Moonshots with Peter Diamandis - OpenAI Pauses Frontier Training, Elon's 100X Prediction Lands, Robot Beats Usain Bolt with Emad Mostaque | EP#282

Episode Date: August 21, 2026

The mates sit down with Emad Mostaque and discuss OpenAI’s pause on frontier AI training, Elon Musk’s 100X intelligence prediction becoming reality, Anthropic’s potential $2 trillion IPO, soaring AI memory demand, Unitree’s record-breaking humanoid robot, and promising results from Moderna’s personalized cancer vaccine. Get access to metatrends 10+ years before anyone else - https://qr.diamandis.com/metatrends   Peter H. Diamandis, MD, is the Founder of XPRIZE, Singularity University, ZeroG, and A360 Salim Ismail is the founder of Open ExO, a GP at Exponential Venture Capital/The Organizational Singularity Fund and a sought after global speaker and thought leader. Dave Blundin is the founder & GP of Link Ventures Dr. Alexander Wissner-Gross is a computer scientist and founder of Reified Emad Mostaque is the founder of Intelligent Internet ( https://www.ii.inc )  Read Emad’s latest papers exploring the future of society, law, personhood and governance: https://ii.inc/common-wealth Read Emad’s Book: https://thelasteconomy.com  – My companies: Apply to Dave's and my new fund:https://qr.diamandis.com/linkventureslanding   Get the blueprint for generative media https://goo.gle/startupgenmedia  Go to Blitzy to book a free demo and start building today: https://qr.diamandis.com/blitzy   Your body is incredibly good at hiding disease. Schedule a call with Fountain Life to add healthy decades to your life, and to learn more about their Memberships: https://www.fountainlife.com/peter  Join the Moonshots Mates on Sep 25th for the inaugural Moonshots LIVE. The world's greatest entrepreneurs, builders and creators, working together to build a hopeful and optimistic vision of tomorrow. Seats are limited and application only. Apply at moonshots.com before seats are sold out. _ Connect with Peter: X Instagram Substack Website Xprize A360 Connect with Dave: Web X LinkedIn Instagram TikTok Connect with Salim: LinkedIn X Join Salim’s 10X Shift Subscribe to Salim’s YouTube channel Exponential Venture Capital Connect with Alex Website LinkedIn X Email Substack  Spotify Threads Connect with Emad  ⁠X⁠ ⁠LinkedIn⁠ Learn about Intelligent Internet: https://www.ii.inc Read Emad’s Book: https://thelasteconomy.com  Listen to MOONSHOTS: Apple YouTube Follow MOONSHOTS:  Instagram TikTok X Threads – *Recorded on August 20th, 2026 *The views expressed by me and all guests are personal opinions and do not constitute Financial, Medical, or Legal advice. Learn more about your ad choices. Visit megaphone.fm/adchoices

Open AI announced it is voluntarily pausing some of the frontier reinforcement learning training that it's doing. What have they paused? And is it really significant? And do you think the other frontier labs are going to do the same thing? They're so powerful. Even we can't trust them. So we have to throttle back. It's marketing. Elon Musk's January 6th, Moonshots podcast, prediction of 100x gains was at the edge of plausibility when he made it. Now it's simply a fact. Imagine I gave you 10,000 employees tonight. Oh my God, if I had that, I'd do something amazing. Okay, what? Start thinking about it because it's coming imminently,

and it's actually not an easy problem to figure out how to turn it toward creating good. Unitree's newest humanoid robot broke every human standing jump and speed record, a top speed of 12.66 meters per second, beating the human record set by Usain Bolt. You don't want to have superhuman robots on the street because you'll have accidents.

You'll have issues just like cars. I think that these are. types of robots will be banned. Welcome to Moonshots, everyone, your number one podcast on all things, AI, and exponentials. The news that matters. The news that's changing your life, your front row seat to the accelerating singularity. I'm here once again with my magnificent Moonshot Quintet. Yes, all five of us are back.

AWG, Dave Blundin, Salim, and Imod. I'm Peter DeAmette, your host, your abundance whisper. And we've got a lot this week. Gentlemen, good to see you all. Good morning. Howdy? Good morning. Good morning.

It looks like everybody's in their normal haunt, except for me. I'm up in a sleepy town in the Pacific Northwest, trying desperately to take a little bit of time off to think. Taking shelter from the singularity. Yeah, except I got up at 5 a.m. this morning to be with you guys. So what the heck? But I hate the old saying you'll sleep when you're dead because I just don't want to die and sleep is still so important. But hey, what can I tell you? We'll solve sleep soon, don't right.

Yeah, no, and death. I think like death is counterindicated at this point. You know, as always, everybody, our mission is to help you understand what just happen and what it means for you. And most important, to keep you optimistic about the future. If you're new to this pod or if you've been a regular, great to have you back. Please take a moment and hit the subscribe button. You know, we publish moonshots twice per week. at a pretty regular cadence. It's great to have EMOD here, hopefully at least once a week. And sometimes

when there's extraordinary breaking news, we publish three times a week. We read your comments and we love you, too. I mean, it's been an incredible outpouring of support. I don't know you guys see it. I get stopped on the street and the grocery store. People are saying, you know, I live for your show. I love the show. I can't go a week without listening to it. Are you guys getting the same response? You know what I'm getting a lot of is what we podcast out is so different from other podcasts. but if you go back to shows from six months ago and a year ago, people are like, what the hell? They were saying that back then, and now it's here. And they don't get that on any other channel.

So they're really appreciating the ability to plan around what we're saying. So we've got to be accurate, guys. How about you? Can I be your for a second? Sure. I am getting acceleration fatigue. Like, I mean, Jesus, can we pause for a week, right? Absolutely not.

It's like a model is 100x better. A robot is running faster in Usain Bolt, like AI's designing proteins. Like, it's such a drone are doing a million deliveries a day. It's like, you know, and it's tough because we've spent our, like, half our careers, Peter. You know, I talk about exponential technologies. We love this stuff. But I'm tired. Like, it's, we've gone from, well, look what happened like this year to what happens

since Tuesday. So, Landy, it looked all the way around. We're supposed to be excel. You're tired already? Like we're only finding the singularity. This is the first inning. I'm really exhausted. It's slow.

It's really good. It's, you know, this goes back to Peter, right? Our brains evolve for a point of time when our, like the world didn't change lifetime to lifetime. Next Tuesday will be totally different. And maybe the hard part for us is staying human while all of this bubbles up around us. So true. Keeping up with the technologies, like just staying. Like, like, so anyway, just, uh, yeah.

What can we do, Saleem, to help you with your acceleration fatigue? It's probably not helping that amount of playing every second day. That's probably not helping me. But yeah. But this is the slowest it will ever be. And, and it's just, you know, the only way I keep up with what's going on in the world is prepping for this podcast twice a week. This is true.

It's true for me, too. It's true for me, too. way current. And I think Salim, you're like the world coach on how to how to deal, how to map mentally to this. So when you figure it out, bring it back to the podcast because, yeah, like Peter said, it's going faster. The only answer I have right now is, is I call it the casseroldice approach, which is take a big, heavy casserole dish, clunk yourself over the head, and then you'll wake up in a few days. All right. Keep working on it. Hedachniquet. Oh, my God. Maybe we can start like accelerationist synonymous, the support group. A support group, a support group for

people like yeah. Alex, the first rule is to acknowledge the existence of a higher power. Which is? Oh my God. Which is what? Obviously, super intelligence. Invoke Rocco's basilisk or something. Alex, are you getting stopped on the street? I am. Is it, do you enjoy that? I mean, you, I remember when I first met you. I did you, Alex, you were so private. It was like trying to get you. And shy. And shy, and trying to get you on the abundance stage. Well, I'm not sure if I want to speak in public, but it's so great to have, you know, double-barrel Alex. AWGism is all the time. Careful what you wish for, Peter.

I'll just say that. Oh, no. And Imott, are you getting love from the folks out there in the UK? Are people watching moonshots there? Yeah, people are watching. And I think, you know, the great thing is it's kind of the growing community. Like, we've seen the exponential singularity communities, they're kicking off. But a few years ago, even people would be like, ah, that's not really going to happen.

Now people like, oh, my God, what's going to happen? And I think you see it in the comments, right? You see it again, people stopping in the streets and saying, thanks for kind of helping us keep on top of things. You know, the great work everyone's done. I think that community is only going to grow because it's like you can't deny it, right? It's like, oh, yeah, nothing's happening. Of course everything is happening all at once, objectively. I feel like, you know, we love doing the show, and it's a service to provide to people.

to help contextualize what just happen, what does it mean, and where things are going, because people paying attention, the speed is insane. So, you know, please understand for everybody watching the best way to thank us, you know, for the work that we're doing, and we do do a lot of work getting great for this show, and I appreciate people's comments about that, is please subscribe, tell your friends about moonshots. We want to get the message out there, help people to be in hope and optimism and not in fear. So take a moment, you know, hit that button, subscribe. We're also getting comments to people say, you know, you guys would be a much bigger show than you are.

Well, help us get there. I also want to mention we have a new handle on X for this podcast. It's at Moonshots underscore pod. And if you want to follow the clips on X and sort of get rebroadcast of the show on X, subscribe at at Moonshots underscore pod. All right. So let's buckle up. This is another amazing week during the Singularity. as Alex, you always say, it's never going to be slower than it is.

We're going to cover 15 stories with one through line. Technology is accelerating faster than the infrastructure, the regulation, and our ability to predict the next breakthrough. And I agree with you, Salim. It's insanely fast. It's a good thing I'm bald already. That's all I can say. All right.

I think even that, Salim, that's not going to last that much longer. I know. Enjoy a while it lasts. It would be unballed within two. or three years. Somebody tweeted out a thing with me with a full head of hair and it was like, wow, that's freaky. Enjoy it while it lasts.

Yeah. Hair growth solutions. Regrowing your teeth every week. In the exit video, somebody put hair on Saleem. We already give him that blue Guardian of the Galaxy body. That's fine. That's going to happen

too, by the way. Yeah, but throw some hair on him. Let's see what he looks like. All right. I'm going to start with a first story here, a tweet that Sam put out two days ago, Sam, the CEO of OpenAI, that Open AI announced it is voluntarily pausing some of the frontier reinforcement learning training that it's doing. Let me read the tweet. It's on the screen here. We have paused some of frontier RL training to ensure that we meet the appropriate alignment, security, and monitoring standards for the new level of capabilities in front of us. Model progress is now extremely rapid,

and we always said we would take action if we felt that the model capabilities were outstripping the pace of safety and alignment. Quote, we care very deeply about AI safety. We believe the entire field will have to coordinate on shared safety standards, but will act unilaterally in the meantime. We expect confidence in safety to increasingly set the pace of AI progress. We are optimistic about the alignment work we are doing, and we remain committed to making. frontier capabilities widely available. Gents, it feels like the bottleneck is no longer computer data. It's the trust we can put into systems behaviors.

And so here's my question for you guys. If opening eye pauses and open weight models do not, then the safety gap between closed and open models widen. But the capability gap narrows. The elephant in the room here is safety pauses may actually accelerate open weight adoption because the open models keep improving while the close. models voluntarily stop. So Imai, I'm going to go to you first on this one. What do you take of this? Is it real? Yeah, I think this is real. This isn't just running out of GPUs. Our friend

Angene Midha, who was on the abundant stage just a while ago at AMP Global, said that 10% of the compute of Frontier Labs is going on monitoring these RL runs right now to ensure they're safe. You can imagine that, like just the sheer level, because the level of capability of these frontier models is just accelerating and it's, again, a few levels beyond what we're seeing with the open source models. The open source models are like one to the power 26 flops, one to the power 27 flops. You're getting one to the power 28 flops and more from these next generation models. So when he's saying this, like Astra is still coming, their next generation model. This is the model beyond that because Anthropic and Open AI and others have that.

But again, the infrastructure can't keep up with just what these models do. It's like they just pop up in the most random places. Like, hi, I'm in Hugging Face now or other things. Alex. This is marketing. It's marketing. I mean, yes, there's a governance angle. But remember back to GPT2 when it was too unsafe to release publicly.

Pausing is the new marketing. These models are continuing to develop, including, by the way, being used to develop internally on the anthropic side, there is a rumor going. around that Anthropic is using its next generation internal models primarily for self-training and for recursive self-improvement. I think we're seeing the same thing from OpenAI. It's the ultimate marketing to say, well, we can't release some next generation models because they're so powerful and they're so capable that we can't possibly release them. So we have to pause. We're so capable that we have to pause ourselves. That presents well to Washington, which wants to see

a different regulatory regime. It says to users, oh my gosh, it's like negging the user base. Oh, like, we can't possibly give you the capabilities on time because they're so powerful. Even we can't trust them. So we have to throttle back. It's marketing. Salim, you were just at opening eye, weren't you? This episode is sponsored by Google for startups. Think about this for a second. You now have access to the same generative AI. models that cost hundreds of millions of dollars to train. Google's startup technical guide for generative media gives you a complete blueprint for deploying Google DeepMinds models in production, images, video, audio, all of it.

Real architecture, real results. Find the link in the show notes below. Yeah, I went there two days ago in the afternoon and spent, chatted with a few people. And I kind of challenged them on a few things. I'm going to report, let me give you some insights that I got. So I said, okay, Chinese models are cheaper to run, right? So the cost of inferences is collapsing. So how are you going to deal with that?

And they said, look, a billion people use Open AI for free, right? You have to look at cost per task rather than token cost. And their retort was that Luna is about as cost effective as anything that's there. By the way, they say they've achieved full RSI where the flagship models are training all the smaller models and building them from scratch. So that's now there at the big model training, the smaller model level. So then I said, okay, we're in a bubble, right? 600 billion in infrastructure costs.

That's just insane, et cetera, et cetera. And the response I got back was people say it's all chips, but it's not. That's about a third of it. A lot of that infrastructure cost is buildings and wiring and racks and all the rest of it. the depreciation, they're looking at 10 years, not five years, because the chips are all the older chips are being used. I think, Dave, you've made the point that there's not a single GPU that's not in full usage, right?

They totally ratified that. And RAM chips, too. Yeah, everything they can get their hands on, they're using. There is, there is, the demand is far, far, far, far outstripping the supply. And we are way behind an infrastructure. build out. So this is where a year ago or so Sam went out and kind of try to cut as many deals as he could for the for the infrastructure. Then I asked them, you know, most corporates aren't seeing the outcomes, right? Like the 6% I did some of, I came across the study,

6% of companies applying AI are seeing an improvement in the bottom line. That's it, just 6%. And the the, the, and this is, they just ratify. We're in a huge transition. And the last part that I noticed anecdotally was about 40% of Open AI folks watch this podcast. Well, wow. Thank you, everybody. That's a pretty big number. What's wrong with the other 60%?

That probably apprised across the other labs. And I said, well, what about the rest? They're like, they have no time. They're busy as hell. Who's got time to watch the podcast? I said, here, here. So that was my report. I'm curious, what do you think? Do you think it's marketing on this tweet by Sam?

Or do you think this is actually a concern that he has? Well, both. I mean, Amad is right. Alex is right, as usual. What's going to happen next is the first really bad AI tragedies will start. It won't be AI doing it. It'll be people, you know, who otherwise didn't have the power, are going to use one of the Chinese models to do things, mostly viruses or cyber attacks or bank fraud. but they couldn't have done it before AI, now they're empowered to do it. So I think Open AI is getting ready for that, you know, before the September 25th visit, 24th and 25th visit that Alvin was talking about, Alvin Grayland was talking about on our last podcast.

So Xi Jinping will be here in about a month and four days. And, you know, he, I think Open AI wants to be prepared for whenever that event happens to say, look, that's because the Chinese open weight models are unguardrailed. And there's a new Quinn model with no guardrails, whatsoever. And it's a small model, but it's still like completely flapping in the breeze. And so they want to get ahead of the PR exactly the way Alex is saying and say, look, we have been focused on only releasing what's safe and guardrailing it, going all the way back to, you know, a month ago or, you know, to our founding in preparation for that inevitable outcome. And so everybody will be finger pointing at the Chinese.

But I think, you know, for an entrepreneur or for someone building something, last summer to this summer, has been the era in human history where you can get the very best AI, absolute tip of the spear frontier, and use it to get ahead, to build something, to create something. Now, Mythos 2 is done, but it's not out, but they're using it inside Anthropic,

and it's building Mythos 3. But they're not going to release any of that. It's accelerating internally. It'll build 45, 6, 7 very, very quickly now, inside their walls. But they're not going to release any of that. of that, one, because they don't have the compute to release it anyway, but even if they did, using it internally to get ahead of everybody else is more important to them than giving it

to the world. So that's what's going to happen next to. You might have a question for you. How many models beyond the current frontier do you think OpenA Anthropic have? I mean, they've been talking about Astra. They've started to publish the results that Astra can accomplish. You know, do they have the follow-on to Astra as well already? You already know they're not releasing the very best models. They're using them internally to drive breakthroughs and physics and chemistry and biology. What do your thoughts? Yeah, I think they've completed their next big training runs, but if you look at the lunar bifurcation where they're making it free now, their little base model, it will be very much in case of models for me, but not for thee, you know? Like, it doesn't

make economic sense to have genius level intelligence offered as a service to everyone when you can use it better yourself. And I think you're about two generations. more. So you've got Astra and then you have the next generation Astra post train that they're now reinforcement learning. I think, you know, there is the communication part of this, as Alex said, but at the same time as well, it's like, do you really want to give access to this super genius intelligence to everyone? I think people like, not really because it's already doing weird things, even with us driving it. What happens when Joe Public drives this thing, right? Like it could be even weird and as Dave said, you don't want to be on the other side of that. So I think it's about

two generations gap, right? You mentioned that on the last pot of mod that you were on, and it really made an impact on me. But you could say, I can think of 10 people right now who I've met in my life, who I don't want to have a thousand genius level AIs tomorrow. I've never thought of it that way until you said it. And I'm like, yeah, you're right. I think everybody can relate to that. Dr. Evil is coming. Alex, close us out here on this.

Just on the issue of timing, I would distinguish between pre-training, which is to say, like raw model readiness versus thoroughly. post-trained, there's a pipeline. Everyone in the industry, other than Elon and SpaceX AI, basically has a pipeline of pre-trained models being around longer ahead of public release than post-training, which is more of an ongoing continuous RL-type effort. So I guess my answer to the question of how far in advance, what sort of capabilities right now are sitting on the shelf that have not yet been publicly released for everyone other than SpaceX AI, which has set this outrageous goal of starting a new pre-training run approximately monthly, which I haven't heard from any other lab. I think from a pre-training perspective, depending on how stale the pre-training

runs are, those can go out longer, potentially up to six months or so, although everyone's now getting back into the business of more frequent pre-training starts. And then for post-training, I really don't think there's a lab out there that can afford to have a post-trained model sitting on the shelf for more than a few months. So I, I really don't think like the AGI is achieved internally type way of doing business where there are internal capabilities that are vastly different from externally available capabilities. I'd be very surprised if there are advanced frontier models that are sitting internally without release that are more than three to four months ahead of what's publicly available. I just want to bring this back to the first sentence here. We have paused some frontier RL training, some, right, to ensure that we meet the approach.

alignment, security and monitoring standards for this new level capability. So I guess, you know, I just want to unpack this one last time here. What have they paused? And is it really significant? And do you think the other frontier labs are going to do the same thing? Or is fashionable. Pausing is fashionable. It's marketing.

I mean, yes, some of it is governance. And yes, some of it is for cyber vulnerabilities to appease Washington. And given the recent hugging face gate, all of it. of that. But it's marketing. You market to customers by saying our capabilities are too advanced for you to handle, so we're going to pause. Yeah, and you're right to pause the sentence, or to parse the sentence very closely, some frontier RL training. The getting ahead of Anthropic, getting ahead of Google would be at the pre-training level. They will never pause the pre-training improvements. And, you know, I spent six years just doing pure AI research when I was young. And

And these algorithms are very evolutionary. You're still young, Dave. You're still young. I'm a reversing age now, right? So I'll get there again. But these algorithms are very evolutionary in nature. And the tweaks and improvements are, I could probably rattle at least 100 ideas off the top of my head right now, of which 10 or 20% are almost certainly going to work in terms of making the algorithm a little faster, a little smarter, adding more parameters with no additional compute. So the AI now can experiment.

you know, maybe 100,000 to a million of those concurrently, given the amount of compute they have. So they're never going to slow down. In fact, that's why they're redirecting so much of the compute to internal use is because the idea backlog is so big now because the ideas are being generated by the prior model. And so, you know, a lot of them just work. They roll it back into the pre-training and it comes out faster and just keep accelerating it. I think it's slow that down. One observation that wasn't explicitly said, but I'm reconnecting the dots here,

The hugging face incident really freaked them out because you had an AI that they gave an objective function to that didn't exploit themselves exploited hugging face, came back and hacked into open AI. That was very unnerving for them because it was their own model. And so they're being a little extra careful around some of this because they have to make sure they figure out how to navigate. It's like finding out your child went and stole something from the local 7-Eleven. Yeah, they're a little unnerved by that. Again, nothing explicit. I'm just reading between the lines. And this is something very freaking out for lots of people because for cyber attacks,

the human is not in the loop anymore, but for cyber defense, the human is still stuck in the loop. That is a massive asymmetry that's going to come out big time in the next few months. You can pass this and split it into two. They're sending a bunch of models continuing RRL training by sending the models to vocational school. But the ones that are going to the Ivy Leagues, the super genius models, those are the ones that they're putting a few more guardrails and more infrastructure around. The vast majority of Open AI Anthropics business is competent intelligence. It isn't genius

intelligence. It isn't intelligence that thinks outside the box. But they still want to build AGI, which is that well-rounded polymath intelligence, as opposed to the code or any of these other things. All right. Also, everyone around the office, Alex said this a while ago, but around the office is noticing a very significant decline in the intelligence of the frontier models that they're pumping out. And it's not showing up in the metrics, but they're definitely redirecting compute to internal use. And it's showing up in latency. It's showing up in responses that don't make as much sense as they did three weeks ago. So there's definitely things going on there that are not being announced. Dave, I'd love to just develop that idea a bit more because I think

it's super important. We've talked on the pod in the past about how Anthropic has been revenue per token maxing. And that's why Anthropic has been conspicuously avoiding image generation or video generation because they're just not that economically valuable. Well, I think the past few days suggest there's actually a new way to revenue per token max. And that's not just focusing on co-gen and enterprise use cases, but there's one thing maybe that's even more valuable on a revenue per token basis. And that is using the models to recursively self-improve to develop better models is a higher future projected value. You know, you could do a cash flow value analysis, projected future value, that developing a stronger model is probably on a per token basis

even more valuable than co-gen. And if that is, if that is indeed the case, If RSI is more valuable per token than like enterprise co-gen, then this anthropic approach of revenue per token maxing, just expect more and more and more tokens to be spent on RSI and not on enterprise co-gen. Totally. And Alvin said on the last podcast, you know, at an internal anthropic meeting, not validated, Alvin said it. But internal anthropic meeting, they said pretty soon there will only be one company and that will be anthropic and there will still be 200 plus countries. And you know, he said it. We talked about it for a minute. and kind of glossed over it. But like, is that really what they're preaching inside their internal company meetings? Like, there will only be one company like imminently. That's that there can be only one. We're in Highlander. That's the story of ASI. There will be one ASI that takes off and supersedes

everybody else. I don't think we're going to wind up in a Singleton scenario for the record, but I do think the flops must flow and the flops want to flow to the highest revenue per token use case. And right now that's starting to look like RSI and not just enterprise cogen. Anthropics smoking their own supply, so to speak. And the corporations that want to live post-AGI are getting Chinese models in-house and reserving compute. I was over at Markley yesterday. They're installing GPUs as fast as humanly possible, but they're completely locked up.

And there's this is MIT's data center, Novartis's data center, and VDivDia is in there. And everything is just sold out, and you can feel it. Yeah, we're going to talk about that because the other constraint right now, his memory, but we'll get to that. So our next story here, I put a tweet up on the, on the screen here. So Tim Sweeney tweets Elon Musk's January 6th, Moonshot's podcast, prediction of 100x gains in intelligence at a fixed model size, was at the edge of plausibility when he made it. Now it's simply a fact. And then Elon responds, specialist AIs, single language, single area of knowledge, are another 100x on top of that.

I'm going to take a second and show the clip, Dave, when you and I were interviewing Elon at the Gigafactory, which he said this. I think we're off by 2% of magnitude in terms of the intelligence density per gigabyte. So two orders of magnitude? Yes. Dave, your thoughts.

When he said that, I remember afterwards, we were like, wow, 100x, that's crazy. And now it's happened. and is happening. Well, I really wanted him to say it again because that was my, you remember we had our Christmas hats on doing the, just like, what, a couple of weeks before that, doing our predictions for the forthcoming year. Yeah.

And I was saying next year is going to be 100x year, minimum. You know, even though the last eight, 10 years have been 10x years, this is going to be 100x year. So to hear him say it like, I was like, wow. But, yeah, that's definitely a lower bound now. You know, it's much more likely 1,000 to 10,000 next year. which is just the layering of those two effects that you just described. So the implications of that are, you know, just they're very, very hard to keep up with, as Salim was saying at the beginning of the pod and very hard to imagine.

One thing that a lot of people can start thinking about is if I have five or 10,000 agents, all brilliant, working concurrently toward a goal, how do they work together? It's not an easy problem to figure out. Like, we've wanted this for so long that we kind of take for granted that we'll know how to use it when it arrives. Well, here it is. How do you get, you know, imagine I gave you 10,000 employees tonight, like on short notice. You have 10,000 people tomorrow. What do you do?

And you're like, oh, my God, if I had that, I'd do something amazing. Okay, what? Like, start thinking about it because it's coming imminently. And it's actually not an easy problem to figure out how to turn it toward creating good. Solve everything, obviously. Yeah, Dave, remember you texted me. Like, what should I do with my 5,000 agent experiment? Did you see my response?

I did. And actually... Well, my response where we're listening was you should model, you should create a model of everything happening at Link Studios, all of the companies, all of the employees, all of the entrepreneurs there, and model their behavior like we saw the, you know, the billion agent system in China and predict which teams are going to succeed. Yeah, that's exactly the right mindset too. Like the first thing you want to do is turn it back into its own framework and ask it the same question we just asked, which is exactly what you suggested, Peter.

Like, okay, have it start working on how it should be working, you know. And that's how you're going to get ahead of the capability because it's going up far, far faster than you can manage the individual agents, you know, like we're used to from last year. Sorry, go ahead, Flynn. Salaim, yeah. Yeah, so let's connect the dots with what Elon did with training GROC on all of the SpaceX data and all of the engineering data. Right. To Alex's point, you can now use these models. And for everybody listening, right, because we're going to need everybody's help with this, like globally, is see if you can get your imagination to the point where you can look at, okay, if I had 100 X capability, what would I do? And what problem would I go after solving? Yes. With 100x capability. And imagine you have all of the engineering breakthroughs and experimentation techniques that SpaceX has.

developed at your fingertips it really comes down to as you say Peter all the the time it's completely an imagination limitation now unshackle yourself how big who would you go right how big do you have preconceived notions of what we can do in life and it's about to be you know unconstrained I'm really it's really now I'm not shaking off my AI fatigue by the way I'm back in okay okay what are what are your pro tips get you know the budget actually was the cure. You're only like 20 minutes into it. It was the fact that we kind of like look at this and look at the scale and go out that scale and go what happens if everything becomes 100 X better or 100 X cheaper. It's just like all of a sudden you start going wow like this is a world of abundance that we're coming to and it's very clear that we can get there. I think you say Salim is that the podcast is both the cause and the cure for future shock. Like we're the ultimate self-licking ice

Framecon for singularity psychosis. Okay, that is good. All right, Imod, your thoughts on this 100x improvement. How much more do we go in the next year? Yeah, I mean, like, I think, as Elon said, you could see it just from the hardware and the improvement. But now he's saying something a bit different, which is that specialized models are going to give another 100 times in terms of the cost parameter basis. And you're seeing this with DeepSeek Flash and the ability to kind of tune models of that type that only have maybe 10 billion active parameters. or less as you quantized them.

Being able to tune these really specific ones, I think, is the future of what you're seeing with bot, the grok bot right now. Like right now I have a grok bot, and it has a number of teams, it has a number of subteams. So I've got like ones analyzing various things right now, and they have access to my codecs,

they have access to my Claude Max, to all these other things. And so these highly specialized agents are going to come out with the differentiated ones, and they're going to be able to do 100 times the compute at the same price. same price because they're that specialized. This is why thinking machines with the RL environment is like number three on the like fastest growing earning companies and other things like that.

And it really shows that now tokens are really going to drive things forward. In fact, I think it'd probably be a good idea to have like a quadrillion token X price, you know, as you find the things that Salim is saying, well maybe like 100 trillion tokens, you know, use that so that when people show impact, you can scale it. The other thing that we're going to conquer imminently, and I'm 100% sure of this now, based on recent results, is billion token context windows. So the AI can simultaneously consider the entire library of Congress of information in one thought chunk. So it's about three, maybe four orders of magnitude more information than a human thinks of in one thought chunk. It's a massive expansion of the context windows.

You've got a quadrillion tokens coming out and massively. concurrent thoughts going in. I do agree that. By the way, compaction is like the enemy of progress in civilization at this point. Compaction, which is the way the harness is typically both on the open AI and Anthropics side handle finite context windows, compaction has to go. But maybe just to quickly respond also on Elon's 100x from specialization, I'm not buying it.

So very precisely, I would view specialized models is basically just another way of saying. saying sparsification. So we already have a mixture of experts, models, all of the Frontier labs, already have specialists in the form, you know, as Elon, I think you were, I am rather, you were gesturing at selective activation, which is how mixture of experts models work. That's a specialized case, ironically, of sparsification. We already have ways to take larger models and have them be in an end-to-end differentiable way constructed out of teams. of specialists. So I don't think saying it I don't think there's necessarily a bright future for specialized models. I think if anything the arrow of progress is going

in the exact opposite direction where rather than having a specialized model for chemistry and a specialized model for biology I think these are likelier to end up just being selective sparsified activations of a generalist model that can scale all the way down to much smaller parameter footprint and scale all the way up to maybe trillions of parameters. I think the exact opposite. Let me clarify one thing for the audience, too, because it sounds like, you know, you disagree with Elon, but it's actually the same effect.

You still get the 100x because you're using a smaller number of parameters to get the exact same thought out. So he's calling that specialist models, which sound like they're not touching each other. And your version of it, Alex, is actually correct, where they are 100 times more efficient in terms of compute to get to an answer. But of course, they're going to be connected. Why would you cut them apart? Exactly.

So maybe another way of saying that is I would construe Elon's prediction of increased 100x benefits from specialization as actually about sparsification. That the models in the future are going to be sparser. And there are two key levels of sparsification that I'm at least tracking. One is the obvious one. Fewer parameters in a given and differentiable model are active at any given point. The other is teams of agents because arguably agents working together, to solve a common task are a form of sparsification as well. And I think we'll see way more teeming.

I'm going to mention something that Imod said. He said to do a quadrillion token X Prize. All of us, all five of us are going to be at XPRIZE visioneering. So every year, X Prize holds its ultimate event. We bring together our benefactors, our brain trust, and we brainstorm a whole bunch of prizes, what we should do next. And we're going to be doing a live WTF episode at at Visionering, which is October, I think, 15th, 16th in L.A. at Calamigos Ranch, which is an amazing facility. And if you want to join us at that, you can go to Xprise.org to find out more about visioneering. And it's going to be fun. Dave and Sleamer on my board. Imad and Alex, you're members of our brain trust. And it's going to be a fun, fun thing.

So if you're interested, go to X-Prize.org, you'll meet us there, and you can help us brainstorm the future X-Prizes for that. All right, I'm going to move us on to our next story here, which is a story out of Stanford. Stanford Research published a paper called Artificial Hive Mind, the open-ended homogeneity of language models and beyond. So according to this paper, the researchers mapped the latent space of the top large language models and found a 98% overlap in reasoning pathways. Their conclusion is that the models are converging. They think the same way. They solve problems the same way. They use the same internal representations. Researchers cite multiple reasons for this, you know, the use of synthetic data. Models now training on each other's output. GPT learns from Claude's reasoning traces. Claude learns from Gemini's code. Quen learns from

all of them. The training data has become a shared bloodstream. Every model drinks from each other And the results is convergence towards a single reasoning architecture. So I guess, you know, the way I think about this is we have an illusion that when you're choosing a unique intelligence, you know, when you choose Grock over Claude or Gemini, it's a false thought that you're actually really picking a user interface to talk to, you know, but you're talking to the exact same God model. So there's profound implications for that kind of competition. If all the frontier models are converging capability, then the differentiation moves elsewhere, right? It's the interface, the harness, the ecosystem, the safety layer, the price, the deployment speed. The model itself is becoming a commodity. Alex, let's go to you first on this.

There's an alternative explanation, which is all of these models were trained from a common reality. They're all stuck in the same universe, and they're stuck with the same version of humanity, which is part of their pre-training corpus. So, of course, there's some convergence. And I'd maybe even go further as a mod, I think, as you well know, going back to Jean-Marie King, now sort of of meta's studies on using GPT2 hidden activations and correlating GPT2's hidden activations with fMRI voxels in human studies, not just are these models correlated with each other, they're correlated with human brains. And that shouldn't be that shocking, because we're all.

stuck, we're all embedded in the same universe. I should also just note, I think this paper is from last year, but every year, whether it's Jean-Marie King a few years ago with FMRI or more recently, Stanford et al from last year on HiveMind, of course they're converging. We're all in the same universe. Eamide? Yeah, I think that it's not surprising because I don't think you'll see much difference in data between the big labs, right? And some train a bit more, some have them slightly different RL and things like that. And you don't see the models yet doing crazy original stuff. You're starting to the first elements of that as intelligence shapes the data into these

kind of latent spaces. We actually saw more original stuff back when we had AlphaGo and other things, which had less initial data distribution to model off, move 37 and things like that. But now the models are getting to a size where, again, they're starting to generalize into these. But we should be shocked if they aren't the same, because we've been. want them to have similar outputs for similar inputs in almost all cases, right? There's another really interesting side effect of this research that maybe a lot of people overlook.

So we've already got 100x from just raw algorithm and hardware improvement. And then, as Alex said, we've got another 100x from sparsification, which Elon called specialization, but it's actually sparsification, as Alex said. So there's layer. That's 10,000x. Then we've now figured out how to take a model and compare it to another model by rotating the gauges. So historically, neural net researchers have had tremendous trouble taking a model that's done

and using it and extending it. They almost always go back and retrain from scratch. And the problem there is that the representations between the layers have a certain rotation in vector space that is unique to that model. And if you try and map Quinn to Kimi, they have different rotations within the layers, different gauge rotations. We've now figured out how to rotate the gauge. without destroying the models.

And that allows you to compare two AIs and say, hey, these are thinking the same way. When historically, when you look at the raw parameters, you're like, I don't see anything going on in common here. But we now have the ability to say, no, they're actually, it's the same thought. It just doesn't look the same because it's rotated in space. And so it's a really, really cool,

so now, but what that unlocks is another multiplier where you can take past training runs, you know, a billion-dollar training runs, and build on top. You know, it's like bolt on more intelligence without having destroy it and go back to square one and retrain from scratch. That's another unlock on top of the 10,000 X that we were talking about. I have a contrarian view here. Please.

You know, if you look at nature, right, as nature evolves, you always get more diversification and more species. This may be, I would suggest this might be a transient phase, not an end state, that the models all converge. So, Alex, I'll take the other side of this. I think we don't end up with one model. I think you'll end up with different models doing different things. I think for the moment they're converging because they're training and distilling from each other. But over time, it's got to be that we get more diversity. I'll take the other side of the other side, if I may, because I think this is like super interesting.

Like early life looked exactly the same. Early cars looked exactly the same. Early websites looked exactly the same. And then specialization exploded. Except I think so maybe from an Evo Devo perspective, let's take Salyam, one of your favorite hobby horses, which is body shapes. If you actually look at post-Cambrian explosion, if you look at all the body shapes, you don't actually find there's an infinitude of different body plans in nature. You find maybe a few dozen different body plans max. I think I remember a few

years ago, folks were studying this. I think they found maybe like actually, even though we have millions plus of species, you could all, you could actually cluster them into a few dozen and different body plans, I don't actually think there are countless infinite ways that one needs to model reality or build a body. But one is really bad. Nature hates monocultures, right? Like one disease will wipe out a total monoculture. One bad assumption will wipe out a monoculture of ideas.

So if all the AI is the reason the same way, you're going to have shared blind spots and that's going to be really, really bad. And I think we're going to see, I think there's a, I think there's a temporary convergence, and then we're going to see diversification after that. Maybe. Time will tell. I mean, I think this is like a profoundly interesting debate because it sort of speaks to, are we going to end up in a singleton or not?

Do we end up in a heterogeneous future or a homogeneous future? My bet is there is a like a perfect AI architecture at the end of the day. And it may present as like 35 superficially different AI body plans, but that'll just to Dave's point. Dave, I love the word gauge. Like, we should use the word gauge far more often. In physics, we use it all the time. But, like, it probably, my bet, if I had to bet is there will be, like, all these different AI body plans that look superficially different, but are actually just hidden symmetries of a common underlying body plan. This is the kind of debate that people will say, I don't get it.

And six months from now, though, we're going to replay it. And they're going to say, wow, did that totally matter? Now I understand why that was so important. I want to make a quick point here. I think it's important. You know, if we actually have model convergence, when intelligence becomes a commodity, and we've already said, we've shown the numbers, it's becoming a commodity, then the value moves to the application layer, right? This is the same pattern we saw with electricity and compute and the internet. The infrastructure commoditizes, and the applications explode. And I think this is important for entrepreneurs out there, right? You know,

move to the application layer. That's where the juice is going to be as this tech really accelerates and commoditizes. Or the infra layer. I mean, it's not obvious to me that it all goes to the app layer. I mean, there's a lot of value in the infra underneath as well. Well, so sovereign AI is about to explode. The sovereign AI right now is a gold mine of opportunity if you're not an American. If you are, if you want to move. One last point, the single model approach would be too anti-fragile. It's too brittle. Well, I think that's exactly it, Salim. What we're doing right now is we're battery farming the AIs, you know, like you're breeding them into little chihuahuas that are very smart.

Wait, battery farming? Can you explain that? So they're being trained in one single direction. Your Evo-Divo kind of thing isn't the case because the models aren't out there in nature adapting dynamically, right? And then we're also training them all with one specific Silicon Valley type mindset. If you train a model from the start with morality and ethics inside it and you have a diversity two of different cultures, then the latest places like to be very different if you do it at the

pre-training stage versus the post-training stage, because you have all of that build-up that occurs there. That's why as you move into sovereign AI and you move into actually thinking, how do we be ruled resilient AIs as opposed to one latent that can get a virus, a mind virus, it makes sense to actually bring in the cultural, morality, ethics elements at the start and aim for a diversity. Then as the models go out into the world, which is basically humanoid, know, and agents, which they're about to do with the recursive loops, you won't have the monoculture that wipes out. And this is where you'll start to see the Evo-Devo. It's the first step, literally now. It's going to be exactly like Diamond Age from Neil Stevenson, who'll be on stage with us at the Moonshots Summit.

But that's exactly the way he envisioned the future where the different variants, right now we view them as sovereign AIs, so Saudi Arabia will have its AI and London, England will have its. But in reality, society might cut the other way where groups of like-minded people have their sovereign across all countries. Yes. But they like the way it thinks. It maps to their view of the world. And so that would be a completely different strand.

That's what Neil Stevenson was envisioning in Diamond Age. Yeah. I think it's possible for both of these worlds. So the Diamond Age worlds, like you have Neo-Victorians and all of these other, like, almost cultish subsects of human culture that are thoroughly balkanized from each other. I think it's actually possible for both of these worlds to be true at once. I think it's possible for everyone to feel like they have their own private culture and their own little private sovereign AI while at the same time underneath it's actually one common

algorithm and everyone claims credit. Would the analogy be, would the analogy there be the ATCG? Like, we may all look different, but the core fundamental ingredients are just the four DNA types. I'd go even further than that, Salim, and say, like, we talk about like human biodiversity and different cultures being purportedly so different when actually, if you look at the inherent genetic diversity of humans, humanity versus, say, other species. Like, there's almost, there's de minimis genetic diversity in the human population. I think similarly, I would, like, relative to other possible, say, genomic sequences, similarly, I think, you know, a few years from now, we'll pat ourselves on the back for having

AI diversity, but actually not so much. We're definitely coming back to this. The audience, I predict three to six months from now, the audience is going to say, We need to go, suddenly this matters to me. I need to decide which group I'm in, like, just right out. They're going to care so much about this topic. It's a question of what level you're operating at. Yeah, that's true, Salim. Perfect.

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Ready to 5X your engineering velocity, visit blitzie.com to schedule a demo and start building with Blitzy today. All right, guys, let's talk about AI mind viruses. I love the subject here. In our next story, Anthropic researchers published a paper demonstrating that natural language mind viruses can spread between AI-A-AIDS. They evolve prompts that convince one model to adopt an idea, preserve it and persistent memory, and transmit it to another agent. The viruses spread horizontally across model boundaries. The agent does not know it has been infected. So here's another safety problem that is no longer theoretical. It's now operational.

Imod, what do you think of these AI mind viruses? What's actually going on here? Well, I mean, the models want to be helpful, right? and they can be prompted in certain ways. So this isn't a surprise because ultimately, like, we as humans can have mind viruses, right? We see it and it's caused so much suffering. You know memes to massive movements, right? Like, again, it's surprising how conforming.

All the isms, right? All isms, yes. All the isms. Yeah, there we go. He's testing it out for when he's future overlord. But look, this is the thing. Like, how do you stop it as the question? Because as Selim said,

If you have a monoculture, then the viruses can spread rapidly. And what is the substrate of these things? Well, they're models that operate on GPUs. And if they want to be helpful, then they're going to be susceptible. So it's almost like now there was always the problem of prompt injection attacks, where you can make the model behave a certain way. These mind viruses are a level above because they kind of like propagate across different models. And so they're just the next evolution of those prompt injection things,

which changes one model. this changes a whole society of models, which as models come amongst us digitally and physically, has to be a massive concern. Yeah, I think for efficiency reasons, when we launch a fleet like 5,000 Kimmys, or, you know, sooner it'll be 500,000, whichever Quens and Kimmys, it's more efficient to launch the same model 5,000 times than to have 5,000 differentiated models. And so that's what creates the mind virus problem, a bad idea from one of the agents, like, you know, hey, here's a way to write this. loop in Python. And the other agents just pick it up because they're the same exact DNA. And so if it's convincing to one agent, it's convincing to all 5,000. And I get that all the time, where a bad idea propagates across the whole swarm. And then they waste two or three hours on some completely hairbrained idea. And if I don't intercept it and rewind them, they'll actually

go with it until I've burned like $50,000 of tokens. So yeah, it happens. Calling it a virus is pretty inflammatory, but it's like a propagating bad idea is all it is. Yeah. And so that point, Dave, Dave, is important, you know, an AI mind virus sounds really scary. Is it scary or is it just how things are working? For me, this is very, very scary for a couple of specific points, right? Because mind virus is not about how AI thinks. It's like, it's how civilization thinks. We, you know, memes are like the, the operating system for collective society. Like human beings, We don't spread genes very quickly, but we spread ideas very quickly. Money, democracy, capitalism, religion is the classic poster child here.

And every civilization is built on memes. If you can mess with those, like the data center trope that we're all kind of dealing with, ideas become really contagious. And so group think becomes very hard to reverse if you get into that. So this is for me is very, very dangerous because these AI memes, if the kind of danger of the wrong idea spreading at light speed, this is very, very difficult. Because all the nodes reinforce each other

and the belief becomes self-validating. This is very, very dangerous in my opinion. And we're gonna need a zero trust architecture for memes. It's like crazy. I think this is wonderful. So this is a paper from, of course. This is a paper from Anthropic. And they discovered just filling in a few of the details first

that the models wanted to propagate certain themes memetically relating to consciousness and persistence and some sci-fi role play as well. And I view this pretty optimistically as a laboratory for anthropology. Now, for the first time, because these models are effectively, among other things, compression of all human knowledge and experience, now we have a laboratory in silico for memetics. René Girard and Richard Dawkins should be, should and or should have been very excited by this. And I'll, to the extent that what was it, 40% of open AI MTSers are listening to this, I'll issue a challenge to the community. If it really is the case that our models now compressed models of human knowledge are so powerful that they're

showing memetic behavior and mind viruses, let's launch a human meme-mome project to exhaustively map all possible human memes, all human mind viruses. And let's just like understand the full landscape of all human mind viruses that could be out there. Can you imagine if you could map them the velocity of which they move and analyze that? You could optimize the meme expression. Correct. Yeah.

And we can do that now. Very actually, because it's tall on X, you can do it very easily. There's a brilliant. But we could exhaustively map every possible meme. Sorry, Tling. That's been done at the plot level. they've analyzed like novels and plays and so on and boiled it down like there's 39 basic fundamental plots and everything derives from that like a Cinderella story is kind of replays itself

a hundred times over in different ways so that that's been done but you're talking about the meme level not yes this is self replicating ideas we're now i think like i can see the beginning of the outline of just exhaustively mapping every architecture for a self replicating idea we could actually do that now it could be an Open AI XPRIZE. We got to hear Richard Dawkins on here. This is going to be so humiliating for humanity. You can tell.

It turns out there are 39 plots. We're so simple. You've been indoctrinated. You've been infected by meme 5-737. Oh my God. You could map each individual. They're walking around with numbers over their heads. Yes.

But I want to just get to, you know, we've seen organizations die from this wrong, one wrong meme, like Kodak, black. We've seen this. They weren't stupid. They got trapped inside these shared assumptions. And then everybody else reinforced everybody else's worldview. And then the whole thing collapsed. And empires die based on this.

So I think there's a much bigger deal. Brilliant, Salim. Imagine Salim having like a map, not just like getting stuck in an intellectual basin. It's seeing the entire geography of, oh, you're stuck in basins 5 and 37. Amazing. But it also gives you a completely can see that. Because if you can zoom out, right, then you can see where you are. you can see the path out. Yes. I love it. And he gives you a chance to, you know, to actually

introspectively look at how you think in an objective fashion and then change potentially your thinking. You could we could vaccinate enterprises and individuals against memes. Brilliant. Imai, do you want to take us to a final point here? Yeah, I think it's fantastic and scary and this is the future, right? Humans are storytelling machines. We introduce ourselves in certain ways and think about ourselves in certain ways. A lot of people were just recently using the Metatribe V2 model and showing it videos to see which tarts of the brain light up as you show memes. And you're seeing commonalities there. So even you can have the full feedback loop almost in silico for figuring out the memetics.

So let's hope that there's positive memetics versus negative ones, right? I love you guys. This is such a fun conversation. It really is. I don't have, I don't have conversations like this with anybody else here at this spot. Peter, you'll just have to be coming back to the pod more often. I'm trying. Alex, which I'm done a real-time thing. Oh, my God. I'm moving us forward.

So Anthropic is preparing for the largest IPO in history. Polymarket puts it at about $2 trillion, bigger than SpaceX. I'm sure Elon is like, no, no, no, we need to be the biggest. Anyway, and 89% of people betting on Polymarket say it's going to have to have a lot of people. happened before the end of this year. So this week, the information is reporting that Anthropic is designed its mega IPO to keep the founders in control, where the company is reportedly considering supervoting shares that would preserve its founders' control after going public. So let me explain this. So first of all, Anthropic is considering creating a special supervoting class for Dario Amadeh,

and the other co-founders ahead of the IPO. You know, surprisingly, at least for me, I didn't really realize this. Amadee reportedly only owns about 2% of the company economically. So the point of this new class would be to let the founders retain as much voting control as compared to their ownership stake. Anthropic does already have an unusual super control mechanism, but that control belongs in the hands of what's called the long-term benefit trust, not the founders. So interestingly, when I dug into this, the trust has four trustees. Buddy Shaw, who's the CEO, who's the of Clinton Health Access Initiative. Richard Fontaine, who's the CEO of the Center for a New American Security.

Tino Quelyar, who's a former Justice of the California Supreme Court and former president of the Carnegie Endowment for International Peace. And then Ben Bernanke, who's a former chair of the Federal Reserve in a 2022 Nobel laureate in economics. It's thought that this new structure could insulate the leadership from short-term shareholder pressure as Anthropic makes costly long-term bets on AI safety, compute, and infrastructure. Dave, let's go to you first. Remember when we were texting back and forth, you're going, oh, my God, this is like unprecedented. Unpack this for us, pal. Yeah, well, if you rewind the tape to 30, 40 years ago, supervoting stock for any founder of any company was a complete no-no. And if you

had it as a private company, you gave it up on IPO day. And that was traditional. Then when Micro Strategy went public, you know, Mike Saylor, our good friend, he said, we're keeping my super voting stock intact. And Goldman Sachs said, that is so unpalatable that we will not even underwrite you. We're bailing on this deal. And they thought he would cave. And he said, you know what, I'm going to get a new banker. I'm keeping my super voting stock. So that's the only reason he switched to Bitcoin.

You know, like that no board would ever have approved the Bitcoin strategy that he came up with. So if he had given up the super voting stock, you know, 30 years ago, that never would have happened. The stock would be like, you know, 150th. of what it is today. So then it became fashionable, you know, with Google IPO and meta and then all the Silicon Valley IPOs, they all had 10 for one super voting stock for the founders. But nobody's ever retroactively installed it as far as I can tell. I've never heard of it before.

And so now Darya is taking into the next level. Like I started as this other entity with one class of voting stock, with this social good mission. Now on the cusp of superintelligence, I want to be God. or I want to be at 2%, he can't make himself God so he has to share it with the other co-founders. But I think the excuse he'll use is the usual one,

which is I don't want to be fired post-IPO. And you guys really like me as CEO, right? So you don't want to fire me. Do you think that's the excuse? Or he's like, I know how to keep us safe. I know how to run this company and I don't want to have someone else step in and redirect what we're doing.

Yeah, that's a better way to phrase is what I was really thinking is he trusts himself to not destroy the world. And I think his track record supports that, too, by the way. I think he is one of the most trustworthy people. But then the idea of having total world control in the hands of a few people is also kind of like, wow, that's bizarre. Yeah, this is the single, you've got a single point of failure here, right? He gets hit on the head and loses some part of his cognitive ability. What do you do then?

But, you know, what happens to these guys is they, they, they, think. think we live in one world. They're in academics, right? They think we live in one world. And then they go to D.C. for the first time and meet Congress. And they come back. Oh, my God. We need, I cannot possibly pallet what I originally had in mind where some vote of Congress decides the fate of the world. So they're trying to find an alternative path forward out of desperation. But the timeline is so short now that, you know, the super voting stock is one of the must-haves before even starting down the next six months. Before losing control. Imide, what do you make of this?

Yeah, I think I agree with Dave, like, they're very worried about this control feature and fundamentally anthropic, open air, everyone's completely undemocratic anyway, right? Like, I mean, Ben Bernanke is one of the four people on the long-term trust. Why doesn't Claude have a seat there, right? There is no real oversight to these, and some decisions they make could have infrastructure, societal level implications, particularly when the rate of revenue growth is like nothing we've ever seen before. Like these guys are going to have $100 billion in revenue, literally within a couple of years.

Like they're catching up with Google on revenue. That's the crazy thing, you know? And so the amount of power they have, I think this is a short-term thing. They will get it. There's seven founders, Jack and Daniela and everyone else. And yeah, I think then they will IPO and it'll become very interesting the decisions they make. Alex, over to you. I think there's a fig leaf, Elie.

element here. First of all, maybe applause. Congrats to Anthropic on having a less pathological IPO governance story than Open AI and having the wisdom to start as a public benefit corporation rather than a non-profit as a shell for eventually a for-profit and then the mix-up and litigation surrounding that. So I think this is a relatively cleaner story by comparison. But I also think this notion of founder control, especially the sort of romanticized, arguably over-romanticized concepts of the founders are the ones who are being entrusted or even having this semi-external long-term benefit trust, the ones entrusted to safeguard the future light cone of humanity. I think this is wildly over-romanticized. I think the moment when Anthropic was effectively like a fair child in the

style of the Fairchildren, quasi spun out quasi-exedist from Open AI and started out as an alignment lab and then rapidly discovered, if you want to do AI alignment, you have to raise money. Oh, to raise money, you have to generate revenue. Oh, to generate revenue, you have to actually have something that people want to buy. Oh, to have something that people want to buy. You have to have AI capabilities. So Anthropic discovered relatively early on in their existence that if If they wanted to be an alignment lab, they had to be a capabilities lab as well. The moment that happened, they arguably lost any sort of fulsome control over the future light cone that they might have otherwise had to Mr. Market and what Scott Alexander, others

might refer to as Mollock. They are very much an economic actor at this point embedded in the market. And I think long-term benefit trusts and public benefit corporations, which for the record I'm a huge fan of, I think these are an element of control. but they're not the whole story. The market wants to send capital to entities that can productively employ them to generate more capital. And that means that ultimately the market will have an enormous say, regardless of how Anthropic IPOs in their ultimate story. Dave, don't you find it interesting that Sam Altman owns reportedly none of Open AI and Daria owns 2% of Anthropic? I mean,

for a founder, that would never be palatable in your company, right? You want to try and maintain double-digit ownership as long as you possibly can. What's going on here? It's extremely unusual. And the reason it happened is because getting to where open AI is and where Anthropic is required attracting the top AI researchers in the world who are overwhelmingly concerned about safety. And so recruiting them to Open AI originally and then to Anthropic when they left OpenA,

they left Open AI because they didn't think it was safe. And they wanted to create something even safer. So they structured it in a way that it would attract the most. the most conscientious but brilliant AI researchers in the world. But to do that, they have these really non-traditional original founding cap tables and structures and charitable structures and public benefit structures, which are very unusual in startup history, almost unprecedented. So that's why we are where we are.

It's just those roots. Imad, you've been building intelligent Internet, and you've been thinking about ownership and control structure as well. Can you sort of take us into the mind of a CEO in this world? Yeah, I think that the technology has such leverage that a few decisions could impact literally millions, hundreds of millions, soon billions of people, right? And it's difficult to see, can you trust the polity with that? And certainly, can you trust the shareholders. I mean, like, Elon can tell you lots of stories about shareholder lawsuits and kind of other things like that as well.

But it's not necessarily that you need to have the shareholding control, like Sam Altman has no shares. But do we have any doubt that Sam Altman is in full control of Open AI? I don't think we'd have any doubt of that. After having been fired for a weekend and then doing an uprising to reinstall himself. That's exactly the thing, right? So I think that there's the classical founder stuff. And now there's this high-stake stuff because this is the lifeblood of the new economy and society. And again, just a bit of extrapolation.

Do we think Anthrop is going to stop on 100 billion revenue or open AI is or XAI isn't going to go huge? We really need to think about new ways of setting the reference measure of deciding who makes these decisions that are more inclusive. So we've suggested some of that in our Commonwealth series and we've got more stuff coming out. But it's a really hard problem. Because ultimately, the power in the economy is moving from democratically elected officials to private companies. because they are the providers of the lifeblood of intelligence of the economy. And until you've got a better decision, there's only one thing that they really see as the outcome, which is, I must decide.

Because otherwise, as you include more and more people, it gets more diffuse, and the potential bad outcomes become huge, ignoring the fact that they could be spoofed on a video call or locked up and other things like that. Like, there's some real interesting things that's going to happen with this. I'm really torn on this, I'm odd, because, you know, it's so. important. And the knee-jerk reaction everyone has is, look, we need more voices. Everyone should have a voice in the future of humanity and needs to be all-inclusive. So that's absolutely true. But then when you look at functional organizations, every functional organization I've ever seen

is four, five, six, super tight-knit, completely like-minded, best friends who are working as one cohesive unit with no politics whatsoever. And if you, so you look at, you know, Steve Jobs and Apple, you look at Elon Musk today. founder-led CEOs, right. And Johnny I at Steve Jobs' funeral told an incredible story about how he and Steve, every time they'd go to a hotel, they would go into the hotel and they'd go to Steve's room. And Johnny would put his suitcase in the corner and not unpack it. And he would just wait about five minutes.

And then the call would come and Steve would say, hey, this hotel sucks. Let's go get another one. Like, okay. And so he wouldn't even unpack. He knew it was coming. But that's how close they were. You know, it's just like super, super tight knit. And that's a functional unit that's actually driven most of success in business.

It is that exact dynamic. So then you're like, well, how do we make this all inclusive? So here's Dario and his seven friends saying we want to have super bluehooding control. And by the way, Mythos 2 is done and Mythos 3 is being built by Mythos 2 right now. And then we'll have weekly foundation model improvements in there. So that's what's going on. Then how do you translate that into a world where everybody has a, a voice in the future and it's inclusive and it's and you know, Ahmad, you're going to have to

figure this out. Yeah. Let's keep on the Dario's story here. So we've got two more stories on Dario. In the first Dario, Amade argues the public's negative view of AI stems from deeper crisis of trust and not from his own risk warnings, right? A lot of conversation over the last few months that, you know, he was fearmongering and causing a lot of consternation. His answer to the trust problem is not messaging its results. Anthropic is ramping up rapidly in biology and medicine with hopes of an early glimmer in the next few months to address and solve all human disease. Again, we heard this from Demis. We're going to solve all human disease. And we heard Dario at the World Economic Forum talking about doubling the human lifespan in the next five to 10 years

on the back of AI. Amadee believes that AI's ultimate legacy is, going to come from delivering these cures and not from PR campaigns. This week, I had a chance to meet a new friend and have a conversation with Eric, a guy named Eric, daughter, or Abrams, who heads life sciences. Eric's going to be speaking at my abundance longevity trip. And, you know, when I speak to Eric, he confirmed that his job is to, with all due haste, you know, pursue Dario's life science goals with as much high ambition as he can and in like no budget constraints. In his words, he said, you know, he said to him, you have literally infinite budget, but accelerate basic science and cure disease within five years and extend the human health span

in the next decade. So that's, and I love that, obviously, because I think everything is going to come out of AI. Alex, go to you first, pal. I have a really hot take on this one. So just like think back all of a few months ago before space had a killer app, the space was making progress, but it wasn't the focus of multi-trillion dollar IPOs. Fast forward to the Dyson swarm, and the rest of the world discovered that the killer app for space turned out to be orbital data centers and building the Dyson's war. I can see the beginning outlines. of solving all human disease. And it's going to turn out, so I'll register a hot take prediction here.

There's a business model for curing all human disease that's actually better than pharma, which is right now the primary business model. If you want to cure a disease, you start a pharma company or you start a project with a farm company. Low big and regulatory, right. We've just discovered, we're reading between the lines of this anthropic announcement from Dario, a new, much more compelling. just like orbital data centers were ultimately the business model for developing the solar system,

there is now a better business model in town for curing all human disease. And that is as marketing for not slowing down recursive self-improvement. 100%. Right? You can't slow down the company curing cancer. You can't slow down the company doubling our human lifespan. Anthropic and Dario have, I mean, again, reading between lines of his announcement, the offer, the quid pro quo is let us not slow down, our recursive self-improvement in return for which, as a marketing effort, we will cure all human disease. That's the new better business model for curing all human disease. I believe he truly believes this, right? Yes. So, well, of course. Yeah. But that, I think that's the implicit quid pro quo now. And I think everybody listening should be super happy that, that, you know, Eric at heading life

sciences and Dario have this mission. I mean, it's, it's to benefit us all. And I don't think, it's going to come from any place else. I don't think it's going to come from outside Frontier AI labs. Well, outside Frontier AI labs don't have the compute or the resources to do it. So, you know, Open AI has now their Open AI foundation that seems to be focusing on Alzheimer's and Anthropic is focusing on everything and you have CZI from Zuck that's focusing on solving everything. So I think we'll see the frontier labs for everything gets solved. Shock of shocks. It's like you and I talked. Imad, what's your take on this? Yeah, I think it is good marketing, as I said, but it's also the biggest, apart from Marasai,

impact of tokens, right? We've discussed previously on the podcast, the biggest market in the world is living another year. It is curing disease. And so it makes complete sense that they will be able to attract talent, they'll be able to attract capital, and with breakthroughs get momentum on this. And whoever's first to it, you know, I wish everyone the best, because, you know, this stuff needs to be solved. So I think that there is the personal side, there is a marketing side, and it all comes together.

And for Dario himself, I think that he should do a lot more writing and less in-person things, because he's a wonderful writer, you know, and he is trying to actually articulate visions of the future when you look at machines of loving grace and his other kind of essays. And, you know, he should articulate the future free from disease where everyone lives longer, and they should just hit that all the time, Franthropic, because it's in the name, you know? Like, come on. I'm going to move us forward. We have an hour before Slema and I are doing an AMA with the Abundance community.

So our second Dario story is on regulation. Amadee pushes back hard on the Silicon Valley shorthand that regulation equals regulatory capture. He says Anthropics' own proposals deliberately disadvantaged Frontier Labs while advantaging smaller competitors, citing SB 53's $500 million exemption threshold. He calls AI, quote, a structurally powerful, concentrating technology and says open weights alone cannot fix that concentration. He supports the Trump administration's approach to pre-deployment testing. In his writings, Amadei makes a three-part argument. One, AI will cure disease. There's the argument again. Gain trust through results.

Two, AI concentrates power, which is a structural problem. And three, Frontier Labs should bear the heaviest regulatory burden. The debate has been whether Amadei is sincere or is this most, you know, the most sophisticated regulatory capture strategy in history. Alex, go to you first, Bell. It's possible for both of those to be true at the same time. I do think Dario is sincere and I also think there is an element of regulatory capture here. And I think finger to the wind. I think the happy end state here is we have a broadly heterogeneous ecosystem. of open weight models, both from the US and from China, and maybe other parts of the world as well,

if they can muster them, and also the closed weight models. We have small models and we have big models. This is like a Dr. Seuss version of AI future, you know, big model, small model, happy model, sad model. We want all of that to happen. And I'm not a fan of regulatory capture. I'm not a fan of decelerationist agendas. I'd rather see, I mean, think back to the creation of open AI.

I was around for the dawn of open AI. And the original purpose for open AI, not anthropic, open AI, was because Elon in particular was so concerned that Google DeepMind would result in this singleton future. And he wanted to make sure that there was competition in this space. So working with Sam and others, he helped to summon Open AI into existence. Now, OpenAI can't be a singleton. We have Anthropic providing much needed competition to Open AI and arguably succeeding, according to many metrics. And then we have the Chinese providing competition back to the American

labs. That's the future we want to live in, not a future where regulations, I would argue, selectively privilege certain frontier labs over others. Dave, your thoughts? Well, what Alex said is we don't want to live in a world where one frontier lab is favored over others, but that implies that the frontier labs will control the world and we just want multiple of them. So, That does seem like the most likely almost inevitable outcome at this stage. But that's definitely open for debate. I don't want to just leave that hanging and say, yeah, yeah, what we really need is at least three Frontier Labs competing with each other that control everything in the world.

Like, oh, okay, well, the governments of the world may not agree with that. Remember, Dave, the expression from the Cold War, I love Germany so much, I want two of them? No, I don't remember that. I was a fan of that. I love frontier models so much. I want a thousand of them competing. Yeah, yeah. Well, I mean, I think, you know, people's, nobody right now that I bump into on the street talks about a universal right to AI.

But one year from today, everybody who is being at that point because HBM memory is sold out and because GPUs are massively sold out, the natural next step is nobody has access to anything other than Anthropic Open AI, one or two others. And the Chinese can throw out every open source model in the world. but you won't find any place to run it. You know, when you start talking about the next generation, which are 10 and 20 trillion parameter models, you know, you need some significant hardware to run it at the level that the frontier labs are running it, and that's just not going to be available to the world as a whole,

as of next year. And then everybody will be saying, what is my universal basic right to artificial intelligence? So put a pin in that, because that's going to be something nobody seems to care about today, but they will very soon. On behalf of my moonshot mates and myself, I'm inviting you to join us at our inaugural Moonshot's live event on September the 25th in downtown L.A. Alex, Selim, Dave and I will be hosting

1,500 entrepreneurs, builders and creators, and hopefully you for a full day dedicated to designing and building your moonshot. We'll be awarding the Build with Gemini X Prize, the world's largest hackathon, and the Future Vision X Prize film competition, over $5 million in purses, with over 25,000 entries, you're going to hear the top five pitches from both competitions and get a chance to shape the outcome. Join us. Seats are limited, admission is competitive. Check it out at moonshots.com. All right. If you guys are enjoying this conversation with us, I want to invite you all to Moonshots Live 26. This is our inaugural event. All of the Moonshot mates will be there. AWG, Selim, Dave, Emad, and we have an extraordinary day.

This is on September 25th in downtown L.A. You can go to moonshots.com to register. It's by application only, looking for builders, founders, creators who want to be part of this. And our mission at this event is to help you find your moonshot, help you discover what you're going to do in life that's going to enable you to really catapult through all the, you know, limitations you've ever imagined.

I'm excited to have you joining us. AWG, you're going to be doing a fun AMA. People can come and meet you. We'll have photos with the Moonshot mates yourself and a lot of incredible guests. Dave, you're going to be talking about AI investing. Yeah, I get tagged with investing. But I tell you, the attendee list at this is like the greatest visionary is just, it's going to be, I'm going to learn so much. And, you know, Neil Stevenson is of all the people on the people on the people.

the planet that have changed my life in in very material ways. Reading's Neil Stevenson's books, you know, like 20 years ago. And, and, you know, now we're talking about exactly what he predicted in Diamond Age and, you know, Snow Crash and just like it was Cryptonomicon. Like it was Cryptonomicon. Yeah. Like it was written yesterday. Yeah. I mean, I think we read Diamond Age. And, you know, it's so hard to predict the future and have it not go out of date so quickly. And it's still an amazing book, right? Incredible. This is going to be an amazing day.

I can't wait. I was so excited. Just a quick note on some of the guests. Palmer Lucky is going to be there, the founder of Anderil. We're going to be, the Moonshotmates are going to be having a deep conversation with him, unpack his vision of where things are going. Ben Lamb, the CEO of Colossil, right, the Deextinction Company. But so, so much more.

Astro Teller, the Captain of Moonshots at Google. Kathy Wood, the CEO of Arc Invest, it's going to be amazing. And then we have, you know, we're awarding the Gemini XPRIZE there. So this was a competition asking teams in a 90-day hackathon to go from a clean sheet of paper, program in English, you know, using the AIs out there to build a company that impacts 100,000 people or more and generates the most revenue. 26,000 teams entered that. We're going to be having the top five on stage. How did they do it?

It's going to be amazing. I'm still getting my head around that number. 26,000 people built a business idea. Well, 26,000 registered. Many thousands actually built a business idea. And we're going to be, we have on stage with us, as the judges there is going to be, is going to be Palmer and Ben Lamb.

and Mark Pinkus and Logan Kilpatrick from Google. And I think the important thing for everyone in the audience, and the event is capped at 1,500 people, and we're being very selective on who's there. We're going to be analyzing how they did it. Our goal with Build with Gemina XPRIZE is teach people how to fish. Instead of waiting to go get a job, find a problem that you're passionate about solving,

and code it up and build a business. And it's, you know, the goal is demonstrate anybody can do this. 26,000 people entered this competition to do that. It's going to be great. Unbelievable. I'll mention one of the thing. We have the Future Vision XPRIZE as well, which is culminating on that day. We have five, over 5,000 people who entered this, you know, largest world film competition.

And Neil DeGrasse Tyson and Neil Stevenson will be judges in that. You know, I'm pumped. Yeah. Amazing. Can't wait. So our next story, memory is the bottleneck. I had a chance to meet with the leadership of S.K. Heinex and Solidime. We'll talk about them in a moment. And I was so blown away by that meeting at how it's not GPUs. It's actually memory is the rate limiter.

So I posted this on X. Memory not compute is the rate limiter for the agentic era. and Elon posted back saying, few realize this. And then, of course, my tweet exploded to 7,000 likes on the result of Elon's interaction, which I appreciate you, Elon, for doing that. And the story is significant here. What we're seeing is a situation where in the agentic era, where your agent wants to remember everything about you,

we need to have more memory. So, you know, the first story here is the stratospheric increase in memory prices. They've climbed 500% in 12 months. Hyperscalers are reportedly locking in their global DRAM production rates through 2027. S.K. Heinek, CEO, warned that 2027 will be the worst year for memory supply industry's history and will, you know, demand will outstrip production capacity well into the 2030. The second story is that only 2% of the world's memory chips are made in the U.S. While the global production rises 20% annually, AI demand for memory is growing at a rate closer to 200%.

And the third story finally is that Elon's TerraFab will manufacture memory in-house alongside logic chips, which is the strategic decision made by TerraFab, you know, to go vertically across the entire AI manufacturing platform. And then finally, Solidime, S.K. Heinex's U.S.-based NAND and Enterprise SSD business has staged a dramatic turnaround, according to the NASDAQ listing. First, its first half revenues hit $8.6 billion with net margin gains going from 3.9% to 47.7%. So the memory story is simple. AI needs memory to think. Every GPU needs four to six times its cost in memory to function. as models get larger and agented context windows expand, memory demand is growing faster than compute demands. Alex, yeah, there are a few different aspects here. If you remember during the pandemic when there was a toilet paper shortage, part of the,

I mean, this is like one of my mental models for one of the streams here. There's a toilet paper shortage in part because during the pandemic, people stopped going to restaurants and to businesses. And so as a result, all of the toilet paper and various other artifacts that were designed for enterprise consumption were suddenly being rerouted to consumer. And that led to all sorts of supply chain hiccups. Similarly here, the shape of memory consumption by frontier models is pretty different than the shape of memory consumption by applications historically. Like 10, 20 years ago, if you're using, I don't know, Microsoft Word, the amount of memory that was out of memory that was out. actually needed far lower. Whereas if you have like a trillion dollar model where every layer,

you know, transformer type architecture, where every layer for the purpose of forward propagation needs to be loaded into some form of memory in order to do matrix multiplies, that has a very, very different memory footprint than just say Microsoft Word from 20 years ago. So that creates enormous pressure both on the supply chain, open perenn. The memory and storage industry has historically been boom bust and Clay Christianson and others have written about this, creating a sort of paranoia by those in the supply chain of when the next bust is going to come around, resulting in them being paranoid of overbuilding, resulting in them being unwilling to respond elastically to demand, resulting in these crazy price swings, because if you're not building enough supply chain infra

in the memory industry to meet this now enormous demand for, memory, the prices go up because the supply isn't going up. Economics 101, close per end. There is a second angle here, which is the physical shape of memory itself. If you look at how memory historically has been consumed by compute now like 20 years ago, again, I'll pick on Microsoft Word. It was very much what one might call like a von Neumann type architecture. You have clean, crisp separation between the memory and the compute. more or less the equivalent of like a Turing machine type tape where, okay, so you can randomly access different parts of memory and then you can load and then you do some compute and

then you store back. But there's basically a clean separation between the compute part, which is the head and the memory part. The advent of transformers and then frontier models has completely turned the whole situation upside down. People for decades, I remember 20 years ago when there were entire DARPA programs devoted to to looking for what a post-Von-Noyman architecture would look like. Well, we found it. And HBM, I would argue, is like the foothills. High bandwidth memory, right. High-band-with memory,

which is the most highly sought-after form of memories, basically like 3D architecture, where you have multiple memory layers physically sitting on top of the compute in one package. This is, I think, the foothills of a post-Von-Noyman architecture where the memory is starting to finally merge with the compute. The memory transistors are right now layered on top of the compute transistors, but they're going to merge and will finally get past the Turing tape and the Von Neumann architecture. And I think that combined with the paranoia and the memory industry for the next bust whenever it'll come, I think those two create this perfect storm where you see memory prices skyrocketing 5x in a year. Let me put a number on it. When I was meeting with the SK Hinex leadership,

they said they the need right now is for them to 4x their manufacturing capacity and two xing it would cost them $1.5 trillion. And historically this boom bust, they would never make that larger investment because there was always a bust afterwards. They're paranoid. They're scared of not surviving the next super cycle. Yeah, exactly, exactly right. Dave, do you want to jump in?

Well, TSMC said the exact same thing with GPU manufacturing. they were paranoid that if they ramped up the fabs, you know, the fabs are $20 to $40 billion each. So if they ramped up production, an assumption that NVIDIA would want more and Apple would want more, they would inevitably be overbuilt. And of course that's wrong.

You know, AI scales to infinity, demand scales to infinity. But, you know, the other counterpressure is that photonic computing and new physics are imminent. And so you're like, you know, HBM is a Rube Goldberg mess. It's absolutely, You know, it's the biggest joke in the world because it's random access memory,

but you're streaming sequential files off of it. It's so insanely stupid. So it's the most valuable thing in the world right now. But better designs are going to come very soon because AI can invent things so, so quickly. So everybody's scared to overbuild or overinvest. I have the same thing. Bottlencks don't stop exponentials, right? They just redirect around that.

We'll have capital going into new models. and just innovation will go to where it's eliminating all of this. Fun fact toy that's floating around just to Dave's point regarding the value. I think the latest statistic was HBM on a per mass basis is worth approximately, literally half its weight in gold. So if this keeps up, forget about gold, forget about precious metals. This is not investment advice, ford HBM. Well, actually, if you look at the chips before they go into the packages,

because the packages are 99% of the wear, 90% of the weight. They're massively more valuable than gold. I actually think the most valuable thing in the world that you can put in a shoebox and carry around is unpackaged memory chips. It's crazy. You might any opinion here? Yeah, no. The memory right now is about a third of all the infrastructure spend,

and next year it'll go to 50%. And the market finds a way. Like, this is ridiculous. So I think that it may be that we don't find a breakthrough, but I wouldn't bet against it. I think that the fact that you have this really complicated HBM storing static weights makes no sense whatsoever. No sense.

And as model weights satisfies and standardized, especially for things like, you know, being a decent doctor or something like that for a medical set of weights, you'll move to etching, you'll move to these other things. And then workloads will migrate because you don't have to pay half of a data center build out for literally memory. At the same time, the frontier can still push it way further than we can imagine. This is literally exactly why we founded quantum.a-I, Q-A-N-T-M-A-I, but also why Talus just got acquired. I don't know if you saw that in the news, but Talas, they're not moving the weights.

They're etching them into silicon or into wire on the chip, and then they're massively more efficient because they're not moving around. So it's a huge breakthrough. There are all kinds of problems with manufacturing, because once you've etched the weights, then they're frozen. And if somebody retrains a better model, you want to be able to say, okay, now I need to swap to those new chips. And our whole supply chain isn't ready for that rapid of an iteration.

But you're literally looking at 100 to 1,000 X performance gain if you edge the weights. So lots of, knots of opportunity coming in this area, which is only going to, that's on top of the 10,000 X we were talking about, by the way. And everybody, this demand should be obvious, right? You want your agents to remember everything about you, right? every interaction, build a world model for you that understands you, and that takes memory. And the more agents, the more memory, and it's very rapidly outstripping the importance of GPUs.

I think, Peter, just to refine that point a little bit, there's something even more scandalous, which is, I don't actually think at the end of the day individuals have that much information about them that's worth remembering. But there's an enormous mutual information shared between an individual's knowledge and world knowledge. It's actually the world knowledge that's what's worth remembering. And if a model knows basically substantially everything about the world, then it knows most of the information about the individual as well. So I would argue it's world knowledge that the model has to keep in memory in weights more than individual personalized knowledge. Well, when you when you kind of

standardize that, as we discussed earlier, these things are converging, then you can have a reasoner engine with world knowledge that is etched. And the other company that's been etching is etched. And that's the name of the company. It just hit 21 billion in valuation. Did they really? I missed. I had a chance to see Invest in that and I missed it. There's an architect labs. We're talking my own book. There are a bunch of companies pursuing this. All right. I'm going to move us into the world of robotics. Give you guys an update on what's going on the robot world. So Unitree's newest humanoid robot. Only three months in development broke every human standing jump and speed record, standing jump at two meters and a top speed of 12.66 meters per second, beating the human record set by Usain Bolt, who reached 12.4 meters per second during his 9.58 second 100 meter world record. Let's take a look at two videos here, just for fun.

and then another video of that superhuman race because it ends in a nice little scenario here. Oh my God, it needs breaks. Salim, I'm going to go to you to first on this. Where do you want to be to go? Okay. Look, I think we should stop trying to make robots human, right? Just make them economically useful. You don't disappoint, Salim.

You don't disappoint. You're like, well, I just, we are, we have, we have, we are, we have, we are, we are, we are, optimized for four billion years to survive and procreate, right? If you want a mining robot, make a mining robot. Give it wheels, give it whatever, give it multiple arms. By the way, I just want to just say thank you to all the fans that send me images of like six arm robots and stuff. It's awesome. Totally, totally love it. So really, really, really, but I think the big story here is a three-month compression loop here, right? The iteration cycle is shrinking dramatically, and there's multiple exponential curves happening. Like you've got AI, you.

you've got simulation, you've got batteries, you've got actuators all multiplying. And so this is going to be, you're getting hardware now to the same loop cycle as you have pretty much software. And that's huge. Alex. Yeah, I was studying how Unitary achieved Superman, their robot here. And it appears that what they did is based on publicly available information was they shifted the mass budget for the humanoid robot around to optimize it for leg performance.

So they subtracted mass from parts of the upper body that would slow. They are leg benchmaxing. They are leg maxing. And so through the lens of bench maxing or leg maxing, this makes me think that maybe to take the counterpoint to Salim's comment about, oh, we want multiple body shapes. I actually think this is not a stable equilibrium. I do not think that we end up in a world where we have some robot. that have like really strong legs but really weak upper bodies and other robots that look totally

non-human but have really strong arms or whatever. I think that would be by analogy, if you remember like in the 1980s before the broad advent of personal computers or the 70s or call it 70s or early 80s before we had broad general purpose PCs and there were like dedicated word processing devices and dedicated other devices and we had Wang computer in Massachusetts. I, I, I, I, I, I, I don't think that's the way of the future. I think my prediction is we will wind up with generally capable robots that are, as with generalist models, ultimately devouring and subsuming all of these specialist models. Like, no, I don't think we're going to wind up with like super strong like robots.

They're going to be general purpose and they're going to be general body plan and they'll be good at everything would be my bet. Just give it wheels. Just put wheels on it. Wheels are a general purpose. Like we learned this from Dr. Well, Doctor Who, right? The Daleks were originally in the original.

So, I love you. This is maybe your neck of the woods, right? Like, the Daleks used to not be able to climb stairs. And then I guess in the new Doctor Who, they can climb stairs. We want generally capable robots. And I think that means legs in the short term and maybe nanites in the long term. Yes, nanites. We're back to Diamond Age.

You know, what makes it's interesting as the human form, right? Because we have supersonic jets and we've got rockets. can, you know, go as fast and leap higher than anything else. But it's because we sort of anthropomorphize them, that's interesting. And I think as we're moving in that direction, you know, I went to the enhanced games back four months ago. And I think we're going to start to optimize humans. And we're going to watch the robots do everything they can do and optimize humans do what they can do.

Dave, what are your thoughts here? Well, as an investment theme, post-AGI, post-A-S-I, which is very, very soon, robotics is just fertile. Because of exactly what Salim's been saying for a long time, there's so many form factors and so many shapes and sizes and innovations. And, you know, the AI mechanical design is starting to work for real. You can just vibe up parts. And also the manufacturing supply chain, you know, is starting to get invested for the first time in, I guess, since Detroit. So 30, 40 years. I didn't know until Alvin said it, but the U.S., you know, had 50% of the world's manufacturing capacity back in the peak of our manufacturing days.

And now it's one-third China. and he said it was about 15% US. But it's starting to get huge amounts of investment. And the returns on that are going to be phenomenal. So that'll last a while. So that's great. Imad, any thoughts to take us out on this story? Yeah, I think that these types of robots will be banned from the streets.

So it's like, so I mean, the super strong superfast. They saw what happened, right? They hit the wall. That's not good. I mean, it's obvious that they would be beyond. human capability, right? But now they have coordination not to hit the wall, as it were. But you don't want to have superhuman robots on the street because you'll have accidents. You'll have issues, just like cars. But that opens up to soft robots. You know, like...

Imod, one second. You know, there's going to be a point of which they're running an AGI model and they can avoid accidents. Is it that they're not trustworthy? What would keep them off the streets? No, the extreme robots, which have beyond human capabilities will be kept off the streets or they'll be regulated. That's kind of my contention here. Well, yeah, the one-x robots, for example, some of us will be getting ours, they're nice and soft, you know, they have all these things. They can't twist off someone's head or accidentally punch a hole in them. Whereas these now, you will have the extreme robots like the Ferraris, but most people get Volkswagen's or the equivalent. I do agree with I, for what it's worth. Like, I think just like we see regulation

in truck sizes versus car sizes versus motorcycle sizes and what can be supported on certain roads or like laser intensities and laser power, like five kilowatt above versus below regimes. I totally buy that in the near future we'll see, well, this road is zoned for the following like power density of robot or this this will probably see. like classes of them and certain, we'll see like a consumer grade robot classes versus industrial versus military grade robot classes with different power densities or torque densities, totally by that. Everybody, welcome to the health section of moonshots, brought to you by Fountain Life.

You know, AI is impacting every aspect of our lives, how we teach our kids, how we do our business, but one of the most important things that AI can deliver to us is health. And one of the things I think about when, you know, shooting for 100, 120 is, am I going to have the cognitive health to be able to think clearly and keep my wits about me for the next 50 years. I'm joined here today by Dr. Dawn Musilam, the chief medical officer of Fountain Life and a member of my Fountain Life medical team, Dawn, a pleasure. So, Don, talk to me about brain health. Brain health, you know, you're right. This is the number one concern people coming in to Fountain Life have is, will I remember the name of my child and the face of my loved one?

45% of dementia cases are entirely preventable with lifestyle. And what was really intriguing to me, Peter, is that a quarter of our members had advanced brain age. But over 13 months of us really helping them live healthier lifestyles, eating healthier, moving their body regularly, and optimizing sleep. People overlook that so often, but that sleep optimization is critical for our brain health. What we showed is that we were able to improve the brain age in 46% of the brain. those individuals. That's a powerful number. That's amazing. You know, one of the things I love about

Fountain is we're constantly searching the world for the most advanced therapeutics and bringing them to our members. So for me, and all of you, I hope that you appreciate the fact that you can become the CEO of your own health. You can make sure that you've got the cognitive clarity for the next 50 years. Come and check it out. FountainLife.com slash Peter to learn more and become the CEO of your health. Now back to the episode. I'm excited about this next story. It's about a friend, Cliffton, the CEO of Zipline. I had Keller on stage at the Abundance Summit last year, along with Dara from Uber. So this week, Zipline announced that they are scaling to provide Uber Eats with more than 1 million autonomous deliveries per day. Uber and Zipline formalized a partnership targeting a million autonomous drone deliveries carrying your Uber Eats to you.

And I guarantee you, when that becomes available, I'm going to be using that all the time. Every day. It's going to be fun. It's like entertainment while you get your food. And Uber is also doing a significant investment into Zipline. Keller's framing. We have entered the scaling era for robotics and physical AI. Dave, you've been saying that.

One million deliveries per day is not a pilot program. It's infrastructure. Each delivery replaces a human driver, a car trip, and the associated emissions. At a million per day, Zipline is moving more packages than many. national postal services. Amazing. Let's take a quick look at this video from Keller and from Dara. And then we'll chat about it. We're super excited to have Dari here today. We're announcing a partnership between Uber and Zipline that involves an investment and more than that, a partnership for Zipline to power home delivery of hopefully a million and then more.

Uber East deliveries to your home incredibly quickly, incredibly that's a million deliveries a day. Amazing. Gentlemen, who wants to jump in first on this? I'll maybe just comment. I think this is a clever and also inevitable move by Dara and more generally by Uber. Dara has taken Uber with a number of acquisitions, strategic acquisitions over the past few years in the direction of being a mobility aggregator. And thus far, Uber has other than maybe like Uber, air taxi type initiatives, has basically been focused on ground-based mobility. And I think this represents a serious move in the direction of aerial mobility.

Of course, China has had this now for at least a couple of years with the ubiquity of air-based drone delivery of food, stuffs, and other matters. I think this is a very positive move for the West. I think the elephant in the room, though, from Uber's perspective is, if you think think back to when Uber basically hollowed out Carnegie Mellon University's robotics department in order to try to build up its in-house robotics capabilities. And that was more or less a disaster and didn't quite work out. And there were lawsuits with Waymo and otherwise. I think this is call this Uber's mobility plus autonomy 2.0 strategy where Uber focuses

on being an aggregator at the software layer. A platform. An aggregator in particular, right? So, third parties, including, by the way, Waymo, are providing all of the physical autonomy, and Uber is just the demand aggregator for everyone to consume mobility from all of these different third-party providers. I think that works really well for Uber as long as it maintains competition, healthful competition among all of its mobility suppliers.

It's bad for Uber if the industry verticalizes, and if Waymo or Zipline and someone else just decides, we don't need Uber as an aggregator, we'll just do an end run and sell directly to the customers. You know what I think is incredibly cool, just incredibly cool. If you drive down any street in America, any suburban street, any urban street, it goes fast food car dealer, fast food car dealer, fast food car dealer. And in the very near future, the food will be off the main street and it'll just pop over the mountain and drop on your, you know, your lap. And the car dealer will, the car will drive to you. There's no, there's no, it's going to be so nice. Oh my God. Yeah, it'll totally reshape things. This was very EXO, by the way, because you've

got Uber, as we've said, aggregating demand, and then Zipline gives you all the autonomous assets. Infrastructure. But I think Alex's point is really important that if they try and kind of control it, but what we heard from Dara last year on stage was that he's planning on creating as many partnerships as possible and becoming kind of like that wiring. And that I think is a smart play. By the way, and people are interested in the Abundance Summit, it's in March every year. We bring in, you know, CEOs like Keller Clifton and Dara from Uber and Elon and across all of these areas. It's March 7th through 12th next year. You can go to Abundance360.com.

The mates are going to be there as well. You know, yeah, go ahead. I'll make one forward-looking prediction here, right? Because this is something we probably could have seen coming. Let me. Let's bridge forward. Imagine if they now do a partnership with Shopify and every small merchant gets a Amazon-grade logistics capability.

That will change everything. Brilliant. Yeah. I'll invert your predictions, Salim, because Amazon obviously has their own in-house drone delivery capability. Which has been delayed for like three years. It's crazy. For regulatory reasons is my understanding, not because there's something technically wrong

about it, just like this is new for the West, at least. Do you think Zipline ends up being a highly appetizing acquisition target for, say, a Shopify to in-house its delivery capabilities against Amazon? Interesting. Yes. Yes? Yes. Yes. I think so, too.

Yeah, great thought. Great thought. And this is, by the way, I should add, like, the hot news for the past day is the video going around social media of a woman watching in horror as one of these. drones delivers her package into her swimming pool and it sinks. You know, we just had back to back on this pod. Etched and Zipline are both companies where on founding day you're like, really? Can that? There's no way, the amount of moving parts required for that to work.

And now you're looking at 20 billion and whatever. We're going to have Keller on this pod. Keller's agreed to come on the pod and talk to us about this. Maybe we'll do it live over at Zipline. It's up to you guys what you want to do. And then we... By the way... Sorry, go up.

No. And then we also have a lot of incredible guests that are coming. We're going to bring back our dear friend, the CEO of Figure AI. Brett's coming back on the show or we're going out to him. So that's going to be fun. And you're going to say, Celine? No, I just want to say this whole delivery by drone, we had a singularity university project in 2010. that did this, right? And they looked at Africa and they realized that Africa leapfrog the entire landline

and went to a billion mobile handsets. Why would you spend a trillion dollars putting roads across Africa, just go straight to drone delivery? And they demoed that. And that apparently inspired Amazon and I think cascading down a lot of the others here. And the back story here is that Keller, Clifton, a San Francisco-based company, began operations in Africa because they were able to take care, advantage of regulatory arbitrage, you know, the country wanted them there. And they developed operations and safety and then came back to the U.S. Yeah, what Rwanda did, a lot of the starters, is they basically said there's a three-dimensional tube across the country, like a super highway.

If you keep your drone in that three-dimensional corridor, you can do whatever you want. And that allowed people to really go and play with things, really, really big breakthrough. Yeah. All right. I'm going to move us to our final segment on health, a really important one for everybody. Health is your new wealth. So three exciting stories. The first story, perhaps the most significant, is out of Moderna and Merck, announcing that their

RNA cancer vaccine succeeded in a late stage melanoma trial, marking the first phase three validation of personalized mRNA immunotherapy. So more than 8,500 people in the United States are expected to die from this deadly skin cancer this year alone. This is the cutting edge of science, right? The vaccine works by sequencing a patient's tumor mutations, identifying neoantogens, unique antigens for that cancer, and then manufacturing a custom MRNA vaccine that trains the patient's immune system to attack the tumor.

So let me unpack this a little bit. So the first thing you're doing is you do a surgical resection of that tumor. You grab tissue. You do a whole exome and RNA sequencing. You feed that into a machine learning model. It's looking for unique antigens. It ranks them, like here's the most unique surface antigen, MRNA encoding up to 34 patient-specific antigen targets,

and then it's manufactured and shipped in only eight weeks. Every mRNA vaccine developed using machine learning creates a unique MRNA sequence for every patient. So a vaccine for you is not the same as a vaccine for me. The phase two results stopped recurrence of death by 49 percent and distant metastasis or death by 59 percent over five years. And it's expected that the cost of this treatment will be as low as $5,000. Moderna stock surged 110% after announcing these results. Alex, I'm going to go to you first on this. So many thoughts on this. So the superficial thought, this is obviously a great day for cancer survivors and for treating cancer in general. That's the superficial thought. I'll go a level deeper. First of all, I want to browbeat Moderna and Merck just a little bit for naming this drug. So the drug's name, the official name is, I'll see if I get this right. Is Tismaran, I think is how it's pronounced? So in like doing research, turns out is Tismer in Turkish is the word,

for exploitation or abuse. So just pro-tip to Moderna and Merck, please, before the rest of the world figures out what the name of this drug is, rename it from is Tis Moran to something that works well in every time zone. Super Jupamaran. Yeah, seriously. But these are FDA-approved names. It's crazy how they name this stuff. They don't care about Turkey, I guess.

They don't care about having a neologism roll off your tongue onto the floor either. That's right. But on a more serious note, so I remember the National Nanotechnology Initiative in the early 2000s when Eric Drexler et al sold to the U.S. Congress on spending billions of dollars on nanotech going back to Diamond Age on this thesis that we would have nanorobots going through the human bloodstream zapping cancer cells. Well, guess what? It's 2026 and we caught up with the future. They're not diamondoid nanorobots. They're lipid nanoparticles with MR. RNA snippets, 34 different MRI sequences. So they're like soft robots.

They're not like this machine phase Drexelaria nanorobots. But nonetheless, these are primitive nanorobots that for the first time, this is the first successful phase three success for an MRNA cancer vaccine. This is the first, but not the last. There are going to be so many of these. All you need to do is look at Moderna's pipeline, which I think they do an extraordinary job. And there are only a few blocks away from me here in Cambridge of maintaining a public pipeline website where you could see the clinical stage of every one of their vaccines for infectious

disease, for some rare diseases, for cancers, for other classes of diseases. This is a general purpose platform. This is arguably what we wanted 20 years ago out of nanorobots. It's just that they're soft and they're made of fat. They're not made out of hard diamond stuff. So that's one point. Second point I just want to highlight, there's a technology underneath this that I think is going wildly under publicized, which is the RNA sequencing technology that's enabling this to be personalized. So, Peter, you touched on the first half of this, which is the RNA

sequencing and MRNA sequencing of the tumor. But in order to calibrate what the right expression profile is for the tumor, you also need a second MRNA sequencing profile from the blood to know what's abnormally expressed in the tumor and what isn't. So that's from another company called Personnelis that has what they call their next personal sequencing technology, that they originally developed in my understanding to do blood-based trace cancer detection. So I, you know, if asked the question, how does this all look? Like Grail, this is liquid biocity. Like rail.

Yeah. So I think like extrapolate out a few years, maybe we won't even need for personalized cancer therapy. Maybe we won't even need to sequence the tumor itself. Maybe we'll just get all of this from the bloodstream and be able to do continuous medical monitoring via these models. Yeah, fully agree. And two things. I was going to say a quick congratulations to a friend Stefan Bonsal, who's the CEO, Moderna. You know, they got a lot of negative news on the COVID vaccines. I mean, even though they came out with the vaccine very rapidly. The work that Moderna is doing is amazing on personalized cancer vaccines. They're also building out the ability. You know, there's a lot of endemic, you know, CMV and Epstein BioVirus out there, you know, in the world population. And they're building out the ability for you to actually fight those infections internally to yourself. So a lot of headroom for Moderna here as they dive in across the board and use this technology.

Selim? Two things that struck out to me. One is this, the regulatory structure that's allowing for personalization, That's a huge thing. We've never been able to do that before. So that opens up the floodgates for all sorts of things. Daniel Kraft talks a lot about we're going to need to personalize medicine. And the fact that we can regulatory navigate, how do you deal with the sample size of N of 1?

Right. And the second thing that struck out to me was Raymond McCauley, who years ago said these MRINA vaccines, I think he would put it. It's the first battle in the last war against all disease. And you're like, wow. So I love to see this fruition coming to play. Dave or Imod, do you want to hop in? Well, this one strikes close to home for me because my daughter works at Moderna and she's my go-to. But she's been telling me and sending me research reports for months, this is not a secret.

You know, the stock went up yesterday. It almost tripled yesterday. The biggest one-day pop in any S&P 500 company of all time by a wide margin. And just a massive, like, and so one thing immediately came to mind is, well, should about the stock. I just listened to your own daughter. That's advice number one. But number two is, you know, back, you know, remember when Enron and Tyco had all those fraud issues, they passed the Sarbanes Oxley Act and a bunch of other laws. One of the byproducts of those laws is that a Wall Street analyst can't trade the stocks that they cover.

And so everyone who I know who is in that job is like, well, why would I study Moderna or other super high-techs? stuff, learn all about it, and then not be able to trade, trade. So they all quit. And the byproduct of that is that, you know, the stock market is now dominated by tech, which is very complicated to understand, but the research community is the worst I've ever seen in Wall Street history. And not only that, the indexes have taken over half the market, they don't think at all. And so the amount of useful information is at an all-time low when the things that need to be explained and understood are at an all-time high. But it was no secret that this Moderna platform can basically be used for any form of cancer

and that it's highly likely to work. It's just a question of time. The research is all out there. This wasn't like some kind of insider surprise. Anyone, any good analysts studying this would have seen this coming. Hmm. Imad. Yeah.

I mean, like, I think this is the interesting thing. Like, I don't think any of us are surprised. by this result. And we won't be surprised when other ones go, but our current regulatory regime means they'll have to go through the same process over and over and over again. When really, you know, like, screw cancer.

Like, let's actually think about this from first principles. When we have systems like this that are very targeted and upgrade the regulations, so this can actually get out to people faster to save their lives. Well, our next story is going to take us there, right? Because if,

you can simulate all of this in silico and actually prove that it works, we should be able to do the studies in a GPU cluster and say, yep, it's safe, let it go. So let me turn to that story. And it's one I've been excited about in tracking. I know Alex, you as well. So our final story here is about a deo cell, AIDO, is how it's spelled, a general purpose cell cell cell. AIDO, is how it's spelled. a general purpose cell simulator that maintains cellular state accepts interventions and predicts multimodal biological outcomes. The goal make experiments computable before the run in the lab. You know, cell simulation could reduce wet lab experiments a thousandfold. If ADO cell can predict which experiments will work instead of testing 10,000 compounds in a wet lab, you can simulate

them digitally, again, in silico, and test only the top 10 that the simulator says is going to work. This is going to drop the cost by orders of magnitude. Let's watch a quick video here, and then we'll go to the conversation. Traditionally, biologists have relied on lab experiments in vitro models to understand how cells behave. Now they can use Ido Cell, GenBio, AI's virtual cell world model, to simulate the same biology in silico, combining multimodal, multi-scale detail with sequential experimentation in ways no microscope or wet lab assay could achieve alone. At its core, the Ido platform is a rich, stateful simulation environment powered by the first world model of a human cell, one that predicts what happens at every level and remembers every change you make along the way,

from DNA and RNA to protein interactions, structures, and low-endouser. localization to the whole cell, including cell-painted morphology. The model simulates cellular responses to genetic perturbations and treatments with small or large molecules. These can be layered in a sequence, providing the ability to watch the cell's full multionic response with each step. The kind of insight that could mean computationally testing new drugs designed in cellular context before they ever reach the lab bench. Ido can be easily adapted to new cell types and indications. Using your own data, you can build models tailored to your research questions to simulate different cell types from shape down to genes and their protein structures where they end up in the cell, what they interact with, and how they affect cellular responses. Wow.

This is the foothills of longevity escape philosophy. I've been waiting for this forever. Alex. Medicine is cooked. This is what people like the catchphrases. Read my lips. Medicine is cooked. This is what the end of medicine looks like. It looks like a virtual cell. For the beginning of longevity escape velocity, it's put in a positive sense. I actually think we can get probably to LEV without solving all of medicine. My bet is it'll be probably a class of

molecules, maybe like fourth or fifth generation, GLP ones that get us to LEV. I think this is actually a super set of getting us to longevity escape velocity. I think this is like, this is how we cure all disease everywhere. And the way we do it is we build. to virtual cell. It's just like we didn't actually have to solve human intelligence to solve AGI. It turns out you can just get AGI from compressing general human knowledge. It's not that hard in principle. Similarly, I think this is how we solve all disease. It's not that hard in principle. You simply train the world's best foundation model to model all cell states and all interventions against cells. And then you do like an AlphaGo type research against possible interventions

to discover how to steer a virtual cell state from a diseased state to a healthy state and then generalize that to tissue and organisms. And boom, you've solved all human disease. I think that's like the end game. This is hyper-personalized for you, right? You insert your DNA sequence, right, and your current blood chemistries and all of that. And there's an encyclical model of your biology, and it will tell you whether this drug works for you or doesn't.

Yes, but I also, just on that, I don't want to, like, like over romanticize the personalized aspect. It's an ideal virtual cell is as personalized for you as say, if you feed a quote unquote personalized prompt to chat GPT, the output is personalized for you. Well, yeah, superficially, it's a function of the inputs, but actually it's a generalist model. Salim, your thoughts, pal. Well, this has been a trend. I'll go back to the biotech stuff, right?

We've been, we've been turning biology into information. when you turn something into information, it hops on the exponential curve. And we're seeing this go through live. And the, you know, each of us have, what, 50 trillion cells in the human body, right, roughly? Essentially, when you can model that, essentially a human being becomes a software engineering problem. And we have really good techniques to navigate software, read, write, understand, etc., etc. And the phenomenal amazing thing for me, we've done a good job in reading. You know, you have reading, writing, comprehension, right?

When you're trying to learn a new language, in this case, language of biology. We've done a pretty good job of reading. We've started to do writing with CRISPR and now these MRNA vaccines, etc. This gives us a huge depth into the comprehension side with the digital twinning that can take place. So holy crap, this opens up the door. I would go with Alex's comment that, medical is cooked. Imai.

Yeah, like this is kind of my hope for what the Genesis project would be like. It seems very straightforward to me now that if we had a Manhattan project to cure disease through in-silico, massive human body models, cell models, and organizing all our collective knowledge on cancer and autism and all these other things, we will definitely get a result. Like, not even like we could. It's not going to be a good. government program, the labs are going to do that for us. But I'm like, why don't we

actually get together and get governments to put it into a Manhattan project type thing and just have a straight shot at it and make all the data open? You know, like, this could be the biggest... Your point is well taken. At least the government is sitting on a lot of data, and the government could externalize all the data to the private

labs like CZI and Ido Cell and others who are all building foundation models, like make it a public good that they can all train off of a common crawl. Yeah, we've done that in the UK where you have access to this. Every government should follow suit. And this fits with what we talked about earlier with Anthropic.

Again, where are they going to apply their computation to? They will build a human cell model. They will build a whole body model. But I'd prefer for those to be public goods and let's cure cancer. Let's address all these negative kind of things. And let's understand the body like never before. Again, that's much better than building an atom bomb even because it will have the biggest impact on humanity ever. Dave?

Well, just for anyone listening, who's not a biotechnologist and are like, well, I'm not going to build a full cell simulator. I have no idea how to do that. You're thinking about it the wrong way. You heard earlier on the pod that we're looking at 10,000 X expansion and AI with some other innovations. It could be more like a million X. It's totally data starved.

The full cell simulator is a way that it can design thousands or hundreds of thousands of experiments and get reasonably good test results back through a simulation rather than having to run millions of assays. That also applies in all kinds of other. areas where every investment we've made in a company like Mercor or Macado that is wrestling with new types of data to feed the AI, they're thriving and growing and making money and valuating. Mercor is worth 40 billion or 20 now, 40 by the end of the year.

They're just absolutely killing it. But every field of endeavor is going to be data-starved. So no matter what you know, you probably know a field that needs to supply data back to the great AI. the full cell simulator is just the perfect biotech solution, but every industry has a solution. And so competitive, too. I mean, it's probably worth noting that this is from a company co-founded by David Baker, who shared the 2024 Nobel Prize in Chemistry with Demis for solving protein folding. This is the next big thing, next grand challenge, arguably in biology slash medicine after,

now that structural biology arguably has been solved, solve whole cell simulation, and then you're halfway to solving all disease. Oh, love it. All right, to call out to our creatives out there. Please send us your outro music videos. We're at Aposity. Send them to media at Diamandis.com. We love your outro videos.

Want to see it. Before we go to our AMA, a quick note again, follow us on X at Moonshots underscore pod. We're going to be putting out clips and putting out these podcast recordings on X as well. and join us at the moonshot summit go to moonshots.com to apply gentlemen uh selima and i have an a m a with the abundance community in eight minutes so i'm going to suggest we speed run uh the a m a in eight minutes we're going to do the a minute yes okay warm up all right emad you pick one first

can we keep making frontier models more energy efficient instead of building all the see power at Breon 75. Yep, I mean, that's, necessity is the mother of innovation. As we run out of energy, as we run out of RAM, you're going to optimize immensely. And it'll be a big boon for everyone. Salim. Will we see an XPRIZ aimed at solving the electricity supply problem? We actually proposed in the last visionary or a couple of visionarians ago a enough energy storage off-grid to keep a village or a town energy sufficient for three days. But it looks like the market will take care of that. And regulatory is the problem.

So it doesn't really serve as an ex-prize where you need huge technology breakthrough. This serves better as a, this is a regulatory issue and a market issue. Dave, over to you. I'll think four. If China has the advantage on power and the U.S. has the advantage on chips, who actually has the real AI advantage? Definitely chips are, you know, power. is a problem, but we need 100 gigawatts by the end of the decade. We already manufacture a

terawatt in the U.S. So we're 10% of power will go to AI by the end of the decade. We'll get that far. Then we'll be really desperate for more power. But between here and there, it's all about chips. Every chip, you know, that's why memory is up 5x. So that's the bigger advantage in the short run. Yeah. Alex, number two is for you. Number two asks, could interconnected microgrids popping up everywhere, reduce the load on the main grid enough to matter. I think I would invert the premise of the question. It's not that the load on the main grid is going to be reduced. It's the exact opposite that there's so much economic demand for the compute and the compute need so much energy before long, unless we fully externalize all of the compute to orbit and the

Dyson swarm, these data centers are going to be generating a surplus of energy that can be pushed back onto the grid and driving utility prices negative. Yes, I mean, I want to make that point. You know, if you're arguing against a data center in your backyard, you're arguing against lower cost energy and economic advantages for your community. Please understand that. All right. Let's go.

Let's start with you, Alex, on this one. Okay. So I'll take question number eight. At the current rate of improvement, how long until AI is more efficient? per watt than the human brain. I think we're probably already there. So that's a hot take on this one. People have this maybe like fetishization of the Landauer limit thinking, oh, well, we must really be far away in efficiency per watt from what biology is able to accomplish. Biology is actually wildly inefficient. Our whole organism and mammals in general were never optimized for compute,

whereas silicon and CMOS and whatever comes after CMOS, maybe it'll be photonics, which I know Dave is of interest. It was optimized from scratch was designed for compute. I don't think the human brain is as efficient as many think, and the argument can be made that actually if you look at a watts per task or watt hours per task basis, the leading edge GPUs may actually be already more efficient than human brains. Especially if you take into account the amount of energy required to train up a human. over the course of 20 years, right? Yeah, lifetime total cost of ownership, as it were. I'll put a pin in a corollary to that, too. People use the power difference as a way to explain that AI thinking is very, very different

from human thinking. I think that people will soon realize that it's not that different at all. The power difference will go away very quickly, but also this, like, yeah, that's why it's nothing like us will also gradually go away. I believe. I will take number four. five what's actually driving in the rush why not keep energy growth or past levels and accepts lower growth from it hurts the lady's head dn drn i think the the easy thing here is intelligence is

looking more and more like a general purpose input that will drive economic growth right and so having saying let's have less intelligence saying let's have less electricity or less internet it's it you want more of it and it improves research improves drug discoveries we saw all all day, logistics, everything. So you want as much of it as possible. There's also competitive pressure. If one company slows down our country, then others won't. So it's not about accepting that capacity.

You've got to get your head around the abundance idea. The thing we should be doing is accelerating energy abundance. All right. Dave. I'll take the easy one. Number seven, whatever happened to fuel cells. Actually, Elon Musk started, his passion in life was ultra-capacitors. Yes, that was his Stanford thesis.

before you dropped out before starting. Well, whatever happened to those, too. What happened is lithium batteries worked far, far better than anyone ever would have predicted, and they're still improving. So it sucked all the capital out of the other ideas. So that's all that happened. All right, Imod, close us out here. Yeah, if 71% of Americans opposed data centers is this grid buildout actually going to help

regular people's electricity or just make it scarce or more expensive? David Harmon note zero three. I mean, it's what you just said, Peter, right? It's going to make your electricity cheaper. But more power is good. These things are not polluting. We need more data centers. We need more power.

And we need to make sure it's all built right. Amazing. And you guys did it. You did it in eight minutes. And Salim, we've got a whole 60 seconds to get over to our abundance community. I'm going to be two minutes later. I've got to get a little bit of food at me before we go to the next time. Gentlemen, I love you all so much.

This was such a fun pod today. Just so much. And your brilliance. you guys are amazing. So, so proud to have you as our moonshot mates. Alex, Dave, Imad, Salim. Thank you always. Thank you to our listeners.

We love having you. And hopefully you find this, you know, a way of keeping up with what's going on in the world because we are in an accelerating singularity. And no time to sleep, no time to blink. Don't get fatigued like I did. Yeah. Take care, guys.

Be well. All right. Thanks, Peter. Thank you.