Podcasts about Steinberger

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

En este episodio, Johnny y Karen discuten las últimas novedades en tecnología, incluyendo integraciones en Jira, avances en IA de OpenAI, regulaciones de seguridad y las implicaciones de las restricciones gubernamentales en modelos de IA. Analizan cómo estas tendencias impactan el desarrollo de software y la seguridad digital.Integración de Jira con agentes para gestión de ticketsAdquisición de Steinberger por OpenAI y su impacto en IAEvaluación de vulnerabilidades y seguridad en herramientas de IARegulaciones europeas y su efecto en la protección de datosRestricciones gubernamentales en el uso de modelos de IA de AnthropicChapters00:00 Introducción y novedades en tecnología03:07 Integraciones y herramientas de gestión de proyectos05:56 Desarrollo y seguridad en herramientas de IA09:04 Vulnerabilidades y ciberseguridad11:59 Regulaciones y protección de datos14:46 Impacto de la prohibición de Anthropic18:02 Ética y límites en el uso de IA29:05 Inteligencia Artificial y su Uso Militar34:53 Ética y Valores en la IA37:52 Cumbres Internacionales y Compromisos Globales40:19 Innovaciones de Nvidia y el Futuro de la IA42:10 Experiencias Personales con Herramientas de IA resourcesJira - https://www.atlassian.com/software/jiraOpenAI - https://openai.comAnthropic - https://www.anthropic.comGDPR - https://gdpr.euMeta y las Rayban Metas - https://about.fb.com/news/2023/02/meta-rayban-stories/

Did insider trading lead to the price collapse of cryptocurrency?Victoria Jones (https://www.twitter.com/satoshis_page)Thomas Hunt ( https://www.twitter.com/madbitcoins)THIS WEEK:  Exclusive | Jane Street Accused of Insider Trading That Helped Collapse Terraform - WSJhttps://www.wsj.com/finance/currencies/jane-street-accused-of-insider-trading-that-helped-collapse-terraform-659e6993?gaa_at=eafs&gaa_n=AWEtsqfdoOrRHF1p0b8whSLAQAaFViXe1E7fCEvmlAq-zStoZyQzViUZC7gIuH-1G3A%3D&gaa_ts=69a1e84b&gaa_sig=jUnopi2wHcho5NoV3w-gzC32a5aO9mFS2N6E_MIxKTEEvdqzhI_7kq1DLDjy-Bt4oeHGQbsgNREHD_d0CzkG0A%3D%3DAnatomy of a Run: The Terra Luna Crashhttps://corpgov.law.harvard.edu/2023/05/22/anatomy-of-a-run-the-terra-luna-crash/The Celsius Crash: Explained. How Alex Mashinsky's Celsius became one… | by Pontem Network | Pontem Networkhttps://blog.pontem.network/the-celsius-crash-explained-be91ef715cd9Jack Dorsey's New Company Falling Apart as It Forces Employees to Use AIhttps://futurism.com/artificial-intelligence/jack-dorsey-block-falling-apart-aiBlock spent ~$68 million on an event for employees last quarter, as the stock gets crushed in early trading - Sherwood Newshttps://sherwood.news/markets/block-spent-usd68-million-on-event-for-employees-stock-crushed-earnings/Money Ape on X: "TRUMP & HIS FAMILY HAVE PULLED 1.3 BILLION OUT OF CRYPTO IN JUST 13 MONTHS. MORE EXTRACTIONS ARE EXPECTED THROUGH WLFI TOKEN, ALONG WITH CONTROVERSIAL MOVES LIKE THE CZ BINANCE PARDON. DAMAGE DONE TO CRYPTO'S REPUTATION IS MUCH BIGGER. WILL US COURT TAKE ACTIO…Show more https://t.co/4nlMGCXFTi" / Twitterhttps://x.com/themoneyape/status/2025521222298308800Crypto Rug Muncher on X: "This wasn't a coordinated attack. $USD1 de-pegged, in part, because Eric Trump was frantically deleting tweets about the token in real-time. If anything, that panicked backtrack did more to tank the price than any external factor could have ever hoped to. Whether or not ZachXBT" / Twitterhttps://x.com/cryptorugmunch/status/2025962096895439131Darky on X: "Eric Trump deleting all his posts about $WLFI , $USD1 depegging… This smells to Luna 2.0 https://t.co/Ma8SJlTGEK" / Twitterhttps://x.com/darky1k/status/2025971046482895053StockMarket.News on X: "Block just FIRED 4,000 people. Nearly half the company, gone in a single day. The reason Jack Dorsey gave? AI can do their jobs now. But here's what nobody's talking about. 200 days ago, Block threw a party. Not a regular company party. A three day festival in downtown https://t.co/ANYJjrHk3m" / Twitter https://x.com/_investinq/status/2027225213843198220Crypto exchange Binance may have funded Iranian entities, reports say :: Reader Viewchrome-extension://ecabifbgmdmgdllomnfinbmaellmclnh/data/reader/index.html?id=292397285&url=https%3A%2F%2Fwww.theguardian.com%2Fbusiness%2F2026%2Ffeb%2F23%2Fbinance-iran-fund-billionsbarney on X: "Sam realizing CZ not only caused the FTX crash, but also received a presidential pardon and is roaming free, while he has to rot in his cell. https://t.co/9aKnv8xzVZ" / Twitterhttps://x.com/barneyxbt/status/2026391293593632983Bitcoin News on X: "NEW: OpenClaw founder Peter Steinberger banned a contributor for simply mentioning the word “Bitcoin” on the OpenClaw server. The user was referencing Bitcoin's block height as a clock, not even using it for transactions. Steinberger says he hates “crypto.” At some point, he https://t.co/4uqX2bEchd" / Twitterhttps://x.com/bitcoinnewscom/status/2025291558568759807John Law on X: "In a curious twist of corporate strategy, Bitcoin Standard Treasury appoints Bob Stefanowski as CFO. A sign of institutional momentum in crypto affairs? Evolution unfolds: https://t.co/J8P0JmgB21 #FinancialEvolution" / Twitterhttps://x.com/scotonomist/status/2027426755552686562Tone Vays on X: "The following is a full & detailed thread on what lead to #Bip148 #UASF that ended the Scaling Debate with #SegWit Activation. ANYONE that is currently pushing for UASF #BIP110 should take the time to learn the history of this Controversial Consensus Change Method!" / Twitterhttps://x.com/tonevays/status/2026890359477862717BitcoinSapiens ⚡️ on X: "Hiker waves bitcoin flag at peak of Mount Everest

Fredrik river av en länklista, och snackar om fascination för språkmodeller, ansvar som utvecklare, jobb på 8k pixlar, vad man lär sig med tiden, och ganska mycket mer. Som inledning diskuterar han två blogginlägg med lärdomar av tio år som engineering manager respektive utvecklare. Minns du några tydliga åsiktsändringar du gjort under din tid som utvecklare? Berätta! Därefter funderar han över hur Apple tappat sin magi på sistone, och till och med för honom som långvarig användare mest känns som det företag som tillverkar trevlig hårdvara och sakta tappar greppet om allt annat. Sedan pratar han om det oväntat trevliga i att jobba på två 4k-skärmar - med skarven mitt i synfältet dessutom! Andra halvan av avsnittet kretsar kring språkmodeller, utvecklaransvar, och arkitektur. Och den intressanta boken Resisting AI som går igenom många av de problem och problematiska synsätt som finns inbyggda i modellerna vi använder som om de var någon sorts neutrala verktyg. (Varning: köp den inte som e-bok i Glassboxx!) Varför blir folk så uppslukade, kan man tänka på modellerna som automatisering av implementation, och vad har Steve Yegge lyft för en bra poäng på sistone? Som avslutning och uppmuntran: En trevlig video med Dylan Beattie om CSS. Ett stort tack till Cloudnet som sponsrar vår VPS! Har du kommentarer, frågor eller tips? Vi är @kodsnack, @thieta, @krig, och @bjoreman på Mastodon, har en sida på Facebook och epostas på info@kodsnack.se om du vill skriva längre. Vi läser allt som skickas. Gillar du Kodsnack får du hemskt gärna recensera oss i iTunes! Du kan också stödja podden genom att ge oss en kaffe (eller två!) på Ko-fi, eller handla något i vår butik. Länkar Jampa/Joao Uchoa Things I've learned in my 10 years as an engineering manager jampa.dev Wardriving Wardriving for a place to live Software development topics I've changed my mind on after 10 years in the industry Chris Kiehl Lärdomarna efter sex år Komplext och komplicerat Monad Query planner How to influence query planning in Postgresql - "the query planner is a harsh mistress" John Siracusa ATP Mysql ORM SQL Liquid glass Macos Tahoe Podcast chapters SRT Descript Voxicon - ett märke vars skärmar Fredrik inte haft tur med på jobbet Barry O'Reilly Kodsnack med Barry, och det om hans artikel med starar där bilden till bokens omslag var med Barrys inlägg om boken på Linkedin Leanpub Procreate Repobar Openclaw Peter Steinberger Peter pratar PSPDFKit i Swift by Sundell från 2018 Steinberger nu en del av Openai Chris Lattner Chris Lattner om språkmodeller och framtiden Clojure Clojureteamet och språkmodeller Steve Yegge Artikeln där Steve uppmanar till återhämtning En av Steves gamla bloggtexter Gas town 4D Resisting AI av Dan McQuillan En artikel om hur oväntat stor spridning Resisting AI fått Glassboxx - rekommenderas ej Calibre Dylan Beattie Rockstar Avsnittet med Dylan Beattie Dylan Beattie om CSS Titlar Målet med en engineering manager (Vem vet) Hur en amerikan sätter upp sitt datumformat Saker jag inte har bytt åsikt om Sedan är det absolut inte enkelt längre (Långt) Innan en enda rad kod skrivs Blind hängivenhet till vad som helst Skriv bara koden du behöver Mikrotjänster kräver motivering En offermaskin I vägen och suddigt Vänta ut Tahoe Till höger om utvecklarverktygen När skarven är i mitten Min flock med starar En annan flik När jag kom tillbaka till den fliken Oansvarighetsgrejen Nu kan vi släppa koden Fokusera på arkitektur Automatiserande av implementation En väg till pålitlig automatisering Tankesteget i sidled Från noll till rörelse I en loop med en robot Ett slutet kretslopp Den perfekta processen Ta oss utrymmet att andas Algoritmerna låser fast det förflutna

Send a textInvest in pre-IPO stocks with AG Dillon & Co. Contact aaron.dillon@agdillon.com to learn more. Financial advisors only. www.agdillon.com00:00 - Intro00:02 - AG Dillon Funds closing on Mar 31, 202600:51 - OpenAI Financials $280B revenue target meets $665B cost wall03:58 - OpenAI “buys” OpenClaw, Steinberger joins OpenAI04:42 - OpenAI Series C aims to shatter records at $850B post money05:41 - OpenAI and Tata bet on India with a 100 MW to 1 GW buildout path06:29 - Grafana's $9B round talks ride a $400M ARR wave07:23 - World Labs lands Autodesk and targets a rumored $5B valuation08:18 - Temporal wants to be the load bearing layer for agent execution09:31 - Mesh Optical's $50M Series A targets the chokepoint inside AI data centers10:43 - Render's $1.5B valuation is a bet that AI apps need a new runtime11:40 - Stash acquired by Grab for $425M13:06 - Physical Superintelligence pitches a physics breakthrough factory with a 20 person team14:07 - Figma plugs Claude Code into design and risks losing the workflow15:00 - Anthropic ships Sonnet 4.6 just 12 days after Opus 4.615:26 - Stripe's Bridge wins OCC trust charter signal as stablecoin scrutiny rises16:37 - Cohere puts 70 plus languages on device with a 3.35B parameter model17:53 - ElevenLabs turns agent risk into an insurable product at $12.2B secondary19:05 - Mistral buys Koyeb and adds 16 engineers to harden its compute stack

Brought to you by TogetherLetters & Edgewise!In this episode: The DJI Romo robovac had security so poor, this man remotely accessed thousands of themWordPress.com adds an AI Assistant that can edit, adjust styles, create images, and moreOpenClaw founder Steinberger joins OpenAI, open-source bot becomes foundationExclusive: Pentagon threatens to cut off Anthropic in AI safeguards dispute'If someone can inject instructions or spurious facts into your AI's memory, they gain persistent influence over your future interactions': Microsoft warns AI recommendations are being "poisoned" to serve up malicious resultsNew nickel-iron battery charges in seconds, survives 12,000 cycles Weird and Wacky: This 14-Year-Old Is Using Origami to Imagine Emergency Shelters That Are Sturdy, Cost-Efficient and Easy to Deploy Kévin: "Q: I want to wash my car. The car wash is 50 meters away. Should I walk or drive?" In a blind test, audiophiles couldn't tell the difference between audio signals sent through copper wire, a banana, or wet mudTech Rec:Sanjay - Nextmug Plus

In today's Cloud Wars Minute, I unpack why one founder's departure may mark a turning point in the AI Era. Highlights 00:03 — There's huge news today in the AI space. Peter Steinberger, founder of OpenClaw, has joined OpenAI. Now I'll start by giving you some background on OpenClaw and its significance in the industry, followed by my commentary on why this is such a shake-up. 00:56 — Perhaps the most remarkable aspect of OpenClaw is its capability to handle these [active computer use] tasks through just basic prompts. For instance, you can say, "Book me a flight from New York City to Austin, Texas, leaving Friday around 9 a.m," and it will go ahead and do it for you. 01:29 — [OpenAI CEO] Sam Altman mentioned that Steinberger is joining OpenAI to drive the next generation of personal agents. This move by OpenAI will no doubt garner significant support from the open-source community, as well as see the recruitment of a talented individual who's already proven his worth in building a new class of AI products. 02:09 — The community even described OpenClaw as, and I quote, Claude with hands. It was a major driver of traffic for Anthropic, recommending Claude Opus 4.5 as its default model. Ultimately, Steinberger fell out of love with Anthropic, and as a result, the company may have missed out on one of the most important hires in the AI Era to date. Visit Cloud Wars for more.

Jakob Steinschaden, Mitgründer von newsrooms und Trending Topics, und Clemens Wasner, CEO von EnliteAI und Vorsitzender von AI Austria, sprechen heute über den Wechsel von OpenClaw-Schöpfer Peter Steinberger zu OpenAI: 

In questa puntata, Pasquale Viscanti e Giacinto Fiore analizzano tre segnali fortissimi del cambiamento in atto: il modello di RentAHuman.ai, dove sono gli agenti di Intelligenza Artificiale a “ingaggiare” esseri umani per completare attività nel mondo reale; l'annuncio di Sam Altman sull'ingresso di Peter Steinberger, il programmatore che ha creato OpenClaw, in OpenAI per guidare la nuova generazione di personal agent; e la decisione del doppiatore Luca Ward di depositare il marchio sonoro della propria voce per difendersi da possibili utilizzi illeciti dell'AI.Una conversazione che intreccia lavoro, potere tecnologico e identità personale, mostrando come l'Intelligenza Artificiale stia riscrivendo non solo i modelli di business, ma anche il concetto stesso di autonomia e tutela individuale.Libro HUMAN RELOADED: https://amzn.to/4evkVWvIncontra tutti i protagonisti dell'AI alla AI WEEK 2026: Arsenalia, PwC, AlterMind, NTT Data, Reply e tanti altri. Scoprili tutti su https://www.aiweek.it Pasquale Viscanti e Giacinto Fiore ti guideranno alla scoperta di quello che sta accadendo grazie o a causa dell'Intelligenza Artificiale, spiegandola semplice.Puoi iscriverti anche alla newsletter su: https://www.iaspiegatasemplice.it

The Mag 7 have committed over $700 billion to AI infrastructure, but the companies building the models may never capture the value. Thank you to our sponsors: Adaptive Security Fuse: The Energy Network The BLS just quietly revised away 862,000 jobs, and real-time inflation trackers now peg price growth below 1%, less than half of what official figures report.  If the Fed is steering monetary policy with stale data, investors need to ask what else the models are getting wrong.  At the same time, the Mag 7 have committed more than $700 billion to AI infrastructure, with Anthropic alone projecting $1 trillion in revenue within five years. Is that conviction or the early stages of a debt cycle nobody is pricing?  And then there is the institutional side of crypto: BlackRock's BUIDL fund just landed on Uniswap with $2.4 billion in assets, Apollo acquired $90 million in Morpho tokens, and AI agents are already settling micropayments in stablecoins.  Austin Campbell, Ram Ahluwalia, and Christopher Perkins sit down with Truflation's CEO Stefan Rust to ask whether the numbers we trust are telling us the truth. Hosts: ⁠Ram Ahluwalia⁠, CFA, CEO and Founder of Lumida ⁠Austin Campbell⁠, NYU Stern professor and founder and managing partner of Zero Knowledge Consulting ⁠Christopher Perkins⁠, Managing Partner and President of CoinFund Guest: Stefan Rust, Founder and CEO of Truflation Links: Unchained:  BlackRock Just Chose Uniswap. The Market Didn't Care. Here's Why. Apollo Moves Into DeFi Lending With Morpho Token Deal UNI Spikes on BlackRock DeFi Move, Then Gives It All Back Macro: NBC: U.S. had almost no job growth in 2025 PBS: Inflation measure falls to nearly five-year low as gas prices fall and housing costs cool Crowdfund Insider: Secretary Of The Treasury Scott Bessent Calls Out Truflation's Inflation Numbers At Senate Banking Hearing AI CapEx: Amazon, Google And Others Are Pouring $700 Billion Into AI CapEx, Top Analyst Explains Why This Makes It 'Hard' To Bet Against Nvidia CIO: Data center capex to hit $1.7 trillion by 2030 due to AI boom Reuters: OpenClaw founder Steinberger joins OpenAI, open-source bot becomes foundation Learn more about your ad choices. Visit megaphone.fm/adchoices

The Mag 7 have committed over $700 billion to AI infrastructure, but the companies building the models may never capture the value. Thank you to our sponsors: Adaptive Security Fuse: The Energy Network The BLS just quietly revised away 862,000 jobs, and real-time inflation trackers now peg price growth below 1%, less than half of what official figures report.  If the Fed is steering monetary policy with stale data, investors need to ask what else the models are getting wrong.  At the same time, the Mag 7 have committed more than $700 billion to AI infrastructure, with Anthropic alone projecting $1 trillion in revenue within five years. Is that conviction or the early stages of a debt cycle nobody is pricing?  And then there is the institutional side of crypto: BlackRock's BUIDL fund just landed on Uniswap with $2.4 billion in assets, Apollo acquired $90 million in Morpho tokens, and AI agents are already settling micropayments in stablecoins.  Austin Campbell, Ram Ahluwalia, and Christopher Perkins sit down with Truflation's CEO Stefan Rust to ask whether the numbers we trust are telling us the truth. Hosts: ⁠Ram Ahluwalia⁠, CFA, CEO and Founder of Lumida ⁠Austin Campbell⁠, NYU Stern professor and founder and managing partner of Zero Knowledge Consulting ⁠Christopher Perkins⁠, Managing Partner and President of CoinFund Guest: Stefan Rust, Founder and CEO of Truflation Links: Unchained:  BlackRock Just Chose Uniswap. The Market Didn't Care. Here's Why. Apollo Moves Into DeFi Lending With Morpho Token Deal UNI Spikes on BlackRock DeFi Move, Then Gives It All Back Macro: NBC: U.S. had almost no job growth in 2025 PBS: Inflation measure falls to nearly five-year low as gas prices fall and housing costs cool Crowdfund Insider: Secretary Of The Treasury Scott Bessent Calls Out Truflation's Inflation Numbers At Senate Banking Hearing AI CapEx: Amazon, Google And Others Are Pouring $700 Billion Into AI CapEx, Top Analyst Explains Why This Makes It 'Hard' To Bet Against Nvidia CIO: Data center capex to hit $1.7 trillion by 2030 due to AI boom Reuters: OpenClaw founder Steinberger joins OpenAI, open-source bot becomes foundation Learn more about your ad choices. Visit megaphone.fm/adchoices

Jeff Stanfield & Andy Shaver sit down with Chad Steinberger, a second-generation dairy farmer from Windthorst, Texas, where he operates his family's third-generation dairy farm alongside his father and son. Chad breaks down the ins and outs of running a modern family dairy, the challenges of navigating government regulations, and how technological advancements have brought a more data-driven, scientific approach to milking and herd management. The conversation also touches on where the beef market may be headed and what it was like growing up in small-town Windthorst in the 1980s.

Welcome aboard our Safe Space Ship!   Ariana Perry will be hosting this completely spoiled, totally unofficial, deep dive into Our Flag Means Death every Tuesday!   This week I'm talking to Aimee Steinberger aka AimeeKitty about animatics and art!    Episode Mentions:  Never Left Pateron AimeeKitty(RevolutionaryGirl) on Ao3 storyboard-pro Aimee's website Aimee's you tube channel aimeekitty's Etsy Shop Don't forget to follow us on social media (@NeverLeftPodcast on BlueSky, @NeverLeftPod on Twitter, NeverLeftPodcast on Ig, Never Left on FB), and check out our Pateron.. The links are in our linktree!  Feel free to contact us at neverleftofmd@gmail.com with any thoughts or questions   Please remember to #DontStreamOnMax and #FireDavidZaslav If you want you can also let Netflix, Amazon Prime and Apple + know that you would still love to see Our Flag Means Death on their platforms. #SaveOFMD #AdoptOurCrew   Our artwork was created by Amy Gleason, you can see more of her art @AmysBirdHouse on instagram and in the comic series Mighty Mascots.   Our theme music is Gnossienne 5 by Erik Satie, preformed by La Pianista   Image Description: A lighthouse stands above the inn, wrapped in a purple Kraken tentacle. The text reads "Never Left: Our Flag Means Death"      

Eveline Steinberger ist erfolgreiche Unternehmerin, Gründerin und Investorin in der Energiebranche. Als Chance für unsere Zukunft sieht sie die nachhaltige Transformation unseres Energiesystems. Teil des Problems sind die Treibhausgase, die es gilt, unserer Erde auszutreiben. Auftreiben möchte Eveline Steinberger möglichst viele innovative Ideen junger Gründer:innen als eines der Jurymitglieder in der Start-Up Sendung 2Minuten – 2Millionen auf Puls4. Impulsgeberin ist sie für den Energiewandel seit Jahrzehnten – anfangs als Führungskraft in großen Energie- und Technologieunternehmen, seit 2014 als Gründerin und Geschäftsführerin der Blue Minds Group. Blaues Wunder hat sie trotz Risikoinvestitionen in Zukunftstechnologien wie KI, Robotics und Cybersecurity noch nicht erlebt. Angeregt durch ihre leidenschaftliche Neugierde auf bahnbrechende Innovationen hat sie bisher die richtigen Startups ins Boot geholt. Ob es daran liegt, dass sie auch begeisterte E-Boot Kapitänin ist? Sicher ist jedenfalls, Eveline Steinberger ist ein Energiebündel. Wie sie ihre Energie bündelt und wann sie ihr auch mal ausgeht, erfahrt ihr in dieser Podcastfolge. Außerdem spricht sie in dieser Podcastfolge über den Unterschied zwischen dem Glücklichsein und der Zufriedenheit und darüber, welcher der beiden Zustände erstrebenswerter ist. Veränderungen sind ständige Begleiter, beruflich ganz bewusst gewünscht, privat machen manche Angst und sind dennoch wichtig. Auch als Topmanagerin hat sie ihre Emotionen nicht immer im Griff. Aber wer sagt eigentlich, dass man sie im Griff haben muss? In schlaflosen Nächten findet Eveline Lösungen. Spannend ist ihre Theorie, weshalb gerade in der Nacht die negativen Gedanken oft so übermächtig werden. Am Schluss erzählt sie humorig eine Anekdote, die beschreibt, wie andere sie in einer bestimmten Situation wahrnehmen und obwohl sie es nicht wahrhaben möchte, könnte unter Umständen etwas dran sein. Folgt uns gerne auf unseren Social Media Kanälen: Eveline Steinberger | LinkedInEveline Steinberger (@evesteinberger) • Instagram-Fotos und -VideosMag. Dr. Eveline Steinberger – The Blue Minds CompanyEveline Steinberger - Investorin, Unternehmerin und AufsichtsrätinMiriam Labus (@labusmiriam) • Instagram-Fotos und -VideosMiriam Labus | FacebookTeam 1 — miriam labusAbonniert "1 Gast 2 Seiten" per RSS-Feed, auf Apple Podcasts, Spotify, Deezer oder Google Podcasts. Ich freue mich außerdem über eure Rezensionen und Bewertungen. Dieser Podcast wird produziert von Asta Krejci-Sebesta für Happy House Media Wien.Falls ihr Interesse habt, Werbung in meinem Podcast zu schalten, setzt euch bitte mit Stefan Lassnig von Missing Link Media Homepage - Missing Link Media (missing-link.media) in Verbindung.Vielen Dank! 

Palantir is one of the world's most valuable companies, analyzing data for businesses, but also for U.S. and Israeli intelligence agencies. The Philosopher in the Valley, a new book by Michael Steinberger, is a portrait of the company's CEO, Alex Karp. In today's episode, Steinberger speaks with NPR's Steve Inskeep about Palantir's operations at the nexus of technology and national security, Karp's liberal arts background, and the CEO's unusual lifestyle.To listen to Book of the Day sponsor-free and support NPR's book coverage, sign up for Book of the Day+ at plus.npr.org/bookofthedayLearn more about sponsor message choices: podcastchoices.com/adchoicesNPR Privacy Policy

Balzer, Jens www.deutschlandfunkkultur.de, Studio 9

Balzer, Jens www.deutschlandfunkkultur.de, Studio 9

Balzer, Jens www.deutschlandfunkkultur.de, Studio 9

Balzer, Jens www.deutschlandfunkkultur.de, Studio 9

POTUS is firing or censoring the statisticians who collect data on health and climate, as well as the kind of experts who could verify his lofty claims of an A++++ economy. And while Vance says that Trump is really turning things around, job losses are rising from his destructive tariff and immigration policies. Plus, the back story on Palantir and how it's helping to facilitate the administration's authoritarian ambitions. Author Mike Steinberger and Catherine Rampell join Tim Miller. show notes Tim's 'Bulwark Take' on current China policy Catherine's newsletter, "Receipts" Mike's new book, "The Philosopher in the Valley" For a limited time only, get 60% off your first order, plus free shipping, when you head to Smalls.com/THEBULWARK.

Warning: This episode contains strong language.Palantir, a data analysis and technology company, has secured federal contracts worth hundreds of millions of dollars during President Trump's second presidency, including to develop software to help Immigration and Customs Enforcement deport people.Michael Steinberger, who spent six years interviewing Palantir's chief executive, Alex Karp, for the book “The Philosopher in the Valley,” explains how Mr. Karp went from a self-described lifelong Democrat to a champion of Mr. Trump, and the impact this transformation could have on American democracy.Guest: Michael Steinberger, a contributing writer to The New York Times.Background reading: Listen to an interview with Mr. Karp from the DealBook Summit this month.In May, the Trump administration tapped Palantir to compile data on Americans.Here is Mr. Steinberger's book, which this episode is based on.For more information on today's episode, visit nytimes.com/thedaily. Transcripts of each episode will be made available by the next workday.  Subscribe today at nytimes.com/podcasts or on Apple Podcasts and Spotify. You can also subscribe via your favorite podcast app here https://www.nytimes.com/activate-access/audio?source=podcatcher. For more podcasts and narrated articles, download The New York Times app at nytimes.com/app.

Who does our data belong to? In this episode, Carl Miller speaks to NYT magazine journalist and author Michael Steinberger about Alex Karp, Palantir and the rise of the surveillance state. Founded in 2003, Palantir is widely regarded as the most interesting company in Silicon Valley – as well as its most controversial. It aided the US government in the war on terrorism and is now used by the CIA, the NHS, the US military and corporate giants like Airbus and BP. But its billionaire CEO, Alex Karp, is not like the other CEOs. In The Philosopher in the Valley, Michael Steinberger, who had unprecedented access to Karp during the writing of this biography, offers a detailed account of Karp's singular approach to leadership and how he is preparing Palantir, and the world, for a future dominated by technological power.  Michael Steinberger is a longtime journalist who writes primarily for The New York Times Magazine. He has written cover stories for the magazine about Joe Biden, George Soros, and Roger Federer. Before becoming a journalist, Steinberger spent several years working on Wall Street. He is the author of Au Revoir to All That: Food, Wine, and the End of France and The Wine Savant: A Guide to the New Wine Culture.  If you'd like to become a Member and get access to all our full conversations, plus all of our Members-only content, just visit intelligencesquared.com/membership to find out more. For £4.99 per month you'll also receive: - Full-length and ad-free Intelligence Squared episodes, wherever you get your podcasts - Bonus Intelligence Squared podcasts, curated feeds and members exclusive series - 15% discount on livestreams and in-person tickets for all Intelligence Squared events  ...  Or Subscribe on Apple for £4.99: - Full-length and ad-free Intelligence Squared podcasts - Bonus Intelligence Squared podcasts, curated feeds and members exclusive series … Already a subscriber? Thank you for supporting our mission to foster honest debate and compelling conversations! Visit intelligencesquared.com to explore all your benefits including ad-free podcasts, exclusive bonus content and early access. … Subscribe to our newsletter here to hear about our latest events, discounts and much more. https://www.intelligencesquared.com/newsletter-signup/ Learn more about your ad choices. Visit podcastchoices.com/adchoices Learn more about your ad choices. Visit podcastchoices.com/adchoices

Welcome back to another high-energy edition of the Keepin' It Rio Podcast.  Today, we're diving deep with one of the roofing industry's most driven and dynamic entrepreneurs — Joshua Steinberger, the founder and CEO of NextGen Restoration.Josh's journey is nothing short of incredible. He started out pounding the pavement in door-to-door Internet sales, learning firsthand what it takes to connect with people, face rejection, and stay relentless. Those early days built the grit and mindset that would later propel him into the world of roofing — where he built NextGen Restoration into one of the most respected and recognized roofing companies in the nation.In this episode, Josh shares the hard-earned lessons from that climb — from mastering sales and leadership to building company culture, managing growth, and developing the systems that separate the pros from the pretenders. We'll talk about mindset, consistency, leadership through adversity, and what it really means to scale a business the right way.So buckle up, because this one's full of real talk, insight, and inspiration for anyone chasing greatness in roofing — or in life. This is Episode 237 of the Keepin' It Rio Podcast featuring Joshua Steinberger… let's go!

The Lincoln Project’s Rick Wilson examines the civil war inside the White House and how Trump’s chief of staff may be on the way out. Author, Michael Steinberger, details his new book, The Philosopher in the Valley: Alex Karp, Palantir, and the Rise of the Surveillance State.See omnystudio.com/listener for privacy information.

Die Künstlerin und Autorin Niccel Steinberger malt, zeichnet und collagiert in bunten Farben. Sie leitet Lachseminare und weiß um die Kraft des Humors. Seit 25 Jahren ist sie mit dem Schweizer Kabarettisten Emil verheiratet. Wiese, Tim www.deutschlandfunkkultur.de, Im Gespräch

„Die Barmherzigkeit Gottes“ – So der Titel des Impulses von Pfarrer Thomas Steinberger aus dem Pfarrverband Emmerting im Bistum Passau bei Adoratio Altötting 2025 vom 26. bis 28. September. Hier in voller Länge als Podcast. (Quellennachweis: Dieser Podcast entstammt dem Livestream von EWTN.TV @ewtnde)

Übertr: Basilika St. Anna, Altötting (Bistum Passau) Adoratio Kongress in der Basilika St. Anna in Altötting.

Episode Description - Join host Martin "Marv" Bel as he sits down with podcaster John from "What's Up with John and Rena" for an in-depth conversation about the evolution of podcasting, mental health awareness, and the art of authentic audio storytelling. From interviewing people on Skid Row to creating successful podcast partnerships, John shares his journey through the podcasting landscape and offers invaluable advice for aspiring podcasters.  Key Timestamps & Topics -  [00:00:00] - Introduction & Show Origins  ● Welcome to Pods Like Us with Martin "Marv" Quibell  ● Introduction to John and the "What's Up with John and Reena" show  ● The confusing history and evolution of the podcast  [00:01:00] - Mental Health Journey & Podcast Genesis  ● John's misdiagnosis story: from bipolar to depression and ADHD  ● Living next to Skid Row in Los Angeles (2014)  ● The birth of "Bipolar Style" podcast  ● Cautionary tale about podcast naming and mental health stigma  [00:02:00] - RSS Feeds & Podcast Evolution  ● Understanding RSS feeds as the backbone of podcasting  ● Treating first podcast as "practice feed"  ● Evolution from "Signal Jams" to "Deviant Lounge" to "What's Up"  ● The importance of adaptability in podcasting  [00:03:00] - Partnership with Reena  ● Meeting co-host Rena through Twitter/X  ● Rena's background: Jerry Springer Show producer  ● Creating a "super group" approach to podcasting  ● The concept of podcasting as a "lounge for podcasters"  [00:04:00] - Content Strategy & Social Media  ● Using X/Twitter for podcast guest discovery  ● Topic selection process for episodes  ● Recent discussions: cell phone bans in schools and concerts  ● Organic conversation development  [00:05:00] - Editing Philosophy & Audience Retention  ● Unique editing approach: cutting conversations mid-topic  ● Background editing while gaming technique  ● Achieving 110% completion rates vs. industry 70%  ● The "shave and a haircut" psychological hook  [00:07:00] - "Daily Emotions" Era  ● Transition from "Bipolar Style" to "Daily Emotions"  ● The challenge of trauma dumping in mental health podcasts  ● Learning when to pivot podcast focus  ● The consuming nature of mental health content creation  [00:08:00] - Podcasting Influences & Inspirations  ● Dean Delray's "Let There Be Talk" as major influence  ● The power of reaching high-profile rock and metal guests  ● Mark Marin's WTF show impact  ● Transitioning from music industry to podcasting  [00:09:00] - Early Broadcasting Background  ● High school radio station with actual transmitter  ● Public access cable TV experience in San Francisco  ● "Wayne's World" style local TV show  ● The "simulation" approach to content creation  [00:12:00] - RSS & Download Philosophy  ● RSS and downloadability as core podcast elements  ● Avoiding "streaming subscription hell"  ● 20 years of RSS technology celebration  ● Focus on audio vs. video debates  [00:13:00] - Rena's Background & Skills  ● Jerry Springer Show production experience  ● Natural interviewing and listening abilities  ● The maven quality: connecting people and opportunities  ● Play-by-play vs. color commentary dynamic  [00:15:00] - Interview Dynamics Analysis  ● Rena's therapeutic listening approach  ● John's self-awareness about talking too much  ● The balance between liberal and conservative perspectives  ● Finding common ground through shared topics  [00:17:00] - Jerry Springer Connection  ● Jerry Springer's appearance on "Better Call Daddy"  ● Recognition of Rena's producer skills  ● The importance of information gathering in production  [00:19:00] - Podcast Industry Observations  ● Musicians vs. music industry people comparison  ● Podcasters vs. podcast industry professionals  ● The commodification of creative passion  ● Live Nation experience and craft services anecdotes  [00:20:00] - Branding & Visual Identity  ● The critical importance of podcast naming  ● Etymology and word psychology in naming  ● Domain availability considerations  ● Logo design: "Does it look cool on a t-shirt?"  [00:21:00] - Music Rights & Audio Strategy  ● The sticky nature of music rights in podcasting  ● Recommendation for original music performance  ● Minimalist intro approach vs. TV-style intros  ● The power of simple audio stingers  [00:23:00] - Content Longevity & "Zombie Podcasts"  ● Creating evergreen content without rights issues  ● The concept of "zombie podcasts" living forever  ● Authentic vs. polished AI content predictions  ● The value of human authenticity  [00:25:00] - Life Experience as Research  ● Being kicked out at 14 and learning independence  ● Life experiences as natural podcast material  ● The balance of sharing vs. professional discretion  ● Using stage names and artistic personas  [00:27:00] - The Power of Memorable Names  ● Single-syllable name effectiveness  ● Comparison to Cher, Norm, and other one-name personalities  ● The hook quality of punchy names  ● Domain purchasing with special characters  [00:29:00] - Advice for New Podcasters  ● "Make a fucking mess" - authenticity over perfection  ● Approach podcasting as an art project  ● The mechanical aspects are teachable in a week  ● Being yourself is the hardest part  [00:30:00] - Technical Accessibility  ● Free tools and apps like Riverside  ● No excuse for technical barriers  ● Borrowing equipment to start  ● The importance of experimenting before committing  [00:31:00] - Community & Networking  ● Don't be afraid to reach out on social media  ● Asking to be guests on shows you enjoy  ● Building circular podcast community  ● The "jam session" approach to podcasting  [00:32:00] - Show Recommendations & Contact Info  ● Let There Be Talk with Dean Delray  ● Mark Marin's WTF show  ● Dave Jackson's School of Podcasting  ● Contact: lillystudios.com and deviantlounge.com  [00:34:00] - Music Discussion & Equipment Talk  ● Bass guitar preferences and Steinberger memories  ● The Police concert memories from age 12-13  ● Fender artist relations and Tony Franklin connection  ● The evolution of electronic drums integration  [00:42:00] - Future Music Projects  ● "Bomb Repair" EDM project concept  ● Uploading music as podcast episodes  ● Exploring synth music and experimental styles  ● The cassette culture connection  Key Takeaways - 1. Authenticity Over Polish: Focus on genuine conversation rather than perfect  production  2. Community Building: Podcasting success comes from connecting with other  podcasters  3. Adaptability: Be willing to evolve your show's name, format, and focus  4. Technical Simplicity: Don't let equipment concerns prevent you from starting  5. Unique Editing: Experiment with non-traditional editing to improve retention  6. Strategic Naming: Choose names that are memorable, shareable, and brandable  7. RSS Independence: Maintain downloadable content to avoid platform dependency  8. Life as Content: Your experiences are your greatest source of material  Mentioned Resources & Tools - ● Riverside (podcast recording app)  ● Hindenburg (audio editing software)  ● YouTube Sound Library (royalty-free music)  ● RSS feeds and podcast hosting platforms  ● Social media for guest discovery (X/Twitter)  Contact Information - John Lilly: Website: lillystudios.com / Podcast: deviantlounge.com  Martin "Marv" Quibell: Website: themarvzone.org / Podcast: Pods Like Us (available on all streaming platforms)  #PodcastingTips #MentalHealthPodcasting #AudioStorytelling #PodcastCommunity  #IndependentPodcasting #ContentCreation #PodcastInterview #DigitalMedia #PodcastStrategy  #AudioProduction  This episode of Pods Like Us showcases the authentic journey of podcasting evolution, from mental health advocacy to community building, offering practical insights for both new and experienced podcasters looking to create meaningful audio content. 

Was passiert, wenn ein Kabarettist, der bei der Post fehl am Platz war, und eine Autorin, die im Studium den falschen Film erlebte, gemeinsam über Schule, Leben und Humor sprechen? Genau: Es wird tiefgründig, überraschend ehrlich, berührend - und herrlich unterhaltsam.In dieser Spezialfolge mit Live-Publikum begrüssen wirNiccel und Emil Steinberger, ein Duo, welches das Leben nicht nur kommentiert, sondern auch beobachtet und reflektiert. Emil erinnert sich an Lustiges, aber auch an nachdenkliche Momente in der Schulzeit, an Improvisation als Lebenskunst und an den Mut, loszulassen. Niccel erzählt, wie sie von der «Untergerdaristin» zur Fachfrau für Humor wurde - und wie sie durch Emil lernte, sich selbst treu zu bleiben. Wir sprechen über Schulerlebnisse, prägende Lehrpersonen, skurrile Kindheitsträume und die Kunst des Humors. Dabei zeigt sich: Schule ist mehr als ein Ort des Lernens - sie ist Bühne, Stolperstein und Sprungbrett zugleich.Ob Bildungsinteressierte, Humorliebhaberinnen oder einfachFans des Lebens in all seinen Facetten: Diese Folge ist eine Einladung zum Schmunzeln, Nachdenken und Loslassen.

Hello dear listener, Welcome to another episode of Guitar Nerds. This week, JD and I are talking all about our favourite wild guitar brands from the 70's and 80's. With especial focus on Kramer and Steinberger, we'll be going through all our favourite bits, and trying not to talk about bass too much! Hosted on Acast. See acast.com/privacy for more information.

Heute erwartet euch ein ganz besonderes Paar im aktuellen BB RADIO Mitternachtstalk-Podcast: Zwei Menschen, die nicht nur gemeinsam durchs Leben gehen, sondern auch gemeinsam Geschichte schreiben: Emil und Niccel Steinberger. Er ist der wohl bekannteste Kabarettist der Schweiz – eine lebende Legende. Und sie? Seine große Liebe, seine kreative Partnerin – und seine Wundertüte, wie er sie liebevoll nennt. Gemeinsam sind sie aktuell mit ihrem Dokumentarfilm „Typisch Emil – Vom Loslassen und Neuanfangen“ unterwegs - auf Kinotour quer durch Deutschland und die Schweiz. Dieses Gespräch ist für mich etwas ganz Besonderes. Ich kenne und verehre Emil seit meiner Kindheit - seit ich eine Vinylplatte von ihm geschenkt bekam. Ich konnte die meisten seiner Gags auswendig. Für mich gab es damals nur drei große Komiker: Loriot, Otto und Emil! Jahrzehnte später treffe ich jetzt mein Idol: Emil - 92 Jahre jung, voller Energie, Charme und Neugier. Und Niccel - rund drei Jahrzehnte jünger – steht ihm in nichts nach. Sie wollte als Kind Clown werden und schrieb Emil deshalb einen Brief. Der Beginn einer zehnjährigen Brieffreundschaft, aus der später eine glückliche Ehe wurde. Heute sind sie ein unschlagbares Team - privat und beruflich. Wir sprechen über Emils und Niccels Leben, über das, was war, bevor sie sich begegneten – und was seither alles passiert ist. Denn Emil war nicht immer der gefeierte Bühnenstar. Er begann als Postbeamter, lernte 3000 Poststellen auswendig, saß neun Jahre am Schalter - bis er merkte: Das kann's noch nicht gewesen sein! Er kündigte - und startete ein Leben voller Wendungen: Grafikstudium, erste Sketche, Fernsehauftritte, große Tourneen: „E wie Emil“, „Emil träumt““, „Geschichten, die das Leben schrieb“. Millionen Zuschauer feierten ihn – und seinen feinen Humor. Jetzt kehrt er – gemeinsam mit Niccel – auf die Leinwand zurück. In ihrem Film „Typisch Emil“ treffen wir auf legendäre Sketche und bekommen ganz persönliche Einblicke in ihr gemeinsames Leben. Emil sagt: Jahreszahlen? Sind mir völlig egal! Ich hab‘ sogar mein Pensionsalter verpasst. Aber: Wie hält man sich mit 92 so fit? Was macht ihre Liebesgeschichte so besonders? Und was kommt nach dem aktuellen Blockbuster? All das – jetzt im BB RADIO Mitternachtstalk-Podcast. Mit zwei außergewöhnlichen Menschen, die zeigen: Humor, Neugier und Liebe - das ist das wahre Lebenselixier. Und Alter? Ist wirklich nur eine Zahl! Emil und Niccel Steinberger – jetzt bei mir!

This week I'm joined by Aimee Steinberger, Assistant Director for the OG Run of Futurama and the storyboard artist that is responsible for one of the most recognizable, shared and reused piece of animation, "Shut up and take my money". We are chatting about Futurama folks so buckle up!   Join our Patreon: https://patreon.com/CartoonChronix   Follow Aimee: https://www.youtube.com/@aimeekitty Follow Aimee: https://www.aimeemajor.com Follow Aimee: https://bsky.app/profile/aimeekitty.bsky Follow Aimee: https://www.instagram.com/aimeesteinbergerart/   Follow Us On Social Media: Facebook: https://www.facebook.com/CartoonChronix Instagram: https://www.instagram.com/CartoonChronix X: https://x.com/CartoonChronix Youtube: https://www.youtube.com/@CartoonChronix #Futurama #bender #futuramamemes #futuramaedit #futuramafandom

If you love your office, show it! WestchesterTalkRadio.com's “I LOVE MY OFFICE!!” promotion gives you the chance to win a live broadcast produced by Sharc Creative, plus amazing gifts from local sponsors. Winners receive floral arrangements from Joseph Richard Florals in Armonk and Grayrock Florist in Valhalla, delicious chocolate treats from Chocolations of Mamaroneck, tickets to Westchester Soccer Club games at The Stadium at Memorial Field, concert passes to The Capitol Theatre in Port Chester, fun swag from Purple Frog Graphics, and even a catered Happy Hour Party by Caperberry Events at Sam's of Gedney Way or Sharc Headquarters. The latest winner was Cuddy & Feder LLP, a nationally recognized law firm known for solving complex legal challenges. Westchester Talk Radio visited their office, and host Andrew Castellano spoke with Marketing Director Ashley Steinberger about what it's like to be part of the Cuddy & Feder team. Register your office now at westchestertalkradio.com! 

Annika B. (32) geht mit ihrem Mann wandern – aber nicht irgendwo, sondern in den USA auf dem Appalachian Trail. Die Ehe ist gefühlt am Ende, passiv-aggressive Vibes dominieren die Reise, und so dauert es nicht lange, bis ein heftiger Streit ausbricht.Annika hat die Schnauze voll und macht Tempo – so viel, dass sie ihren Ehemann irgendwann nicht mehr sehen kann.Und dann passiert's: Sie rutscht aus, verletzt sich – und steht beim Einbruch der Nacht plötzlich allein im Wald. Wird sie frieren? Wird ihr Mann sie finden? Oder wird sie von einem wilden Tier entdeckt?Wer wissen will, was passiert, wenn man mit einem Kontrollfreak wandern geht und statt einem Bären plötzlich Mr. Right auftaucht – unbedingt reinhören!Wenn ihr mehr über unsere wundervolle, diesmalige Gästin Eveline Steinberger erfahren wollt, ja, die Frau hat einen Wikipedia Eintrag! Und das völlig zurecht, denn sie ist Managerin, Unternehmerin, Tech-Investorin und Expertin für Digitalisierung und Energiewandel. Als Gründerin der Blue Minds Company setzt sie auf innovative Technologien wie Künstliche Intelligenz, Big Data und Augmented Reality, um nachhaltige Geschäftsmodelle voranzutreiben und obendrauf sie ist, so wie wir, Seeliebhaberin und leidenschaftliche E-Boot Kapitänin!Zudem ist seit 2024 Jurorin bei der PULS4-Show 2 Minuten 2 Millionen, wo sie Gründer*innen nicht nur finanziell unterstützt, sondern auch als Mentorin wertvolle Tipps gibt. Achja auf Instagram ist sie natürlich auch! ---Euch hat diese Geschichte gefallen, aufgeregt oder ihr habt euch darin sogar wiedererkannt? Das interessiert uns brennend!Schreibt uns in Kommentaren über Facebook und Instagram unter @dramacarbonara. Dort werdet ihr auch die in den Geschichten besprochenen Fotos finden und endlich sehen können, was wir sehen ... Falls ihr noch mehr fantastische Geschichten mit uns lesen wollt, können wir euch schon jetzt versprechen: das Repertoire ist unerschöpflich, wir staunen jedes Mal aufs Neue, was möglich ist. Abonnieren per RSS-Feed, Apple Podcasts, Spotify, Deezer oder Google Podcasts ist der Schlüssel zur regelmäßigen Versorgung. Über Rezensionen freuen wir uns natürlich extrem und feiern diese gern auch prominent in unserem Social Media Feed.Jede zweite Folge kommt übrigens ein/e GastleserIn zu uns ins kuschelige Wiener Hauptquartier und unterstützt uns mit Theorien zu Charakteren und Handlungssträngen. Wenn ihr einen Wunschgast habt oder gern selbst mal vorbeischauen wollt, sagt Bescheid. Wir können nichts versprechen, aber wir freuen uns immer über Vorschläge.Wenn ihr Lust auf Extra-Content und Community-Aktivitäten habt, unterstützt uns mit einem Abonnement auf Steady und kommt in den Genuss des kompletten "Drama Carbonara"-Universums: https://steadyhq.com/de/drama-carbonara/aboutFalls ihr daran interessiert sind, Werbung in unserem Podcast zu schalten, setzt euch bitte mit Stefan Lassnig von Missing Link  in Verbindung. Verbindlichsten Dank!  NEUER PODCAST!Wer in den neuesten Podcast, den Tatjana und Asta für HAPPY HOUSE MEDIA Wien produziert haben mit dem vielversprechenden Namen "Wo die Geister wohnen" reinhören mag - schaut mal hier & hier findet ihr den Geister Instagram Account! Es wird schrecklich schön!!--Link zur Podcast Hörer:innen UMFRAGE!Danke für die Mitarbeit und euer wertvolles Feedback :) & hier zur legendären Spotify Drama Carbonara Soundtrack Playlist - folgen folgen folgen!! liebe Freund:innen des unberechenbaren Musik-Algorithmus!

Steinberger, Luise www.deutschlandfunk.de, Europa heute

There's a new archetype in Silicon Valley, the AI researcher turned founder. Instead of tinkering in a garage they write papers that earn them the right to collaborate with cutting-edge labs until they break out and start their own. This is the story of wunderkind Eric Steinberger, the founder and CEO of Magic.dev. Eric came to programming through his obsession with AI and caught the attention of DeepMind researchers as a high school student. In 2022 he realized that AGI was closer than he had previously thought and started Magic to automate the software engineering necessary to get there. Among his counterintuitive ideas are the need to train proprietary large models, that value will not accrue in the application layer and that the best agents will manage themselves. Eric also talks about Magic's recent 100M token context window model and the HashHop eval they're open sourcing. Hosted by: Sonya Huang, Sequoia Capital Mentioned in this episode: David Silver: DeepMind researcher that led the AlphaGo team Johannes Heinrich: a PhD student of Silver's and DeepMind researcher who mentored Eric as a highschooler Reinforcement Learning from Self-Play in Imperfect-Information Games: Johannes's dissertation that inspired Eric  Noam Brown: DeepMind, Meta and now OpenAI reinforcement learning researcher who eventually collaborated with Eric and brought him to FAIR ClimateScience: NGO that Eric co-founded in 2019 while a university student  Noam Shazeer: One of the original Transformers researchers at Google and founder of Charater.ai  DeepStack: Expert-Level Artificial Intelligence in Heads-Up No-Limit Poker: the first AI paper Eric ever tried to deeply understand LTM-2-mini: Magic's first 100M token context model, build using the HashHop eval (now available open source) 00:00 - Introduction 01:39 - Vienna-born wunderkind 04:56 - Working with Noam Brown 8:00 - “I can do two things. I cannot do three.” 10:37 - AGI to-do list 13:27 - Advice for young researchers 20:35 - Reading every paper voraciously 23:06 - The army of Noams 26:46 - The leaps still needed in research 29:59 - What is Magic? 36:12 - Competing against the 800-pound gorillas 38:21 - Ideal team size for researchers 40:10 - AI that feels like a colleague 44:30 - Lightning round 47:50 - Bonus round: 200M token context announcement

Today on No Priors, Sarah Guo and Elad Gil are joined by Eric Steinberger, the co-founder and CEO of Magic.dev. His team is developing a software engineer co-pilot that will act more like a colleague than a tool. They discussed what makes Magic stand out from the crowd of AI co-pilots, the evaluation bar for a truly great AI assistant, and their predictions on what a post-AGI world could look like if the transition is managed with care.  Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @EricSteinb Show Notes:  (0:00) Introduction (0:45) Eric's journey to founding Magic.dev (4:01) Long context windows for more accurate outcomes (10:53) Building a path toward AGI (15:18) Defining what is enough compute for AGI (17:34) Achieving Magic's final UX (20:03) What makes a good AI assistant (22:09) Hiring at Magic (27:10) Impact of AGI (32:44) Eric's north star for Magic (36:09) How Magic will interact in other tools

IronMen of God - August 2024 Coffee Speaker: Rick Steinberger Topic: Relationships and Community

Will's websiteJewish Plays ProjectDavid Winitsky's Positive Creativity Podcast Episode

A few weeks ago, David Gilmour announced Luck and Strange, his first release since 2015, as well as a select set of tour dates and dropped a new video. On the second episode of the 100 Guitarists podcast, hosts Jason Shadrick and Nick Millevoi break down the video, from Gilmour's collaborators and gear to his climactic solo. Friends and listeners call in to support their favorite member of the '80s Armani and Strat mafia.Get at us: 100guitarists@premierguitar.com Call/Text: 319-423-9734 Sponsored by EMG Pickups: https://www.emgpickups.com/ Podcast powered by Sweetwater. Get your podcast set up here! - https://sweetwater.sjv.io/75rE0d Subscribe to the podcast:Spotify: https://open.spotify.com/show/0aXdYIDOmS8KtZaZGNazVbApple: https://podcasts.apple.com/us/podcast/100-guitarists-you-should-know/id1746527331 Check out the playlist: https://music.apple.com/us/playlist/david-gilmour-100-guitarists/pl.u-ReW7Sq7RWADavid (w Steinberger) and Kate Bush playing “Running Up That Hill” at the Secret Policeman's Ball 1987: https://www.youtube.com/watch?v=Lk7AVm0Ome0David Gilmour's “The Piper's Call” : https://www.youtube.com/watch?v=gMr5GpCpKyAAll about the “Black Strat”: https://www.gilmourish.com/?page_id=66

Guess who's back? Die Vergesellschaftungskonferenz! Ich hatte die große Freude, wieder mit Future Histories dabei sein zu dürfen. Mehrere Folgen sind entstanden, den Auftakt bildet das Gespräch mit Katharina Keil zu Vergesellschaftung und Transformation. Shownotes Die zweite Vergesellschaftungskonferenz fand vom 15.-17. März 2024 am Werbellinsee in Brandenburg statt. Allgemeine Infos gibt es hier: https://vergesellschaftungskonferenz.de/ Programm: https://vergesellschaftungskonferenz.de/programm/ Die Vergesellschaftungskonferenz auf Twitter: http://www.twitter.com/vergesellschaf1 Über demokratische Wirtschaft: https://communia.de/was-ist-eine-demokratische-wirtschaft/ https://communia.de/formen-einer-demokratischen-wirtschaft/ Katharina Keil (Universität Lausanne): https://igd.unil.ch/akeil/en/presentation/ Keil, A. K., & Steinberger, J. K. (2024). Cars, capitalism and ecological crises: understanding systemic barriers to a sustainability transition in the German car industry. New Political Economy, 29(1).: https://doi.org/10.1080/13563467.2023.2223132 Keil, A. K., & Kreinin, H. (2022). Slowing the treadmill for a good life for All? German trade union narratives and social-ecological transformation. Journal of Industrial Relations, 64(4), 564-584.: https://journals.sagepub.com/doi/10.1177/00221856221087413 Weitere Shownotes Grundgesetz der Bundesrepublik Deutschland, Artikel 15: „Grund und Boden, Naturschätze und Produktionsmittel können zum Zwecke der Vergesellschaftung durch ein Gesetz, das Art und Ausmaß der Entschädigung regelt, in Gemeineigentum oder in andere Formen der Gemeinwirtschaft überführt werden.“ https://www.bundestag.de/gg Amsel 44 (kämpfen u.a. für eine Konversion von VW): https://amsel44.de/ Kampagne „VW für Alle“: https://vw-fuer-alle.de/ Blog zur Verkehrswendestadt: https://blog.verkehrswendestadt.de „Ein Hauch von Klassenkampf“, Artikel von Franziska Heinisch zum Aktionstag im Boschwerk München (Jacobin): https://jacobin.de/artikel/ein-hauch-von-klassenkampf-bosch-werke-muenchen-ig-metall-autoindustrie-klimakrise Artikel zur Seifenfabrik Vio.me aus Thessaloniki (nd-aktuell): https://www.nd-aktuell.de/artikel/1170925.selbstverwaltete-seifenfabrik-vio-me-ungewisse-zukunft-fuer-vio-me.html Satzung der IG-Metall: https://www.igmetall.de/download/20231222_IGM_Satzung_2024_232da4272e6e85e92c762acbccd45acb4569dafd.pdf Homepage der Initiative "Deutsche Wohnen & Co enteignen": https://www.dwenteignen.de/ Artikel zum GKN-Fabrikkollektiv in Campi Bisenzio (Florenz): https://www.sozialismus.info/2023/10/insorgiamo-die-geschichte-des-militanten-werkskollektivs-bei-gkn-in-florenz/ „Regionale Gestaltung der Transformation in den Bundesländern“ (Working Paper der Hans-Böckler Stiftung): https://www.boeckler.de/fpdf/HBS-008767/p_fofoe_WP_317_2023.pdf&ved=2ahUKEwjWueXwnrqFAxX2AtsEHb9zDzwQFnoECBIQAQ&usg=AOvVaw218lX7FoGgTrzcCSjziDtL „The Social Responsibility of Business Is to Increase Its Profits“ von Milton Friedman (New York Times, 1970): https://www.nytimes.com/1970/09/13/archives/a-friedman-doctrine-the-social-responsibility-of-business-is-to.html Fieber, Tanja und Konitzer, Franziska. 2021. Treibhausgase: Wie der CO2-Fußabdruck die Klima-Realität verschleiert. ARD alpha: https://www.ardalpha.de/wissen/umwelt/nachhaltigkeit/co2-fussabdruck-carbon-footprint-shell-exxon-bp-taeuschung-klima-100.html Buchhandlung Bücherkiste in Siegen: https://www.buecherkiste.net/ Weitere Future Histories Episoden zum Thema S02E23 | Nina Scholz zu den wunden Punkten von Google, Amazon, Deutsche Wohnen & Co.: https://www.futurehistories.today/episoden-blog/s02/e23-nina-scholz-zu-den-wunden-punkten-von-google-amazon-deutsche-wohnen-co/ S01E48 | Sabine Nuss zu Eigentum: https://www.futurehistories.today/episoden-blog/s01/e48-sabine-nuss-zu-eigentum-teil-1/ S01E15 | Rouzbeh Taheri zu Enteignung, Vergesellschaftung & demokratischem Sozialismus: https://www.futurehistories.today/episoden-blog/s01/e15-rouzbeh-taheri-zu-enteignung-vergesellschaftung-demokratischem-sozialismus/ S02E59 | Lemon und Lukas von communia zu öffentlichem Luxus: https://www.futurehistories.today/episoden-blog/s02/e59-lemon-und-lukas-von-communia-zu-oeffentlichem-luxus/ Wenn euch Future Histories gefällt, dann erwägt doch bitte eine Unterstützung auf Patreon: https://www.patreon.com/join/FutureHistories? Schreibt mir unter office@futurehistories.today und diskutiert mit auf Twitter (#FutureHistories): https://twitter.com/FutureHpodcast oder auf Reddit: https://www.reddit.com/r/FutureHistories/ www.futurehistories.today Episode Keywords: #Vergesellschaftungskonferenz, #KatharinaKeil, #JanGroos, #FutureHistories, #Podcast, #Interview, #Vergesellschaftung, #Transformation, #demokratischeWirtschaft, #Demokratie, #Wirtschaftsdemokratie, #Marktwirtschaft, #Solidarität, #Utopie, #Eigentum, #Enteignung, #VwEnteignen, #Konversion  

We continue with our OU812 rankings. (0:55) We touch on lyric writing, James Brown, if the Sammy era songs had happened during Dave's era, just how amazing Darby Mills is and the greatness of Chilliwack. (9:08) Todd talks shop about Kramer and Steinberger guitar, locked tremolos and other Eddie gear. (19:52) What about Eddie and Sammy's clothing choices during 5150? (26:32) And what famous shirt did Sean wear hoping people think he was as cool as Michael Anthony? We answer the question (likely incorrectly) of what exactly is the Pleasure Dome and why is Alex so amazing? (33:12) Can Todd and Sean execute poor Sammy lyrics better than Sammy? (44:24)#podcast #vanhalen #ou812 #5150 #chilliwack #headpins #Kramer #Steinberg #tremolo #PleasureDome #AlexVanHalenWebsite: www.seanmcginity.caMerch: Red Bubble: https://www.redbubble.com/people/seangeekpodcast/shopTee Public: https://www.teepublic.com/seangeekpodcast@seangeekpodcast on Twitter, Instagram and Facebook@fastfretfingers on Instagram@ToddGeeks Tech Talk on Facebook @captivatefmMentioned in this episode:New Merch AdAn ad that incorporates Red Bubble and Tee PublicThis podcast uses the following third-party services for analysis: Chartable - https://chartable.com/privacy

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In this episode, Aviva Steinberger takes us through a journey of self-discovery and empowerment, sharing her insights on embracing authenticity, cultivating meaningful change, and finding balance across different aspects of life. Through her journey, Aviva inspires us to unleash our full potential and live with purpose.  Aviva Steinberger is the Director of Innovation Diplomacy at Start-Up Nation Central. In May 2023, SNC co-hosted with their Moroccan partner CPR, a 3 day event at Marrakesh which brought together women from Bahrain, Benin, Egypt, Israel, Jordan, Kenya, Morocco, Nigeria, Palestine, South Africa, Sudan, United Arab Emirates, the United States, and others, focused on the shared challenges faced in the Middle East and Africa. In 2009, Aviva was the Director of World Trade Center Business Recovery and Industry Development at the NY State Governor's office responsible for the economic development and recovery efforts to revitalize lower Manhattan after 9/11, allocating $800M in funds to more than 14,000 businesses. Aviva's experience in business, government and non-profit helped to forge her passion for collaborating across boundaries and appreciate the potential of unlikely partnerships.  References: Check out episode 32 "I am Remarkable" with Dona Raz Levy from Google!  Also do not miss episode 6 "Embracing the Power Of Vulnerability" Let's connect- Contact us on Linkedin or Instagram: Aviva on Linkedin  Manal on Linkedin and instagram (@manalbernoussi). More info on Women Connect to Innovate here. You can find photos from the experience on my instagram account.  

Episode full contents: [For full episode interviews join via Patreon: https://patreon.com/genncc or on Youtube: https://youtu.be/v9fEcRYVaf4 ] 1. Fossil fuel companies were never a partner is solving climate change. 2. The possible world that we see emerging around us. 3. How do we face the strength of the fossil fuel industry? 4. COP28 is symbolic of political failure. 5. Fossil fuel companies are trying to take over key structural processes. 6. We must all use our collective agency. 7. The Energy Charter Treaty (ETC), and why it must be ended. 8. The fossil fuel industry is fragile; don't be duped into inaction. 9. There is another world we can create from this. 10. Become the mainstream by better articulating the mission. Links: https://www.fossilbanks.org/ https://fossilfueltreaty.org/ https://www.celinekeller.com/dawn-of-the-ect https://www.beyond-growth-2023.eu/

This episode recorded live at the 20th Annual Becker's Healthcare Spine, Orthopedic + Pain Management-Driven ASC Conference features Dr. Jeremy Steinberger, Director of Minimally Invasive Spine Surgery at Mount Sinai Health Systems, Department of Neurosurgery; Assistant Professor of Neurosurgery & Orthopedics at Icahn School of Medicine, Mount Sinai. Here, he discusses his background, his excitement surrounding innovative neurosurgery technologies, what the most effective healthcare leaders need to be successful in the next 2-3 years, and more.

This episode recorded live at the 20th Annual Becker's Healthcare Spine, Orthopedic + Pain Management-Driven ASC Conference features Dr. Jeremy Steinberger, Director of Minimally Invasive Spine Surgery at Mount Sinai Health Systems, Department of Neurosurgery; Assistant Professor of Neurosurgery & Orthopedics at Icahn School of Medicine, Mount Sinai. Here, he discusses his background, his excitement surrounding innovative neurosurgery technologies, what the most effective healthcare leaders need to be successful in the next 2-3 years, and more.

This Week in Startups is presented by: Crowdbotics. Great ideas can change the world, and Crowdbotics is the fastest way to turn those ideas into code. Get a free scoping session for your next big app idea at http://crowdbotics.com/twist. The Microsoft for Startups Founders Hub helps all founders build a better startup, at a lower cost, from day one. Startups get up to $150K in Azure credits, access to free OpenAI credits, free dev tools like GitHub, technical advisory, access to mentors and experts, and so much more. There is no funding requirement, and it only takes minutes to join. Sign up today at http://aka.ms/thisweekinstartups. Release. Large enterprises pose unique challenges for SaaS startups. Unlock customers with unique needs for private and single-tenant hosting without the toil of DIY with Release Delivery. Get your first month free at https://release.com/twist. * Today's show: Jason is joined by Magic.dev CEO and Co-Founder Eric Steinberger to discuss how his startup makes developers more efficient with AI by auto-generating code. The first portion of the interview features Eric demoing his software. Then, Jason and Eric dive into the impact that these rapid AI advancements will have on society (31:28), how their tools have the potential to significantly minimize coding time and what that means for entrepreneurship (13:55), and much more! * Time stamps: (00:00) Eric Steinberger joins Jason (1:44) Eric and Jason explain what Magi.dev is (3:43) Eric Demos Magic.dev (9:13) What makes this AI model unique (11:02) Crowdbotics - Get a free scoping session for your next big app idea at ⁠http://crowdbotics.com/twist⁠ (12:11) Magic.dev's motivation behind building their own language model (13:55) The efficiency gains achieved with Magic.dev (17:32) Exploring reinforcement learning and grounding the AI model (19:45) Microsoft for Startups Founders Hub - Apply in 5 minutes for six figures in discounts at http://aka.ms/thisweekinstartups (21:19) The two parallel paths unfolding (23:57) How close we are to developing more capable AI systems (31:28) The impact of Moore's Law on technology and society (37:34) Release - Get your first month free at ⁠https://release.com/twist (39:03) Alternative perspectives on the pace of AI advancement (43:14) The origins of Eric's positive outlook on AI (47:49) Thought's on AI regulation and choke points * Read LAUNCH Fund 4 Deal Memo & Apply for Funding Buy ANGEL Great recent interviews: Brian Chesky, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarland, PrayingForExits, Jenny Lefcourt Check out Jason's suite of newsletters: https://substack.com/@calacanis * Follow Jason: Twitter: https://twitter.com/jason Instagram: https://www.instagram.com/jason LinkedIn: https://www.linkedin.com/in/jasoncalacanis * Follow TWiST: Substack: https://twistartups.substack.com Twitter: https://twitter.com/TWiStartups YouTube: https://www.youtube.com/thisweekin * Subscribe to the Founder University Podcast: https://www.founder.university/podcast

Professor Julia Steinberger researches and teaches in the interdisciplinary areas of Ecological Economics and Industrial Ecology.  She is the recipient of a Leverhulme Research Leadership Award for her research project 'Living Well Within Limits' investigating how universal human well-being might be achieved within planetary boundaries. She is Lead Author for the IPCC's 6th Assessment Report with Working Group 3.She has held postdoctoral positions at the Universities of Lausanne and Zurich, and obtained her PhD from the Massachusetts Institute of Technology. She has published over 40 internationally peer-reviewed articles since 2009 in journals including Nature Climate Change, Nature Sustainability, WIRES-Climate Change, Environmental Science & Technology, PLOS ONE and Environmental Research Letters.As part of our drive towards finding the people at the leading edge of change, we wanted to connect with Prof Steinberger really to unpick the detail of personal and collective action. Each of us is only one person and the nature of the change can feel overwhelming even while it feels urgent.  So we need to hear directly from the people whose entire lives are given to solving this problem and who have concrete ideas of what we can do and how, who can direct our priorities and show us where the best leverage points lie.  Prof. Steinberger has clear ideas of how our culture can live within planetary boundaries and we unpick them in this podcast.  Enjoy! Julia on Medium https://jksteinberger.medium.com/an-audacious-toolkit-actions-against-climate-breakdown-part-1-a-is-for-advocacy-7baa108f00e9Living Well Within Limits https://lili.leeds.ac.uk/Positive Money https://positivemoney.org/Fossil Banks, No Thanks https://www.fossilbanks.org/