Dario vs Jensen on Open Weights, OpenAI & Anthropic in DC, Xi Exports AI to Global South | EP #275

22:52I think that's too clever by half in some sense because they're not the same models. From a deployment perspective, which is half the battle, deploying an open-weight model has a very different deployment situation than access via gated API to a closed-weight model. So I think that's sort of the obvious story. Slightly less obvious story may be where the enforcement happens. What's the right bottleneck for defensive co-scaling to work? And I think one of the more interesting bottlenecks or, let's say, comparative advantages that we've seen over the past few months hasn't been quite reported this way for defensive co-scaling is just simply a matter of time.

23:36If the good guys, however you want to construe that, have access to the strongest models just a little bit ahead of everyone else inclusive of the bad guys, in an era of recursive self-improvement, what historically might have looked like only marginal advantages turn into enormous advantages. If the next generation model suddenly generates step function leaps in terms of their capabilities, then even just a period of a couple of months or one month could make all the difference in the world. This is the recursive self-improvement argument as well. It is. Well, it's the regulation of RSI argument.

24:14The second point also, I continue to think enforcement is being leveled at the wrong part of the stack. Fundamentally, aiming enforcement at intelligence is like thought policing, but for the AIs, not for the humans. I'd much, much rather see enforcement leveled at the action layer. Police what the AIs are doing or being used to do, not what they're thinking or how smart they are. You know, I've been thinking a bunch about the conversations going on. If we have incredibly powerful open-weight models, how do the top frontier labs make money? How do they survive against, you know, this onslaught of free?

24:53And the way I think about it, and I'd love your feedback, guys, is like a four-layer cake. So layer one is the top layers. Call it the wild stallions inside of open AI and anthropic, right? Unreleased, brilliant AIs. You can think of it as GPT-6. You don't let it out. You keep it to yourself. You use it for breakthroughs in material sciences, biology, building new businesses. This is what you and I have discussed, AWG, and Solve Everything. These models are going to create you trillions of dollars in other adjacent spaces, longevity, material sciences, energy, et cetera. So that's the first layer, the most advanced models you use for yourself.

25:35The second layer is the models on the Pareto frontier, right? This is GPT 5.6 Sol. This is Fable 5. people will still pay for that a little bit better than Kimi K3, right? So you'll make money, you know, providing the just next best model to people just above the open weight models. Layer three here is the open source models. And everyone gets to use them. They're good enough. They are fully commoditized. They're powering everything else. And then layer four, and we've talked about this before, is the fact that we have companies like Google, Meta, and X who have entire ecosystems, right? And they make their money on the application layer.

26:22So Meta has 3.5 billion active users using Muse Spark 1.1. When I'm inside WhatsApp or whatever, I'm not thinking what model am I using. The WhatsApp answers my questions. Google has 2 billion active users using Gemini, and this is before they get on Apple. And then OpenAI has about a billion on chat. So the fourth layer is they make their money when they provide their models to their communities. Yes? No? I think, I mean, reading, Peter, I think your narrative, what I heard you say, you were almost narrating the cost frontier of capabilities versus cost, starting from the upper right hand going to the lower left hand through different business models.

27:04I think it's an interesting narrative, but my bet, as with so many other things in life, everything follows power laws in the end. So I think just saying, well, there are these four or there are these N business models, in all likelihood, one of the business models is going to account for 80 plus percent of all of the free cash flow and all of the profits. And so I think just saying, well, there are these multiple business models is probably unrealistic. There's probably going to be just one business model that runs away with most of the profits. My point being, don't cry for the closed source companies.

27:38They have plenty of ways to make money, even in a world of - Why would we cry for them? I mean, my goodness, like two or three months ago, we were crying for everyone else who was going to be displaced, all of the labor, the service jobs that are being displaced by the frontier models. Now we're crying for the frontier labs. Cry for everyone. Salim. I think there's a layer zero in your stack, Peter, which is the compute and power. And I think that's where the infrastructure layer, right? I guess the Frontier Labs, as in with SpaceX AI, will own that as well. And Google will own that. I think over time, as you get more and more powerful free models, the value will accrue there.

28:19Because it depends where the bottleneck is. And it's clear that's where the bottleneck is. For me, when I look at this, what's happening with Anthropoc and OpenAI, this is regulatory capture in real time. Every major industry has tried to do this. The railroads did it. The banks did it. Telco did it. Big tech did it. And now they're trying to do it to kind of set up the garbage rails to then decide, A, to keep the government at bay, but also to keep other folks at bay. And so it's right there. And that has economic consequences. I don't think they'll succeed because the open wave models are moving so quickly, but it's a worth try if you were there.

28:52I don't know if you saw Dave Freeberg's comments on this. He had a beautiful soliloquy in which he said, you know, in the 90s, Netscape tried to own the server and the browser, the whole stack. And then Mozilla came out with Firefox and browsers went in for free. And then all of the value shifted to the application layer, Google, Amazon, and so forth. And I think potentially that's the same thing here. And if that's the case, then the fear about open AI and Anthropic running away with the show gets ameliorated.

29:25Dave Blundin:Well, I think that's exactly right. I think actually it's going to go up and down, per Alex's prior comment, where right now, you know, you've got$5,$10 trillion locked up in the labs with their models and the chip companies that don't actually make the chips. So NVIDIA and AMD, et cetera. but underneath the chip companies that don't actually make chips you have the fabs who are largely overlooked tsmc intel samsung and they've been skyrocketing they that's where the value is memory and the memory companies yeah so it's going down and as you said peter it's also going up to the use cases so i'm almost positive that if you look five years in the future there'll be many many multi-hundred billion dollar robotics companies, biotech companies, other use entertainment companies that don't exist today that have used AI to have a hugely impactful either user base, if it's entertainment, drug portfolio, if it's biotech or robotics line, you know, all the manufacturing, all that stuff is incredibly sustainable.

30:26Dave Blundin:What did I just overlook? Oh, the foundation model companies and the chipless chip companies. So that's why there's so much turbulence right now. The stocks are going up and down like yo-yos because no one's sure if they're actually going to have sustainable value in the end as everything moves to the upper and lower layers. But the entire ecosystem moves up and to the right, right? And this is where Elon comes in with saying our GDP is going to double-digit growth and then triple-digit growth. Let's go back to the original story, OpenAI and Anthropic teaming up in Washington, D.C. I mean, this is a regulatory capture story.

31:01Any thoughts on that? I think the open source, again, I've mentioned this now on two prior occasions, the Chinese Communist Party coming to rescue American capitalism from itself. I'm not a fan of regulatory capture or the duopoly scenario that we would have found ourselves in. I hope that the regulators and the applicable regulators are able to see now the vocal majority are interested in keeping the model layer competitive and are not interested in FUD, reminiscent of the late 90s, directed at open weight models, even if the strongest ones do happen to originate from China. I think that's the only way we all win.

31:47What's FUD, Alex? Fear, uncertainty and doubt. FUD. Thank you. Thank you.

31:52Dave Blundin:Honestly, though, I really think it's not a regulatory capture move. I think both guys are genuinely trying to create a safe and secure future world. Because remember, Sam is not even a shareholder in OpenAI. Yes, he runs it. Yes, it's his lifeblood. He has 400 vertical company investments that are overjoyed that Kimi K3 came out. All of our portfolio companies are overjoyed that they have access to Kimi K3. Blitzy was over the moon. This is the biggest boon. And so that's where Sam's economic upside is. But yet he's still going to D.C. to say, look, we got to have some rules. This is this is going to get out of hand.

32:30Dave Blundin:So I don't think they're out there to try and drive up their stock price. I think both guys are out there to try and make the world safe. Then why is it just them? Why isn't it everybody else? Why isn't it a summit to talk about the rules? Well, who is everybody else? Because there's only so many people that will let in on and Google. I mean, there are a few other players. Yeah. I'd like to make a slightly tangential point here. I want to echo what Jensen Huang said, which is he made the point that open models will make the U.S. stronger because you're building an ecosystem. Because you have universities, you have startups, you've got defense contractors, hospitals.

33:08As Dave said, every company is thrilled to bits you have an open source model that's this powerful with open weights. You can go manipulate those weights. And they're all, when you have the whole ecosystem, open beats closed, always. So this is the faster, the better. That was one of the theses of our book together, EXO. Open beats closed. Yeah. Yeah. Over time. I mean, it is amazing that we're living in this incredible demonetization world of intelligence, right? It's just falling through the floor. It's like 99.95 % cheaper over the last three and a half years, I looked at the numbers. And I think Alex makes a really important point.

33:46You don't try and regulate open versus closed. You try and regulate the capability. Yeah. And the actions and the and the outcomes. And I just for the life of me, I don't understand why we're shedding any tears for the profit margins of a couple of frontier labs. This is what intelligence too cheap to meter is supposed to look like. Intelligence is supposed to get cheaper and capitalism is doing its thing and creating competition and driving profit to zero. This is what we want to happen. And full disclosure, I don't own any of OpenAI or any Anthropics, so I'm not shedding tears for that. I don't think any of us do.

34:24Do you, Dave?

34:26Dave Blundin:Not that I know of, but I have a lot of indirect stuff. And Alex, I know you just own the index, so you're set. Just indices. Yeah. All right. Let's go to our next story. And it's one we just we sort of started discussing. Yesterday, July 27th, Kimmy K3 went live for a global download on Hugging Face, a frontier adjacent openweight model that anyone anywhere on the planet can download for free. No API key, no gatekeeper, no revocation switch. You know, once these weights are downloaded 10 ,000 times, they are free. There's no undo button. Kimmy K3's official Hugging Face repository showed 2 ,500 downloads in the first two hours.

35:04And the research I did shows about 100 ,000 downloads in the last 24 hours. I downloaded it. Dave, Alex, are you both?

35:14Dave Blundin:Funny story on that, Peter, because we had a whole bunch of polling agents that were pinging it every 15 seconds because I was worried that it would go away. Yeah, so was I. So I didn't realize a bunch of our companies also were doing the same thing. So of those 2 ,500 downloads, we had dozens of them from here. But mine went through with no trouble. But right before it came out, the whole page went to a 404 error. I saw that. Yeah. Did you see that? I was like, oh, my God, the White House intervened. This is not actually going to happen. Because I've been telling everybody, I think this is the biggest turning point in human history.

35:48Dave Blundin:Like you have an AI capable of self-improvement now out in the wild that anyone can use on your machine. This is massive. And I just feel like I may not get documented in the history books that way. It may be the outcomes of this that get documented. But this is really the moment in the history of humanity that I think is so pivotal. It was yesterday. But anyway, it downloaded just fine. I got it up and running on my own dedicated GPUs on modal. and it took less than an hour to get a fully functioning Kimi thinking and working 24 by 7. It's a little pricey, but it's, you know, it's like 55 bucks an hour on modal to run at full throttle.

36:25Dave Blundin:But you can prop up 100 instances like in two minutes now if you want to, just through voice prompting. You don't have to have any technical skill at all. You can just go to modal, ask it to install Kimi K3, download it from Hugging Face, and start talking to you. And you're up and running in no time. It's mind-blowing. Alex, your thoughts? I looked at the architecture. The architecture, now that this is actually open source slash open weight, is pretty interesting. The most interesting thing I saw in the architecture, position embeddings are gone. This was one of the most critical elements of the original transformer architecture.

37:01It's gone. It's literally called nope, no position embeddings, nope. And it's interesting. You could ask, like, how on earth is a model like this that has a million tokens of context, supposed to know what it's looking at without context embeddings. You look a little bit more closely, the attention mechanism, Kimi Delta Attention, KDA, is basically a mini recurrent neural network at the attention layer. And there's a little bit of positional information or positional awareness smuggling going in via their attention mechanism, but otherwise like global position embeddings, gone. And my takeaway from looking at the architecture is if you look at the original vanilla transformer from attention's all you need, and then you compare it with the sorts of, this is arguably probably the frontieriest of open weight, open source models that we have available right now.

37:57So it's pretty instructive for a mere civilian to look at how it's architected, because this is the most capable open architecture model, I think, that most of humanity now has access to. Position embeddings seem like they're going out of the way. And more broadly, I think we're seeing almost a ship of Theseus architecturally, if you will, where the original Transformer architecture, you can still recognize the outlines of Transformer, but piece by piece of all of the original elements, the attention mechanism, The position embedding, the layers, the residual streams, all of the sparsity, all of the original components that made the transformer the transformer are getting swapped out for better versions.

38:41And so if you follow the path of continuous improvement, it looks like the same architecture. And even if you squint at it, you'd still recognize, OK, it's like multi-layer something that is attentiony. But if you look at the fine details, the frontier models now, to the extent that, say, this is indicative of what's actually being used inside OpenAI or Anthropic, if you look at the fine details, they're relatively unrecognizable relative to the original transformer, which I think is interesting. Do you think the U.S. lab will end up replicating it? Should we say stealing that approach? It's open source.

39:17So I don't know what license or IP is associated with a particular architecture, but of course they're looking at it.

39:23Dave Blundin:Well, the nope thing, too, rope is just sort of random positionally. It's rotating positional. Rotational position. But it's sort of like if I have a million token context, it's giving as much weight to something I said a million words ago, which is like hundreds and thousands of pages ago. I said something and you're still thinking about it just as much as what I'm saying right now. People don't work that way. That's nuts. So when they got rid of Rope, they put in Nope, but Nope actually has this fading memory now. So something I said a long time ago gets less weight than something that's more recent.

39:56Dave Blundin:Obviously, like that's so obvious. But that's the beauty of open source. Some guy in China can say, this is freaking obvious. Let me try it. Oh, my gosh. It works. Of course, the other AI labs are going to adopt that immediately. It's just flat out better. The other thing that's really blowing my mind is the attention layers. you don't need them later in the thought process. So when you get to layer 100, 120, you can actually eliminate intention entirely and get almost the exact same result out the other end. But faster. But faster. But what happened there historically is the people who invented the original transformer algorithm just put a four next loop around it.

40:38Dave Blundin:Because they're just, you know, we're writing code by hand back then. It's really hard to try and make different, you know, different logic layer by layer. It's simpler. I mean, in defense of the original attention is all you need team, the original vanilla transformer was just alternating attention and dense linear layers because it's simple. It's simple. It's simple. And also with that few layers, you're really focused on just getting the text to mean anything. Now you've got deep thought. It's just so cool. I've got a couple of comments and a big announcement. Yeah. Comments. A model that you can control locally is way more valuable than a marginally smarter model that you have to access through somebody's API, right?

41:17So organizations now can fine tune their proprietary knowledge around it, put it into secure environments and totally avoid sending any sense of information to the cloud. This is going to be huge for regulated industries and sovereign applications and all sorts of stuff. So remember, Peter, a few weeks ago, we did this, we announced this pilot for the organizational senior. We had almost 400 applicants. We picked 10, so we're running the pilot with them. With the launch of this, I think this is one of the biggest things we'll ever see from a business and application perspective. So we're launching a new program for 30 companies because the big question every company is asking is, what's my strategy?

42:02And it should be, what do I do on Monday? So we're going to answer that question. And we're going to help people weekly just start implementing and rewriting their organizations on the edge. So we're accepting 30 companies into this. We'll put a link below. Where do they go to learn more about it? Go to openexo.com. We'll have a link there. And we're going to give preference to the folks that applied to the original pilot because they were first. and we're going to take a chunk of people and then just start helping to rewrite themselves. Because we did another round of calculations. And the original premise we had is if you rewrite your company in an AI native way, you should end up with about 100x performance than you had before.

42:44100x.

42:45Dave Blundin:This is going to be a goldmine for you, Salim, because nobody up until Kimmy really cared about speed in any corporate environment. They were like, oh, this stuff is super cheap. You know, we'll just use it. We're not doing much with it anyway. So then everyone starts token maxing. All of a sudden, people are looking at their corporation and they're saying, oh, my God, my token costs are actually going to be bigger than my payroll by the end of the year. And then if I forecast out two years from now, my token costs are 10 times my payroll. Speed does matter. But there's an easy, easy 10x and maybe 100x, like Salim is saying, just by tuning it to what your business needs.

43:21Dave Blundin:Get rid of all the cruft. Use these new streamlined models. Tune it to just what you're trying to achieve. You're looking at 10 to 100x. And so now every corporation needs to figure out their strategy. And Salim's business is going to be like sold out. Will you still come on the podcast when that happens? We will still come on the podcast because thank God we've got our community of 50 ,000 people that can help with all this. If I had to help, I'd be bald in two seconds. Oh, wait. But what we're doing with these CEOs is saying, okay, let's pick one process that's going to help you radically increase revenue and take one workflow that'll help you radically reduce cost.

43:55That gets everybody excited and rebuild that native and then do more and just start moving things over. And so we're super excited about where things go.

44:02Dave Blundin:Franchise it, Salim, so all our podcast listeners can start a branch of VXO. Well, that's what our community is all about. Oh, is it? Okay. Yeah, everybody in our community is an independent contract. We have no consultants on staff. This episode is brought to you by Blitzy, autonomous software development with infinite code context. Blitzy uses thousands of specialized AI agents that think for hours to understand enterprise scale code bases with millions of lines of code. Engineers start every development sprint with the Blitzy platform, bringing in their development requirements. The Blitzy platform provides a plan, then generates and precompiles code for each task.

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45:18This is the moment AWG's been waiting for. It's the discussion on Claude Opus 5. So right in the middle of all of this, Anthropic Shipt Claude Opus 5, this is their fourth Claude 5 generation release, and it approaches the frontier intelligence of Fable 5 at half the price. It becomes the new default for Claude Max, priced at$5 per million token input and$25 per million output tokens, unchanged from Opus 4.8. You know, I made the switch immediately on Skippy for myself. Anthropic calls it the most aligned Opus model yet and their strongest model for scientific research. I'm going to go to the slides now, Alex, and walk us through what this means.

46:02How strong is Opus 5 and how excited are you about it? I'm somewhat excited. I'm not over the moon. I'm not as over the moon as I was about Fable 5 becoming available. Fable 5 is incredible. Opus 5, I think it demonstrates, if you look at the benchmarks, so look at the benchmarks. For those who aren't looking, I would say the benchmarks, the evals that demonstrate the strongest performance, and I don't think this is a coincidence, for example, ArcGIS 3, which is focused on the ability to solve interactive visual problems that humans find easy, but AIs have historically found hard. It went from 1.5 at Opus 4.8 up to 30.2%, which is, as of this moment last I was tracking, the highest official score from a baseline model on the Arc AGI 3 challenge.

46:58It's a visual code intensive challenge, something else that's intensive, developing front end software. My overall whiff from using Opus 5 quite a bit is there was maybe mild optimization toward front-end development and anything that touches the nexus of vision and code. Historically, including with Fable 5, if you ask it to generate an image of something, you ask it to generate a chart, it does moderately well. I think with Opus 5, just trying to read between the lines of capability changes that I see, I think Anthropic is attempting to, given that the Opus series and Claude in general doesn't do image generation, they're trying to lean in a bit to some of the gaps at the intersection between Cogen and Vision.

47:48And I think for uses of mine, I still, honestly, I still prefer Fable 5, even though it's more expensive. And even though if you look at, say, the Artificial Analysis Intelligence Index, if you look at their overall chart of performance versus cost per task, according to that chart, Fable 5 is below the frontier. It's slightly below Opus 5 in terms of their capabilities and a lot more expensive. Despite all of that for day-to-day usage, when I use Claude, I still prefer Fable 5. But I'm very glad for one thing about Opus 5, which is it doesn't shut you down as frequently if you ask anything that it misconstrues as being a question about biology or a question about cyber attacks.

48:34Dave Blundin:So, Alex, I have the exact same experience, 100%, the exact same experience. But then I look at these benchmarks. There's a whole bunch on these charts. Yeah. And they seem to tell a different story. Yes. How is that? How do you reconcile that? I'm a little bit scared that there may have been some mild bench maxing here. That's what I was politely gesturing at. These seem to be benchmarks that are involving cogen and or imagery or vision and living at the intersection between them. Some of them, like if you look at Humanity's last exam, there, granted, it's saturating anyway, but the performance improvements are a little bit milder.

49:15So, for HLE, you see from Fable 5 with tools, 63.9%, a modest increase to 64.7 % with tools with Opus 5, and actually a decrease without tools, which is also maybe a sign that there's been a bit of, again, not bench-maxing because it's still, I've used it extensively, it's still very well-rounded. it. I don't want to accuse it of broad bench-maxing. But if you look at the drop relative to Fable V for legal or health or some other areas, obviously there was some sort of distillation. This is the type of distillation that is under the present regime welcome and not disdained. So taking a larger model and using it to teach a smaller model, a more cost-effective model, there was probably a lot of Fable V or Fable series or Mythos series distillation down to achieve Opus 5.

50:11But the overall sort of distribution of tasks, definitely from interacting with it for a while, feels biased towards cogen and visual stuff and away from general capabilities outside that. So here's our next chart, agenda coding by effort level. You want to walk us through this? Yeah. So we're looking at everyone, at least in the industry's favorite form of scatter plot. So So cost on the horizontal axis, performance on the vertical axis. And what this appears to show is that Opus 5 is both stronger in terms of absolute score and cheaper, that's the horizontal axis, than Fable 5 and Opus 4.8. And interestingly, it appears to be on the same cost performance frontier approximately as Sol.

51:02So I think the subtext that we're supposed to get from seeing this chart from Anthropic is that this should be read as a direct competitor for Sol, which is interesting and slightly, I think, unnerving given that, again, Fable 5 anecdotally seems to give better performance. All right. Let's go out to our third chart here, novel problem solving by cost. And I love this concept. So, this is just wild. Yeah, please. Yeah. So, ArcGIS 3, again, is a challenge that is primarily focused on the ability to solve sort of animated voxel problems. Tetris, for example, if a person had never seen a game like Tetris before with a bunch of blocks moving around and you were trying to do well at Tetris, it's a rough analogy, but that's approximately what Arc AGI 3 is like, animated block world challenges.

51:56So what's really striking, and Dave, you and I have talked about various attempts by pure scaffolding layer parties to just completely saturate ARC AGI 3. According to the official rules, I think there are limitations on how much scaffolding you're allowed to get. And so this is just the raw model being injected in. But what's interesting and what was, I think, especially striking in the Opus 5 performance, this is as relayed by the ARC Prize Foundation organizers, is that it was reasoning algebraically about the visual challenges. So it was handed a visual puzzle involving blocks, and it started to reason.

52:37If you look at some of the founders of the ARC Prize, they will go on forever about how this is actually a prize that tests the ability to do what's called program synthesis, to write programs from scratch in response to novel problems. And so, stunningly, what Opus 5 was able to do was to take a visual problem with a bunch of what to humans look like objects, and it represented the objects algebraically in software and basically did math on the objects in order to solve the problem. This is the first time that any, to my knowledge, anyone's ever seen a frontier model ever do that. A novel approach that was not guided by anybody.

53:16This is its derivative strategy for doing this. That is, unless Anthropic was bench maxing on RKGI 3.

53:24Dave Blundin:Okay. I think that scaffolding argument, though, is really, really important because if it holds up, I tried to replicate it because you can get 98%, I guess, on RKGI 3 if you give it a reframing of the way it interprets the puzzle. Right. And if that holds up, that gives inspiration to a billion entrepreneurs who can take something like protein folding or drug discovery or mechanical design of robot arms and say, Fable 5 can do this or Opus 5 can do this, but I gave it a better way to think about the problem. And now I tripled its intelligence within that domain. So that opens the door for scaffolding improvements in all these domains like biotech, where if you can reframe it so the AI doesn't have to work as hard to understand what you're trying to achieve and can maximize its tokens and its its parameter brain count.

54:19Dave Blundin:That is an entrepreneurial heaven. So I'm really hoping that result holds up. I tried to replicate it. I couldn't quite do it. I didn't work on it that hard, but I do believe it's possible. Did you get to the bottom of it? Is it real? I'm not certain, but the scaffolding advantage is very real. And my understanding is this is why ArcGGI 3 has certain rules regarding what can be submitted and what can't. But I think the elephant in this particular room, to your point is that scaffolding adds an enormous amount of value at the moment at any given point in time over the baseline model. The other side of that is the baseline capabilities tend to dissolve any scaffold.

54:55So today's scaffold is tomorrow's baseline capabilities.

54:57Dave Blundin:Well, I tell you, if that holds up, and I think you're right, I think it will, next semester, every university in the country should have a class called scaffolding. And everybody should have the opportunity to learn how to do this, because that is the power tool of all power tools for any entrepreneur. And so what is it now? It's coming up on August. You have 30 days to get your class curriculum together and launch it for next semester. With prompt engineering as a prerequisite. Alex, let's hit these next two charts and then watch the call of duty. I have a quick comment. Something I noticed was that 4.8 came out on May 28th and 5.0 came out just now.

55:34So it's not that much of a better model, but the efficiency has gone up by twice as much. So we've seen a 2x. And we were saying 10-week doubling price performance for AI this year. It's eight weeks now. It's a model release every six days on average over the last three months. It's unbelievable. Yeah, this is incredible. The other thing I noticed was in the grid, you've got different models that are becoming really good at different things like legal, health, coding, et cetera, which I think will continue. Alex, these next two charts? Yeah, so this chart is interesting insofar as it seems to support the hypothesis that there might have been mild bench-maxing on ARC AGI 3.

56:17So this is a chart by a third party that evaluated Opus 5 on an Arc AGI 3-like game involving a similar genre and discovered actually the performance jump was not material versus, say, Fable 5. So, again, not quite sure what was going on with Arc AGI 3, but that was by far the most prominent increase that we saw from Opus 5. Interestingly, a benchmark that Anthropic did not highlight was frontier math, which is, I think, maybe in some sense a better bellwether for advanced reasoning capabilities by the models. I had to check this independently, and actually, Opus 5 demonstrated inferior frontier math performance relative to Fable 5.

57:05So, again, Fable 5, still my favorite cloud model. All right. Last one here, the live leaderboard. Voxel Bench. So here we see Opus 5 now earning third place, just behind Fable 5 on Voxel Bench. Again, visually intensive tasks, but at a much lower price. And interestingly, but perhaps unsurprisingly, Sol from OpenAI still carrying the lead on this. The reason why I'm not that surprised is visually intensive tasks are an area where I would naively expect OpenAI to be doing a better job because they've continued to invest in image generation, whereas we've seen no generative image capabilities at all, shockingly, from Anthropic at all.

57:47They're busy maximizing the value, the revenue per token, which leads them to code and not to image. And I bet you were going

57:53Dave Blundin:to see... As a practical matter, you know, anytime I'm doing something complicated, I'm working in Fable 5, working in Fable 5, getting a lot done. If I want to see an architecture diagram, I just take the entire thing and dump it over to GPT and say, make me my architecture diagram. Fable 5 is so bad at it. But it does so much work for you. You get confused very, very quickly. And you want to see a simple visual summary of everything going on. It's just so bad. But GPT is amazing. My guess is Grok jumps to the top of this leaderboard in the next release. I mean, Elon's been speaking about that.

58:25Speaking about imagery, this made a viral loop on X. This is Opus 5 recreating Call of Duty from a single prompt. call it a one shot if you would let me go ahead and hit play on this

58:50Dave Blundin:Remember these demos 30 days ago just look like absolute garbage? Yeah, this is incredible. Look at how much is crazy, the rate of improvement. Well, what's amazing to me, I mean, this is sort of the converse, for those who can't see, this does look like Call of Duty. The converse of not having native image generation abilities in defense of Anthropic is that if you look at the entire physical world and you say, well, everything is just code, including code that generates photorealistic video games, then you say you don't need native image generation abilities. You just need the ability to generate photorealistic 3D environments like Call of Duty and you're all set.

59:28Huh.

59:29Dave Blundin:Yeah, the truth is in there somewhere. It's kind of in the middle, I think. But I think really clearly Anthropic cares about recursive self-improvement purely and only. And so they'll build anything and train on anything that helps the ASI. It's the race to ASI. So I think an important article that I just added for our listeners is while we're talking about Claude, I don't know if you heard the story that a significant number of Claude chats were found publicly searchable on Google this past weekend. So a Reddit user discovered that by typing a search operator site colon Claude dot AI slash share into Google, it surfaced a long list of shared personal data, including personal health records, private documents, key names and telephone numbers.

1:00:17Apparently, this originated from Claude's share chat feature, which allows users to share links of their Claude chats between friends via URLs. Did you track this, Alex? Yeah, I saw the story. And on the one hand, it's disappointing to see any information that would be expected to be private find its way out into the public world. Not a fan of that. On the other hand, I think there's sort of another side to the story, which is a feature that was intrinsically designed to be social in nature. Shocked, shocked to see gambling in this establishment, ultimately finding its way into the hands of other people.

1:01:06I think there are two sides that one can see here. Yeah, but I think one of the issues, one of the arguments, and we saw it on the rant a few episodes ago, is that when you're using these models, your competition is in some sense seeing your data and learning from your data. And it's something people need to understand. It's the argument for on-prem. Salim? No, I just doubled down on the same thing. You've got to own your own proprietary data. And I think over time, people move everything to on-prem that's sensitive in any way. Dave, any comments on this before we move on? Nope.

1:01:44Dave Blundin:All right. I think it's just incredible, the rate of change. Just go back and look at an episode from two or three weeks ago and look at the rate at which one shot can create things. Oh, I'll make one other comment, the holodeck. You know, our holodeck is up and running here. I want to see it. You've got to come check it out. It went from like okay to mind-blowing in just a couple of weeks for the exact same reason. You can one-shot a world while you're – and the audio and the visual is so good. The fact that you can one-shot, I think what this will do is – I don't think it affects the commercial games that much, but it allows you to do experimentation in an amazing way because the cost of experimentation just went to zero.

1:02:22So you'll get so many more prototypes.

1:02:24Dave Blundin:That's why Jardis is coming so soon. Yeah, yeah, that entire – that Iron Man, the vision in that movie was so precious. But it's going to be exactly like that and fun. I spoke to Jon Favreau today, the producer of Iron Man 1 and 2, getting him to come to Moonshots Live. We've got amazing, amazing. Yeah, yeah. Elon introduced us. So let's move on to our next story. This was a story, Alex, that you wanted to raise here. So it's the idea, which is obvious, that global AI diplomacy is coming. So the Financial Times is reporting that China's leader, Xi Jinping, is wielding AI as a tool of statecraft, using it as leverage in China's diplomacy across the global south in a strategy that the Financial Times frames as Pax Silica.

1:03:13I love that. While Washington is debating open versus close, Beijing is out in the world country by country exporting AI as an instrument of influence, offering models and infrastructure to developing world that wants to leapfrog what they currently have. AI is becoming an instrument of soft power. Whoever supplies the models and the infrastructure to developing world shapes the next few decades, I would say the next century of global alignment. So, you know, my concern is if the U.S. over restricts, the developing world is simply going to adopt whatever frontier adjacent open models are there.

1:03:50Salim, your thoughts? I can't stress this enough. The whole power of the U.S. is its open and very broad innovation ecosystem. If you create a restrictive open model policy, it's going to be strategically like a self-owned and shoot-your-own-foot of an epic level. Because you're going to protect a small number of domestic labs while giving the entire opening ecosystem, global south AI ecosystem to China. If you want leadership in an exponential era, it has to come from the largest network where everybody's using your tools for stuff, not protecting its strongest incumbent. Openness is not a philosophical preference anymore.

1:04:35It's the tool of soft power. And the U.S. has already lost that in diplomacy and USAID and other stuff. If they close up the open model policy, it's going to be really disastrous for the future. And I don't think they will. I mean, I think we're effectively splitting the world into two AI empires. We should be having a discussion, though. Yeah.

1:04:56Dave Blundin:Yeah. Alex? Well, there is no, as of right now, there is no U.S.-based option at all. You can take everything you just said and swap out the word model and put in fighter jet. Like, should we sell F-16s to XYZ countries? It's a no-win question. Like, you have to pick and choose. But if we don't sell the F-16s, they'll buy Russian and Chinese fighters. And that'll support the creation of more of those fighters. Yeah, but you're also selling an F-16 to like, it's exactly the same problem. There's no easy answer to it. But right now, there is no U.S. open source model to compete with the Chinese anyway, which is kind of sad.

1:05:33Alex, your thoughts? I think, so Paxilica had already been announced by the U.S. before China announced its own initiative. And China, of course, announced many years ago at this point, Xi Jinping announced Belt and Road Initiative. And there's a certain extent to which it's far more, I don't want to say insidious, but far more ultimately invasive and controlling if a foreign country, say, if a foreign country loans you a bunch of money to build a bridge. OK, so you default on the loan that has a certain outcome. Foreign corporation that's basically under the thumb of a foreign government builds telecommunications equipment and deploys it to you.

1:06:17So now you have cell phones. The worst that they can do, they can spy on you and they can shut off your telecom infrastructure. Next level up. Foreign corporation that's heavily involved with foreign government injects superintelligence into the veins and arteries of your country. Now it's not just listening to you or not just loaning money to you. Now it's thinking for you. And I think that's a far more vulnerable position for the so-called global South to be in, regardless of which block or sphere of influence it finds itself in. And I can only imagine that the long term, to the extent there is a long term in the middle of the singularity equilibrium point is going to be pushing more, not just inference to the edge, which is what China, I think Chinese frontier labs would like with open weight models, pushing training to the edge.

1:07:11That I think is the equilibrium point. And curiously, I don't hear that many countries in the so-called global South agitating for domestically pre-trained models. But I do think that's where some sort of equilibrium could lie if there is to be an equilibrium. equilibrium. Can I tell a related story here? A few years ago, I was talking to the prime minister of one of the smaller Asian countries, and their big city had tripled. They needed much more ports to be able to receive more containers for the big, huge population. And they'd just taken a half a billion dollar loan from the Chinese and totally, totally mortgaged the future of the country.

1:07:52And I made the point to look, drones are kind of doubling in their every nine months and their price performance. If you waited a few years, you could have a drone pick up a container. You don't need a port. You could drone, you could have four drones pick up the corner of a container, which is average 20 ,000 pounds. And so you don't have to wait that long for drone doubling to get to a quarter of that weight. And then you just pick it up and put it on a flatbed truck or on a rail car and off you go. And they're like, damn, we just mortgaged the entire country because we You don't understand exponential thinking.

1:08:22And if you go back to what Alex just said, that goes up 10x when you outsource your thinking. And that's really dangerous. I think the safety and the security of the future will be in these open-weight models that give you back your sovereignty. Yeah, talk to California about its high-speed rail when you talk about it. Yeah, let's not go there. All right. So big news this week for my fellow space cadets. A successful launch of Starship 13. SpaceX has confirmed launch and splashdown, an incredible, incredible trip it made for Starship 13, their largest vehicle to date. It accomplished a number of key firsts.

1:08:59Let's run through them. First, it deployed 20 operational Starlink V3 satellites. They were connected to, they were tested in part. And these are the satellites that are going to deliver us a half a gigabit to a gigabit connection speed every place on the planet. You're literally going to have a better connection from space than you have from your home Wi-Fi. They did an in-orbit relight of one of the Starship's Raptor engines, critical for the upcoming Artemis missions, and a successful soft landing on the Indian Ocean with the vehicle remaining intact, which was extraordinary. I'm going to watch two of the videos here.

1:09:35Let's share them because they're just fun. This is space porn. All right, let's take a look at the launch first. It's important. You got to love this drone footage from above the launch at Starbase. Space is big. This is such a beauty. You know, it has a high degree of beauty. Oh, my God. So gorgeous. Yeah. I remember when I was with Elon and we were talking about, you know, the Starship first stage and saying it's the most contained energy that you can ever experience other than a nuclear explosion. All right. And very importantly, the landing, which was the big news on this particular mission.

1:10:15Let's take a look at this sequence. About 10 seconds away. I mean, look at that footage. Unbelievable, baby. Let's see if we can get this thing in the water.

1:10:25Dave Blundin:I got the link from you guys. I was like, yeah, yeah, I'll check it out. And I was like, wow, I got to watch this whole thing end to end. Note the high-res. Ignite the Raptor engines. Yeah. Look at the amount of stress. You can feel it. You know, from these, because you can see like things flexing and warping. Soft landing. Down to one.

1:10:51And we're in the water. Floating in the water for full recovery. Soft slashed down in the water. This is where they thought it would explode. Well, it has in all the previous missions. What happened there? It was so soft. That is a first. Well, it's got excess fuel. Excess fuel.

1:11:08Dave Blundin:Yeah, and when it hits the water, you know, it punches the little holes or whatever in the sides. So that's where it usually explodes. You know, what I'm excited about in particular is Elon tweeted that because the landing was so precise, that Flight 14, he's likely to capture the Starship on the Maxilla device, right? The large chopsticks that come in and grab the vehicle. Yeah, so, I mean, that's a flight. I want to go to Starbase to watch the return. It's going to be awesome. Let's take a second, just talk about the abundance story here. I mean, the cost of launch is plummeting. And let me just give you the numbers real quick.

1:11:42The space shuttle was roughly$54 ,000 per kilogram to orbit, right? So think about, you know, taking a gallon of water, of milk to orbit,$54 ,000. Falcon 9 dropped it to about$2 ,000 to$3 ,000 per kilogram. And Starship's target, and Dave, you and I were discussing this with Elon back in our January podcast, it's between$10 ,000 to$100 per kilogram. I mean, just extraordinary.

1:12:10Dave Blundin:Well, it's also, it's inspiring, the amount of incredibly cool stuff that you can build now, specifically because all the feedback and control and all the remote, you know, intelligence is easy now all of a sudden. You know, we saw the Unitree robots in the last podcast, and they're just beyond cool. And that robot that, you know, is plummeting down the side of the mountain with the wheels, like crazy cool. And then you got the starships, which is the amount of possibility is so exponentially bigger than it was just five years ago. And all the data is on Grok for building starships, which is extraordinary.

1:12:48Dave Blundin:Also, I'm working on a photonic computer to run our new neural nets. And all the parts, it's actually giving me part numbers to order and saying, this vendor in Germany will make this lens for you in exactly this way. Do you want me to write up the specs? I'm like, sure. Can you order it and build it for me too, please? I mean, literally, it'll arrive in boxes. I still have to open the boxes and assemble it. If you're an entrepreneur out there and you've been looking for where to go build, I mean, building hardware, you know, Ben Horowitz, who's a friend of the pod, and we're going to have him back on the pod for one of these episodes.

1:13:26He's the co-founder of Andreessen Horowitz. You know, he wrote the book, you know, Hardware is Hard or Effectively. and the hard things, was it the hard things about hard things? You know, and it used to be that building anything, I built robots in high school and college, and it was tough. Now you can 3D print parts, you can iterate rapidly. So if you're an entrepreneur looking for something to do in the world, you know, what's missing? What do you wish existed? And you can actually use these models to design it, order the parts and start building.

1:14:03Dave Blundin:Yeah, I've got I've got an incredibly cool robot that's giving the top of my pool. It just has eyes and it finds leaves and it just goes and picks them up. But I want someone to build one that dives to the bottom and just just goes down, picks up whatever an acorn, brings it up, throws it out of the pool. I bet you could vibe that up now. Just just crank. Alex, if there's anybody who's as big a space enthusiast as I am here to you. I mean, did the flight bring tear to your eyes? oh i wasn't crying but space is big and i was delighted did you see peter the views from the starlink satellites that were posted later like that that was pure science oh my god it was it was basically uh looking at starship in orbit from the descending booster from a distance yeah yeah that that was incredible that's like something out of star trek or the expanse i was very impressed with that i i certainly hope that this flight 13 ends up in a museum at some point given the soft splashdown.

1:14:59This is a historic first. Hopefully, the SpaceX team will use this as an opportunity to get a good look at the heat shield, which is interesting. If you noticed the drone feed, the moment the splashdown happened, it was just zooming in on all of the heat tiles, looking for damage, trying to analyze the structure, presumably because the team was worried the whole thing might explode a few seconds later. So they were getting whatever footage of the heat shield that they could while they had time, but now they're going to have a a ton of time. So it's very exciting. Yeah, in the past, after the vehicle, after Starship, you know, detonated from the onboard fuel, and that was expected, you know, people say, oh my God, it failed.

1:15:34No, it didn't fail. It did exactly what they expected it to do. They'd have to go diving and find pieces of it to try and reconstruct what happened. And the heat shield here, I mean, people need to understand the amount of energy being dissipated. These vehicles are traveling at 17 ,500 miles an hour in orbit, have to dissipate all that safely and come to a precise landing. It's insane. Salim? I just love the fact, the ongoing flight after flight, he's viewing any kind of failure as information. And you don't get embarrassed by it. You take the data, you learn, and you do it way better next time.

1:16:08And nobody else does that. Yeah. It's exciting. We are, as Alex, you've said many times about the speedrun Star Trek. What an exciting time. Count on it. Yeah. I mean, the only thing better is if we discover that we have access to all the alien UFOs and we can go to jump to light speed. All right. Let's stay on the science theme. Our next story is in the world of brain computer interface. Two stories this week. The first one comes out of Science Corporation. Full disclosure, it's one of my portfolio companies. I love this company. And it's restoring vision for the blind. The company is run by an amazing entrepreneur, Max Hodak.

1:16:46He's the past president of Neuralink. and someone who I've had on the Abundant stage a number of times. Science announced that his first product called Prima, P-R-I-M-A, I'm sure it's an acronym, has been approved for launch in Europe. So Prima is the first BCI device approved for restoring detailed vision in age-related macular degeneration that destroys a central vision of your retina. They just earned what's called a CE mark, which means it complies with European safety, health, and environmental requirements. Let me show an image of what this looks like, and we can talk about how it works.

1:17:27So here it is. What you see there is a pair of glasses that are capturing the image, and then they're beaming back the image via infrared to that little, call it rounded square that's sitting behind your retina. So the signal from that Prima implant behind your retina is turning it into electrical signals and giving it to the remaining retinal cells. And those then get transmitted through your optic nerve to your visual cortex. And it basically restores your central vision. The amazing thing is the patients who've gone through this have experienced five lines of improvement on a standard eye chart after 12 months.

1:18:13So this is a godsend for so many people with macular degeneration. Any thoughts here, Alex? Yeah, so a few things. First of all, the overall setup is, in the spirit of, as I've commented in the past, the singularity is essentially all sci-fi tropes happening everywhere all at once. This is reminiscent of an ocular implant from the Borg, quite literally. It has an external module that, for those who are watching, can see here, so an external camera. that then captures the information broadcasts in human invisible near IR to this chip that sits immediately behind the retina. It's interesting insofar as Max, who was, of course, basically running Neuralink previously.

1:19:01This is a much even though the retina is part of the central nervous system. This is a move away from the brain. But Neuralink, which also has its own approach for curing blindness called Blindsight, seems to primarily be focused on injecting less on the optic nerve, more just focused on direct brain stimulation, direct brain intervention. Yeah. It's interesting to me that Max, with this new venture of his, is sort of moving away from the brain, albeit still in the CNS. And I do think the further you get away from direct brain intervention and placement of electrodes, the easier it is to scale up a mass market consumer device.

1:19:50In this case, obviously, it's obviously surgery on the retina, but I'm very optimistic that advances in ultrasound advances in wearables, A variety of other completely non-invasive advances will enable vision restoration without even needing to have retinal surgery in the next few years. You know, I wrote a chapter about Max and science in my book, Where is God's? And in particular, you know, giving vision back to the blind is biblical, right? It's huge. It is. It's amazing. And God said, let there be special. What he's doing, and so, you know, it's interesting, Prima as a product is his stage zero revenue generating engine.

1:20:31So one of the things that a lot of entrepreneurs do incorrectly is they jump straight to this, you know, massive moonshot that will take them, you know, hundreds of millions or billions of dollars to get to without generating early revenue. So Prima is the means by which he's creating early revenue. He has an amazing BCI approach. I can't say a lot about it, but he's basically growing neurons into the brain, which don't, you know, the issue with Neuralink and many of the BCI companies is their electrodes destroy thousands or hundreds of thousands of neurons when they're placed into the neocortex.

1:21:10but neurons actually can grow into the brain. So he's got an approach of an interface between electrical circuits and neurons and neurons growing into the brain and then, you know, wiring together and firing together. Hopefully he'll disclose it. It's been in animal models and his plan is to get to humans, but it's an incredible strategy for the BCI world. BCIs are super competitive at this point. There are folks trying approaches at the CNS level, at the peripheral nervous system, direct brain stimulation, wearables, ultrasound, fMRI. And I think ultimately, by ultimately, I mean on the five to 10 year timescale, we're going to see something of a shakeout and we're going to discover what are the most ergonomic ways to interface with the brain.

1:21:58So I really hope that for Max's sake, that brain or that science rather does well. And I, for one, would welcome some extra neurons. Yeah. He thinks of it as an extra, you know, the corpus callosum is what connects the right and left hemisphere of your brain. Imagine having a third hemisphere of your brain that actually is connected to the cloud. I mean, that's the way he described it. Exocortex. I want my exocortex. It's extraordinary. Salim, you were saying? There are two things here that I found really interesting. One is the feedback loop, right? Once you have a feedback loop from a sensory back into the brain, et cetera, it learns very quickly.

1:22:35And I think we can see that over and over again in some of these recursive inner loop type applications. The second thing that occurs to me, which goes to your comment, Peter, about business models, is when you have an exponential and it's hard to predict out where the endpoint is going to be, it's not that difficult to look out two, four, five hops and say, what are the business models that may be enabled at each of those things? What are the use cases? So if you're an entrepreneur and you see a technology that's growing exponentially, now there's a dozen of them, you can pick your biggest passion, your favorite technology, look out where it's going, and then say, okay, at that price performance, what applications become enabled?

1:23:12And now you have a very viable roadmap for the future, exactly like the way Max is doing it. And that's going to be the future of companies and how they evolve.

1:23:21Dave Blundin:I really want to echo something Peter said there, too, about go-to-market strategy. because if you look at the most valuable companies in the world, so like an Apple, Google, Meta, and you look at their very first day and their very first product, the Apple One was a box of chips you needed to assemble yourself. And Meta was Facebook. It was a little face - At one university. Picture-sharing thing at just Harvard, yeah. And Google was a plug-in to Yahoo. It was a little search plug-in to Yahoo. They tried to sell themselves to Yahoo for a couple hundred million bucks, and Yahoo's like, you're not worth anything near that.

1:23:53Dave Blundin:But that's the reason Google is right. It's not worth anything near$100 million. Yeah. But these really humble beginnings for a go-to-market strategy, because, you know, we talk a lot about, you know, starships landing in the ocean. And people think, wow, I want to build a company that, you know, creates a new starship. But that's not how these things get started. You've got to start with a go-to-market that actually gets you an initial revenue. And if you really study the outcomes but trace back to the first six months, which not enough people do, like really study the details, the people, the characters, What exactly was that product?

1:24:24Dave Blundin:And then that starts you on the journey and you end up being Google, Apple. You know, we had Bill Gross on stage with us this past year at the Abundance Summit, and he's brilliant. And I love Bill. He's one of the most extraordinary entrepreneurs. He's created more startups that have gone public or been acquired than I think anybody else, period. And he has a great video on DLD, also on TED, which he looked at, I think it was 50 companies in his portfolio that succeeded and 50 companies that failed. And he asked the question, why did they succeed? Was it because the CEO was smarter or trained at an exclusive Harvard or MIT?

1:25:04Was it because they had more money? Was it because – what was it? And his conclusion at the end is an important lesson for all the entrepreneurs listening. It was timing. It was the companies that were there at the right timing that were able to survive long enough to survive forever would intercept good luck. So classic examples are Uber and Airbnb had been tried before. But when they launched in 2008, it was just after the recession and people were looking to make money. They were willing to rent their bedroom out, willing to go and drive a car. You know, our darling here, SpaceX, I mean, you have to remember, Elon in 2008 was effectively bankrupt.

1:25:47He had had three failures of Falcon 1. And the fourth one, which he scrambled to get money together, finally succeeded. And because the space shuttle had been shut down a couple of years earlier, there was a contract out. And he won a billion dollar contract in the in the crew resupply from NASA. And that got him going. Timing is everything. So if you can have an early revenue stream for your company that allows you to stay in business and intercept good luck, that's one of the single most important things.

1:26:20Dave Blundin:Yeah. Just survive. Just find a way of surviving. Elon was 18 years, 18 years from bankrupt to trillionaire. Amazing. But I mean, it took. Yeah. Did you see his tweet, past trillionaire or whatever it was, former trillionaire? A little plug here. Yeah, please. I mentioned this earlier, but we talked just now about the feedback loops. John Hagel and I have come up with a framework where it allows you to measure luck. And so once you have that feedback loop, that becomes very powerful. Yeah, we'll bring him on sometime and talk through it. It'll be useful for the viewers. Everybody, welcome to the health section of Moonshots brought to you by Fountain Life.

1:26:57We talk about AI on this Moonshot podcast all the time. One of the most important things AI is going to be able to do for you, besides educating your kids and helping you with your taxes, is making sure that you're living a healthy lifestyle, that you get a chance to get to 100 plus. I'm here today with Dr. Dawn Musalem, the chief medical officer of Fountain Life and a part of my medical team. Dawn, a pleasure. Great to hear. You know, the thing that people are concerned about most about living to 100 or 120 is their cognitive abilities, making sure they don't have dementia. And the numbers about dementia are problematic.

1:27:34Can you share what you've learned? Such an important point. And you're right. At Fountain Life, our members, the number one thing people are most concerned about is losing their brain health, forgetting the name of their child, forgetting the face of their loved one. And we know that when it comes to dementia, the conservative estimates are that 45 % are entirely preventable. What was amazing is with the advanced testing we're doing at Fountain Life, one quarter of our members had advanced brain age. Wow. But what was really awesome is, again, back to that prevention, when we partnered it with Healthy Living, this gives me chills, eating healthier, moving our bodies, sleep, optimizing sleep is so important.

1:28:11You know what we saw? we saw that we improved that brain age by 26%. That is a big, big number to show that the majority of those individuals were able actually to improve the brain age. And one of the things I love about Fountain is we're searching the world for the best therapeutics, the best approaches, and making sure we bring it to our members. So if having healthy brain function till 100, 120 is important to you, check out Fountain Life. Go to fountainlife.com slash Peter. Make sure you become the CEO of your own health. All right, now back to the episode. Alex, this next story is one that you threw out and happy to talk about it.

1:28:49It's our second BCI story. This one's out of Neuralink. The company just shared a video of people living with paralysis controlling a powered wheelchair using nothing but their thoughts. No joystick, no hand controls, just intention translated directly from the brain into the wheelchair's movements. I mean, think what this actually means. It's massive freedom. Let's roll a video and take a look at this because it's a beautiful thing. And we'll talk about what comes next. Through our clinical trials, we've been working really hard to give the world a brain-computer interface-powered wheelchair.

1:29:24It's designed for anyone with trouble controlling their wheelchair physically by translating their neural signals so they can control the wheelchair with their mind. What we've done here is we've developed a set of custom electronics to take cursor movements from a participant's imagined motions, translate them into analog signals, and then use them to directly drive and control all the functionalities of the wheelchair. This is the wheelchair control app, and we built a custom UI for our users. I can now move my cursor up and slowly move the wheelchair forward, or turn to the side, left or right.

1:30:00And as I get more and more into the ring, it'll go faster and faster. Really, we built the system with safety in mind. As you can see, if I let go, the cursor is slowly going back to the center. So that way, if a user ever becomes incapacitated, you know, they won't go driving directly to a wall. The cursor will allow them to go back to the center here. Alex, your thoughts and what comes next? Well, obviously, this is sort of a visual joystick via brain computer interface. Where this goes, it's hard not to extrapolate this going to full bodily control. Imagine giving people exoskeletons that they can control via BCI, paraplegics, quadriplegics, and basically restoring free autonomy in a physical world, all four limbs.

1:30:46I think that's pretty incredible. It's easy to extrapolate further than that. I think there's probably a sizable subpopulation in many countries. Certain folks would love meccas from anime, would be able to walk around in large robots, Sigourney Weaver aliens style. Or maybe even, I mean, I think the endgame for the motor cortex does look like some variant of partial brain uploading or something adjacent to that. that once we've fully decoded the motor cortex, we're in, I think, a stronger position to take some variant of human mind uploads, could just be behavioral uploads that are generated by pre-training foundation model off of large amounts, say, of fMRI or ultrasonic data, and being able to decode the motor cortex to perform useful functions in the world.

1:31:43That's a low bar. There are much higher bars that would be connectome-based. Something like that, I think we're going to see actually happen in the next five or so years, certainly by the end of this decade. And I think that's a major step toward, you know, in the short term, obviously taking people who can't walk, giving them powers of locomotion. That's now-ish. But in the next few years, it's giving exoskeletons and ultimately human uploads. You know, my answer to that, AWG, is that Neuralink connects these individuals to an optimist robot. right and they see through the optimist eyes and hear through the ears and then they move avatar your vision is avatar it's effectively telepresence you know you can be anywhere you know you can you can inhabit a optimist in japan if you're sitting there in boston i i think that is definitively coming probably over starlink i mean the singularity is here this is insanely fun yeah there were a few i mean in addition to avatar there was a i'm blanking on the name of that other sci-fi movie where people never left their their homes and only went out and interacted with each other via these tele robots i i think every sci-fi scenario plays out at once and i can guarantee you peter if if the scenario that you're describing comes to pass and probably will we'll find some country will a few years from now will be regulating uh the uh hikikomori if if you will, who only stay inside their bedroom and only interact with the outside world via BCI to tell a robot.

1:33:18So, so crazy, so fun, and so liberating for so many people. All right. Our final story before we go to our AMA here is regarding Elon's prediction that AI and robotics is going to make money irrelevant within a decade by 2036, he said. It's his post-capitalist vision. It's a world of radical abundance in which scarcity no longer matters. Money no longer matters. I talked about this with him when he was at the Abundance Summit this past year. Let's take a listen to this video, and then I really want to discuss this one because it has people both excited and fearful. I want to address the fear there.

1:34:00Money won't matter in 2036. I'm not sure that the people who bought your shares think that money won't matter in 2036. Well, what do you want money for? You want money for goods and services. Well, if that is so abundant that there's more, that the robots and AI are providing more goods and services than any human could possibly consume, what do you need money for in that case? I'll make a prediction, which is that deflation will be the issue, not inflation. because because as the output of goods and services increases um if the output of goods and services increases faster than money supply you will have deflation i think it's totally ironic this was an interview by the economist uh of the world's first trillionaire yes yeah gentlemen thoughts salim um you know i think the you're there's a couple of different threads here Thread one is we're reaching abundance and the cost of things will drop radically.

1:35:07But abundance in production doesn't mean you end up with abundance everywhere. Because you could have eliminated scarcity and ownership and access and location, and that would be amazing. But money is going to be relevant as long as you need an exchange mechanism. So as long as you need that to allocate stuff that's scarce, money is the means of exchange will stay. Let's remember there's three uses for money, means of exchange, unit of account, and store of value, right? And so this would hit a store of value to some extent. It would hit the means of exchange, some account, but the exchange unit will become really or unit of account, et cetera.

1:35:48I think the biggest challenge here is not that abundance is impossible. It's that if you end up in the wrong way, abundance will get captured by a few big companies, which is where the wealth inequality has been coming in. I think the hugest opportunity as we distribute and democratize, Peter, back to your words, technology, you also democratize opportunity. And I think the best framing I've seen for any of this is, can we get abundance of opportunity? And I think that's where technology will take us. Yes, Alex, you've made that point, you know, abundance of freedom. Yeah, I construe Elon's comments as, I'll use the technical term, Star Trek economics.

1:36:30I think he's arguing that 10 years from now, we'll live in a Star Trek economy where, and I think there's some fine print on this. I don't think he really means to say everything has been demonetized. I think what he really means, I think what he's shorthanding, is that most aspects of daily living, as we would construe them today in 2026, will have been demonetized 10 years from now. So food, shelter, health care, utilities, education, entertainment, all of these things will have been demonetized, and you won't need money because we'll be living in an abundant in that sense future. But I think there will be many things still that are not so abundant that they've been demonetized 10 years from now.

1:37:17Like, I don't know, if we have the ability to go to another star system, probably still somewhat expensive. Or spend a week on the moon, maybe there's some price there. Or just owning some scarce resource that's antique, collectible. This is not investment advice. But there are some things, I think, that will resist demonetization for longer than 10 years. If I had to put my finger to the wind and guess when demonetization hits the total economy, don't hold me to this and not investment advice, doubly so for anyone investing in 30-year treasuries, I would guess approximately 30 years out. A funny story, AJ Scaramucci, who was one of my interns, one of my Strikeforce members, started a company collecting obviously scarce things like Tyrannosaurus skeletons and Pokemon cards.

1:38:12I know AJ pretty well. AJ, if you're watching, I'm not sure what's up with those Pokemon. Yeah, he's collecting the best first edition comics and so forth. I mean, it's an interesting strategy. But I wrote a piece about this after Elon published it, or after we had the conversation with Elon. And the best way I think this works is we're going to end up providing some level of UBI. I call them COVID checks, right? $3 ,000 a month, which today gives you a bare minimum level of living. But all of a sudden, in this scenario, AI is today already and will be in the future the best physician. And Optimus on AI will be the best surgeon.

1:38:53And the cost of that is capex and electricity. And then autonomous vehicles, we're going to see not just one or two, but a dozen cars of service AVs, right? Beating each other out to bring the cost down. And so all of a sudden,$3 ,000 goes a lot further than ever before. You want a house? Great. A fleet of Optimus robots will build it for you. So it's a massive demonetization in the future. There's a monster elephant in the room, though, which is the radical transition this is going to require in our fiat currency systems, because all our fiat currency systems are absolutely dependent on scarcity.

1:39:32If you move to abundance, we have a huge challenge. We've mentioned this before on the pod. This is Jeff Booth's observation. We actually should have Jeff as a guest sometime. He made the point that over the last 50 years, every dollar increase in GDP has come with a$4 increase in debt. Okay? And I use a metaphor for this. So imagine you decide to build a TV factory. You borrow$10 million to build a TV factory. And your business plan says, I'm going to pay this back if I can sell the TVs at$1 ,000. These shall be able to pay back the loan. The problem is that a year later, that$1 ,000 TV can only be sold for$500.

1:40:08And a year later, it can only be sold for$250. You're never paying back the$10 million. And this is how we're growing the global economy. So this is the printing money problem that we have, where we're just radically printing money to keep the whole thing afloat, which is why assets are so important to own rather than cash, et cetera. Cash is deflating at about 14 % a year. This is going to require a wholesale shift in how we measure the economy, which is why people are pointing at crypto and Bitcoin and other things. But this is the part that's going to kind of cause a massive problem for every currency in the world and every central bank in the world.

1:40:45It's kind of pang-nicking right now because your only resource is to print money and then you have inflation. And then everybody go, oh, my God, we can't have inflation. And so this is a circular wheel that can't be gotten off of. And the whole thing is going to come to a plug. If only the Federal Reserve had access to the same superintelligence that the rest of us did, they could design superintelligent fiscal and monetary, especially policy. That's what you're going to have to do. It's a great point.

1:41:09Dave Blundin:You know what I find incredibly interesting is that all of these AI visionaries, Elon, Demis, Dario, they all have played Civ, Civilization. They all speak in terms of civ. And they've all read Ian Banks, the culture series. And the culture series, the entire book series, is about the post-abundant world and what it will be like. So when they get together and brainstorm on the future, they're so totally on the same page about how this is going to work. So then they do an interview. Like Elon does an interview with The Economist or whatever. And he says, 10 years from now, so 2036, money won't matter.

1:41:51Dave Blundin:And they go, oh, my God, does that mean the exchange rate between the pound and the euro? And then they're like, we're going to make so much stuff and have so much abundance that it won't matter. Did you understand the implication? Like, who gives a crap about the exchange rate or the deflation rate? Like the degree of change that's coming over that decade is so massive that you just mentioned one little aspect of it. Like we don't care about money. It's just a tiny little component of this overall massive change. But all those guys are on the same page because they've all read the same sci-fi books.

1:42:28Dave Blundin:They've all like I get how this is going to play out. And there are different nuances to it. I'm not saying everybody agrees on every part of it. But what we're talking about is you don't care about the cost of things because you just take them off the shelf. It's ironic, given, Dave, that Ian Banks is Scottish. Scotland produces some of the world's best sci-fi writers. So it's interesting that The Economist, based in the UK, doesn't quite appreciate Scottish sci-fi. And then this tweet exchange occurs. Let me just read it. Darren Asimoglu is a Nobel laureate in economics. And he says, I propose a proposed challenge for Elon Musk, an opportunity to put your money where your mouth is.

1:43:07If money won't matter in 2036, why don't you pledge to donate your current wealth of approximately one trillion to charity no later than 2036? this would establish with great credibility your proposal goes on. And Elon responds, I'm actually going to do something along those lines. I thought that was pretty cool. I immediately texted him and say, okay, let's launch 10$1 billion X prizes to solve the world's biggest issues. Haven't heard back from him yet, but hopefully soon. I think he's planning something more along the lines of SpaceX, Tesla stock for everyone via UBE. Yes, perhaps, perhaps.

1:43:47Anyway, this is the abundant story writ large again, where the cost of everything, and it's not going to be trips to the moon or Mars, but if you want your basics, it's raising the floor where every man, woman, and child on the planet has access to food, water, energy, healthcare, education, and freedom. I think that's what we're building here. And I like to say, yes, we're going to have trillionaires living on Mars forever. But in that inflationary world where everybody's, you know, the rising tide for everybody, I'm OK with trillionaires living on Mars as long as every man, woman and child on the planet has access to all the basics.

1:44:24That's a more peaceful world. Can we lift the bottom? Yeah, lift the bottom. Yeah. The gap will get bigger. You know, I agree the gap will get bigger. And yes, but as long as the floor comes up, that's the single most important. Can I mention one of my favorite abundance statistics that you put up, Peter? Sure. If you go back 200 years ago to 1820, 94 % of humanity lived in extreme poverty, being defined as$2 a day on 2011 parity dollars. Today, that number is less than 9%. And you just don't see stuff like that in the news. Yeah. You don't. The news media delivers every murder, every crooked politician over and over again into your living room between 6 p.m.

1:45:08and 8 p.m. As I like to say, I tell my mom this all the time. Mom, turn off the news. Don't watch the Crisis News Network. It will just give you a bad mindset. Join us in our echo chamber. Yes, she does every time. Hey, Mom. Let's do some AMA questions, gentlemen. I think we have some fantastic questions this week. Okay, Alex, let's begin with you. Yeah, so there are a few different interesting questions here. I'll pick number four because I've commented on this one already on the pod. How far off do you think we are from hitting longevity escape velocity? And this is from Sage Freeman 9260. So I think, Peter, if you were to answer this, or if friend of the pod, Ray Kurzweil, were to answer this, I think the answer would be something like 2030 to 2033, I think is the consensus.

1:45:57My mantra is LEV by 2033. Yes. Yes. If I were to answer this, I think it's going to be spiky. Just like superintelligence is spiky along different dimensions and with different skills and capability areas, I think some subpopulations may hit longevity escape velocity by the end of this year. I think others may. It could happen by 2030. But I think there are so many variables that will lead to high volatility or spikiness in terms of who arrives when, in part because there are so many people who qualify for certain medications that, you know, say third or maybe even soon fourth generation GLP-1 RAs.

1:46:44Those could, speaking hypothetically, it's not medical advice, those could end up having profound longevity impact. So actually, I was sufficiently interested in this that I did my own internal mini research study trying to answer the question, have we achieved longevity escape velocity this year? And there are a few confounding variables because you can achieve, in some sense, catch up longevity increases if something terrible happens. Like if there's an agricultural revolution in China and a lot of people die, then average life expectancy takes a huge dive. but then a few years later it zooms back and you could ask the question, well, is catch-up or regression to the mean longevity escape velocity?

1:47:28I don't think most people would consider it that. On the other hand, if you have someone who has some illness, but it's an illness that we've never been able to cure before and now we're able to treat it and now their life expectancy is increasing by almost or approximately one year per year, has that subpopulation achieved longevity escape velocity. Some would say no, because you're just helping a person with some illness regress to the mean. Others, including myself, would say aging is a disease. And so curing aging is basically helping a subpopulation, which is to say more than 150 ,000 people per year dying on this planet, and helping basically the subpopulation that is the entire Earth population survive and get treated from the disease that is aging.

1:48:22So yes, I think some subpopulations are approximately there right now and more to come. And we discussed in the last pod, there are a number of ongoing partial epigenetic reprogramming experiments going on in humans today, which is super exciting. I'm going to take number three before one of you guys grab it. I'm sure you're going to do that. But average. That's yours. If average life. I thought so, too. Average life. It's got your name all over. Average lifespan hits 120 and infertility gets cured, which it will. How does society handle the population boom? And this is from at Mr. Ghanoush Inkton.

1:48:58So here's the here's the reality. We do not have anywhere near an overpopulation problem, even if we start getting to extreme longevity, 120 and plus. The majority of the world is in a population crunch. We're seeing in Asia and Europe, you know, a reproductive rate of under one child per family. Right. The to keep the population, you know, without growth or decrease, it's two point one children per family. Places like South Korea and Japan are hovering at like point six children per family. So we have an issue in a number of generations. These cultures, these countries are going away. The other question that this person might then pose is, OK, what about access to resources?

1:49:49And over and over again, even if we have a population, I think the numbers are going to reach nine and a half, 10 billion and then very rapidly decrease. and people have always said, you know, the one earth precept of we need to divide the resources of earth equally amongst everybody. Well, every time we think there is a scarce resource, we discover, no, it's not scarce. We just innovate around it. You know, lithium was thought to be a scarce resource. So we start discovering lithium deposits every place. Then we start inventing batteries that are better than lithium with sodium that is much more abundant throughout the world.

1:50:27By the way, a quick note, our next podcast is going to be with Ramez Nam going to deep dive into energy. It's going to be amazing. It's going to be amazing. You do not want to miss the Ramez Nam episode. So Mr. Ghanoush Inkton, no fears about overpopulation and no fears about not having sufficient resources. Salim, over to you, pal. Okay. Let me go with number two. Could anthropic hide its model's reasoning to stop competitors from distilling it? So you can kind of restrict the visible reasoning and hide it a bit to make distillation harder, but you can't eliminate it because people can still learn from the inputs and outputs and then reverse engineer that across if you have a sufficiently large number of examples.

1:51:18The capability diffusion is very difficult to stop permanently because once you have useful behaviors, people are going to learn from it and then they have a huge incentive to reproduce it in other models. The sustainable mode is going to be kind of not just the hidden reasoning, but it's going to be the whole thing. Do you have unique data? Do you have infrastructure and compute? Do you have users? Do you have feedback loops? We keep talking about feedback loops. Do you have that to provide proprietary and unique learning loops? And that's the really big deal. And then distribution and the ability to learn continuously from all of that.

1:51:54So there's a whole system approach here that where it's going to be the future of every organization is going to be that kernel of data, compute, learning loops that then can compound on each other. Dave, over to you.

1:52:09Dave Blundin:There's one left. Hey, do I get first pick on the website? Sure, I'll give you that for sure. Awesome. Awesome. Thanks. So what's left? Number one, how long does it take to actually take a patch or take how long does it actually? Sorry, let me start. How long does it actually take to patch a vulnerability like the hugging face breach? And that is from at teach me T3H me teach me. Coolest thing about this question is actually your handle. That's really awesome. It only takes a minute. Once you know the vulnerability, sometimes there's a little bit of time to propagate out the patch. But once you know what the vulnerability is, you can fix it in no time flat.

1:52:45Dave Blundin:And that's all there is to that. All righty. Let's move on to the next four. Dave, you get first pick. Oh, thanks. I love number five. If AI transforms higher education, how should we evolve the high school system? And that's from Dave Wilfart. Okay. I guess that was your mark for me after all. So yeah, I love this. I love this topic and we obviously need to get on it. You know, I did a podcast with Joe and the president of Northeastern. Incredibly great podcast. The guy is brilliant. You should check it out somewhere on YouTube. Joe and his A-O-U-N if you want to search for it. But we were talking about the evolution of the college system that has to happen like right now.

1:53:31Dave Blundin:And he's opening a new incubator on Mass Ave here in Cambridge where the students who, you know, Northeastern has always had a lot of work studies. so you can work instead of taking classes and get real-world experience. But now build a company, be an entrepreneur, that counts. That counts as part of your college curriculum. It's phenomenal. But that same mentality needs to move into high school where you have to first recognize the curriculum can't possibly keep up with the useful knowledge that the kids are going to want to absorb. So you have to switch it over to AI-based teaching, AI-based learning.

1:54:03Dave Blundin:Allow them to learn whatever they want to learn. Purpose-driven. Purpose-driven learning. And we invented a class right in this pod that must exist, you know, prompt engineering and scaffolding. That has to be a new class. But, you know, next semester it'll be something else. Next semester it'll be something else. You just have to allow that to come into your ecosystem. Then reward good behavior like trying to learn or doing something that looks productive. Give that an A+. But don't try to force everybody down an ancient curriculum. Dave, here's an idea for you. Given that I'll get in trouble for saying this but don't really care, MIT does not really take the humanities seriously.

1:54:38As an undergrad at MIT, I got humanities credits for the philosophy of quantum mechanics and set theory, and all my humanities classes had problem sets or lab assignments. What about a humanities credit at MIT for prompt communication, prompt engineering, and context engineering as sort of a stealthy way to introduce communications skills? That's a great idea. Alex, I'd love to hear your answer to number eight. All right, I've been assigned number eight. So number eight asks, does training on synthetic data degrade model quality over time? And this is from QC for Life. Depends on the synthetic data.

1:55:15So you could generate synthetic data for, let's say, prototypically software engineering problems, like generating code and then injecting a bug into the source code and testing whether a model is able to find that bug. There are many reinforcement learning challenges that I think, at least by historic standards, certainly benefit from synthetic data and especially synthetic environments. So creating procedural 3D environments or creating, say, just applications that can generate almost infinite variation that via reinforcement learning and reinforcement fine tuning models can learn from. That is, I think, quite valuable.

1:56:01That, by the way, I mean, I think what maybe the question's subtext is, isn't it sort of a garbage in, garbage out? How could you possibly learn from synthetic data? Isn't it just garbage in, garbage out? And the answer is, in fact, no, it's not garbage in, garbage out. I've mentioned this on the pod in the past, a couple of terms, Solominoff induction and AXE. You could, in principle, train purely, if you had a sufficiently strong model, you could train it off of no physical world and no human data at all, purely synthetic data. if you had a sufficiently powerful model, and this is the premise for ACSI, which is a theoretical, not very practical implementation of Solominoff induction.

1:56:46Solominoff induction is an approach to basically building the perfect inference system. And the premise of it is, if you've just observed a sequence of bits or a sequence of tokens, the perfect next token predictor, which is all large language models are, basically organizes and runs every possible Turing machine, every possible computer program on that history, which is computationally infeasible, but theoretically perfect. So, going back to the question of synthetic data degrading model quality, in the limit of perfect compute and infinite compute, it's actually ideal not even to touch the physical world and not even to touch human data and to train purely off of synthetic data.

1:57:31You know what else?

1:57:32Dave Blundin:Not to beat this to death, but having trained many, many neural nets and training some right now, synthetic data is fine. It's mislabeled data that absolutely kills you. Just one mislabeled data point is a killer. The weights will warp themselves eight ways till Tuesday trying to make it make sense in context of everything else. So clean synthetic data is totally fine. In fact, it's better in a sense because it doesn't have something just blatantly wrong and mislabeled. All right, Salim, six, seven. Why don't you do the next one? No, it's okay. Go ahead. Gentlemen, the questions are abundant. I will go with number seven.

1:58:15What stops Frontier Labs just acquiring other companies in other industries to get their data? This is from David Lee Z5E or Z5E, if you would say properly. So nothing stops them from doing that because you're going to get acquisitions. You can see private equity buying chunks of like mid-market accounting firms and trying to get that stuff. The real goal is the proprietary data they have. The problem that I'm seeing as I'm watching PE try to do this is buying a company doesn't mean you get really useful knowledge because there's a lot of tacit knowledge that's hidden in key employees' heads that's not easy to extract.

1:58:56You've got different operating processes and so on. So traditional companies need frontier models, but the model provider needs proprietary information to make it useful. So I think what we're going to see is a lot more partnerships. For example, we're seeing groups of hospitals band together and then pool their data and then make that data available to pharma companies. It's almost like a co-op model. That becomes really interesting. But based on my previous point in the whole organizational similarity stuff, the implication for companies is super urgent. Organize and protect your proprietary data so that when you add AI, you have the learning loops that become very, very powerful.

1:59:37That will be the engine of growth for your future. And it'll become much more important and much more valuable than your current product. So they may go buy some startups, but it's going to be a harder thing. I think it's easier for the frontier labs to go partner with companies for their data and mutually figure out ways and cooperate rather than trying to do this acquisition stuff because that tends not to work out over time. All right, final question, number six. Yeah, question six goes to the guy who got SpaceX. How can individual investors get involved in cutting edge startups before they go public?

2:00:13That's from Nancy Jenner-C5D. So, Nancy, there are so many ways for you to find cutting-edge startups before they go public. The easiest is getting them at the beginning. You go to your university, first and foremost. A lot of these companies are beginning in the minds of 20, 21, 22-year-olds, right? You can go to equity crowdfunding platforms and see what's going on. There are syndicates on AngelList. Venture capital funds, you know, have, you know, minimums you'd have to buy in there. You can go to demo days. There is so much going on today that can enable you. Dave, what do you want to add to that?

2:00:58I think if you add value, you will get stock.

2:01:05Dave Blundin:And there are so many ways. A lot of these companies are growing so quickly. And if you discover them early and you just try to add value in any way, they need so many. You know, the guy who painted the Facebook office, what did he make,$100 million on that stock because they paid him in stock because they didn't have any cash? He was just there. And so I think, you know, people underappreciate how much you can reach out to these guys, especially early on when they're desperate for help. And then, hey, do you want introductions? Do you want sales help? Do you want help moving your office? What are your skills?

2:01:32Dave Blundin:If you make yourself available. What are your skills you can add? Are you a great coach, right? Do you want to run and, you know, get coffee for the team? My favorite suggestion would be to go to AngelList syndicates because people have syndicates where Jason Kalkanis will invest in a bunch of startups. And you can buy into that syndicate. They get a piece of the carry, but you get participation in all that. And those have done extraordinarily well, and you don't have to put a lot of money up. Yeah. It's funny you say that because we had a summer intern. He just said bye to me today because he's got to go back to school in September.

2:02:06Dave Blundin:But he put together an angel syndicate over the course of the summer. And, you know, he's young. He's still a student, but he's going to manage it. And all the rich, old, famous guys are like, great, if you manage it, you can just participate and we'll lend our names. So he actually pulled together a syndicate in, what, like four weeks this summer. Gentlemen, as always, a pleasure. And to our listeners, thank you for subscribing. Thank you for joining us. It's no time to sleep during the singularity. I have to go talk to all the rad of it. Don't take off the takeoff. What's that? I have to go talk to all the rabid Moonshots fans that were like, we can't wait to talk to you about questions.

2:02:44So I'm going to go talk to them. You look like you're in a consulting office over there. No, I'm in a hotel room. Uh-huh. Okay. Fantastic. All right. All right, Salim. Well, words of encouragement. See you guys very soon. Love you all. Be well. Thanks, Peter.

2:03:35We'll see you next time. 18+. Thank you.