Podcasts about Dartmouth University

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

To help support sustainable surgical careers, the American College of Surgeons recently released a framework of workplace standards that can be customized by surgical discipline. This episode features Douglas E. Wood, MD, FACS, FRCSEd, Vice-Chair of the ACS Board of Regents, and Philip R. Wolinsky, MD, FACS, ACS Regent, discussing the standards, as well as new resources on surgeon unionization.   Talk about the podcast on social media using the hashtag #HouseofSurgery Douglas E. Wood, MD, FACS, FRCSEd, is the Henry N. Harkins Professor and Chair of the Department of Surgery at the University of Washington in Seattle Philip R. Wolinsky, MD, FACS, is the Division Chief of orthopaedic trauma and a professor of orthopaedics at Dartmouth University in Lebanon, New Hampshire   Copyright © 2026 by the American College of Surgeons (ACS). All rights reserved.   The contents of this podcast may be cited in academic publications but otherwise may not be reproduced, disseminated, or transmitted in any form by any means without the express written permission of ACS. These materials may not be resold nor used to create revenue-generating content by any entity other than the ACS without the express written permission of the ACS. The contents of these materials are strictly prohibited from being uploaded, shared, or incorporated in any third-party applications, platforms, software, or websites without prior written authorization from the ACS. This restriction explicitly includes, but is not limited to, the integration of ACS content into tools leveraging artificial intelligence (AI), machine learning, large language models, or generative AI technologies and infrastructures. 

Artificial Intelligence, or AI, is all the buzz right now. It's come on the scene quickly, and so many are enamored with what it can do. For those of us who have engaged with AI through the growing number of apps that are out there, we are generating songs, videos, images, and even text in literally a split second, and what we see is so amazing that it can draw us in just as quickly as it responds to our prompts. Dartmouth University professor Scott Anthony has been watching his students to discern what they're feeling about a future saturated with AI. In an article in Fortune Magazine, titled “They'll lose their humanity: the professor says he's surprised just how scared his Gen Z students are of AI”, Anthony says he's noticing that his students fear losing their critical thinking skills to the AI Machine. The late media philosopher Marshall McLuhan saw this coming. He said this, “We shape our tools and then our tools shape us.” Parents, exercise caution in how you embrace AI in your life and home. 

"AI is going to be as profound as fire or electricity. Even if that's one-millionth true, we have to take it seriously." In this episode of Inside the GMAT, GMAC Zach sits down with David Marchick, Dean of the Kogod School of Business at American University, to explore how business education is being reshaped by AI, career pivots, and the skills that truly matter over a lifetime. Marchick reflects on his unconventional career path and how those experiences shape his student-first approach to leadership. He explains why "psychic income," not just financial return, drives his work in higher education, and why helping students experiment, fail, and grow outside the classroom is just as important as mastering core business fundamentals. A major focus of the conversation is Kogod's rapid and award-winning integration of artificial intelligence into every aspect of the business school—from curriculum and faculty research to operations and student learning. Marchick shares how Kogod moved quickly to embed AI literacy across disciplines, partnered with tools like Perplexity, and created a culture where experimentation with emerging technology is encouraged rather than feared. The discussion also tackles broader questions facing prospective students: how AI is changing leadership, why business degrees still matter in a non-linear career world, and how graduate education can empower creatives, career switchers, and non-traditional students to reinvent themselves. Marchick closes with advice for ambitious young professionals weighing business school, urging them to find the overlap between what they love, what they're good at, and where they're willing to keep learning—and relearning—over time. About David Marchick: David Marchick serves as Dean of the Kogod School of Business at American University. In this role, he leads the school's work to support more than 2,000 students and offer more than two dozen undergraduate and graduate degree and certification programs. He previously was an Adjunct Professor at the Tuck School of Business at Dartmouth University.  Since Marchick took on the role of Dean in August 2022, the Kogod School of Business has unveiled major initiatives in sustainability, AI and entrepreneurship; raised more than the previous 10 years combined; attracted its largest-ever first-year undergraduate class; and almost doubled the number of endowed chairs for the school. Under Marchick's leadership, Kogod faculty and staff developed and implemented what Poets & Quants called "the most consequential AI transformation in business education." Helpful links: The Kogod School of Business: https://kogod.american.edu/ AU's Institute for Applied Artificial Intelligence: https://kogod.american.edu/iaai Register for the GMAT: https://www.mba.com/exams/executive-assessment/register Chapters: 00:00 Introduction and Personal Reflections 02:29 The Evolution of Business Education 05:35 AI's Impact on Business Schools 08:30 The Importance of Communication Skills 11:35 The Changing Landscape of Graduate Education 14:10 Integrating AI into the Curriculum 17:20 Real-World Applications of AI in Education 20:22 Preparing for the Future of Work 23:15 Advice for Aspiring Business Students 26:11 Future Initiatives at Kogod School of Business

ChatGPT, the AI chatbot developed by OpenAI, was the fastest growing app in history. But this achievement, as sudden and remarkable as it might seem, was simply the most recent chapter in a fascinating story that has been unfolding for almost seven decades. This lecture explores the full history of the relationship between AI and work, and how economists have tried to make sense of it. It's a journey that begins with a remarkable gathering of minds in a non-descript mathematics department at Dartmouth University in 1956 and ends with the technological convulsions that we see around us today.This lecture was recorded by Daniel Susskind on the 13th of January 2026 at Bernard's Inn Hall, LondonDr Daniel Susskind is a writer and economist. He explores the impact of technology, and particularly AI, on work and society. He is a Research Professor at King's College London, a Senior Research Associate at the Institute for Ethics in AI at Oxford University, a Digital Fellow at the Stanford Digital Economy Lab, and an Associate Member of the Economics Department at Oxford University.  His new book, Growth: A Reckoning (2024), was chosen by President Obama as one of his ‘Favourite Books of 2024' and was a runner-up for the Financial Times Business Book of the Year 2024. He is also the author of A World Without Work (2020), described by The New York Times as "required reading for any potential presidential candidate thinking about the economy of the future” and a runner-up for the Financial Times Business Book of the Year 2020, and co-author of the best-selling book, The Future of the Professions (2015). His TED Talk, on the future of work, has been viewed more than 1.6 million times. He is currently working on his next book, What Should Our Children Do? How to Flourish in the Age of AI.  Previously he worked in various roles in the British Government – in the Prime Minister's Strategy Unit, in the Policy Unit in 10 Downing Street, and in the Cabinet Office. He was a Kennedy Scholar at Harvard UniversityThe transcript of the lecture is available from the Gresham College website: https://www.gresham.ac.uk/watch-now/economics-aiGresham College has offered free public lectures for over 400 years, thanks to the generosity of our supporters. There are currently over 2,500 lectures free to access. We believe that everyone should have the opportunity to learn from some of the greatest minds. To support Gresham College's mission, please consider making a donation: https://www.gresham.ac.uk/get-involved/support-us/make-donation/donate-today Website:  https://gresham.ac.ukX: https://x.com/GreshamCollegeFacebook: https://facebook.com/greshamcollegeInstagram: https://instagram.com/greshamcollegeBluesky: https://bsky.app/profile/greshamcollege.bsky.social TikTok: https://www.tiktok.com/@greshamcollegeSupport Us: https://www.gresham.ac.uk/get-involved/support-us/make-donation/donate-todaySupport the show

In this episode of Health on the Line, Matthew Taylor speaks with Al Mulley, professor of medicine and professor of health policy clinical practice at Dartmouth University, where he has led a programme dedicated to forging partnerships around the world to build the capabilities essential to achieving sustainable healthcare economies. Together, they discuss the issue of variation in both performance and activity within the healthcare system, emphasising that decision quality, meaning the thoughtful consideration of options, outcomes and patient preferences, is essential for building sustainable neighbourhood health systems. Drawing on his past experience, Mulley also shares a model of primary care that prioritises relational skills and listening capacity over traditional clinical hierarchies. In the context of the NHS's push to implement neighbourhood health, he stresses the importance of cultural context and cultural intelligence, as well as emotional and social intelligence in clinical decision making. We also hear from Heather Moorhead, director of the Northern Ireland Confederation for Health and Social Care (NICON), to hear about the challenges our members are facing in Northern Ireland and what NICON is doing to support them. Health on the Line is an NHS Confederation podcast, produced by HealthCommsPlus. Hosted on Acast. See acast.com/privacy for more information.

Hasan Piker was scheduled to debate Charlie Kirk at Dartmouth University later this month, a left-vs-right, Vidal-vs-Buckley for the streaming age. In the wake of Kirk's shocking death, Piker wants to continue to be clear about who Kirk was, what he stood for, and the reactionary political project he was working to advance. Guest: Hasan Piker, Twitch streamer and left-wing political commentator.  Want more What Next? Subscribe to Slate Plus to access ad-free listening to the whole What Next family and across all your favorite Slate podcasts. Subscribe today on Apple Podcasts by clicking “Try Free” at the top of our show page. Sign up now at slate.com/whatnextplus to get access wherever you listen. Podcast production by Elena Schwartz, Paige Osburn, Anna Phillips, Madeline Ducharme, and Rob Gunther.  Learn more about your ad choices. Visit megaphone.fm/adchoices

Hasan Piker was scheduled to debate Charlie Kirk at Dartmouth University later this month, a left-vs-right, Vidal-vs-Buckley for the streaming age. In the wake of Kirk's shocking death, Piker wants to continue to be clear about who Kirk was, what he stood for, and the reactionary political project he was working to advance. Guest: Hasan Piker, Twitch streamer and left-wing political commentator.  Want more What Next? Subscribe to Slate Plus to access ad-free listening to the whole What Next family and across all your favorite Slate podcasts. Subscribe today on Apple Podcasts by clicking “Try Free” at the top of our show page. Sign up now at slate.com/whatnextplus to get access wherever you listen. Podcast production by Elena Schwartz, Paige Osburn, Anna Phillips, Madeline Ducharme, and Rob Gunther.  Learn more about your ad choices. Visit megaphone.fm/adchoices

Hasan Piker was scheduled to debate Charlie Kirk at Dartmouth University later this month, a left-vs-right, Vidal-vs-Buckley for the streaming age. In the wake of Kirk's shocking death, Piker wants to continue to be clear about who Kirk was, what he stood for, and the reactionary political project he was working to advance. Guest: Hasan Piker, Twitch streamer and left-wing political commentator.  Want more What Next? Subscribe to Slate Plus to access ad-free listening to the whole What Next family and across all your favorite Slate podcasts. Subscribe today on Apple Podcasts by clicking “Try Free” at the top of our show page. Sign up now at slate.com/whatnextplus to get access wherever you listen. Podcast production by Elena Schwartz, Paige Osburn, Anna Phillips, Madeline Ducharme, and Rob Gunther.  Learn more about your ad choices. Visit megaphone.fm/adchoices

Hasan Piker was scheduled to debate Charlie Kirk at Dartmouth University later this month, a left-vs-right, Vidal-vs-Buckley for the streaming age. In the wake of Kirk's shocking death, Piker wants to continue to be clear about who Kirk was, what he stood for, and the reactionary political project he was working to advance. Guest: Hasan Piker, Twitch streamer and left-wing political commentator.  Want more What Next? Subscribe to Slate Plus to access ad-free listening to the whole What Next family and across all your favorite Slate podcasts. Subscribe today on Apple Podcasts by clicking “Try Free” at the top of our show page. Sign up now at slate.com/whatnextplus to get access wherever you listen. Podcast production by Elena Schwartz, Paige Osburn, Anna Phillips, Madeline Ducharme, and Rob Gunther.  Learn more about your ad choices. Visit megaphone.fm/adchoices

Claim your complimentary gift of my exclusive mini weight care guide today!Link: Weight Care Guide — Dr. Francavilla Show (thedrfrancavillashow.com)What if pregnancy wasn't treated like a pause button on a woman's health?What if those nine months weren't just about waiting for a baby but also about real support, smart guidance, and evidence-based care that actually centers the person who's pregnant?That's the conversation we're having today.Pregnancy often gets sidelined in women's health. There's so much focus on fertility and postpartum, but what about the time in between? It matters. A lot.In this episode, we dig into:Why weight during pregnancy isn't something to avoid talking aboutHow we can rethink nutrition without shame or stressWhat to do when the usual guidance is missingSafe ways to stay active while pregnantThe truth about pregnancy food “rules”How clinicians who aren't OBs can still support patients wellMy guest, Dr. Kimberley Sampson, is a board-certified OB/GYN who's also certified in lifestyle and obesity medicine. She's the chair of OB/GYN at Southwestern Vermont Medical Center, teaches at Dartmouth University, and serves as VP of the New England Obesity Society. She brings both clinical expertise and compassion to the table—and she's not afraid to challenge outdated norms.If you've ever felt like pregnancy care forgets about the actual person going through it—you're going to want to hear this.Tune in now and let's talk about what better care during pregnancy really looks like.Connect with me:Instagram: doctorfrancavillaFacebook: Help Your Patients Lose Weight with Dr. FrancavillaWebsite: Dr. Francavilla ShowYoutube: The Doctor Francavilla ShowGLP Strong: glpstrong.com

In the final episode of Season 4, we discuss the science of consciousness and what it reveals about life on our planet, life in our universe and life beyond death. We start with Dr. Eben Alexander III, a Harvard trained neurosurgeon who had a remarkable Near-Death Experience after falling into a coma due to bacterial meningitis. From there, we discuss how consciousness might be a fundamental property of the universe with Dr. Gregory Matloff, professor of physics at New York City College of Technology. Next, we interview Dr. Avi Loeb, professor of science at Harvard University, who is leading the charge in the search for extraterrestrial intelligence and extraterrestrial technology near Earth. Finally, we spoke with Dr. James Bernat, professor of neurology at Dartmouth University, who was instrumental in developing the medical definition of brain death that has been adopted by legislatures and physicians all around the world. Featured Guests (in order of appearance): Dr. Eben Alexander III Dr. Gregory Matloff Dr. Avi Loeb Dr. James Bernat

Longtime listeners have heard Sarah and Matthew talk about ideas like “ecosystem disruption” and “adoption chain risk” and “value architecture,” all of which stem from the works of Ron Adner. Ron is a researcher, strategist, and professor at the Tuck School of Business at Dartmouth University, and the author of two books, The Wide Lens and Winning the Right Game, both of which have been influential at Tenacious. So this week, we're going straight to the source as Matthew sits down with Ron for a wide ranging discussion of how fundamental business strategy has changed in recent decades, and how agtech companies and investors can learn lessons from other sectors to inform their business models, go-to-market strategies, and the very way they understand the spaces where they play. For more information and resources, visit our website. The information in this post is not investment advice or a recommendation to invest. It is general information only and does not take into account your investment objectives, financial situation or needs. Before making an investment decision you should seek financial advice from a professional financial adviser. Whilst we believe the information is correct, we provide no warranty of accuracy, reliability or completeness.

Would you open your heart to a bot? Tell it all your problems? Look to a piece of code, a computer program, for high-quality mental healthcare? Some people have said yes and the results are hard to ignore. Dartmouth University test subjects who sought help from Therabot, a generative AI chatbot, showed a 51% reduction in depression symptoms, 31% for anxiety, 19% for eating disorders. Dr. Nicholas Jacobson, who led the study, says people really bonded with Therabot, called it Thera for short, and would check in with it frequently. But can a bot really provide meaningful advice and therapy if it's not a human being? Are you now interested in Therabot or more likely than ever to stay far away?This episode mentions ELIZA, an early ancestor of Therabot from 1966. You can take Eliza for a spin here.Thank you to all our listeners who support the show as monthly members of Maximum Fun.Check out our I'm Glad You're Here and Depresh Mode merchandise at the brand new merch website MaxFunStore.com!Hey, remember, you're part of Depresh Mode and we want to hear what you want to hear about. What guests and issues would you like to have covered in a future episode? Write us at depreshmode@maximumfun.org.Depresh Mode is on BlueSky, Instagram, Substack, and you can join our Preshies Facebook group. Help is available right away.The National Suicide Prevention Lifeline: 988 or 1-800-273-8255, 1-800-273-TALKCrisis Text Line: Text HOME to 741741.International suicide hotline numbers available here: https://www.opencounseling.com/suicide-hotlines 

Mingwei Huang joins Juliet, Keren, and Sisi to talk about the social and racial dimensions of China's increasing engagement with Africa, with a focus on Huang's research in Johannesburg, South Africa. The discussion is inspired by Mingwei's recent book, Reconfiguring Racial Capitalism: South Africa in the Chinese Century (Duke University Press, 2024).Mingwei Huang is assistant professor of Women's, Gender and Sexuality Studies at Dartmouth University. She is an interdisciplinary scholar of race and migration trained in American studies and gender & sexuality studies. Recommendations:Mingwei:Made in Ethiopia film (2024)Keren:When Life Gives You Tangerines series on NetflixJuliet:Elizabeth Plantan, Wendy Leutert, Austin Strange, Pivoting to Overseas Development: International NGOs' Changing Engagement with China (2025)Thanks for listening! Follow us on BlueSky @beltandroadpod.blsk.social

The 1920s and the 2020s share a special kinship. One hundred years ago, the U.S. was grappling with a mix of growth, technological splendor, and generational anxiety—a familiar cocktail (albeit, from an era where cocktails were illegal). The era's young people felt uniquely besieged by global forces. “My whole generation is restless," F. Scott Fitzgerald wrote in This Side of Paradise. “A new generation dedicated more than the last to the fear of poverty and the worship of success; grown up to find all Gods dead, all wars fought, all faiths in man shaken." America was changing. And change always implies a kind of loss. We were moving toward cars and cities and manufacturing. And that meant we were moving away from horses and farmland and agriculture. And so, in 1930, just months into the Great Depression, Herbert Hoover signed a new piece of legislation to restore farmers to their previous glory. It was a great big tariff—the Smoot-Hawley Tariff. Rather than save the economy, it deepened the depression. Today, the Smoot-Hawley Tariff is one of the most infamous failures in the history of American politics. To suggest that it holds lessons for this moment in history is to state the obvious. Our guest is Douglas Irwin, an economist and historian at Dartmouth University and an expert on the economic debates of the Great Depression. We talk about the economic motivations of the Smoot-Hawley tariff, the congressional debates that shaped it, the president who signed it, and the legacy it left. We talk about the economic instinct to preserve the past—an instinct that has never gone away in American history—and the profound irony, that some efforts to return America to its former glory can have the unintended effect of robbing America of a richer future. If you have questions, observations, or ideas for future episodes, email us at PlainEnglish@Spotify.com. Host: Derek Thompson Guest: Douglas Irwin Producer: Devon Baroldi Learn more about your ad choices. Visit podcastchoices.com/adchoices

Ever wondered how many trail runners are out there? From casual joggers to ultra-marathon enthusiasts, trail running has become an increasingly popular sport. But just how many people are lacing up their trail running shoes and hitting the trails? Mikey Yablong, who currently attends Dartmouth University, co-authored a study aiming to answer this question along with dozens more. You'll be surprised by the numbers. The Study.---- Partners ----Wylder - Host and find Run Clubs, schedule public and private group runsNaked Sports Innovations - the worlds best hydration beltSalt Lake Footshills Trail Races. Salt Lake City, UT - May 31, 2025PATH Projects - My favorite running shorts, Borderlands10 for 10% off.----Borderlands.cc | Instagram----Call RUNMORE649 (786-667-3649). Leave a message for the podcast—hot takes, agreement, anger, or joy.

James Chappel, author of "Golden Years: How Americans Invented and Reinvented Old Age," offers tips for your future. Then, Paul Argenti, Professor of Management and Corporate Communication at the Tuck School of Business at Dartmouth University, discusses what Vail could have done better during the ski patrollers' strike. And, Alejandra Laverde talks about Colombian food available at Encanto Restaurant in Prospector.

The rise of deepfakes—realistic fake videos made with artificial intelligence software—is making it even more difficult to sort fact from fiction.  When this episode originally aired in 2019, 57% of social media news consumers said they expected what they see there to be largely inaccurate. And the public continues to be wary about changes in the digital landscape. In 2023, Pew Research Center found that 52% of U.S. adults said they are more concerned than excited about AI in their everyday lives. In this episode, digital forensics expert Hany Farid—then at Dartmouth University, and now at the University of California, Berkeley—shares how he advises governments and the media on how to meet this growing threat. And he considers the implications for people and societies when we can't necessarily believe what we see. 

The Dartmouth Murders  /// Part 2 /// 779 Part 2 of 2  www.TrueCrimeGarage.comThe 2001 homicides of two Dartmouth College professors completely shocked and rocked Hanover, New Hampshire to it's core.  No one could imagine something like this happening in a town best known for being the home of an elite academic institution.  Half and Susanne Zantop were both loved and very highly respected by students and faculty at the Dartmouth College.  The Zantop's bodies were found on a Saturday evening, inside their home by a friend, who had arrived as an invited dinner guest.  The double homicide investigation that followed was headed up by the New Hampshire Attorney General's office.  This was an “all hands on deck” situation with multiple law enforcement agencies working the case.  The investigation went beyond state lines and tested both the college and the community.   Beer of the Week - Gravel Donuts by Outerbelt Brewing Garage Grade - 4 and a half bottle caps out of 5  Check out “Off The Record” a fun and wild 5 Bottle Caps Garage show available for your listening pleasure on Patreon and Apple Subscription.   Get more from True Crime Garage on Patreonpatreon.com   ‎True Crime Garage: 10 Crimes that left America Speechless on Apple Podcastspodcasts.apple.com

The Dartmouth Murders  /// Part 1 /// 778 Part 1 of 2  www.TrueCrimeGarage.comThe 2001 homicides of two Dartmouth College professors completely shocked and rocked Hanover, New Hampshire to it's core.  No one could imagine something like this happening in a town best known for being the home of an elite academic institution.  Half and Susanne Zantop were both loved and very highly respected by students and faculty at the Dartmouth College.  The Zantop's bodies were found on a Saturday evening, inside their home by a friend, who had arrived as an invited dinner guest.  The double homicide investigation that followed was headed up by the New Hampshire Attorney General's office.  This was an “all hands on deck” situation with multiple law enforcement agencies working the case.  The investigation went beyond state lines and tested both the college and the community.   Beer of the Week - Gravel Donuts by Outerbelt Brewing Garage Grade - 4 and a half bottle caps out of 5  Check out “Off The Record” a fun and wild 5 Bottle Caps Garage show available for your listening pleasure on Patreon and Apple Subscription.  Get more from True Crime Garage on Patreonpatreon.com ‎True Crime Garage: 10 Crimes that left America Speechless on Apple Podcastspodcasts.apple.com

This week on Green Street, Patti & Doug talk about the hazards of pesticides and wildfire smoke. Then Dr. Megan Romano of Dartmouth University talks about how pregnancy can be impacted by endocrine-disrupting chemicals in our air, our water, our food, and the consumer products we buy...impacts that can have life-long consequences for the new baby.

On the latest episode of the Grateful And Full Of Greatness Podcast, host Mark Glicini interviews Devon Wills, current head coach of Harvard women's lacrosse, former pro lacrosse player and hall of famer. Listeners will hear Devon discuss the people that introduced her to lacrosse, what drives her when she's on the field or coaching, and how she overcame some of her lowest moments and reached some of her biggest milestones. To learn more about Devon Wills, visit: https://www.usalacrosse.com/player-profile/devon-wills Devon Wills is a graduate of Dartmouth University and is one of the most-decorated players in U.S. Women's National team history, winning world championships in 2009, 2013, and 2017. She was recently named a member of the National Lacrosse Hall of Fame and in 2014 was drafted by the new York Lizards, becoming the first female drafted in Major League Lacrosse. WHOOP OFFER: FREE BAND + FREE 1ST-MONTH SUBSCRIPTION: https://join.whoop.com/mgpp THORNE OFFER: 25% OFF ALL SUPPLEMENTS: https://www.thorne.com/u/markglicini Listen/Watch on YouTube: https://www.youtube.com/channel/UCZnNdml6HYHdQx48SwmZhWQ Visit Mark Glicini's Website: https://www.markglicini.com/

What does it mean to truly boast in the cross of Christ? Discover how Paul's profound message in Galatians 6 bridges generational language gaps and emphasizes the transformative power of faith. We'll explore the significance of boasting in the cross, address the hypocrisy of demanding actions not followed by oneself, and highlight the true value found in becoming a new creation. This episode unpacks these themes, uniting us as God's chosen people and bringing peace and mercy to all who uphold this standard.In another compelling segment, we delve into the SCAR experiment from Dartmouth University, revealing the profound impact of perceived flaws on self-identity and behavior. We'll draw a powerful metaphor comparing these self-imposed scars to the message of the cross, which declares our inherent worth and purpose. We'll critique the secular pressures that contribute to the mental health crisis and offer the emotional stability found in identifying with the cross. And finally, join us for a spontaneous worship moment, singing "The Goodness of God," and reflecting on His relentless love and faithfulness through a heartfelt prayer.

Conversations with Alexandra Stevenson on "Serving Aces" with co-host Hugues Laverdière talk about Roger Federer and his commencement speech at Dartmouth University, commanding the graduate audience with his timely discussion of life being bigger than a tennis court.  He is now Dr. Roger Federer, with a Doctorate in Humane Letters. Alexandra brings in the Tony Awards to the conversation, discussing the big musical winner, "The Outsiders." Fascinating moments from Alicia Keyes, Jay Z and Hillary Clinton. Ougi discusses the US Open Golf tournament. Alexandra gives Ougi a tutorial on what makes up a grass court - and indeed, takes him back 50 years to Robert Twynam, the venerable Wimbledon groundskeeper.  Grass today is 100 percent rye, something that Alexandra says is noticeably different from her days of playing on fast grass.

Top Psychologists John Gartner and Harry Segal are joined by Dr. John Talmadge, one of the first to have written about Trump's dementia, as they address Trump's fixation on vengeance and peel back the layers of his rapid cognitive decline. Make sure you join us here on Patreon to support our work and gain access to exclusive perks: patreon.com/ReallyAmericanMedia Our site: https://podcasters.spotify.com/pod/show/really-political Subscribe on iTunes: https://podcasts.apple.com/us/podcast/really-political/id1742461616 Subscribe on Spotify: https://open.spotify.com/show/6AEHmPMAqDlLJEbMgXq1iJ Subscribe on Amazon Music: https://music.amazon.com/podcasts/83ca7283-59fb-4cb7-a34b-03c4b0218f29 Subscribe on iHeartRadio: https://www.iheart.com/podcast/269-really-political-169545670/ Welcome to another addition of Shrinking Trump, where we meet each week to present the mounting evidence of Trump's mental decline and early onset dementia. This week was particularly telling for Trump, as he attempts to deal with the reality of his conviction on 34 felony counts. Our guest Dr. Talmadge is a Dartmouth University grad and former clinical professor of psychiatry at the University of Texas. His article from 2015, described Trump as demented, and suffering from malignant narcissism. “Trump's dementia is generally overlooked because of the florid, colorful, and newsworthy nature of his malignant narcissism,” Talmadge wrote. In this episode, Dr. Talmadge explains how Trump's mental deficits and his attempts to conceal them are laid bare in the way he communicates. “With my background, I was struck very quickly by his language, his inability to handle complex ideas, and his difficulty adapting to novel situations,” Dr. Talmadge said. “The fact that he doesn't talk with people, he talks at people, which is called compensating for your deficits.” You are not going to want to miss Dr. Talmadge's diagnosis, in detail, of four of the most significant psychological symptoms that serve as evidence of Trump's mental decline. On today's show, our hosts give us their diagnosis of a pandering, lie-filled, interview the Fox and Friends “B Team” gave to Trump over the weekend. They'll break down Trump's wildest statements from the interview and explain why that kind of unchecked, biased presentation of his lies is so dangerous. “He told lies about the conviction,” Harry said. “They asked him not one question about the charges. Not one question about the substance. They accepted his story that it's all made up.” Our hosts will also examine how Trump's paranoia and malignant narcissism allows him to energize his supporters by creating false threats based on generalities. “He said that there was someone with a machete in a McDonald's,” Dr. Segal said. “It turns out there was once someone with a machete outside of McDonald's. So Trump reads this one little clip, and now suddenly it's an invasion of criminals who are going to chop you to pieces with their machete.” And finally - I hope you'll enjoy this week's segment of Good News, Bad News, where our hosts absolutely rip apart WSJ journal coverage of Biden's mental health, based on statements made by, as Dr. Segal said, “Kevin McCarthy, a pathological liar and psychopath.” Learn more about your ad choices. Visit megaphone.fm/adchoices

Andy Levin is a professor of economics at Dartmouth University and a former senior staffer at the Federal Reserve Board of Governors. Christina Parajon Skinner is a legal scholar at the University of Pennsylvania and formerly was legal counsel to the Bank of England. Andy and Christina have co-authored a new article titled, *Central Bank Undersight: Assessing the Fed's Accountability to Congress,* and they rejoin David on Macro Musings to talk about it. Specifically, they discuss the Fed's power under a constitutional authority, the three sources of Fed undersight, proposals for reform, and more.   Transcript for this week's episode.   Andrew's Twitter: @andrewtlevin Andrew's Dartmouth profile   Christina's Twitter: @CParaSkinner Christina's UPenn profile   David Beckworth's Twitter: @DavidBeckworth Follow us on Twitter: @Macro_Musings   Join the Macro Musings mailing list! Check out our Macro Musings merch!   Related Links:   *Central Bank Undersight: Assessing the Fed's Accountability to Congress* by Andrew Levin and Christina Parajon Skinner   *Andrew Levin on the Costs and Benefits of QE4 and the Future of the Fed's Balance Sheet* by Macro Musings

On today's podcast, a study uncovers secrets of star sand dunes; Europe's Digital Markets Act pushes changes on big internet companies; Dartmouth University's basketball players join a union; what does it mean to ‘take the plunge' followed by a personal stories about moves big and small.

In late January, Reuters reported that “some 70 U.S. cities, including Chicago and Seattle, have passed resolutions on the Israel-Gaza war," with the majority calling for a cease-fire. Several Connecticut city and town councils have considered resolutions calling for an immediate ceasefire in Gaza. Bridgeport passed one of these non-binding agreements in January, Hartford City Council recently rejected a resolution, and Hamden's Town Council is considering one. In New Haven, organizers staged an open hearing for a ceasefire at City Hall on Monday, after they say the Board of Alders "ignored" their requests. Coming up, we discuss the significance of these local resolutions with Eddy Martinez, Connecticut Public breaking news reporter, plus University of Hartford politics and government expert Bilal Sekou, and Dartmouth University professor of government Dr. Nadia Brown. But first, NPR national security correspondent Greg Myre discusses the significance of Sunday's announcement, and the very latest around diplomatic negotiations. GUESTS: Greg Myre: NPR National Security Correspondent Dr. Bilal Sekou: Associate Professor of Politics and Government, University of Hartford Dr. Nadia Brown: Professor of Government, Georgetown University Dr. Emy Matesan: Associate Professor of Government, Wesleyan University Eddy Martinez: General Assignment/Breaking News Reporter, Connecticut Public Christine Squires: President and CEO, Americares Where We Live is available as a podcast on Apple Podcasts, Spotify, Google Podcasts, Amazon Music, TuneIn, Listen Notes, or wherever you get your podcasts. Subscribe and never miss an episode.Support the show: http://wnpr.org/donateSee omnystudio.com/listener for privacy information.

Donald Trump dominates across 14 states and is gearing up for another showdown against President Biden. Also, the men's basketball team at Dartmouth University making a historic vote to unionize after a federal labor board ruled players could be considered employees. Plus, a first-hand look at a new T.S.A. test program for self-screening. And, customers all across the country now voicing their frustrations with the high cost of fast food. 

SJS Hour 1 - Matt Catrillo is not happy the Eagles open in Brazil ..and find out Steve is half Portuguese. Steve also spends a lot of time on the National Labor Relations Board and Dartmouth University. Dartmouth men's basketball is looking to unionize.

In this episode we take a look at the firestorm started at Dartmouth over Leon Black's name being splashed all over the campus after making huge donations to the University. Former and current students have other ideas however.(commercial at 15:52)To contact me:bobbycapucci@protonmail.comsource:https://hyperallergic.com/623741/citing-epstein-ties-dartmouth-community-calls-for-school-to-rename-leon-black-arts-center/

Show Summary In this episode of Admission Straight Talk, host Linda Abraham addresses the concerns of medical school applicants who have not yet received interview invitations. She debunks the myth that not receiving an invitation by Thanksgiving means rejection and shares insights from several admissions directors. She offers tips for both current med school applicants and those preparing for a reapplication.  Show Notes Welcome to the 555th episode of Admissions Straight Talk. Thanks for tuning in. This episode is for those of you who applied this cycle to medical school and haven't received any interview invitations or at least haven't received an interview invitation from your top choice schools. We're also going to discuss a little bit about what you should be doing now –  neither hitting a panic button nor just worrying and chewing your nails – which is preparing for the possibility of a reapplication. Before we dive in, I have two free resources that I'd like to invite you to take advantage of: The Ultimate Guide to Medical School Interview Success and Medical School Applicant Advice: 6 Tips For Success.  Welcome to Admissions Straight Talk. [1:00] If you are a regular listener, you know that during most episodes of Admissions Straight Talk, I interview a guest. Occasionally I give a solo show, but usually I interview a guest and frequently that guest is an admissions directors. I also have many times asked guests who are med school admissions deans or directors, “When do you stop sending out interview invitations?” I started asking this question because many applicants believed incorrectly that if they don't have an interview invitation by Thanksgiving, they are toast. And here we are in the midst of the Christmas and New Year holidays, and if you haven't gotten the invitation by now, are you actually burnt toast? Well, let's hear what five admissions deans and directors have said in response to my question.  The five are:  Roshini Pinto-Powell, the Associate Dean for Admissions at Dartmouth Geisel School of Medicine Paul White, Assistant Dean for Admissions at Johns Hopkins School of Medicine Dr. Kristen Goodell, Associate Dean of Admissions at BU's Chobanian and Avedisian School of Medicine Dr. Michael Ellison, Associate Dean for Admissions at Chicago Medical School at the Rosalind Franklin University Dr. Cynthia Boyd, Associate Dean for Admissions and Recruitment at Rush Medical College Today's episode is a collection of their answers to that question,  “When do you stop sending out interview invitations?” At the end there's a  little commentary from me, but mostly it's admissions directors and their own words. These are admissions directors at top medical programs sharing what you need to know about the interview invitation timeline.  Dr. Roshini Pinto-Powell, Professor of Medicine and Medical Education and Associate Dean of Admissions at the Geisel School of Medicine at Dartmouth University. [4:20] [RPP] So, our process is a rolling process. We do rolling admissions and we continue to send out invitations well into March. And similarly with the waitlist, that's another thing that people worry about. This is a long process, which is why I said I feel sorry for our candidates. It's a long year. It's a long year. Paul White, Assistant Dean for Admissions at Johns Hopkins School of Medicine. [5:09] [PW] Well, when it was in person, the last date would be around the first week of February. With virtual interviews, we literally sometimes invite people three or four days before the interview. I would say at least a week before is ideal. Mid-February to late February, certainly not the day before. Yeah, we want to give a heads-up, but when it was in person because of travel in February, we always did minimally two weeks in advance. The reason I asked this question is because there's this meme out there that if you don't have an interview invitation by T...

In this episode, Doug Noll and I discuss the pain he endured as a child having been born with several disabilities and how he struggled through school until a teacher discovered he could barely see… Doug's life story is one of overcoming, not succumbing to challenges he was faced with… sharing his experience with emotional wounding and deep grief. Doug has taken his experiences and molded them with his purpose for peace. Douglas E. Noll, JD, MA left a successful career as a trial lawyer to become a peacemaker. His calling is to serve humanity, and he executes his calling at many levels. He is an award-winning author, teacher, trainer, and a highly experienced mediator. Doug's work carries him from international work to helping people resolve deep interpersonal and ideological conflicts to training life inmates to be peacemakers and mediators in maximum-security prisons. His fourth book, De-Escalate: How to Calm an Angry Person in 90 Seconds or Less, was published by Beyond Word Publishing in September of 2017. De-Escalate is now in four languages and its second printing. He is the co-founder of Prison of Peace, and creator of the Noll Affect Labeling System. In 2012, Doug was honored by California Lawyer Magazine as California Attorney of the Year.   I am your host, Marci Nettles. I have had a lifetime of opportunities where I had the choice to Breakdown or Breakthrough. It is my hope this Podcast may become your light in the darkness, as you listen to the stories of people I consider “heroes.” Each one had a point where they too had to choose to either Breakdown or Breakthrough! Working from home, with my husband/business partner, helping people around the world find new levels of success in their health and wellness, is part of what makes me tick! If you are open to opportunity, let's connect!    Thank you for listening! Please connect with Doug: DougNoll.com Purchase Doug's Book here: MarciNettles.com/books   Find Marci at marcinettles(.)com Don't forget to claim your FREEBIE from Doug by going to Marcinettles.com/freebies  

RESHARE! Thanks to Paddy Dhanda for having Mark Pesce on his Podcast Superpowers school - we're happy to be sharing here! 

This week's episode is a TARP REPLAY. Andrew re-shares his conversation from August 2021 with University of North Carolina Women's Basketball Head Coach Courtney Banghart. Courtney just kicked off her 5th season at UNC and 17th as a head coach. She's led her team to three consecutive NCAA Tournament appearances, including a trip to the Sweet Sixteen in 2022. Prior to her time at UNC, Courtney was the head coach at Princeton University where she completely transformed the program. In 2015, she led Princeton to a 30-0 season and was named the 2015 Naismith National Coach of the Year. Fortune Magazine also named Courtney one of the World's 50 Greatest Leaders. This conversation is filled with timeless lessons about leadership, coaching, & success — that apply to sports, business, & everyday life. ** NEW EPISODES RETURN JANUARY 4TH **Show Highlights:0:00 - Intro2:19 - Helping others grow3:54 - Courtney's childhood4:41 - Helping others see potential5:53 - Taking career risks6:48 - Thinking about life in chapters9:07 - Building your inner scorecard11:01 - Leading by example11:19 - Blending science & communication14:50 - Staying consistent16:09 - Recruiting a well-rounded team16:59 - Balancing individual needs and team17:55 - Goal-setting process22:05 - Building grit27:13 - Living up to high standards ** Follow Andrew On Social Media **Twitter/X: @andrewhmosesInstagram: @AndrewMoses123Sign up for e-mails to keep up with Andrew's podcast at everybodypullsthetarp.com/newsletter

Rabbi Moshe Leib Gray was a teenage Lubavitch yeshiva student when he found himself in the renowned yeshiva of Gateshead just a year after Gimmel Tammuz. This would not be the last time he'd find himself somewhere unexpected: Never expecting to go on shlichus, today he is the shliach at Dartmouth University. In this podcast he tells us his amazing story and the lessons he learned along the way.

Shari Hubert, Associate Dean of Admissions at Duke University's Fuqua School of Business, discusses what makes the Duke Fuqua MBA unique, the school's admissions process, career opportunities and more. Topics Introduction (0:00) Program Highlights – What Makes the Duke Fuqua Daytime MBA Unique? (6:55) Duke Fuqua MBA Admissions & Scholarships – How to Improve Your Chances? (29:10) Career Opportunities after Duke Fuqua – What to Know & How to Prepare (59:30) About Our Guest Shari Hubert is Associate Dean of Admissions at Duke University's Fuqua School of Business. She has been with Duke for 6 years. Previously, Shari served as Associate Dean of Admissions at Georgetown's McDonough School of Business as well as Director of Recruitment for the Peace Corps. Shari has also worked at Citi, GE, NBC Universal, The Boston Consulting Group and Merck in a variety of recruiting, consulting and marketing roles. Shari graduated from Harvard Business School with an MBA and majored in French at Dartmouth University as an undergraduate. She serves on a number of HBS Alumni Boards, Pyxera's Global Board of Directors and is a Forte Partner Advisory Council Member. Show Notes Duke Fuqua MBA The Fuqua Show on Spotify The Duke MBA Admissions Interview: What to Expect and How to Prepare Touch MBA Episode write-up and snapshot/stats of the Duke Fuqua Daytime MBA:  https://touchmba.com/duke-fuqua-mba-program-admissions-interview-shari-hubert Get free, personalized school selection help at Touch MBA: https://touchmba.com

This week I'm learning about how, in the 1970s, Boston became the poster child for desegregation strife in the North. Professor Matthew Delmont of Dartmouth University shares his insights on the deep structural issues that led to the busing crisis, the role of the media, and how the city's reputation as the "cradle of liberty" led to a fascination with its racial woes.  Plus, I talk about the Phillies.Send us a Text Message.

The American Psychiatry Association defines depression as loss of interest of activities once enjoyed, and that the symptoms must last longer than two weeks before an official diagnosis.   There isn't just one kind of depression and they don't all generate from the same source.    For people that have not experience depression, it is really hard for them to understand. Or they try to related to something that has no relationship to the actual condition.    You can tell they don't know about when they offer responses like, “you just have to get out of yourself.    So this episode is a two-fer. It is for people that have an anxiety condition that may or may not have a side order of depression. You'll need info on what is is and some of the treatment options.   And, if you need a friend or loved one who doesn't connect with what you are experiencing, there are games and simulations that can help them get a glimmer of understanding.   If you need support contact the National Suicide Prevention Lifeline at 1-800-273-8255, the Trevor Project at 1-866-488-7386 or text “START” to 741-741.     Resources Mentioned:    There is a story from New Hampshire Public Radio about a meeting at Dartmouth University with the current and prior Surgeon Generals meeting to talk about the need for ‘stronger communities' to address mental health crisis.    The Verge article about Google shutting down the podcasting app. Option 1 is to move over to the YouTube Music App. Option 2 is to find another podcasting application.   The American Psychiatric Association has information about depression, the various types and some of the treatment options. There is also a short explainer video to help those that take in information visually.   Helpguide.org post on Depression Symptoms and Warning Signs.   Celeste is a game where Madeline journeys up Celeste Mountain with her anxiety. There is an 8-bit version that can be played on the website. The modern version can be found on various playing devices.   Actual Sunlight, a game/narrative about the experience of depression. You also can find it on Google Play, Nintendo, Switch and other gaming platforms   Depression Quest, old school web based HTML journey of depression and discovery.    The Braaains podcast if you want to know more about that tasty organ known as the brain, mental health issues disability representation. The podcast also shows how the topic is reflected in tv, movies and media.    Disclaimer:  Links to other sites are provided for information purposes only and do not constitute endorsements.  Always seek the advice of a qualified health provider with questions you may have regarding a medical or mental health disorder. This blog and podcast is intended for informational and educational purposes only. Nothing in this program is intended to be a substitute for professional psychological, psychiatric or medical advice, diagnosis, or treatment.

In this episode, Professor of Medicine and Medical Education and Associate Dean of Admissions at the Geisel School of Medicine at Dartmouth University explains the draw of the close-knit community at Dartmouth, why the school doesn't send secondaries to applicants with an MCAT below 503, and how to ace Geisel's secondary.  [SHOW SUMMARY] Are you dreaming of becoming a doctor at an Ivy league medical school, one of the best in the country? Do you want to learn how to ace the admissions process at Dartmouth Geisel School of Medicine? Tune in to this episode of Admissions Straight Talk, where I interview Dr. Roshini Pinto-Powell, the Associate Dean for Admissions at Geisel, and get her insider tips on what makes a successful applicant. An interview with Dr. Roshini Pinto-Powell, Associate Dean of Admissions at Geisel and Professor of Medicine. [Show Notes] Welcome to the 530th episode of Admissions Straight Talk. Thanks for joining me today. Are you ready to apply to a dream medical school? Are you competitive at your target programs? Accepted's  Med School Admissions quiz can give you a quick reality check. Complete the quiz, and you'll not only get an assessment, but tips on how to improve your qualifications and your chances of acceptance. Plus, it's all free.  Our guest today is Dr. Roshini Pinto-Powell. Dr. Pinto-Powell grew up and earned her bachelor's degree in chemistry in India. She earned her MD at the Ross School of Medicine. She did two fellowships in infectious disease and returned with her husband to Dartmouth where she actually focused on general internal medicine. She also found that she loved teaching, and today is a professor of medicine and a professor of medical education as well as co-director of On Doctoring at Dartmouth Geisel, Vice Chair of Clinical Affairs at Dartmouth Hitchcock Medical Center, . Aand most importantly for our conversation today, aAssociate dDean of aAdmissions at Geisel.  Dr. Pinto-Powell, welcome to Admissions Straight Talk. [2:08] Thank you. Can you give us an overview of the MD program at Geisel, focusing on its more distinctive elements? [2:17] I think one of the things I'd start off by saying is that Geisel is a small school, relatively. We have 92 students, 90 MD students, two MD/ PhD students, and this is the largest we've ever been. We were a much smaller school, 65 students, until fairly recently, about a decade and a half to two decades ago, and then have grown to 92. I mentioned that because I think that's one of its distinctive elements. It's small enough that in some ways, I would say, we are the “Cheers” of schools where everybody knows your name and everybody's glad you came. And if you ask any of our students or staff or administrators, what is their favorite thing, they will say the sense of community, the sense of feeling like people know you. Our students don't graduate without personally knowing more than 10-15 faculty, have been to their homes, watched their dogs or animals and things like that. I think that makes it just a wonderful place to learn to be a doctor. Sounds like a very close-knit community. [3:35] I believe so. On the website, it mentioned several times that the medical school has a real determination to graduate what they called “the complete physician.” What does that mean, “the complete physician,” and does it tie into the community that you were just talking about? [3:41] It does. It absolutely does. I'm really glad you asked the question because that is our tagline. My silly joke usually is, well, I don't know any medical school in this country or any other that's trying to graduate the incomplete physician. What we mean at Geisel when we talk about the complete physician is somebody who's totally grounded in the foundational science. I think that first point is really relevant and important today. I think we all know that most medical schools have a pass/fail pre-clinical curriculum to stimulate collegi...

Everyone likes to think they've got their finger on the pulse of reality, that they by and large have an accurate perception of the real world. May be not so much...In this 5 Minute Friday Daniel shares a study that took place at Dartmouth University in 1980. The study show the relationship between perception and bias. It's a fascinating study and has implication in manifesting, law of attraction, and virtually every other aspect of life.LINKSGet The Manifesting Study Guide Here: THE ALIGNED SELF COACHING PROGRAM: http://yesdaniel.comFREE VIDEO TRAINING: 5 Mindset Shifts to Up Grade Your Money GameCheckout Daniel's new membership program THE VAULTDANIEL D'NEUVILLE's WEBSITE: http://dneuville.comDaniel's YouTube CHANNELFACEBOOK GROUPSPODCAST LISTENER'S FB COMMUNITYEXTREME GRATITUDE PROJECTBass Slap Intro written and performed by bass player & producer: Miki SantamariaMiki's YouTube Channel: https://www.youtube.com Hosted on Acast. See acast.com/privacy for more information.

Video games are built on creative storytelling and intricate worldbuilding, but what happens when the violence depicted in video games starts to spill over into the real world? Researchers at Dartmouth University have found a link between violence in video games and increased physical aggression in teens and preteens. Game designer Bahiyya Khan says that while violence can be important to video game storytelling, game makers must create responsibly and provide context for players. On the other side, political journalist Josh Ferme argues that video games are art—like books and music—which should never be censored. Listen to the Doha Debates Podcast as they discuss virtual violence, real-life repercussions and the future of video games. Doha Debates podcast is a production of Doha Debates and FP Studios. This episode is hosted by Karen Given. Thoughts on this conversation? Let us know! Follow us everywhere @DohaDebates and join the post-episode discussion in our YouTube comments.

New Guest Expert! On this week's Aftermath, Rebecca speaks with author and historian Dr. Matthew Delmont about the Port Chicago Weapons Disaster. Professor of History at Dartmouth University, Professor Delmont details the humiliating and often dangerous circumstances African American soldiers were forced to endure while defending their own country during WWII. Afterward, Producer Clayton Early and Fact Checker Chris Smith stop by to revisit the verdict. We have merch!Join our Discord!Tell us who you think is to blame at http://thealarmistpodcast.comEmail us at thealarmistpodcast@gmail.comFollow us on Instagram @thealarmistpodcastFollow us on Twitter @alarmistThe Support this show http://supporter.acast.com/alarmist. Hosted on Acast. See acast.com/privacy for more information.

It's February 9th. In 1946, a recently-returned World War II vet by the name of Isaac Woodard is beaten by police, an incident that became a national civil rights rallying cry. Jody, Niki, and Kellie are joined by special guest Matthew Delmont of Dartmouth University to discuss how Black WWII vets were treated when they returned home, and how in many cases their service made them a target. Be sure to check out Matt's book “Half American.” Sign up for our newsletter! We'll be sending out links to all the stuff we recommended later this week. Find out more at thisdaypod.com This Day In Esoteric Political History is a proud member of Radiotopia from PRX. Your support helps foster independent, artist-owned podcasts and award-winning stories. If you want to support the show directly, you can do so on our website: ThisDayPod.com Get in touch if you have any ideas for future topics, or just want to say hello. Our website is thisdaypod.com Follow us on social @thisdaypod Our team: Jacob Feldman, Researcher/Producer; Brittani Brown, Producer; Khawla Nakua, Transcripts; music by Teen Daze and Blue Dot Sessions; Audrey Mardavich is our Executive Producer at Radiotopia

Who brings you to praise? Rumi's great poem of praise to the “you” is to his great friend Shams, and through that friendship, to God.Rumi was a 13th-century Muslim mystic and poet. He left behind a vast body of lyric poetry, metaphysical writings, lectures, and letters, which have influenced Persian, Urdu, and Turkish literature across the centuries.Haleh Liza Gafori is a translator, vocalist, poet, and educator of Persian descent born in New York City. She has sung and translated the poetry of various Persian poets for well over a decade. She is the translator of GOLD (New York Review of Books / NYRB Classics 2022), translations of poems by Rumi, the 13th-century Muslim mystic and poet. Gafori has taught classes at Dartmouth University, Massachusetts College of Liberal Arts, Taos Poetry Festival, and the Omega Institute.Find the transcript for this show at onbeing.org.We're pleased to offer Rumi's poem, and invite you to connect with Poetry Unbound throughout this season.Order your copy of Poetry Unbound: 50 Poems to Open Your World and join us in our vibrant conversational space on Substack.

We're taking a week off so we can prep for the tour and bank some tasty content. But primos will have another episode within the next few days: http://blockedandreported.org/Some tickets are still available:Hanover, NH, Herbert Faulkner West Auditorium in Carpenter Hall at Dartmouth University, FREE UNTICKETED SHOW: 10/22, 5:00 PM at Dartmouth University — with Carole Hooven!Boston, Laugh Boston, 10/24, 8:00 pm: https://wl.seetickets.us/event/Blocked-andReportedPodcast-800pm/506613?afflky=LaughBostonNYC, Village Underground, 10/25, 6:00 pm, sold out but you can apparently get in line, though we don't know how many seats will be available that way: https://www.comedycellar.com/reservation/?showid=1666735200 Arlington, VA, Arlington Cinema and Drafthouse, 10/29, 10:00 pm late show only: https://www.arlingtondrafthouse.com/shows/188752Photo: August in Massachusetts (Jesse) This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.blockedandreported.org/subscribe

In today's episode, we chat with Valeria Aloe, the author of https://www.amazon.com/Uncolonized-Latinas-Transforming-Mindsets-Together/dp/1637308442/ref=sr_1_1?crid=3KU8FLW2NS1OM&keywords=uncolonized+latinos&qid=1645987183&sprefix=uncolo%2Caps%2C1531&sr=8-1 (Uncolonized Latinas; Transforming Our Mindsets And Rising Together. ) Valeria possesses over 20 years of experience in finance, marketing, and business development, she is also a trainer and public speaker.  Valeria was born in Argentina and after getting her Business degree, she came to the US to get her Masters from Dartmouth University. Her grandmothers are her biggest inspiration because of the sacrifices they made. According to Valeria, the Latin American countries and Hispanic culture holds limiting beliefs about who they are and what achievements they can get when they go to the US.  The thesis of the book is for Latinos to become more aware of limiting cultural beliefs that hold them back, and then letting them go.   In her book, Valeria mentions systemic biases and the best way to overcome them is by working on yourself. Not waiting for the system to change, to become responsible for overcoming those limiting beliefs, not being afraid to speak up and ask for what you need to succeed.  Once you  have identified your limiting beliefs, and have started working on yourself, you must take assertive action which involves two steps:  Learning to create your own brand, to bring your full self to the table.  This is about finding your value, understanding what you bring to the table, knowing, knowing what makes you, YOU, and looking to the unique skillset and the values that have to offer.  Creating and finding Allyship. Latinas need to do more by going out there and connecting with allies, and asking for what they need, whether it's asking for sponsorship, getting mentorship,  learning from others, observing what works for those who are non-Latino, navigating the system by learning and expanding your network outside of the Hispanic community.  Valeria's book writing process was new for her, having corporate background which had taught her to think sequentially but when she started writing her book, the creation process was messy and uncomfortable.  She learned that she had to sit and be open to receiving information without trying to put it into categories.  Her publishing company gave her a lot of support by giving writing workshops, coaching from other writers. In conclusion, the advice she would give to creatives is to pay attention to your instincts.  Don't try to silence the intuition that you have, follow the intuition in that messy process. It will guide you to the path that is important for people. As for the allies, offer Latinas help, be willing to lend a hand, to offer guidance,  since they don't speak up and ask for what we need.  To other Latina women, her message is to believe in themselves, to realize the power they have individually and collectively as a community, and not be afraid to bring their full selves to the world because what they have to offer is needed. It matters. It makes a difference. You can connect with Valeria on  LinkedIn: https://www.linkedin.com/in/valeriaaloe/ (Valeria Aloe) Book: https://www.amazon.com/Uncolonized-Latinas-Transforming-Mindsets-Together/dp/1637308442/ref=sr_1_1?crid=3KU8FLW2NS1OM&keywords=uncolonized+latinos&qid=1645987183&sprefix=uncolo%2Caps%2C1531&sr=8-1 (Uncolonized Latinas)     Copyright 2022 Mark Stinson

Russian Air Incompetence, Putin Expert- Why Putin Invaded Now. Why Russia can't take the skies over Ukraine. 16 minutes. Why Putin Chose to Invade Ukraine Now? Was NATO Expansion to Blame? A Chat with William Wohlforth. 36 minutes.   Why Russia can't take the skies over Ukraine https://youtu.be/eXFDc-44YeE 630,066 views Mar 11, 2022 Sandboxx 77K subscribers As experts the world over continue to try to divine why Russia has failed to capture air dominance over Ukraine two weeks into the fighting, stories, pictures and videos of Russian aircraft being downed by Ukraine's military continue to surface. It would seem that popular perceptions of Russia's military—which have been intentionally shaped by Moscow for years—are beginning to unravel as Russian forces pour further into its embattled neighbor.