Podcasts about nten

En kuperad trädgård kan vara en riktig tillgång, men man behöver tänka till! Lär dig fixa din slänt, med de bästa tipsen från John och Pernilla. Lyssna på alla avsnitt i Sveriges Radios app. Tips om terrasser och trick för en användbar släntÄr din trädgård brant som en hoppbacke, eller lutar den bara lite grand? Oavsett så kommer John Taylor och Pernilla Månsson Colt att ge dig tips på hur du kan få det fint och faktiskt glädjas åt att ha en slänt.Du får veta hur man gör den lutande trädgården mer lättskött, vad som får jorden att stanna kvar, vilka växter som trivs där vattnet rinner undan och som kan bromsa erosionen.Avsnittets lyssnarfrågor handlar om att använda gåsbajs som gödsel, goda vindruvor och om det är lämpligt att plantera om sparris.Har du en fråga om odling och trädgård? Skriv till tradgarden@sverigesradio.se. Var gärna någorlunda kortfattad och tydlig med vad du undrar över!Producent och redigering: Anna LandeliusRedaktör: Eva RobildLjud och efterbearbetning: André Ljungberg

Italienske kindkys, tysk begejstring og franske jubelråb. Siden begyndelsen af hans anden præsidentperiode har Donald Trump badet i støtte fra den europæiske højrefløj, som har taget ham til sig som en tæt allieret i kampen for nationalisme på tværs af kontinentet. Indtil nu. For Trumps stærke bånd til politiske stjerner i lande som Italien, Tyskland og Frankrig er begyndt at løsne sig. Faktisk ønsker nogle at kappe dem helt. I dag taler vi med Politikens EU-korrespondent, Karin Axelsson, om, hvordan lykkemønten Trump forvandlede sig til en forbandelse for den europæiske højrefløj. Og om, hvordan det kan forandre det Europa, som Trump længe har ønsket at svække. Vært: Johanne Lerhard Producer: Jonas Bach-Madsen Research: Karoline Bentzen Redaktør: Line PraszSee omnystudio.com/listener for privacy information.

Simon Baumann zeigt in „Wir Erben“, wie die Hofübergabe seiner Eltern an die Kinder mit Erwartungen und Enttäuschungen verbunden war. „Ich bin der qualifizierteste Experte für mein eigenes Leben“, sagt der Regisseur in SWR Kultur über seine Arbeit.

This Week:  Consider The Human Factors We launch our coverage of the 2026 Nonprofit Technology Conference with an NTC perennial: Rubin Singh. This year, he asks you to consider the human side of tech that impacts your CRM, and really, … Continue reading →

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

Sanny rasar på amatörnivån och Svensson kravställer på junioren.

Join Karen Horrocks and Stephen Musgrave as they introduce the upcoming non-profit summit at DrupalCon 2026 in Chicago. In this comprehensive fireside chat, they explore how AI can be integrated to serve a nonprofit's mission, plus the dos and don'ts of AI implementation. Hear insights from leading nonprofit professionals, learn about the variety of breakout sessions available, and discover the benefits of Kubernetes for maximizing ROI. Whether you're a developer, content editor, or a strategic planner, this session is crucial for understanding the future of nonprofit operations with cutting-edge technology. For show notes visit: https://www.talkingDrupal.com/cafe015 Topics Introduction Meet Karen & Stephen Karen's Journey to Nonprofit Work Deep Dive into Drupal and Nonprofit Websites Capella's Approach to Continuous Improvement Nonprofit Summit Overview Exploring Summit Themes: AI and Resiliency Digital Sovereignty and Ethical Considerations Additional Breakout Sessions and Topics Community Engagement and Registration Details Conclusion and Final Thoughts Stephen Musgrave Stephen (he/him) is a co-founder, partner and Lead Technologist at Capellic, an agency that build and maintains websites for non-profits. Stephen is bullish on keeping things simple – not simplistic. His goal is to maximize the return on investment and minimize the overhead in maintaining the stack for the long term. Stephen has been working with the web for over 30 years. He was initially drawn to the magic of using code to create web art, added in his love for relational databases, and has spent his career building websites with an unwavering commitment to structured content. When Stephen isn't at his desk, he's often running to and swimming in Barton Springs Pool, getting a bit too wound-up at Austin FC games, and playing Legos with his little one. Karen Horrocks Karen (she/her, karen11 on drupal.org and Drupal Slack) is a Web and Database Developer for the Physicians Committee for Responsible Medicine, a nonprofit dedicated to saving and improving human and animal lives through plant-based diets and ethical and effective scientific research. Karen began her career as a government contractor at NASA Goddard Space Flight Center developing websites to distribute satellite data to the public. She moved to the nonprofit world when the Physicians Committee, an organization that she supports and follows, posted a job opening for a web developer. She has worked at the Physicians Committee for over 10 years creating websites that provide our members with the information and tools to move to a plant-based diet. Karen is a co-moderator of NTEN's Nonprofit Drupal Community. She spoke on a panel at the 2019 Nonprofit Summit at DrupalCon Seattle and is helping to organize the 2026 Nonprofit Summit at DrupalCon Chicago. Resources Nonprofit Summit Agenda: https://events.drupal.org/chicago2026/session/summit-non-profit-guests-must-pre-register Register for the Summit (within the DrupalCon workflow): https://events.drupal.org/chicago2026/registration Funding Open Source for Digital Sovereignty: https://dri.es/funding-open-source-for-digital-sovereignty NTEN's Drupal Community of Practice Zoom call (1p ET on third Thursday of the month except August and December): https://www.nten.org/drupal/notes Nonprofit Drupal Slack Channel: #nonprofits on Drupal Slack Guests Karen Horrocks - karen11 www.pcrm.org Stephen Musgrave - capellic capellic.com

Het ego is dat innerlijke typetje dat graag de controle houdt, altijd gelijk wil hebben en falen het liefst in een donker steegje parkeert.
Maar wat is dat ego eigenlijk? Waarom raakt het zo in de stress als iets even niet lukt? En hoe komt het dat het zich gedraagt als een overijverige bodyguard die je continu probeert te beschermen, ook als dat totaal niet nodig is? In deze aflevering gaan we op onderzoek uit. Want ja, het ego bedoelt het goed. Het wil je veilig houden, beschermen tegen afwijzing of afgang. Maar eerlijk is eerlijk: het kan je ook flink in de weg zitten. Zeker als je iets nieuws probeert, of juist even helemaal niet weet wat je aan het doen bent. Wat zit er eigenlijk áchter dat ego? (Spoiler: een veel diepere laag van jezelf. Eerlijker, zachter. Zonder masker. Mét ruimte om te durven en te doen wat er voor jou écht toe doet). Dus trek je mentale wandelschoenen aan, want we duiken samen in de krochten van het ego. Je ontdekt de vier vaste ingrediënten van het ego, maakt kennis met het opmerkzame zelf (ja, dat bestaat) én hoort straatinterviews uit Utrecht en muziek van Mark Lotterman als kers op de faalcake. Shownotes: www.instituutvoorfaalkunde.nl

Hoe is het om huisarts te zijn van patiënten die nauwelijks het licht kunnen verdragen, maar aan de buitenkant ‘gewoon gezond' lijken? Huisarts Jojanneke Kant, online bekend als ‘De Vragendokter', ziet van dichtbij hoe long covid levens en toekomstdromen wegvaagt. Ze noemt het een „indrukwekkend en onderschat ziektebeeld”, waarbij mensen buiten beeld raken, omdat ze letterlijk uit het gewone leven verdwijnen.

ChristenUnie-leider Mirjam Bikker wil meer structurele hulp voor long covid patiënten. Bikker heeft in de Tweede Kamer een debat aangevraagd voor donderdagavond en licht in Dit is de dag toe waar het in haar ogen aan schort. Longarts Leon van den Toorn en hoogleraar gezondheidseconomie Wim Groot reageren.

In aflevering 185 duiken we dieper in vitamines en mineralen. We trappen af met een quizje. Want hoeveel vitamines zijn er eigenlijk? Welke bestaan echt en welke zijn 'nep' (vitamine F, G en H). Mr. Food Coach legt uit wat vitamines en mineralen (micronutriënten) precies zijn en waarom ze onmisbaar zijn tijdens het afvallen. Want micronutriënten dragen bij aan belangrijke processen in je lichaam, zoals weerstand, energie en de gezondheid van je huid en haar. In de Calorie Challenge vergelijken we rijstwafels en maïswafels. Ondertussen leert Iris steeds beter luisteren naar de signalen van haar lichaam.Hoe goed is jouw voedingskennis? Maak nu de gratis en gloednieuwe Happy & Healthy Scan van Mr. Food Coach: https://mrfoodcoach.scoreapp.com/ Doe de Clash of Calories hier: https://caloriechallenge.scoreapp.com/Kom bij onze community in Maak Afvallen Makkelijk+Ga naar https://www.maakafvallenmakkelijk.nl/Volg Mr. Food Coach op Instagram via https://www.instagram.com/mrfoodcoachMeer informatie over persoonlijke coaching via https://www.mrfoodcoach.nl/starten/Contact: mail naar info@mrfoodcoach.nl In Maak Afvallen Makkelijk vertellen Jelle (Mr. Food Coach) en Iris je alles over wat er bij afvallen komt kijken. Volgens Mr. Food Coach hoeft afvallen niet moeilijk te zijn, Iris is aan het afvallen en gaat met zijn tips aan de slag.

Join Johanna and Jess as they dive deep into their experiences and insights working with Drupal in the nonprofit sector. Learn about their early careers, the evolution of Drupal's development, the significance of community in nonprofit tech, and the origins and importance of the Nonprofit Summit at DrupalCon. Discover how their community initiatives foster collaboration and support among nonprofit technologists, and get a glimpse into the upcoming summit details. Perfect for anyone interested in Drupal, open-source technology, and nonprofit organizational challenges. For show notes visit: https://www.talkingDrupal.com/cafe012 Johanna Bates Johanna Bates (they/them, hanpersand on drupal.org) is co-founder and co-principal of DevCollaborative, a company that builds accessible and sustainable Drupal and WordPress sites exclusively for nonprofit organizations. Johanna began their formal tech career at WGBH in Boston in 2000 as a front-end developer. They have been building Drupal sites since 2004, and have been co-moderating NTEN's Nonprofit Drupal Community and its monthly chats for over a decade. Johanna was involved in early Nonprofit Summits at NYCcamp starting back in 20-teens 2015, and helped bring the Nonprofit Summit to DrupalCon North America in 2017. Jess Snyder Jess Snyder (jesss on drupal.org and Drupal Slack) is Director of Web Systems for WETA, the flagship public media station for Washington, DC, and has over 20 years of experience in website development. Jess is an organizer for NTEN's Drupal Community of Practice as well as Drupal GovCon. She also co-chaired the triumphant return of the Nonprofit Summit to DrupalCon Portland 2024 and its sequel at DrupalCon Atlanta 2025. When not Drupaling, Jess sits on the Board of Directors for the National Academy of Television Arts and Sciences. Topics Meet the Speakers: Johanna and Jess Johanna's Journey in Nonprofit Tech Jess's Path in Public Broadcasting The Importance of Community in Nonprofit Tech Organizing Nonprofit Summits Challenges and Changes in Drupal The Value of Open Source for Nonprofits Comparing Drupal and WordPress Concerns About JavaScript in Content Editing Importance of Accessibility in Content Management Guardrails for Content Editors The Nonprofit Summit: Origins and Evolution Summit Format and Community Building Sponsorship and Event Details Getting Involved in the Nonprofit Drupal Community Conclusion and Final Thoughts Guests Johanna Bates - hanpersand Jess Snyder - jesss

Kun je met een thuistest echt iets zinnigs zeggen over je vruchtbaarheid? Anne praat erover met gynaecoloog Noortje van den Boogaard, die zich zorgen maakt over de opkomst van deze testen. En er is groeiende aandacht voor postacute infectiesyndromen, zoals postcovid: wat zijn de vooruitzichten voor patiënten? Anne spreekt daarover met internist-infectioloog Joost Wiersinga. De warme douche gaat naar Daan Frehe van het platform Ik Spreek Meer Dan.Gerelateerde artikelenPostacute infectiesyndromenThuis je vruchtbaarheid testenVideoconsulten zijn goedkoper en duurzamerCannabisextract verlicht chronische lagerugklachtenExterne link: de warme douche: Ik spreek meer dan: https://ikspreekmeerdan.nl/

(1) Jan Jaap op Vrijdag (2) Eén op vijf kankerpatiënten sterft aan ondervoeding (3) Voor Nico Dijkshoorn is deugdzonde het ontbreekwoord van het jaar (4) Vrijdagquiz (5) Middagjournaal: Nele Van den Broeck

Die junge, engagierte Lehrerin Karla Nowak liebt ihren Beruf und setzt sich bedingungslos für ihre Schüler*innen ein. Als ein Junge aus ihrer Klasse des Diebstahls bezichtigt wird, versucht sie alles, um den Fall aufzuklären. Doch dabei gerät die Lehrerin zwischen die Fronten und macht alles nur immer schlimmer. An der Schule entsteht ein Klima der Angst – Verleumdung, Rassismus und Hass brechen sich bahn. Der Film „Das Lehrerzimmer“ hat den Deutschen Filmpreis (2023) gewonnen und wurde 2024 auch für den Auslands-Oscar nominiert. Jetzt kommt er am Nationaltheater Mannheim auf die Bühne, nach dem Drehbuch von İlker Çatak und Johannes Duncker. Regie führt Adrian Figueroa. Er hat für seine Inszenierung auch eine Gruppe jugendlicher Laiendarsteller*innen auf die Bühne geholt

De trap oplopen of een paar appjes lezen. Een keer douchen of even aan tafel zitten met de kinderen: de allerziekste postcovidpatiënten moeten zorgvuldig wegen waar ze hun energie aan besteden. Ze leven veelal in het donker en komen soms al jaren niet meer buiten. Toch is er weinig aandacht voor deze groep en is een oplossing ver weg. Luister naar wetenschapsredacteur Ellen de Visser en fotograaf Linelle Deunk die vier van deze patiënten hebben gevolgd. Lees het gehele verhaal van Ellen en Linelle hier. Studenten opgelet! De Volkskrant biedt een gratis studentenabonnement aan, af te sluiten via volkskrant.nl/studenten Presentatie: Pieter KlokRedactie: Corinne van Duin, Lotte Grimbergen, Julia van Alem, Jasper Veenstra en Iris BransMontage: Rinkie BartelsSee omnystudio.com/listener for privacy information.

Why a 2025 technology equity guide for nonprofits? Part 1 covers introductions and a deep discussion on the issues of equity in the technology your nonprofit staff use and how they use it. Part 2 delves into questions of funding tech at nonprofits and touches on creating technology tools and applications that can disrupt inequity in our communities, finishing with Q&A.Nonprofit technology is marked by inequities within our organizations and our sector.  You can see this in staffing and processes, and the way technology tools are implemented. Learn to use the free NTEN Equity Guide for Nonprofit Technology as an active and regular part of your strategy discussions and policy review processes and as a resource for evaluation.Join Tristan Penn to learn how nonprofit staff can use technology strategically in racially equitable ways to meet our missions and community needs.Worried about inherent bias and inequity built in to the technology your nonprofit uses? Wondering how to implement strategies and frameworks to make sure your technology use aligns with your organizational values? Navigating technology can be challenging for nonprofits, especially with the inequities in our sector. How can you use technology as strategically and equitably as possible to advance your mission? This session will explore how to use the NTEN Equity Guide as a key part of your strategy and policy reviews. You'll learn how to implement technology in racially equitable ways to better meet community needs. Get a head start on building a more equitable tech future for your organization.Presenter:Tristan Penn is the Equity and Accountability Director at NTEN, where he works to promote, coordinate, and evaluate best practices that support Diversity, Equity, Inclusion, Accessibility, and Liberation. His work focuses on equitable development and capacity building within the nonprofit sector. He manages a staff, community, and board-specific DEI Taskforce, creating long-term work plans and goals for equity initiatives both within NTEN and across the broader community.In his role, Tristan supports and coaches conference speakers and course faculty on creating equitable presentations and manages an annual community survey to gather demographic data and assess customer satisfaction and goal alignment. He is also responsible for designing and implementing audit processes to evaluate the staff, board, and volunteer policies outlined in NTEN's Equity Commitment, and for developing appropriate methodologies to measure the impact of NTEN's equity efforts. _______________________________Start a conversation :) Register to attend a webinar in real time, and find all past transcripts at https://communityit.com/webinars/ email Carolyn at cwoodard@communityit.com on LinkedIn Thanks for listening.

Anne de Jong en Nadia van der Vlies hebben elf jaar lang met succes samengewerkt. Ze bouwden NONONS op tot een bloeiend bedrijf met vijftig medewerkers, vijf panden en tweehonderd klanten. Nu gaan hun wegen scheiden. Hoe pak je zo'n zakelijke scheiding goed aan? En wat zijn de lessen die zij in al die jaren hebben geleerd over samenwerken? In deze aflevering zijn Anne de Jong en Nadia van der Vlies te gast. Anne is oprichter van NONONS en begon zestien jaar geleden met het ontwikkelen van praktische coachopleidingen en -trainingen. Ze startte omdat ze de coachwereld te zweverig vond en geloofde dat het beter kon. Elf jaar geleden werd Nadia haar businesspartner. Nadia komt uit sales en marketing en heeft samen met Anne NONONS uitgebouwd tot een organisatie waar leiderschapsontwikkeling centraal staat. Nu gaat Anne verder met haar nieuwe bedrijf De Relatiecoach, terwijl Nadia NONONS voortzet als directeur. In dit gesprek delen ze openhartig hoe ze deze scheiding aanpakken en wat ze hebben geleerd over succesvol samenwerken.De belangrijkste gespreksonderwerpen Waarom Anne en Nadia na elf jaar uit elkaar gaan en hoe dit proces verliep De rol van eerlijkheid en kwetsbaarheid in een zakelijke relatie Hoe ze financiële problemen overleefden door elkaar echt te leren kennen Het belang van elkaars talenten zien, waarderen en op een podium zetten Vrouwelijk leiderschap: verbinden, empathie en tegelijk duidelijkheid en moed Waarom investeren in je relatie met je compagnon net zo belangrijk is als andere bedrijfsinvesteringen De cultuur van NONONS: practice what you preach en eerlijkheid als veiligheid Hoe Anne haar missie vervolgt met De Relatiecoach: liefde is te leren Wat Nadia vasthoudt en mogelijk verandert als zij NONONS voortzet Hun definitie van succes: niet omzet, maar een leuk bedrijf met fijne mensen Relevante links en bronnen Website NONONS: nonons.nl Website De Relatiecoach: derelatiecoach.nl Boek No-nonsense leidinggeven van Nadia van der Vlies Boek Sorry, schatje van Anne de Jong LinkedIn-profiel Anne de Jong LinkedIn-profiel Nadia van der VliesIs jouw marketing klaar voor 2026? AI verandert de manier waarop kopers bedrijven vinden, en de meeste bedrijven zijn hier absoluut niet op voorbereid. Doe het gratis assessment (kost je nog geen 3 minuten), ontvang een persoonlijke scorecard met concrete acties, en krijg een goed beeld van waar jij omzet misloopt.

Why a 2025 technology equity guide for nonprofits? Part 1 covers introductions and a deep discussion on the issues of equity in the technology your nonprofit staff use and how they use it. Part 2 delves into questions of funding tech at nonprofits and touches on creating technology tools and applications that can disrupt inequity in our communities, finishing with Q&A.Nonprofit technology is marked by inequities within our organizations and our sector.  You can see this in staffing and processes, and the way technology tools are implemented. Learn to use the free NTEN Equity Guide for Nonprofit Technology as an active and regular part of your strategy discussions and policy review processes and as a resource for evaluation.Join Tristan Penn to learn how nonprofit staff can use technology strategically in racially equitable ways to meet our missions and community needs.Worried about inherent bias and inequity built in to the technology your nonprofit uses? Wondering how to implement strategies and frameworks to make sure your technology use aligns with your organizational values? Navigating technology can be challenging for nonprofits, especially with the inequities in our sector. How can you use technology as strategically and equitably as possible to advance your mission? This session will explore how to use the NTEN Equity Guide as a key part of your strategy and policy reviews. You'll learn how to implement technology in racially equitable ways to better meet community needs. Get a head start on building a more equitable tech future for your organization.Presenter:Tristan Penn is the Equity and Accountability Director at NTEN, where he works to promote, coordinate, and evaluate best practices that support Diversity, Equity, Inclusion, Accessibility, and Liberation. His work focuses on equitable development and capacity building within the nonprofit sector. He manages a staff, community, and board-specific DEI Taskforce, creating long-term work plans and goals for equity initiatives both within NTEN and across the broader community.In his role, Tristan supports and coaches conference speakers and course faculty on creating equitable presentations and manages an annual community survey to gather demographic data and assess customer satisfaction and goal alignment. He is also responsible for designing and implementing audit processes to evaluate the staff, board, and volunteer policies outlined in NTEN's Equity Commitment, and for developing appropriate methodologies to measure the impact of NTEN's equity efforts. _______________________________Start a conversation :) Register to attend a webinar in real time, and find all past transcripts at https://communityit.com/webinars/ email Carolyn at cwoodard@communityit.com on LinkedIn Thanks for listening.

Tenenberg, Miron www.deutschlandfunkkultur.de, Aus der jüdischen Welt

Met vandaag: Hoeveel kinderen uit Gaza hebben acute medische zorg nodig? | Laatste Tweede Kamer debat voor de verkiezingen | Waarom wil Meta haar algoritme niet aanpassen? | De rijke historie van vrouwen op zee | Presentatie: Lucella Carasso.  

Er komt uit een onverwachte hoek kritiek op de pensioenhervormingen van de regering De Wever. Kom op Tegen Kanker bij Knack reageert scherp op de pensioenmalus die duizenden kankerpatiënten hard kan treffen. Trends blijft met grote aandacht de ongerustheid op de obligatiemarkten en de politieke crisis rond de Franse begroting volgen. En we sluiten af met Elon Musk die opeens Oracle-CEO Larry Ellison boven zich zag staan in de ranglijst 'rijkste mens ter wereld'. De hosts vandaag zijn hoofdredacteur Bert Bultinck (Knack) en Stijn Fockedey (Trends). In Trends podcasts vind je alle podcasts van Trends en Trends Z, netjes geordend volgens publicatie.  De redactie van Trends brengt u verschillende podcasts over wat onze wereld en maatschappij beheerst.  Vanuit diverse invalshoeken en met een uitgesproken focus op economie en ondernemingen, op business, personal finance en beleggen.  Onafhankelijk, relevant, telkens constructief en toekomstgericht.  Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

Onze biologische klok bepaalt veel meer dan alleen wanneer we moe worden. Het interne ritme in onze hersenen en cellen stuurt ook hoe we voedsel verteren, hoe ons immuunsysteem reageert en zelfs hoe goed medicijnen werken. Maar in de praktijk houden we daar in de zorg en in de maatschappij nauwelijks rekening mee. Van nachtdiensten tot vaste schooltijden en ziekenhuizen die patiënten midden in de nacht wakker maken: ons natuurlijke ritme raakt uit balans, met grote gevolgen voor gezondheid en herstel. In deze aflevering van BNR Beter spreekt presentator Nina van den Dungen met twee experts: Inês Chaves (Erasmus MC), chronobioloog die onderzoekt hoe te vroeg geboren baby’s hun biologische klok ontwikkelen op de intensive care. Ze laat zien hoe licht-donker-ritmes en de samenstelling van moedermelk invloed hebben op de ontwikkeling van deze kwetsbare kinderen. Dirk Jan Stenvers (Amsterdam UMC), internist-endocrinoloog die onderzoekt hoe slaap, voeding en medicatie in ziekenhuizen beter afgestemd kunnen worden op het ritme van patiënten. Hij werkte mee aan projecten waarin slaap op ziekenhuisafdelingen actief werd verbeterd. Daarnaast hoor je een reportage van verslaggever Stijn Goossens vanaf het festival Lowlands, waar onderzoekers testen hoe slaaptekort en een verstoord ritme de alertheid en prestaties beïnvloeden. Het laat zien dat dezelfde principes gelden voor festivalgangers, nachtwerkers én patiënten in de zorg. Onderwerpen die langskomen in deze aflevering: Het verschil tussen ochtend- en avondmensen en de invloed van licht. Social jetlag: waarom een wekker ons vaak te vroeg uit bed haalt. Hoe nachtwerk en verkeerde eettijden bijdragen aan obesitas en diabetes. Het belang van slaapkwaliteit in ziekenhuizen en simpele interventies die patiënten sneller kunnen laten herstellen. Wat de politiek en maatschappij kunnen doen: van afschaffen van de zomertijd tot flexibelere school- en werktijden. Redactie: Stijn GoossensSee omnystudio.com/listener for privacy information.

Hoeveel kan er veranderen in een half jaar? Meer dan je nu misschien denkt. In deze podcast aflevering deel ik 4 essentiële ingrediënten die je nodig hebt om je eigen plafond te doorbreken, mét voorbeelden uit de praktijk. Luister je mee?

Sander Janssen en Sjoerd Keizer hebben het over de coëfficiëntendomper van AZ, dat verloor van Ilves Tampere (4-3), maar ook over de overwinning van FC Utrecht, NEC, Vitesse, Feyenoord en Liverpool. 00:00 Coëfficiënten-stress: AZ verliest, FC Utrecht wint 09:00 Tengstedt naar Feyenoord 11:30 Vitesse 15:45 NEC 18:15 LiverpoolSee omnystudio.com/listener for privacy information.

Fecke, Britta www.deutschlandfunk.de, Forschung aktuell

Nonprofit Technology Conference Insights: Navigating Change and Building Community Resilience In this special episode of the Nonprofit Newsfeed, Whole Whale's Nick hosts colleagues Axel and Kathleen as they share experiences and insights from the recent Nonprofit Technology Conference (NTC), hosted by NTEN. This premier event for nonprofit technology professionals highlighted the sector's adaptability and resilience in the face of rapid technological and political changes. Main Topics and Guests: NTC Overview: Kathleen introduces NTC as a key event for nonprofit technology, emphasizing its role in networking and understanding sector challenges. Key Takeaways: Axel discusses NTC's focus on adapting to current events, including political and budgetary changes, and the strategic use of technology like AI to enhance nonprofit operations. Critical Insights: Adapting to Change: Both speakers noted the conference's emphasis on addressing immediate challenges facing nonprofits, such as economic and political shifts impacting funding and operations. AI and Technology Integration: The conference underscored AI's growing role in nonprofit strategies, from fundraising to narrative building. Sessions explored how AI tools can be tailored to nonprofit needs, highlighting both opportunities and ethical considerations. Community and Resilience: The speakers emphasized the importance of community and collaboration among nonprofits to build resilience and adapt to ongoing challenges. The conference provided a platform for open dialogue and strategic planning. Reflections and Calls to Action: Building Resilience Together: Kathleen and Axel stress the need for nonprofits to engage in community-driven efforts to navigate uncertainty, urging professionals to attend such events to foster collaboration and innovation. Embracing Technological Tools: The discussion encourages nonprofits to leverage technology strategically, ensuring it aligns with their mission and community needs.

This Week:  #25NTC  We launch our 25NTC coverage with the CEO of NTEN, which hosts the Nonprofit Technology Conference, sharing the numbers and the experience of this year's Conference, earlier this month in Baltimore, Maryland. They're Amy Sample Ward, and … Continue reading →

The Nest welcomes Linette Garcia: actress, influencer, and social media star —- you probably follow her on Instagram @linettestorybook. We talk miami characters, Hispanic households, getting discovered, leftovers, and becoming our grandmothers. 

The nest welcomes actress, comedian, producer, and overall badass, Natalie Birriel, as we talk about Miami Magic and Miami returns. We also talk about things like crying in a McDonald's take-out line, finding your tribe, and the Artists v. Money line we all walk. 

Lucy Lopez, the voice of the 305, and the Nest talk about “plomo,” and what it's like to carry the weight of responsibility, but live and love in the light of familia. You know…nest life! Let's whistle, connect, and add a little Cubaneo to the sazón. 

Join us for some Cuban food, cigars, friendship, Michelin Stars, and new baby talk with the award-winning chef and owner of Ariete Hospitality, Michael Beltran, alongside Nicolas Jimenez, the Cigar guy at El Vecino and so much more!  

Making friends in adulthood can be a challenge, but maybe that's not terrible. Maybe we're just more discerning. Or, maybe to make it easier, we just have to cut through life's built-up static. Trust, intuition, auras— we get into all of it on this episode! Welcome back, friends. 

Making-of · Einstündige Reise an die Produktionsstätten des Hörspiels "Der Zauberberg". Wie lässt sich der voluminöse Roman in ein Radiomanuskript umwandeln? Mit welchen dramaturgischen Mitteln arbeitet der Regisseur? Lassen sich die berühmten Schachtelsätze Thomas Manns überhaupt radiogerecht aufbereiten? Und wie passt der dafür nötige lange Atem zur krankheitsbedingten Kurzatmigkeit der Personen? Valerie Stiegele, Autorin, der Regisseur Ulrich Lampen, Komponist Michael Riessler sowie Konstantin Graudus, Sophie von Kessel, Karina Krawczyk, Felix von Manteuffel u.v.m. geben Einblick in ihre Arbeit am Hörspiel. | Von Roana Brogsitter | Mit Esther Hausmann, Peter Weiß, Joachim Höppner, Helmut Stange | Regie: Christiane Klenz | BR 2000 | Das 10-teilige Hörspiel "Der Zauberberg" finden Sie exklusiv in der ARD Audiothek: https://www.ardaudiothek.de/sendung/thomas-mann-der-zauberberg-das-hoerspiel/13912231/

Confused or overwhelmed by capital campaigns? I've got just the right person for you! In this episode, I welcome Steven Shattuck, Director of Engagement at Capital Campaign Pro and a highly respected thought leader in the nonprofit sector. Steven shares his perspectives on the 2024 Capital Campaign Benchmark Report findings, the balance between heart and data in fundraising, and how nonprofits of all sizes can achieve their capital campaign goals. From the role of board support to the power of feasibility studies, Steven provides actionable insights into building a campaign that not only raises funds but strengthens an organization's mission and community impact.Key Topics Covered:Balancing digital strategy with donor relationships in capital campaignsThe 2024 capital campaign success rate and factors driving higher achievementsThe evolving role of boards and diverse donors in campaign successEffective use of feasibility studies and data in campaign planningMaintaining momentum during multi-year campaigns and keeping donors engagedAbout Steven ShattuckSteven Shattuck is the Director of Engagement at Capital Campaign Pro. A frequent webinar presenter and conference speaker in the nonprofit sector, he has over 18 years of experience advising nonprofits on donor communications, data management, and digital content.He is the author of Robots Make Bad Fundraisers – How Nonprofits Can Maintain the Heart in the Digital Age, published by Bold and Bright Media (2020), and a contributor to Fundraising Principles and Practice: Second Edition.Steven has contributed content to the National Council of Nonprofits, AFP, Advancing Philanthropy, NTEN and Nonprofit Hub, and has spoken at AFP ICON, NAYDO, Cause Camp, ADRP, the Nonprofit Storytelling Conference, and Planet Philanthropy to name a few.Recipient of the David Letterman Scholarship, Steven graduated with honors from Ball State University in 2006 with a degree in Telecommunications and Creative Writing. He resides in Indianapolis with his wife, son and daughter.Links:LinkedIn: Steven ShattuckLatest Research: The State of Capital Campaigns in 2024This Episode Sponsored By Neon One:Convincing your board to invest in nonprofit tech can feel like a challenge. That's why Neon One created ‘6 Steps to Sell Your Board on Nonprofit Technology.' This guide walks you through identifying your needs, showing how technology can streamline operations, and tackling common objections—all to make your case confidently. Visit neonone.com/julia to download it free and empower your mission with the right tools.Take my free masterclass: 3 Must-Have Elements of Social Media Content that Converts

Jasmin Pfeiffer gehört zu den spannendsten und talentiertesten Autorinnen, die die deutsche Spielebranche kennt - das findet nicht nur Gastgeber Dom Schott, der Jasmins Spiele kennt und sehr schätzt, sondern auch die ein oder andere Preisverleihung: DigiTales Interactive, das kleine Entwicklerstudio von Jasmin und ihrem Mitstreiter Julian Colbus aus dem Saarland, hat bereits ein paar digitale Pokale in seinen Vitrinen stehen. Höchste Zeit also, Jasmin vor dem Mikrofon über ihre Arbeit, ihren kreativen Prozess und ihre Erfahrungen in der deutschen Spielebranche auszufragen. Neben ihrer Arbeit bei DigiTales Interactive interessiert sich Dom aber auch für Jasmins Leben vor der Spielebranche: Damals nämlich studierte sich an mehreren Universitäten Germanistik und Literaturwissenschaften, um ihre akademische Laufbahn schließlich mit einem Doktor-Titel zu krönen. Beeindruckenderweise überschnitt sich dieses letzte Kapitel mit der Gründung ihres eigenen Spielest udios - ihr fragt euch, wie sie all das unter einen Hut bekommen hat? Auch davon erzählt sie bei OK COOL.

Oranje heeft 2024 afgesloten met 1-1 gelijkspel in en tegen Bosnië. Ronald Koeman stuurde, zoals verwacht, een flink gewijzigd elftal in het veld. Welke speler schurkt nu tegen de basis aan? Etienne Verhoeff bespreekt het met Sjoerd Mossou, die de wedstrijd bekeek in Zenica. ,,Er lagen kansen voor sommige Oranje spelers om zich in te bewijzen. Alleen Noa Lang liet zich zien de eerste helft", analyseert Mossou het duel. ,,De andere spelers schurken niet heel erg tegen een basisplaats aan. Eerlijk gezegd verwachtte ik ook wel zo'n wedstrijd. Er stond niets meer op het spel, de spelers spelen bijna nooit samen en dan nog het decor waarin het duel gespeeld werd. Het zijn factoren die niet meewerken." Verder bespreken ze het nieuws uit Engeland dat Pep Guardiola zijn contract bij Manchester City met een jaar lijkt te verlengen en het nieuwe/oude logo van Ajax. Beluister de hele AD Voetbalpodcast nu via AD.nl, de AD App of jouw favoriete podcastplatform.Support the show: https://krant.nlSee omnystudio.com/listener for privacy information.

Abonneer op deze wekelijkse Podcast voor wekelijkse onderwijzing van het Woord van God om je geloof te bekrachtigen. Support de Podcast via www.riverchurch.nl/giving

Abonneer op deze wekelijkse Podcast voor wekelijkse onderwijzing van het Woord van God om je geloof te bekrachtigen. Support de Podcast via www.riverchurch.nl/giving

On this episode of the RKD Group: Thinkers Podcast, we're excited to sit down with Steve MacLaughlin, an accomplished leader in nonprofit technology, serving as Vice President of Client Success at SJ Consulting and author of the book, “Data Driven Nonprofits.”His thought leadership has been featured in publications like The Washington Post and The Chronicle of Philanthropy, and he's a regular contributor to discussions on how data and innovation shape the future of fundraising. In addition to his industry roles, Steve teaches at Columbia University and has served on the board of NTEN, furthering his commitment to advancing nonprofit impact. Follow RKD Group on LinkedIn, Instagram, and Facebook @RKD GroupFor more information, info.rkdgroup.com/podcast.

When life and death are in the balance, we don't talk about it. Meaning women, we keep a lid on it, to survive. In trying to make sure everything goes alright, we forget to keep the blueprints of the emergency, however. Once urgency passes, we forget the details: birth, divorce, menopause, rearing adolescents, etc etc etc. So how do we make sure our daughters know the way, once we've blazed through the trail at least once, how do we make sure to light the path well? Journal, women, journal. Maybe that's the answer. Write. It. Down. While. It's. Happening.

Karen Graham is the founder of Karen Graham Consulting, with whose "20+ years experience in nonprofit leadership, consulting, and capacity building earned me a broad knowledge of how people, process, and technology can work together to create impact." Karen was part of a team with NTEN and Lehman Associates collaborating on a survey of donor management system (DMS) satisfaction in the nonprofit community. The full survey materials are available at Karen Graham Consulting. Karen joins host Steve Boland to discuss the survey and the implications for organizations working with DMS' - which according to the survey is most nonprofits! Karen shares insights on the issues rated with highest and lowest satisfaction, the most commonly used DMS', and investing in the people operating the systems to understand the highest level of return.

The nest jokes that Jackie is their “Yoda Mom,” because she kind of knows it all, oh wise sage. We all have one of these in our nests— here's to them, all of them, the wise we learn from. 

Woah, dating is hard right now, bruh. Where are the eligible bachelors? This is what the nest discovered when it set itself upon a hunt, to find Victoria Collado (see Season 5, Ep 7) a date. Come on the adventure with us. 

Writer, director, and storyteller, Andi Teran talks to the nest about her life as a writer and life's latest series of plot twists, the ups and downs on her journey toward recovery from a breast cancer diagnosis. Teran is the author of the wonderful coming of age novel, Ana of California, a Latinx version of Anne of Green Gables. On this episode, she talks to us about being born in El Paso, being a Mexi-Texican Yorker en Cali, her early days in NYC, where inspiration was everywhere, and about what it means to choose “visibility over vanity,” and “voice over silence.” 

Clinical social worker, psychoanalyst and parent guidance expert, Erica Komisar, joins the nest to talk about those two paramount moments of child rearing — those first three years, and that second chance (cue horror yelp): adolescence! It's all about Being There, which is the title of one of her books on the subject. 

Jennifer Lucio Vargas, founder of 305 Communications and Events, a Global live and virtual events company, talks to the nest about working for U.S. presidents, and what it was like to start her company. She talks to Vanessa and Nicole about moving back home and taking care of her parents, about the storm that came with losing them and the strength they left in her that will never leave – their mark. If this episode were an emoji it would be an arm flex right next to a giant heart. 

Without the Jewish Deli, we'd be a nation without Pastrami on Rye and Matzo Ball Soup. But, it's so much more than that. It's the stories carried across generations and exile, which the Deli slices, pickles, and serves, that are so important. So what happens when the Deli, as an institution, starts to die? Author David Sax tells us what's at stake in a book he wrote around 15 years ago, but which the nest is revisiting because of a project Vanessa has embarked on with her company, Abre Camino Collective.

Our nests are not just our immediate family, they are also our extended families. Our doctors, our friends, our priests and spiritual guides, our counselors, our aunts and uncles, our honorary aunts and uncles, our teachers, our mentors. On this episode of nest, we cast the nest's net to faith and the community it catches, as a result. 

Join us on an enchanting journey as our guest today, Steven Shattuck, unveils the secrets of capital campaigns, igniting a spark of creativity and innovation. Together, let's embark on a quest to redefine fundraising excellence, guided by wisdom and inspired by possibility. It's time to unlock the hidden treasures that await those who dare to dream big and strive for greatness! Steven Shattuck is the Director of Engagement at Capital Campaign Pro, where his expertise shapes strategies for effective donor communications, data management, and digital content. With over 15 years of experience in the nonprofit sector, Steven is a recognized thought leader renowned for his insightful contributions. He has authored compelling content for esteemed platforms like the National Council of Nonprofits, AFP, Advancing Philanthropy, NTEN, and Nonprofit Hub. As a dynamic presenter, Steven frequently leads webinars and speaks at prestigious conferences, including AFP ICON, NAYDO, Cause Camp, ADRP, the Nonprofit Storytelling Conference, and Planet Philanthropy. Additionally, he is the author of Robots Make Bad Fundraisers: How Nonprofits Can Maintain the Heart in the Digital Age. In this episode, you will be able to: Appreciate the value of research and data in dispelling fundraising myths and guiding decisions. Recognize the importance of board engagement in capital campaign success. Evaluate the effectiveness of pausing a capital campaign amidst external challenges. Learn strategies for maintaining momentum in fundraising efforts during crises. Explore the concept of non-transactional fundraising relationships and their impact on donor engagement. Identify best practices for successful fundraising endeavors in the nonprofit sector. Get all the resources from today's episode here.  Support for this show is brought to you by a beloved nonprofit fundraising platform Givebutter. Our friends at Givebutter really understand what it takes to stay connected to your donors and how to use your CRM to do it. Their free fundraising platform empowers millions of changemakers to raise more, pay less, and give better every single day. To learn more about them, head on over to givebutter.com/mallory Connect with me: Instagram: https://www.instagram.com/whatthefundraising_ Facebook: https://www.facebook.com/whatthefundraising YouTube: https://www.youtube.com/@malloryerickson7946 LinkedIn: https://www.linkedin.com/mallory-erickson-bressler/ Website: malloryerickson.com/podcast Loved this episode? Leave us a review and rating here: https://podcasts.apple.com/us/podcast/what-the-fundraising/id1575421652 If you haven't already, please visit our new What the Fundraising community forum. Check it out and join the conversation at this link. If you're looking to raise more from the right funders, then you'll want to check out my Power Partners Formula, a step-by-step approach to identifying the optimal partners for your organization. This free masterclass offers a great starting point