked really hard and they were correct. So anyway, so then it's like, okay, you know, say history doesn't repeat, but it rhymes. It's like, okay, does that mean that there's gonna be another, like, you know, basically boom buzz cycle.And I, I will tell you, like, let, like in a sense, like yes, everything goes through cycles and, you know, people get overly enthusiastic and overly depressed and there's, there's a time, there's a timelessness to that. Having said that, there's just no question. Um, so the form, the foremost dangerous words in investing this time are, this time is different.Do you know the 12 most dangerous words investing? No. The four most d foremost dangerous words in investing are this time is different. Yeah. Um, the 12 most dangerous words. And so like, I'll tell you what's different. Like now it's working like, like there's just no, I mean, look, there's just no question.And by the way, I, I'll just give you guys my take. Like L LLMs, like from, from basically the Chad G PT moment through to spring of 25. I think you could still, I think well intention, well, and of. Form skeptics could still say, oh, this is just pattern completion. And oh, these things don't really understand what they're doing.And you know, the hall hallucination rates are way too high. And, you know, this is gonna be great for creative writing and creating, you know, Shakespeare and so sonnets and, you know, as, as rap lyrics or whatever, like, it's gonna be great and all that stuff, but we're not gonna be able to harness this to make this relevant in, you know, coding or in medicine or in law or in, you know, you know, kind of feels that, you know, kind of really, really matter.And I think basically it was the reasoning breakthrough. It, it was oh one and then R one that basically answered that question basically said, oh no, we're gonna be able to actually turn this into something that's gonna work in the real world. And, and then obviously the coding breakthrough over the, over basically the coding breakthrough that kind of catalyzed over the holiday break was kind of the third step in that.Mm-hmm. Where you're just like, alright, if, if, you know, if Linus Tova is saying that the AI coding is no better than he is like. Like, that's, that's never happened before. That's theswyx: benchmark.Marc: Yeah. That's never happened before. And so now we know that it's, it's gonna sweep through coding and, and then, and then we, we know, you know, we know that if it's gonna work in coding, it's gonna work in everything else.Right. It's just then, because that's, that's like, that's like, that's like the hardest in many ways. That's the hardest example. And how everything else is gonna be a, a derivative of that. And then on top of that, we just got the agent breakthrough, you know, with Open Claw, which is fantastic. Which is amazing and incredibly powerful.And then we just got the, the, um, the auto research, uh, you know, the, the self-improvement. You know, we're now into the self-improvement breakthrough. And so the, so the way I think about it is we've had four fundamental breakthroughs in functionality, l OMS reasoning, uh, agents, um, and then, uh, and, and then now RSI, um, and, and they're all actually working.Um, and so I'm, I'm just, as you like, you can tell I'm jumping outta my shoes. Like, like this is, like this is it like this, this is the culmination of 80 years worth of worth of work, and this is the time it's becoming real.Alessio: Yeah.Marc: I, I'm completely convinced.Alessio: I think the anxiety that people feel is like during the transistor era, yet Mors law, and it's like, all right, we understand why these things are getting better.We understand the physics of it. Yeah. With ai, it's. It's so jagged in like the jumps where like, like you said, it's like in three months you have like this huge jump like, and people are like, well this can keep happening. Right? But then it keeps happening,Marc: it'll keep happening.Alessio: And so like how do you think about also timelines of like what's we're building?I think we always have this question with guests, which is like, you know, should you spend time building harness for a model versus like the next model just gonna do it one shot in the lead space. Right. And how does that inform, like how you think about the shape of the technology? You know, you talk about how it's a new computing platform.If you have a computing platform, then like every six months it like drastically changes in what it looks like. It's hard to build companies on top of it.Marc: Yeah. So, so a couple things. So one is like, look, the, the Moore's law was what we now call a scaling law. Like Moore's Law was a scaling law and for your younger viewers, more Moore's Law was every chip chip chips either get twice as powerful or twice as cheap every, every 18 months.And that, and that and that, you know, that it's gotten more complicated in the last few years. But like that, that was like the 50 year trajectory of, of, of the computer industry. And then, and then by the way, and that's what took the mainframe computer from a $25 million current dollar thing into, you know, the phone in your pocket being, you know, a million times more powerful than that.Like that, you know, for, for 500 bucks. And so that, that was a scaling law. And then, and then, and then key to any scaling law, including Moore's Law and the AI scaling laws is, you know, they're not really laws, right? They're, they're, they're, they're predictions, but when they work, they become self-fulfilling predictions because they, they, they, they, they set a benchmark and, and then the entire industry, right?All the smart people in the industry kind of work to make sure that, that, that actually happens. And so they, they kind of motivate the breakthroughs that are required to, to keep that going. And, and in and in chips, that was a 50 year, that was a 50 year run. Right. And it, it was amazing. And it's still happening in, in some areas of, of chips.I think the same thing is happening with the, the core scaling laws. The core scaling laws. In, in, in ai, you know, they're, they're not really laws, but like they, they are basically. There are predictions and then they're motivating catalysts for the research work that is required to be. And, and, and, and by the way, also the investment, uh, dollars, um, uh, you know, required to basically keep, you know, keep the curves going and, and look, it, it is, it's gonna be complicated and it's gonna be variable and they're, you know, there're gonna be walls that are gonna look like they're fast approaching, and then they're gonna be, you know, engineers are gonna get to work and they're gonna figure out a way to punch through the walls.And obviously that's, you know, that's been happening a lot, you know, and then look, there's gonna be times when it looks like the walls have, you know, the, the, the laws have petered out and then they're gonna, they're gonna pick up again and surge and then, and then, and then it, it appears what's happening to the eyes is there's not multiple, you know, multiple scaling laws.Um, there's multiple areas of improvement. And, and I think, you know, I don't know how many more there are already yet to be discovered, but there are probably some more that we don't know about yet. You know, they, like, for example, there's probably some scaling law around, um, world models and robotics that we don't fully understand, you know, kind of acquisition of data at scale in the real world that we don't fully understand yet.So that, that, that one will probably kick in at some point here. There's a bunch of really smart people working on that. Um, and so, yeah, I, I think the expectation is that, that, you know, the, the scaling laws generally are gonna continue. Yeah. The, the pace of improvement will continue to move really fast.Um. To your question on like what to build. So, uh, I'm a complete believer the scaling laws are gonna continue. I'm a complete believer the capabilities are gonna keep getting amazing, um, you know, leaps and bounds. Uh, the part where I kind of part ways a little bit with how, what I would describe as the AI purists, um, you know, which is, which I would characterize as like the people who are.In many ways, the smartest people in the field, but also the people who spend their entire life, like at a lab, um, and have, have, I would say, have very little experience in the outside world. Um, the, the, the nuance I would offer is the outside world of 8 billion people and institutions and governments and companies and economic systems and social systems is really complicated.Um, and, um, and doesn't, you know, it it 8 billion people making collective decisions on planet Earth is not a simple process of like, just like you see this happening now. It's like a bunch of AI CEOs have this thing, which is just like, well, there's just this, they just all have this kind of thing when they talk in public where they're just like, well, there's these, these obvious set of things that so society to do.Alessio: Mm-hmm.Marc: And then they're like, society's not doing any of those things. Right. And it's like, how can society not, you know, what, whatever their theory is, how can society not see x, y, Z? Mm-hmm. And the answer is, well, society is number one. There's no single society, it's like 8 billion people. And they like all have a voice, and they all have a vote, like at the end of the day of how they, they react to change.And then, you know, it just like, it's just human reality is just really complicated and messy. Um, and, and, and so the specific answer to your question is like, as usual, it depends. Um, you know, it, it depends. Look, pe there's no question people are gonna, like, there's no question they're gonna be companies.It's already happening. There are companies that think that they're building value on top of the models and then they're just gonna get blissed by the, by the next model. There's no question that's happening. But I think there's no question also that just the process of adaptation of any technology into the real and into the real messy world of humanity is, is just going to be messy and complicated.It's, it's not going to be simple and straightforward. It's gonna be messy and complicated. And there are gonna be a lot of companies and a lot of products, um, uh, and in, in fact entire industries that are gonna get built to, to, to basically actually help all of this technology actually reach real people.Alessio: The amount of capital going into these companies, I mean, Dario talked about it on the Door Cash podcast and Door Cash was like, why don't you just buy 10 x more GPUs? And he is like, because I'm gonna go bankrupt if the model doesn't exactly hit the, the performance level. How do you think about that?Also as a risk on, you know, you guys are investors, open AI and thinking machines and world apps. It seems like we're leveraging the scaling loss at a pretty high rate, right? Like how comfortable, I guess, do you feel with the downside scenario, like, and say like things Peter out, you think you can kind of like restructure uh, these build outs and uh, you know, capital investments.Marc: Yeah. So should start by saying, so I live through the.com crash, um, and I can tell you stories for hours about the.com crash and it was horrible. No, it was awful. It was, it was, it was apocalyptic by the way. The, a lot of the.com crash was actually at the time, it was actually a telecom crash. It was a bandwidth crash.Like the, the thing that actually crashed, that wiped out all the money with the tele, the telecom companies.swyx: GlobalMarc: crossing. Global, global, yeah.swyx: I'm from Singapore and they, they laid so much cable o over over our oceans.Marc: Actually there was a scaling law in the.com. Era. And it was literally the, the US Commerce Department put out a report in 1996 and they said internet traffic was doubling every quarter.Um, and, and actually in 1995 and 1996, internet traffic actually did double every quarter. And so that became the scaling law. And so what all these telecom entrepreneurs did was they went out and they raised money to build fiber, anticipating that the demand for bandwidth is gonna keep doubling every quarter.Doubling every quarter though is like, you know, grains of chess and the chessboard, like at some point the numbers become extremely large. Right. And, and, and it really, and really what happened was the internet. The internet by the way, continuously kept growing basically since inception. And it's, you know, it's, it's continuously grown.It's never shrunk. And it's grown really fast compared to anything else. Mm-hmm. You know, in, in, in human history. But it wasn't doubling every quarter as of 19 98, 19 99. And so there was this gap in the expectation of what they thought was a scaling law versus reality. And that's actually what caused the.com crash, which was the, it they, they way over companies like global crossing way overbuilt fiber, which is sort of the, and by the way, fiber, telecom equipment, you know, so all the, all the networking gear, you know, and then, and then by the way, the actual physical data centers, like that was the beginning of the, of the, of the data center build and then, and the data center overbuild.And so you had that, but it was, it was literally, I think it was like $2 trillion got wiped out, right? It was like Jesus, it was like a big, it was. And by the way, the other, the other subtlety in it was the internet companies themselves never really had any debt. ‘cause tech, tech companies generally don't run on debt, but the telecom companies run on debt.Physical infrastructure companies run on debt. And so the companies like Global Crossing not just raise a lot of equity, they also raise a lot of debt. So they're highly levered. And so then you just do the thing. It's just like, okay, you have a highly levered thing where you're, you're just over, you're overbuilding capacity.Demand is growing, but not as fast as you hoped. And then boom, bankrupt. Right. And, and then it, and then it's like they say about the hotel industry, which is, it's always the third owner of a hotel that makes money. It has to go bankrupt twice, right? You have to wash out all of the over optimistic exuberance before it gets to actually a stable state.And then it makes money. So by the way, all of those data centers and all of those, all the fiber that they're in use, it's all in use today. Yeah. But 25 years later. But it, it, it took, and actually the elapsed time was, it took 15 years. It took 15 years from 2000 to 2015 to actually fill, fill up all that capacity.The cautionary warning is the, the overbuild can happen. Um, and, and, and, and, you know, you, you get into this thing where basically everybody, everybody who basically has any sort of institutional capital, it's like, wow. It's just, I, I don't know how to invest in these crazy software things. For sure I can put build data centers and for sure I can buy GPUs that I can deploy, you know, compute grids and, and all these things.Um, and so, you know, if you're a pessimist, you could look at this and you could say, wow, this is like really set up to be able to basically replicate, you know, what we went through, what we went through in 2000. Obviously that would be bad. The counter argument, which is the one I I agree with, which is the counter on, on the other side is a couple things.One is the companies that are investing all the, the companies that are investing the money are like the bluest chip of companies. And so back, back, back in the, in the do, like Global Crossing was like a, it was like an entrepreneur. It was like a, a new venture, but like the money that's being deployed now at scale is Microsoft, and, you know, and Amazon and Google, Facebook and Facebook and Nvidia and, you know, these, these, these, and, and now you know, by the way, open ai philanthropic, which are now at like, you know, really serious size, um, you know, as companies with, you know, very serious revenue.These are very large scale companies with like, lots, lots of cash, lots of debt capacity that they've, they've never used. And so th this is institutional in a way that, that really wasn't at the time. And then the other is, at least for now, every dollar that's being put into anything that results in a running GPU is being turned into revenue right away.Like so, and you guys know this, like everybody's starved for capacity, everybody's starved for compute capacity and then, you know, all the associated things, memory and, and, and interconnected and everything else. Um, data center space. And so e every dollar right now that's being put into the ground is turning into revenue.And, and it, and in fact, I actually think there's an interesting thing happening, which is because everybody starve for capacity, the models that we actually have that we can use today are inferior versions of what we would have if not for the supply constraints. That's true. Um, if Right pose a hypothetical universe in which GPUs were 10 times cheaper and 10 times more plentiful mm-hmm.The models would be much better. ‘cause you would just allocate a lot more money to training and you'd just build better models and they would be better. Um, and so we're, we're actually getting the sandbag version of the technology.swyx: Yeah. No. Everything we use is quantized because the, the labs have to keep the, the full versions,Marc: right?swyx: LikeMarc: we're not even getting the good stuff.swyx: Yeah.Marc: But, but getting the good stuff, it's, it's just, even if technical progress stops. Once there's like a much bigger build of like GPU manufacturing capacity and memory, you know, all, all the things that have to happen in the course of the next five or 10 years.Once it happens, even the current technology is gonna get, gonna get much better. And then as you know, like there's just like a million ways to use this stuff. Like there's just like a million use cases for this. Mm-hmm. Like, it, it, you know, this isn't just sending packets across a, a thing, whatever, and hoping that people find something to do with it.This is just like, oh, we apply intelligence into every domain of human activity. And then it works like incredibly well. Yeah. Um. Here's what I know, here's what I know. Um, in the next three or four year, it's like somewhere between three or four years out, basically everything is selling out. So like the, the entire supply chain is, is, is, is sold out or, or, or selling out.And so there, there's no, like, we're just gonna have like chronic supply shortage for, you know, for years to come. Um, there's going to be a response from the market that's gonna result in an enormous, you know, it's happening now. An enormous flood of investment in a new fab capacity and ev you know, every, everything else to be able to do that, at some point the supply chain constraints will unlock, you know, at least to some degree that will be another accelerant to industry growth when that happens.‘cause the products will get better and everything will get cheaper. Um, and so, so I know that's gonna happen. I know that, you know, the deployments, you know, the, the actual use cases are like really compelling. And then, like I said, you know, with reasoning and agents and so forth, like, I know they're just gonna get like much, much better from here.And so I, I, I know the capabilities are like really real and serious. I also know that the technical progress is not going to stop. It. It, it is excel. It is, is accelerating. Like the, the breakthroughs are are tremendous. I mean, even just month over month, the breakthroughs are really dramatic. And so, you know, I think if you were a cynic and there, there are cynics, you can look at 2000, you can find echoes.But I can't even imagine betting it that this is gonna like somehow disappoint and, you know, at least for years to come, I think it would be essentially suicidal to make that bet. Yeah. Um, it was that Michael Burry, uh, uh, that'sswyx: anMarc: interesting guy, huh? We'll pick on a guy. We'll pick, let's pick on one guy.We'll pick. Well ‘cause he did, he he came out with, it was, it was the, heswyx: doesn't mind.Marc: It was the Nvidia short. Right. He came with the Nvidia short. And then if you guys probably talked about this, which is the, the analysis now that like the current models are getting better faster at such a rate that if you are running an Nvidia, if you're running an Nvidia inference chip today, that's three years old, you're making more money on it today than you did three years ago because the pace of improvement of the software is, is faster than the, the, the depreciation cycle, the chip.And then my understanding is Google is running. I don't if they've, I don't know exactly what, uh, these are rumors that I've heard or maybe it's public, but, um, I think Google's running very old TPUs, very profitably. Ference. Yeah. And very profit and very profitably. Yeah. Um, and so, so it actually turns out, as far as I can tell, it's actually the opposite of the Beery thesis is actually.He was actually 180 degrees wrong. It's actually the, the, the, the old Nvidia chips are getting more valuable, which is something that's like literally never happened before. Like it's never been the case that you have an older model chip that becomes more valuable, not less valuable. And that, and again, that's an expression of the just ferocious pace of software progress.Ferocious pace of capability payoff. Yeah. Uh, that you're getting on the other side of this. And so I just, the idea of betting against that, like.swyx: Yeah. Yeah. Well, one ofMarc: my, it seems like an invitation to get your face ripped up.swyx: One of my early hits was like modeling the lifespan of the H 100 and h two hundreds and, and going like, you know, usually they advise like four to seven years and it was, you know, maybe you sort of realistically haircut cut it down to two to three.Yeah. But actually it's going up and not down. Yeah. And, and uh, that's, I mean that's, I think that's the dream. Uh, we are finding utilization and I think utilization solves all problems. Like, you can, you can find use, use cases for even like the poor, like even memory, we're having a shortage. Right. And, and even like the, the shittier versions of, of memory that we do have, we are finding use cases for it.So like That's great.Marc: Yeah.Alessio: How, how important is open source AI and kinda like edge inference in a world in which you have three years of supply crunch. Like, do you think in the, like, you know, if you fast forward like five years, like how do you think about inference, uh, in the data center versus at the edge?Marc: Well, so just to start, yeah. So I think, I think open source is very important for a bunch of reasons. I think edge, edge inference is very important for a bunch of reasons. I, I think just practically speaking, if we're just gonna have fundamental construc, supply crunches for the next, I mean, you, you guys know if you just project forward demand over the next three years, right?Yeah. Relative to supply, one of the, its main predictions you can do is what's gonna, what, what's gonna happen to the cost of, of inference in the core, uh, over the next three years? And like, it may rise dramatically, right? Like, so, so what is, and then is, is, you know, like the, the, the big model competition are subsidizing heavily right now.Right? Right. And so, so what's the, what will be the average person's, you know, per day, per month token cost, you know, three years from now to do all the things that they want to do. And I, I don't know, it's gonna. I mean, I have, you guys probably have friends, I have friends today who are paying a thousand dollars a day for open claw, for claw tokens to run open claw.Right? And so, okay. $30,000 a month. Right? And, and by the way, those, those friends have like a thousand more ideas of the things that they want their claw to do, right? Yeah. And so you, you could imagine there, there's like latent demand of up to, I don't know, five or $10,000 a day of, of, of tokens for a fully deployed, you know, per personal agent.Uh, and obviously consumers can't pay that, right? And so, so, but it gives you a sense of the fu of the fu of the future scope of demand, right? And so, so even, even if there's a 10 x improvement in price performance, that still, you know, goes to a hundred dollars a day, which is still way beyond what people can pay.Mm-hmm. So there's just gonna be like. Ferocious to me, by the way. The agent thing, the other interesting thing is I think the agent thing, so up until now, a lot of the constraints of GGPU constraints, I think the agent thing now also translates into CPU constraints. Mm-hmm. Right?swyx: CPU memory.Marc: Yes. CPU memory, right?And so, like the entire chip ecosystem is just gonna get wait,swyx: wait for network constraints, that that will be the killer.Marc: It's all bottleneck potentially for years. And so, so I, I think that Brad, and, and I think it's actually possible, I mean, generally inference costs are gonna keep coming down, but I think the, let's put it this way, the rate of decline, I think may level out here for a bit because of these supply constraints.And then at some point, maybe the lab stops subsidizing so much and that, that, that again, will be, be an issue. And so there's just gonna be so much more demand for inference than, than can be satisfied. Um, you know, kind of with the centralized model. And then, and then, you know, you guys know this, but like all the, just the dramatic, I mean just the dramatic innovations that have happened in the Apple silicon to be able to do, uh, inferences, it's quite amazing the level of effort being put.Like the open source guys are putting incredible effort into getting, you know, this recurring pattern where the big model will never run on a pc, and then six months later mm-hmm. Oh, it runs in a pc, right? It's like amazing. And there's very smart people working on that. So there's all that. And then look, there's also, you know.There's also like other, there's other motivators. There's other motivators which is just like, okay, how much trust are the big centralized model providers? You know, how much trust are they building in the market versus, you know, how much are, you know, at least for, in certain cases with some people, for certain use cases, people being like, well, I'm not willing to just like, turn everything over.So there, there, there's all the trust issues. Um, by the way, there's also just like straight up price optimization. There's many uses of AI where you don't need Einstein in the cloud. You just need like a, a a, a smart local model. There's also performance issues where you want, you know, you want, you know, you're gonna want your doorknob to have an AI model in it.Right. You know, to be able to, you know, do, um, you know, to be able to do access control. Um, obviously like everything with a chip is gonna have an AI model in it. Mm-hmm. And it, a lot of those are gonna be local. Um, and so, yeah. No, like I think, I think you're gonna have ti and then you're gonna, by the way, also wearable devices, you know, you don't wanna do a complete round trip.You want, you know, you, whatever your smart devices are, you want it to be like super low latency. Yeah.swyx: The question, do we care who makes it? Yeah. One of the biggest news this week was the collapse of AI two, the Allen Institute. Mm-hmm. One of the actual American open source model labs. Yeah. Um, and, uh, I'm not that optimistic on, on American open source.Yeah. Like you, you guys invested in MIS trial and MIS trial's doing extremely well outside of China. That's about it.Marc: Yeah. We'll see. We'll see. I look, I, number one, I do think we care. Uh, I do think we, I do think we care who makes it. Um, I would say this, the, the, the, the previous presidential administration wanted to kill it in the us Oh yeah.They wanted to drown in the bathtub. Um, and so they wanted to kill it. So at least we have a government now that actually like, actually wants it wants it to happen. And youswyx: earned to councilMarc: and Yeah. And the new and the P pcast. Yeah. So the, the, you know, this admin for whatever other political issues people have, which are many, you know, this administration has, I think a very enlightened view and in particular an enlightened view on AI and in particular on open source ai.Uh, and so they're very supportive. Um, my read is the Chi. The Chinese have a very, the various Chinese companies have a very specific reason to do open source, which is, they, they, they don't fundamentally, they don't think they can sell commercial, uh, AI outside of China right now. And or at least specifically not, not in the US for a combination of reasons.And so they, they kind of view, I think, open source AI as a bit of a loss leader against basically domestic, uh, you know, paid, paid services. And then kind of an, you know, kind of an ancillary products. You know, they're, they're very excited about it, by the way. I think it's great. I think it's great that they're doing it.Um, you know, I think Deeps seek was like a gift to the world. Um, I think. The great thing about open source, open source, the, the, the impact of open source is felt two ways. One is you, you get the software for free, but the other is you get to learn how it works, right? And so like the paper, the paper, the paper and, and the code, right?And the code. And so, like, for example, I thought this was amazing. So open comes out with L one and it's an amazing technical breakthrough, and it's just like, absolutely fantastic. But of course they don't explain how it works in detail. And then of course they hide the, they hide the reasoning traces, right?And, and then, and then, and then everybody's like, okay, this is great, but like, who's gonna be able to replicate this? Are other people gonna be able to do this? You know, is their secret sauce in there? And then our one comes out and it's just like, there's the code and there's the paper, and now the whole world knows how to do it.And then, you know, three months later, every other AI model is, is adding reasoning. And so, so you get this kind of double, like even if the Chinese models themselves are not the models that get used, the education that's taken place to the rest of the world, the information diffusion, you know, is incredibly powerful.So that happens and then, I don't know. We'll, we'll see. You know, there are a bunch of American, you know, open source, you know, ai, uh, model companies. I mean, look, there's gonna be tremendous, you know, there already is. There's, you know, there's gonna be tre there's tremendous competition, uh, among the primary model companies.You know, there's, depending on how you count, there's like four or five, you know, big co model companies now that are, you know, kind of neck and neck, uh, in different ways. Um, uh, you know, and, and, and, um, you know, and then obviously Bo Bo both X and then MetAware involved are, you know, both have huge, you know, huge attempts to, you know, kind of, to kind of leapfrog underway.And then you've got, you know, a whole fleet of startups, new companies, including a whole bunch that we're backing, that are, you know, trying to come out with different approaches. And then you've got whatever it is. I don't know how, how many, how many, like main line foundation model companies are there in China at this point?It's probably six. It'sswyx: five Tigers is what they call it. Yeah. Uh, Quinn is in questionable because there's change in leadership,Marc: right?swyx: Yeah.Marc: But that, does that include, that includes like Moonshot,swyx: yes. Can deep seek, uh, uh, ZI, um, Quinn oh one is in there.Marc: Right. And then, um, and by dance and, and then you see,swyx: ance would be like the next tier ance.They weren't as prominent. They weren't, didn't haveMarc: a leading. Yeah. But they, you at least, you know, ance is very inspiring and presumably they have more stuff coming and Tencent probably has more stuff coming and, and so forth. And so, so, so like, look, here, here would be a thing you can anticipate, which is there are not these markets, there are not going to be between the US and China right now, there's like a dozen primary foundation model companies that are like at scale, at, at some level of a critical mass.It's not gonna be a dozen in three years, right? Like, it just because these industries don't bear a dozen, it's, it's gonna be three or you know, there's gonna be three or four big winners or maybe one or two big winners. And so there's gonna be like a whole bunch of those guys that are gonna have to figure out alternate strategies.Um, and I think like open source is one of those strategies. And so I, I think you could see like a whole, i, I, I think the questions like, who's gonna do open source? I think that could change really fast. I, I think that, that, that's a very dynamic thing. I think it's very hard to predict what happens. And, and I think it's very important.swyx: NVIDIA's doing a lot.Marc: Well, I was gonna say. Well, exactly. And then you're got Nvidia and then, and then, you know, just to, again, indu, there's an old thing in business strategy, which is called, uh, commoditize Compliments. Commoditize the compliment. That's right. And so if your Jensen is just kind of obvious, of course, you wanna commoditize the software.Yeah. And he's, and to his enormous credit, he's putting enormous resources behind that. And so maybe it, maybe it's literally Nvidia and I think that would be great.Alessio: Yeah. Uh, narrative violation to European projects, uh, in the, uh, damn.swyx: I'm hosting my, uh, Europe, uh, conference soon. And I got both of them.Alessio: They got us.They got us. MarkMarc: finished. They got us, us. Well, wait a minute. Where was Peter? So where was Steinberger when he did? In AustriaAlessio: was, yeah, yeah, yeah.Marc: He was in what? He was in Vienna. Oh, he was in Vienna. And then where is he now?swyx: Uh, he's moving to sf.Marc: Okay. Okay. Alright. Okay, there we go. And then, yeah, the PI guy, right?The PI guys are European.swyx: Yeah, they're also, they're buddies inAlessio: Australia. Mario's also there. Yeah.Marc: Right. And are they, yeah, they haven't announced yet. Any sort of change changed or have theyAlessio: No, they're, they have a company there.Marc: Okay. Got, okay. Good.Alessio: Good, good,good.Alessio: Um,Marc: yeah, good.swyx: Anyways, I think pie and open cloud very important software things and, and I just wanted you to just go off on what you think.Marc: Yeah. So I think in co the, the combination of the two of them I think is one of the 10 most important softwares. Openswyx: Claw got all the attention, but Right. Talk about pie,Marc: pi pie's, kind of the Yeah. PI's, PI's kind of the architectural breakthrough for those of us who are older. There was this whole thing that was very important in the world of software basically from like 1970 to, I don't know, it still is very important, but like 19, from 1973 to like basically the creation of Linux, which is basically this, this thing used to call like the Unix mindset.Like so, so, ‘cause there were all these different, you know, theories. There are all these different operating systems and mainframes and, and then you know, all these windows and Mac and all these things. And then there was this, but kind of behind it all was this idea of kind of the Unix mindset. And the Unix mindset was this thing where basically you don't have these, like, like in the old days, like, like the operating system that like made the computer industry really work, like in the 1960s mm-hmm.Was this thing called o os 360, which was this big operating system that IBM developed that was supposed to basically run everything. And it was this like giant monolithic architecture in the sky. It was like a, you know, it was like a giant castle. Um, of software. And, and by the way, it worked really well and they were very successful with it.But like, it was this huge castle in the sky, but it was this thing, it was almost unapproachable, which is like, you had to be kind of inside IBM or very close to IBM. And you had to really understand every aspect, how the system worked. And then the, the Unix sky is originally out of at and t and then out out of Berkeley, um, you know, came out and they said, no, let's have a completely different architecture.And the way architecture's gonna work is we're gonna have, we're gonna have a, a prompt and, and a, and a shell. And then, and then we're gonna, all, all the functionality is gonna be in the form of these discreet modules, and then you're gonna be able to chain the modules together. Mm-hmm. Yeah. And so like the, the, the op, it's almost like the operating, operating system itself is gonna be a programming language.Um, and then that led led to the, the, the sort of centrality of the shell. Um, and then that led to sort of, uh, you know, basically chaining together Unix tools. And then that led to the emergence of these, these scripting languages like Pearl, where you, you could basically kind of very easily do this, and then the shells got more sophisticated and then, and then, and then look like, you know, that, that, that number one, that worked and that, that was the world I grew up in.Like I was, I was a Unix guy. You know, sort of from, call it 1988 to, you know, kind of all, all the way through my work and it worked really well. It, it's in the background, um, you know, nor normal people don't need to, didn't need to necessarily know about it, but like, if you were doing like system architecture, application development, you, you, you knew all about it.Um, and then, you know, it's been in the background ever since. And, you know, look, your Mac still has a Unix shell, you know, kind of in there, and your iPhone still has a Unix shell kind of buried in there somewhere. So they're kind of in there. And then, you know, the Windows shell is kind of a, you know, sort of a weird derivative of that.But, um, you know, but look, the inter, the internet runs on Unix, um, and that smartphones, actually, both iOS and Android are Unix derivatives. And so, you know, kind of Unix did end up winning. But, but anyway, and then we just started taking that for granted. And then, and then so, so basically the, the way I think about what happened with Pie and then with Open Claw is basically what those guys figured out is, I always say the, the great breakthroughs are obvious in retrospect, right?Which is the best kind, the best kind. They weren't obvious at the time or somebody else would've done them already. Um, and so there is a, like a real conceptual leap, but then you look at it sort of the backwards looking and you're just like, oh, of course. Mm-hmm. Like the, the, to me those are always the best breakthroughs.Well, actually language models themselves are like that. It's just like, oh, next token completion. Oh, of course.swyx: Yeah. What other objective mattered?Marc: Yeah, exactly. But, but like it, right. But she's even saying it wasn't obvious until somebody actually did it. Right. And so the conceptual breakthrough is real and deep and powerful and, and very important.And so the way I think about pie and olaw is it's basically marrying the, the language model mindset to the un to the Unix, basically shell prompt mindset. And so it's, it's basically this idea that what, what, so what is an agent, right? And as, as, and as you know, like many smart people who have been trying to figure out what an agent is for, for, for decades, and they've had many architectures to build agents and the whole thing.And it turns out what is an agent. So it turns out what we now know is an agent is the following. It's, so it's a language model. And then above that, it's a ba, it's a bash shell. Um, so it's a, it's a Unix shell, and then it's, and then the agent has access, uh, has access to, to the shell. And, you know, hopeful, hopefully in a sandbox, maybe in, maybe in a sandbox.So it's, it's the model. Um, it's the shell. Um, and then it's a fi, it's a file system. Um, and then the state is stored in files. And then, you know, there's the markdown format for the, you know, for, for the files themselves. And then, and then there's basically what in Unix is called Aron job. There's a loop and then there's a heartbeat for the, there's heartbeat and, and the thing basically Wake Wakes up.Wakes up. So it's basically LLM plus shell, plus file system, plus markdown, plus kron. And it turns out that's an agent. And, and, and every part of that, other than the model is something that we already completely know and understand. And in fact, it turns out that like the latent power of the Unix shell is like extraordinary because basically like all, like, there's just like an, there's just enormous latent power in the shell.There's enormous numbers of Unix commands, there's enormous number of command line interfaces into all kinds of things already in the, you know, your entire, I mean your entire, just to start with, your computer runs on a shell. If you're running a Mac or a, or, or a phone, your computer, your computer's running on a shell, uh, already.And so like the full power of your computer is available at the command line level. Um, and then it turns out it's really easy to expose other functions as a command line interface. And so like this whole idea where we need like MCP and these like product mm-hmm. Fancy protocols, whatever, it's like, no, we don't, we just need like a command, command line thing.So that's the architecture. And then it turns out what is your agent? Your agent has a bunch of files starting a file system. And then there's the thing that just like completely blew my mind when I write my head around it as a result of this, which is like, okay. This means your agent is now actually independent of the model that it's running on.Because you can actually swap out a different LLM underneath your agent and your, your agent will change personality somewhat. ‘cause the model is different, but all of the state stored in the files will be retained.swyx: Yeah. Different instruction set, but you just compiledit.Marc: Right, exactly. And it's all right.It's like right. Swapping out a ship and recompiling, but it's, it's still, it's still your agent with all of its memories. Um, and with all of its capabilities. And then by the way, you can also swap out the shell, uh, so you can move it to a different execution environment that is also, is also a b shell, by the way, you can also switch out the file system, right.Uh, and you can, and you can, and you can swap out the, the, the heartbeat for the, the crown framework, the, the loop that the agent framework itself. And so your agent basically is ba basically at the end of the day, it's just. It's just, its files. Um, and then, and then there's of course it a openswyx: call.Marc: Yeah, it's, it's basically, it's, it's just the files.Um, and then by the way, as a consequence of that, the agent and then the agent itself, it turns out a couple important things. So one is it, it's, it, it can migrate itself, right? And so you're, you can instruct your agent, migrate yourself to a different, uh, runtime environment, migrate yourself to a different file system, migrate yourself to a different, you know, swap out the language model.Your agent will do all that stuff for you. And then there's the final thing, which is just amazing, which is the agent is the agent actually has full introspection. It actually, it actually knows about its own files and it could rewrite its own files. Right. Which by the way, is basically no widely deployed software system in history where the, the, the thing that you're using actually has full introspective knowledge of how it itself works and is able to modify itself.Like that, that, I mean, there have been toy systems that have had that, but there, there's never been a widely deployed system that has that capability and then that leads you to the capability. That just like completely blew my mind when I wrap my head around it, which is you can tell the agent to add new functions and features to itself and it can do that.Extend yourself. Yeah. Right? Extend, extend yourself. Like extend yourself. Give yourself a new capability. Right? And so, and so literally it's just like you run into somebody at a party and they're like, oh, I have my open claw, do whatever, connect to my eat, sleep bed, and it gives me better advice and sleep.And you go home at night and you tell your claw, or if they're at the party, by the way, you tell your claw, oh, add this capability to yourself. And your claw will say, oh, okay, no problem. And it'll go out on the internet and it'll figure out whatever it needs and then it'll go out to claw code or whatever.It'll write whatever it needs. And then the next thing you know, it has this new capability. And so you don't even have to, like, you can have it upgrade itself without even having to, without having to do anything other than tell it that you want it to do that. And so anyway, so the, the combination of all this is just, I mean, this is just like a massive, incredible, I mean, it's just incredible.Like if I, if I were, if I were 18, like this is a hundred, this is what I would be spending all of my time on. This is like such an incredible conceptual breakthrough. Yeah. And again, pe people are gonna look at it and they already get this response. People are gonna look at it and they're gonna say, oh, well, where's the breakthrough?‘cause these, the, all of these components were already known before. Mm-hmm. But, but this is the key, the key to the breakthrough was by using all these components that were known before, you get all of the underlying capability of that's buried in there. And so all, and so for example, computer use all of a sudden just kind of falls, trivi, trivial.Of course it's gonna be able to use your computer. It has full access to the shell. Right. And then, and then you just, you, you give it access to a browser, and then you've got the computer and the browser and, and often away it goes. And, and then you've got all the abilities of the browser also. Um, yeah.And so, and so the capability unlock here is profound. My friends who are, you know, deepest into this, are having their claw do like a, like, literally like a thousand things in their lives. They have new ideas every day. They're just like constantly throwing new challenges at the thing. And by the way, it's early and, you know, these are, you know, these are prototypes and there are, you know, as you guys know, there's security issues.Yeah. And, and so, you know, there's a bunch of stuff to be ironed out, but the, the unlock of capability is just incredible.swyx: Yeah.Marc: And I, I have absolutely no doubt that everybody in the world is gonna, is gonna have at least, you know, an agent like this, if not an entire family of agents. And w

Mix Name: DJ El Nino – Shatta Dancehall Mix 2026 | Vybz Kartel, Super Cat, Red Fox, Chaka Demus & Pliers Website: https://www.iamlmp.com/ Join Our Discord: https://discord.com/invite/iamlmp Join Us DJs New Remixes & Blends: https://www.iamlmp.com/recordpool Instagram: https://www.instagram.com/iamlmp/ DJ Instagram: https://www.instagram.com/djelninolmp/ Download our DJ Music App Daily Mixes: https://linktr.ee/iamlmp —— 01. Moliy, Silent Addy & Shenseea vs Dawn Penn vs Gualtiero – Shake It To The Max (Spydat.E.K No No No Edit) 02. AVI S x Don Juan – Badboy 03. Konshens – Gal A Bubble (Da Nillo Remix) 04. Vybz Kartel – Turn & Wine (DJ Lub’s Shatta Remix) 05. Super Cat – Ghetto Red Hot (DJ Fasta x Walshy Fire x Team Damp 24k Shatta Edit) 06. Mikado x Shabba Ranks – Regular 07. Natoxie x Ward 21 – Show Me Pussy 08. Deeps x Fasta – Choli Ke Peeche (Bolly Shatta Edit) 09. Red Fox – Pose O? (DJ Lub's Remix) 10. Chaka Demus & Pliers – Murder She Wrote (Karyo Ragga Edit) #dancehall #iamlmp #reggaeton

03 Mar 2026 - All sectors retreat as geopolitical tensions weigh on sentiment

Send us a textThe Team Releases that they may have forgotten about a problem in their ranks and Wraith and Deeps gets dressed up.Cyberpunk Red & DLChttps://rtalsoriangames.com/cyberpunk/ https://rtalsoriangames.com/downloadable-content/Help us out with Patreon!https://www.patreon.com/savesvsdeathChat with us on discord!https://discord.gg/rbrb6tuGj7Join us on social media!https://bsky.app/profile/savesvsdeath.bsky.socialhttps://www.facebook.com/Saves-Vs-Deathhttps://www.instagram.com/savesvsdeath/Music used under Creative Commons provided byKarl Casey @ White Bat AudioCheck our their work athttps://www.youtube.com/c/WhiteBatAudioSupport the show

00:00 - Common Sayings and Improv Class13:32 - Dating The Same Men23:09 - Ashley Tisdale Drama42:28 - Friendship BreakupsThis episode is sponsored by:- Blissy: Wake up with clearer skin, smoother hair, and cooler sleep. Use code OOTP for an extra 30% off at https://www.Blissy.com/OOTP - Blueland: Get 15% off your first order by going to https://www.Blueland.com/OUTOFTHEPODS - Nutrafol: Get $10 off your first month's subscription and free shipping when you go to https://www.Nutrafol.com and enter the promo code OOTP- Marley Spoon: Head to https://www.MarleySpoon.com/offer/outofthepods for up to 25 FREE meals

(Conclusion) Of fluid dynamics, labyrinths and transformations. Players: Duck, Art GM: BlackRock

Now that fall camp is closed to the media, the Dawgman guys - Kim Grinolds, Chris Fetters, and Scott Eklund go in-depth with their observations on Washington's depth on the defensive side of the ball. They did the same for the offense yesterday, so now it's time to check out how things look on the other side, as well as with their special teams. Starting with the defensive linemen, they work their way down the recent two-deeps that they released this week. Some of the sub-topics discussed were the EDGEs and who is going to step up, the depth at defensive line and how DL Coach Jason Kaufusi will use them, how some of the current players coming back from injury like Jayvon Parker, Jacob Manu, and Zaydrius Rainey-Sale could be used, how the transfers and true freshmen are impacting the defensive backs room, who won jobs on special teams under the charge of new coordinator Chris Petrilli, and more. To learn more about listener data and our privacy practices visit: https://www.audacyinc.com/privacy-policy Learn more about your ad choices. Visit https://podcastchoices.com/adchoices

Of scooter swarms, drowned towers and the calm before the storm.   Players: Duck, Art GM: BlackRock

** Pre-order my new book: https://geni.us/AtlasOfUFOs ** I am joined by tech entrepreneur, physicist & experiencer, Deep Prasad to discuss: What Deep thinks is actually going on with UFOs The Continuous Spectrum of Interdimensional Beings The Rise of Private Space Companies The Role of NHI in Disclosure UFOs & Open Source Data Advancements in Anti-Gravity Research The Implications of AI and Model Collapse The Future Impact of AI on Society Listener Questions on AI Quantum Computing and Higher Dimensions Conclusion and Future Projects Check out Deeps work: https://x.com/Deepneuron https://www.sf-uap.com/ https://www.starvasa.space/our-origins Get in touch with the show: https://www.thatufopodcast.com/contact Twitter: @UFOUAPAM Facebook, YouTube & Instagram: "That UFO Podcast" YouTube: ⁠⁠YouTube.com/c/ThatUFOPodcast⁠⁠ Email: ⁠⁠UFOUAPAM@gmail.com All podcast links & associated links: ⁠⁠Linktr.ee/ufouapam⁠ https://www.thatufopodcast.com/ Don't forget to subscribe, like and leave a review of the show Enjoy folks, Andy

** Pre-order my new book: https://geni.us/AtlasOfUFOs ** I am joined by tech entrepreneur, physicist & experiencer, Deep Prasad to discuss: 00:00 Intro / Book promotion https://geni.us/AtlasOfUFOs 01:14 His Background and Achievements 03:17 Involvement in the UFO Community 04:18 AI and Material Science Innovations 10:37 The World's First UFO Hackathon 15:21 Hackathon Mission Tracks and Challenges 30:51 Future of UFO Detection and Public Involvement Check out Deeps work: https://x.com/Deepneuron https://www.sf-uap.com/ https://www.starvasa.space/our-origins Get in touch with the show: https://www.thatufopodcast.com/contact Twitter: @UFOUAPAM Facebook, YouTube & Instagram: "That UFO Podcast" YouTube: ⁠⁠YouTube.com/c/ThatUFOPodcast⁠⁠ Email: ⁠⁠UFOUAPAM@gmail.com All podcast links & associated links: ⁠⁠Linktr.ee/ufouapam⁠ https://www.thatufopodcast.com/ Don't forget to subscribe, like and leave a review of the show Enjoy folks, Andy

Of hidden rooms, amulets and silent children Players: Duck, Art GM: BlackRock

Of hippie cults, the outer dark and watery tarts Players: Duck, Art GM: BlackRock

Of ventriloquism, head wounds and bloody scrawls Players: Duck, Art GM: BlackRock

Of life jackets, creepy old men and gravity's revenge Players: Duck, Art GM: BlackRock

Riveting character creation!  You won't be able to turn your ears away.  Then the scenario begins with a scene of horrifying madness: giving away collectibles for no reason! SETTING BACKGROUND Set in the fictional town of New Braunstein, Wisconsin, which broods on the south shore of Lake Geneva, glaring across the watery expanse at its famous twin to the north.      The region, nestled in the fertile lowlands of the state's southeastern corner, has been at the center of many larger than life legends from Chicago crime boss shootouts to the excesses of the Playboy mansion hosting secret midnight revels in the 1970s.  The Lake itself has earned its own share of legends.  Boats and passengers gone missing on still, cloudless days, never to be seen again.  Nights when the water seems to exude a slight but unmistakable aura that just doesn't show up in photographs.  Many of the older residents who've watched the Lake over many years will swear that on certain clear nights under the new moon they looked into the lake and saw lights that reflected no heavenly constellation but were otherworldly beacons in the starry depths. Players: Duck, Art GM: BlackRock

Send us a textTeam must make progress in their current missions but when Deeps has a date how will he make it out? Join Us to Find Out!!!Cyberpunk Red & DLChttps://rtalsoriangames.com/cyberpunk/ https://rtalsoriangames.com/downloadable-content/Help us out with Patreon!https://www.patreon.com/savesvsdeathChat with us on discord!https://discord.gg/rbrb6tuGj7Join us on social media!https://bsky.app/profile/savesvsdeath.bsky.socialhttps://www.facebook.com/Saves-Vs-Deathhttps://www.instagram.com/savesvsdeath/Music used under Creative Commons provided byKarl Casey @ White Bat AudioCheck our their work athttps://www.youtube.com/c/WhiteBatAudio

In this episode we answer emails from Deeps, David, James, Steven and Jordan.  We discuss the PHYS vs other gold ETFs, the podcast feed link, using AVGE in a risk parity style portfolio, why we do this and tail risk hedging.  And THEN we our go through our weekly portfolio reviews of the eight sample portfolios you can find at Portfolios | Risk Parity Radio.Additional links:PHYS vs. GLDM:  testfol.io/analysis?s=1lK9VB9xqaMRPR Main Feed Link (all the podcasts -- open in browser):  Risk Parity Radio RSS FeedAVGE Composition And Other Info:  AVGE – Portfolio – Avantis All Equity Markets ETF | MorningstarPortfolio Matrix:  Portfolio Matrix – Portfolio ChartsCAOS Fund:  CAOS – Alpha Architect Tail Risk ETF – ETF Stock Quote | MorningstarAmusing Unedited AI-Bot Summary:  Gold continues to shine while stocks falter in 2024's challenging market environment. This episode demonstrates the power of diversification during turbulent times, with precious metals up over 17% year-to-date as the S&P 500 struggles down nearly 5%. We explore why truly diversified portfolios are proving their worth yet again.Responding to a listener question about gold ETFs, I break down why PHYS's potential tax advantages rarely outweigh its higher expense ratio compared to traditional options like GLD. The physical gold redemption feature sounds appealing but offers little practical benefit for most investors. The entire physical gold storage industry largely profits from fear rather than delivering substantive advantages to everyday investors.The highlight of this episode comes from a fascinating listener discovery – combining the comprehensive Avantis AVGE fund with treasuries and gold creates a remarkably simple yet effective portfolio. This approach addresses a critical concern: ensuring surviving spouses can easily manage investments without sacrificing performance. Our analysis using Portfolio Charts shows this simplified approach delivers comparable results to more complex allocations while dramatically reducing management complexity.We also tackle tail risk hedging strategies, explaining why these insurance-like approaches rarely justify their ongoing costs, especially for investors in the accumulation phase. True diversification provides more reliable protection than specialized instruments designed to profit from market crashes.The portfolio performance review tells the real story – while traditional stock allocations struggle, our diversified sample portfolios are mostly holding steady or positive for the year. Historical patterns suggest diversified portfolios experience down years only about 20% of the time versus 30% for traditional approaches – a meaningful difference that compounds over retirement timeframes.Have questions about navigating today's challenging markets? Send them to frank@riskparityradio.com – I'd love to answer them in an upcoming episode!Support the show

Deeps thoughts on excess, margin, and more as we close out this Make it Sing season of Homemaker Chic Podcast.SEASON SPONSOR DRY FARM WINES!Get a bottle for a penny with your first order of these beautiful, biodynamic wines. Low alcohol, no sugar added wines from Europe and beyond.https://www.dryfarmwines.com/homemakerchicGet luxury linens from our friends at American Blossom Linens and save 20% with code SING20: https://americanblossomlinens.comFind chemical-free, designer-quality skincare and makeup and save 10% with the code HMC10: https://toupsandco.com/Clean, CLEAN with Branch Basics! https://branchbasics.com/ Coupon code HOMEMAKERCHICIf you enjoy wine, drink Dry Farms: https://www.dryfarmwines.com/homemakerchicBe your home's BEST interior designer with Angela's Old World Design Society. Click here for ONE WEEK FREE.Want to skill up in the kitchen? Visit cook.theelliotthomestead.com for 5 new recipes and tutorials a month!Follow up on YouTube for FULL Videos:https://www.youtube.com/@homemakerchicpodcast (Please note episodes can run up to a couple weeks late on Yout...

Has the globalist cabal been trying to poison us for decades now? It could be the case. The truth is on the way... And, can the .223 Remington make a 1000 yard shot? It can; we'll tell you now. And what is wrong with these presumed former Navy SEALS? Are these dude for real? Or, are they merely fake SEALS, trotted out for the purposes of deception? 

I so want to connect with my hearers when I preach or speak. Yes, one has a Message -- the One-Way Love of God embodied in the Compassionate Christ. But if it doesn't really connect with the listener -- with the sufferer! -- it is not able to do its job. J.B. Priestley (d. 1984), who had basically lost whatever faith he had been exposed to as a child, spent a lot of years looking for... something. He would gladly have capitalized "something" (i.e., Something). In 1960 Priestley wrote specifically about the decline of Christianity in the West. He wrote that the only way the "Church" could 'come back' -- which he would have welcomed given the cultural despair and nihilism he observed everywhere around him -- was to get through to the unconscious. Christianity's original, great and contagious strength had been to reach individuals in their depth/s. I agree with JBP. For many years Mary and I have listened to sermons that are sincere, sound theologically, and well prepared exegetically. Yet we often leave the service untouched, un-addressed, un-healed. As Herr Kaesemann said once, after listening to a sermon during a conference at Yale Divinity School: "Es gibt keine Anrede!" In other words, the Word has to address me in the deeps. The preacher's "deeps" need to be calling out to mine (Psalm 42:7). This cast draws on Priestley's "Presence of the Absence"; a John Wyndham paperback from 1953; and -- wait for it -- Spanky & Our Gang. The last track, from 1969, is IMO pure perfection. Oh, and "Out of the Deeps" is dedicated to Mary Zahl, whose recent talk to the Women of the Advent in Birmingham, entitled "The Things That Remain" (https://talkingbird.fireside.fm/400) is as fine as anything I have ever heard her present. LUV U.

Simon's weekly chronicle of events in the United States for Tom Swarbrick's drivetime programme on the UK's LBC.  Listen live every Friday at 5:50pm or find it here on catchup afterwards. #Harris #Kamala #Trump #Election2024 #USElection2024 #Biden #news #politics #uspolitics

Girls Gone WoW keeps the Warcraft community in the know from a fresh perspective. Join #teampositive and their plethora of guests from the community each and every week! We're talking about the Ringing Deeps this week! What did you make of our new Kobold law? Or Magni's story? Short one this week but lots of views from us and the GGW family. We hope you enjoy the show – if you want to be a guest you can get in touch with us on Discord by joining us at bit.ly/ggw-discord or email us at girlsgonewowpodcast@gmail.com Find this episode and many others at https://www.bonusroll.gg/directory/girls-gone-wow/

Matthew Raghunauth always felt like he was a little lazy and sluggish — that's just how he was. Then the time came to return to office after the pandemic, and he really started struggling at work. He questioned why he would put things off so much. He was scared to mess up, and afraid that his colleagues would think he's a bad employee. Matthew is an artist and UX designer who was diagnosed with ADHD about a year and a half ago. Join Laura and Matthew as they talk about this ADHD fear of being “found out,” and a grown-up view of growing up.Related resourcesADHD and rejection sensitive dysphoria (RSD)Imposter syndrome at work: How I stopped feeling like a fakeNot lazy, but exhausted from analysis paralysis (Emily's story)Timestamps(01:25) Why did Matthew seek out an ADHD evaluation?(05:59) ADHD and prioritization overload(07:23) Anxiety and fixations while growing up(10:10) Putting off things out of fear of failing and being rejected(12:34) ADHD and catastrophizing(15:32) Are we really “too sensitive”?(16:38) When “growing up” means taking care of yourself(21:20) The added pressure of being first generation American To get a transcript of this show and check out more episodes, visit the ADHD Aha! podcast page at Understood.Want to share your “aha” moment? We love hearing from our listeners. Email us at ADHDAha@understood.org. Introducing “MissUnderstood,” the first-ever podcast channel for women with ADHD. Listen now: lnk.to/missunderstoodUnderstood is a nonprofit organization dedicated to empowering people with learning and thinking differences, like ADHD and dyslexia. If you want to help us continue this work, donate at understood.org/give

Praises or critics can be send here! Also if there's anything you wish to hear about please send your requests here!Discover the lush and perilous landscapes of World of Warcraft's latest expansion as we embark on an adventure starting from the destruction of Dalaran. Imagine a city that marries the grandeur of Stormwind with the mystic allure of Valdrakon—welcome to the Isle of Dawn. Join us as we navigate this chaotic yet beautifully designed zone, where I've encountered a welcoming PvP vendor and a bustling training dummy area. Plus, there's a hint of what's to come in Hallowfall and Ajkehet.Ever wondered what it would be like to listen to a grandma's tales in the midst of a cavernous adventure? In the Ringing Deeps, you'll experience just that through engaging side quests that bring depth to the storyline, with familiar faces like Magni and Dagraan adding layers of lore and continuity. This zone, unlike the Isle of Dawn's battle-centric setup, promises rich character engagement and storytelling. Don't miss out as we anticipate exploring Hallowfall and the Nerubian zone, promising a cohesive and immersive experience for all adventurers. Hope you all enjoy and hope you relate to any of these stories. And I will speak to you all in the next episode!Want some 3D printed Merch, find it here!https://pigandwhistletales.etsy.comSupport the show here:https://www.buzzsprout.com/1196870/supportpatreon.com/Pigandwhistlehttps://www.buymeacoffee.com/PigandWhistleSocials :Twitch : https://www.twitch.tv/pigandwhistletalesYoutube : https://www.youtube.com/channel/UCAOi6rHO3x90lOmmb82Jv1wWebsite : https://www.pigandwhistletales.com/Instagram : https://www.instagram.com/pigandwhistletales/Facebook : https://www.facebook.com/PigAndWhistleTalesTry out Buzzsprout yourself! https://www.buzzsprout.com/?referrer_id=1154066Listen to the podcast on other platforms:https://www.listennotes.com/podcasts/pig-whistle-tales-from-azeroth-gabriel-nsa902LrQVw/https://www.podchaser.com/podcasts/pig-whistle-tales-from-azeroth-1315927https://open.spotify.com/show/5ZTkLtQvRSm4PStUfZquWkhttps://podcastaddict.com/podcast/3032607The Music at the start is from Tony Catch they do many amazing cover songs for games you can find the link here:https://www.youtube.com/channel/UCHiF0dAkbpPMtQSwvAxcapQCall Me By Your Gamea nostalgic video game podcastListen on: Apple Podcasts SpotifySupport the Show.Support the show here: https://www.buzzsprout.com/1196870/support patreon.com/Pigandwhistle https://www.buymeacoffee.com/PigandWhistle

Moxie, Deeps and Quinn spend some time at the mall Moxie finds out information on some of the other players and Wraith and Deeps goes to she someone from Wraiths pass. Cyberpunk Red & DLChttps://rtalsoriangames.com/cyberpunk/ https://rtalsoriangames.com/downloadable-content/Help us out with Patreon!https://www.patreon.com/savesvsdeathChat with us on discord!https://discord.gg/rbrb6tuGj7Join us on social media!https://bsky.app/profile/savesvsdeath.bsky.socialhttps://www.facebook.com/Saves-Vs-Deathhttps://www.instagram.com/savesvsdeath/Music used under Creative Commons provided byKarl Casey @ White Bat AudioCheck our their work athttps://www.youtube.com/c/WhiteBatAudioSaves Vs Death is unofficial content provided under the Homebrew Content Policy of R. Talsorian Games and is not approved or endorsed by RTG. This content references materials that are the property of R. Talsorian Games and its licensees. 

Footprints, The Sanctuary Service, May 5, 2024

Maybe you think you know the story of the events that took place when God, working through Moses, parted the Red Sea, congealed the waters to allow the Hebrews to pass over on dry land to deliver them safely out of the hands of their enemy, the Egyptians, But did you also know that event is connected to the deeps, the frozen firmament and the Jordan River? There's a whole lot more of the story to tell than what's been told. On this episode of Rightly Dividing, Moses was an amazing man, and biblically as we shall see, he was a wonderful type of Jesus Christ in many ways. The parting of the Red Sea, which I believe literally happened exactly as the Bible says it did, contains much more in its storehouse than simply the mind-blowing miracle of the waters parting. It is also a beautiful picture of God's promises to the Jews, His promises to the born again Church, and His miracle working power in every dispensation. If you think you know what happened at the Red Sea, we invite you to come and learn the 'rest of the story' about the Red Sea, the Deeps and the frozen firmament up over your head.

Jess didn't know how much she'd enjoy exploring caves until she tried it, now she's been hooked and can't get enough. She books a cave tour of the newly discovered Ephemera Cave, and won't let anyone ruin her excitement... until it all goes wrong in the dark. Access Exclusive Stories and other bonus content through our ⁠Patreon⁠. Join our ⁠Discord Community⁠ and connect with us. Jess is voiced by Rosie Knuckles Frank is voiced by Gorath Hyun Marge is voiced by Iriska Redding Young Man is voiced by James Belknap Young Woman is voiced by Iriska Redding Female Extra 1 is voiced by Rosie Knuckles Male Extra 1 is voiced by James Belknap Male Extra 2 is voiced by Devin McCamey Shack Man is voiced by Jonathan Capers Narrated by Jeremiah John Written and Directed by Devin McCamey Produced by Jonathan Capers Soundscape, Audio Engineering, and Original Soundtrack by Michael Glassel Original Artwork by Brandon McCamey For Fans Of: - Old Gods of Appalachia  - H.P. Lovecraft  - Joe Abercrombie  - Neil Gaiman - Jim Butcher - Kevin Hearne - The Magnus Archives - Welcome to Night Vale - Malevolent - The White Vault - The Black Tapes - LORE - Limetown - Tanis - Archive 81 - Alice Isn't Dead - The Lovecraft Investigations

McAnally's Pubcast - A Dresden Files PodcastHere we discuss Chapter 40 in which Raith roleplays villain fantasies, Trixie skydives using a Spider Pucky Parachute, and Madge talks to herself.Blood Rites Chapter 40 Summary:Raith brings Murphy and Dresden into the Deeps where he divulges the details of his evil plan. Madge and Trixie are present as well but Trixie is thrown to her death in the cavern. Raith goes to investigate the sirens while Madge begins the entropy curse. While Madge is busy with the curse, Dresden and Murphy free themselves and make a plan. When Raith returns Dresden launches a surprise attack but Raith survives and kills all of the lights. Find Us Elsewhere:Do you want to follow up with us for even more Dresden? We're all over the internet - you can email us at pubcast@freeflowrambling.com, or you can track us down at Facebook, Instagram, Discord, Twitter (X?), Reddit, our Dresden Files website, or our parent website. If you want hypnotic visuals with your podcast, you can find us at YouTube. Not enough? Why not show your support by clicking here and donating or joining us on our Patreon. Also, if you're in the market for some merch, you can click here. If you still aren't satisfied, click here and tell us all about it!Try Magic Mind: https://www.magicmind.com/mcanally and use the code MCANALLY20

There are new drill results from Collective Mining, Li-FT Power, Bravo Mining and Galway Metals to report. Vista Gold has updated its feasibility study for Mt Todd. We'd like to thank our sponsors: Arizona Sonoran Copper Company (ASCU:TSX) is focused on developing its brownfield copper project on private land in Arizona, a tier 1 location. The Cactus Mine Project is located less than an hour's drive from the Phoenix International airport via highway i-10, and with grid power and the Union Pacific Rail line situated at the base of the Cactus Project main road. With permitted water access, a streamlined permitting framework and infrastructure already in place, ASCU's Cactus Mine Project is a lower risk copper development project in the infrastructure-rich heartland of Arizona.For more information, please visit ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.arizonasonoran.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Fireweed Metals is advancing 3 different projects within the Yukon and Northwest Territories, including the flagship Macmillan Pass Project, a large zinc-lead-silver deposit and the Mactung Project, one of the largest and highest-grade tungsten deposits in the world. Fireweed plans to advance these projects through exploration, resource definition, metallurgy, engineering, economic studies and collaboration with indigenous people on the path to production. For more information please visit ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠fireweedmetals.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Vizsla Silver is focused on becoming one of the world's largest single-asset silver producers through the exploration and development of the 100% owned Panuco-Copala silver-gold district in Sinaloa, Mexico. The company consolidated this historic district in 2019 and has now completed over 325,000 meters of drilling. The company has the world's largest, undeveloped high-grade silver resource, which will grow with a resource update in early 2024. Learn more at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://vizslasilvercorp.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Victoria Gold operates the Eagle Gold Mine within the Dublin Gulch Property. Eagle is the largest gold mine in Yukon's long history of gold production. In addition to the long-life Eagle Gold Mine, the Dublin Gulch property has upsized exploration potential including priority targets Raven and Lynx among others. Follow all the gold production and exploration news at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠vgcx.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.

"Perpetual Zoo of Machines" by Sara Omer Manawaker's Patreon: http://patreon.com/manawaker/ Manawaker books: https://mybook.to/manawaker More info / Contact CB Droege: https://cbdroege.taplink.ws Author Bio: Sara Omer is a first reader for Orion's Belt and Uncharted Magazine. Her first short story appeared this year in The Deeps, and she has more work forthcoming at other publications. She is currently querying a fantasy novel.

"Perpetual Zoo of Machines" by Sara OmerManawaker's Patreon: http://patreon.com/manawaker/Manawaker books: https://mybook.to/manawakerMore info / Contact CB Droege: https://cbdroege.taplink.wsAuthor Bio: Sara Omer is a first reader for Orion's Belt and Uncharted Magazine. Her first short story appeared this year in The Deeps, and she has more work forthcoming at other publications. She is currently querying a fantasy novel.

Ari Sussman of Collective Mining provides his corporate commentary on the latest drill results out of the Guayabales Project in Colombia where a deep hole has discovered a new brecciated porphyry called "Olympus Deeps".

Collective Mining published new drill results with a discovery called Olympus Deeps. NiCAN assay results from Phase III. Dakota Gold discovers rare earth element mineralization. Aya Gold & Silver drills high grade at depth. Sigma Lithium updates its resource in Brazil. We'd like to thank our sponsors: Arizona Sonoran Copper Company (ASCU:TSX) is focused on developing its brownfield copper project on private land in Arizona, a tier 1 location. The Cactus Mine Project is located less than an hour's drive from the Phoenix International airport via highway i-10, and with grid power and the Union Pacific Rail line situated at the base of the Cactus Project main road. With permitted water access, a streamlined permitting framework and infrastructure already in place, ASCU's Cactus Mine Project is a lower risk copper development project in the infrastructure-rich heartland of Arizona.For more information, please visit ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.arizonasonoran.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Fireweed Metals is advancing 3 different projects within the Yukon and Northwest Territories, including the flagship Macmillan Pass Project, a large zinc-lead-silver deposit and the Mactung Project, one of the largest and highest-grade tungsten deposits in the world. Fireweed plans to advance these projects through exploration, resource definition, metallurgy, engineering, economic studies and collaboration with indigenous people on the path to production. For more information please visit ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠fireweedmetals.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Vizsla Silver is focused on becoming one of the world's largest single-asset silver producers through the exploration and development of the 100% owned Panuco-Copala silver-gold district in Sinaloa, Mexico. The company consolidated this historic district in 2019 and has now completed over 325,000 meters of drilling. The company has the world's largest, undeveloped high-grade silver resource, which will grow with a resource update in early 2024. Learn more at ⁠⁠⁠⁠⁠⁠⁠⁠https://vizslasilvercorp.com/⁠⁠⁠⁠⁠⁠⁠⁠ Victoria Gold operates the Eagle Gold Mine within the Dublin Gulch Property. Eagle is the largest gold mine in Yukon's long history of gold production. In addition to the long-life Eagle Gold Mine, the Dublin Gulch property has upsized exploration potential including priority targets Raven and Lynx among others. Follow all the gold production and exploration news at ⁠⁠⁠⁠⁠⁠⁠⁠vgcx.com⁠⁠⁠⁠⁠⁠⁠⁠.

Today on The Prather Point LIVE at 4 pm ET / 1 pm PT on RUMBLEhttps://rumble.com/v47dy0u-trumps-win-blows-deeps-states-over.htmlMIKE ADAMS 2024 ANALYSIS!WIGGINTON: EXTREME COLD WEAPONIZED FOR IOWA!US-UKRAINE FAST & FURIOUS: 1 BILLION $US, 40K GUNS! AMERICANS RED PILL BIO-WEAPON ANTIDOTE: AWARENESS! 

In part three of this 3-part series, we continue to explore the recent publication related to marine biomimetics and the deep sea, identifying the seven broad categories of biomimetic design, discussing each with examples of application, technological invention, and as effective solution models for response to negative human intervention and climate change, and for ocean protection and conservation.World Ocean Radio provides coverage of a broad spectrum of ocean issues from science and education to advocacy and exemplary projects. Hosted by Peter Neill, Director of W2O, World Ocean Radio is a weekly series of five-minute audio essays available for syndicated use at no cost by college and community radio stations worldwide.World Ocean Radio offers five-minute weekly insights that dive into ocean science, advocacy and education, hosted by Peter Neill, Director of the W2O, author, and lifelong ocean advocate. Episodes offer perspectives on global ocean issues, today's challenges, marine science and policy, and exemplary solutions. Available for RSS feed, podcast, and syndicated use at no cost by community radio stations worldwide.

In these three episodes of World Ocean Radio we are exploring a recent publication entitled “A Forgotten Element in the Blue Economy: Marine Biomimetics and Inspiration from the Deep Sea,” authored by Robert Blasiak from the Stockholm Resilience Center in Sweden. The article identifies seven broad categories of biomimetic design: adhesion, anti-fouling, armor, buoyancy, movement, sensory, and stealth. In this 3-part series we'll discuss each with examples of application, technological invention, and as effective solution models for response to negative human intervention and climate change, and for ocean protection and conservation.World Ocean Radio provides coverage of a broad spectrum of ocean issues from science and education to advocacy and exemplary projects. Hosted by Peter Neill, Director of W2O, World Ocean Radio is a weekly series of five-minute audio essays available for syndicated use at no cost by college and community radio stations worldwide.World Ocean Radio offers five-minute weekly insights that dive into ocean science, advocacy and education, hosted by Peter Neill, Director of the W2O, author, and lifelong ocean advocate. Episodes offer perspectives on global ocean issues, today's challenges, marine science and policy, and exemplary solutions. Available for RSS feed, podcast, and syndicated use at no cost by community radio stations worldwide.

It's time for the first guest of Season 2, and she's one you've been waiting for. This week, Morgan sits down with incredible author, podcaster, reality TV star and friend, Deepti Vempati. Deeps is here to answer all of your questions and spill some tea. The girls share their opinions on the latest season of Love is Blind, Taylor and Travis, and bond over their previous relationship experiences. How long should you date someone before a hard launch? Why did Deepti decide to write a book? Who are the biggest celebrities who have slid into Deepti's DMs? Where are Morgan and Deepti dying to go? Morgan and Deeps cover ALL the topics in episode 17, Sharing Your Truth. Follow Morgan: https://www.instagram.com/morganleighwillett/ Follow Deepti: https://www.instagram.com/lifewithdeeps/ Follow Your Internet Bestfriend: https://www.instagram.com/yourinternetbestfriendpod/ Watch the full episode on YouTube: https://www.youtube.com/@morganleighwillett Produced by SocialPodcast.co

in what distant deeps or skies burnt the fire of thine eyes - #3559 by chair house 230912.mp3in what distant deeps or skies burnt the fire of thine eyes★本日のYoutubeビデオマガジンです。ピアノ音楽とアート４作を３分の動画で確認できるのでいかがでしょうか？　下記のnoteでは創作活動含めてすべて毎日の記事に書いています。..

NOTE: Lately I've started to feel that I don't have enough time for my creations. So, I rearrange my daily activity schedule so that my SNS activity execution time does not occur during the prime time of my creative activities. So the update time of my SNS activities will change. However, this soundcloud activity is my top priority, so I will continue to do the first activity every morning in Japan, as I always have. #3559: Sep. 12, 2023: In what distant deeps or skies burnt the fire of thine eyes ("William Blake's Poetry (Japanese version)" from Aug. 24, 2023) Today's pure primal piano music here. Happy if this music makes you feel peaceful.. : ) Looking for absolute natural beauty every day for Piano Ten Thousand Leaves. Target number is 4536 and 3559(78.5%) achieved today. Find my project.. : ) This piece may might have good 1/f fluctuation characteristic although I stopped investigating it each piece. My new message: "Does it make sense to preserve it for 1000 years?" Today's cover ART is created by #Midjourney (Art Generating #AI), according to my wish. Happy if you like it. Today's chairhouse's daily video magazine of piano ten thousand leaves music & AI created Artworks. https://youtu.be/ihBU7Otn4zc I'm now making Archive site of Piano Ten Thousand Leaves project by utilizing #wordpress. Basically nice direction I've already gotten.. : ) Currently 1100 pieces already achieved. But this week I need to do something else, so I'm going to stop this task for a bit. ######## NEW 24th SELECTION ALBUM JUST RELEASED ######## "Deep Forest Girl" - the 24th selection album of piano ten thousand leaves Youtube: Full(20 songs, 50 minutes) and HD video by Midjourney - AI https://youtu.be/-pvjcnFysTk spotify https://open.spotify.com/intl-ja/album/6zftjWuL7JMF0vNYgLTSaQ apple music https://music.apple.com/jp/album/deep-forest-girl-piano-ten-thousand-leaves-volume-24/1692518303 amazon music https://www.amazon.co.jp/s?k=chair+house+%E6%B7%B1%E3%81%84%E6%A3%AE%E3%81%AE%E5%B0%91%E5%A5%B3+-+%E3%83%94%E3%82%A2%E3%83%8E%E4%B8%87%E8%91%89%E9%9B%86+-+%E7%AC%AC24%E5%B7%BB&i=digital-music&ref=nb_sb_noss_2 line music https://music.line.me/webapp/album/mb0000000002e6f6be AWA: https://s.awa.fm/album/bd73bf6d8ea694823e31 Other Every music streaming services in the world https://linkco.re/yDNpmUYN?lang=en

Mallory and Sal face fresh drama; Shake and Deeps dissect their chemistry; special guests help the couples find wedding dresses and tuxedos. Hosted on Acast. See acast.com/privacy for more information.

We're currently on a short break (returning in mid-August), so THIS WEEK ONLY I'm making my audiobook of Tolkien's Overture: Concerning the Music of the Ainur available!Get 20% OFF of everything at https://TrueMythsPress.com when you use the code EP300.Now available in signed paperback, Kindle, and via Audible! Learn more: https://TolkiensOverture.com .'And thus was the habitation of the Children of Ilúvatar established at last in the Deeps of Time and amidst the innumerable stars.'Originally published as part of The Silmarillion in 1977, “Ainulindalë” is the creation story of Middle-earth. Like the biblical account, it begins mysteriously with one great Divinity, but from there goes down a far different path. Whereas the biblical story involves speaking creation into being, Tolkien's vision involves the creation of lesser gods who then create a great music that brings Middle-earth into reality.In Tolkien's Overture, John Carswell conducts a close reading of the text of “Ainulindalë”, and then goes on to explore the role of music in Middle-earth's history, from the creation of Elves, Dwarves, and Men in the First Age to the great events of the late Third Age as recounted in The Hobbit and The Lord of the Rings. Furthermore, it delves into the mystery of evil, as embodied in the mighty Melkor, the great villain of the First Age and the mentor of Sauron, the Dark Lord of Mordor.From the mystical song of the seas to the voice of Lúthien to the strangely musical ways of Tom Bombadil, the reader will come away with a far deeper understanding of Tolkien's imaginary world, and see clearly how music is truly the preternatural fabric from which Middle-earth is made.

Will and Brian venture to The Deeps to see what boon gifting entities reside there. They'll also be going over all the essential details of the Fathomless Warlock as well as each building a character of their own. Find out what's possible with this powerful Tasha's Cauldron of Everything subclass this week on The Dungeoncast! Looking to sponsor an episode or just say hello? Reach out thedungeoncast@gmail.com Or send us something by mail at: Po Box 1784, Upland, CA - 91785 Get your Dungeoncast Merchandise Check out our D&D Liveplay, Superquest Saga Support us on Patreon Join the community on Discord Get us a gift from our Amazon Wishlist  Follow us on Twitter, Instagram, and Tiktok Learn more about your ad choices. Visit podcastchoices.com/adchoices