The Singularity is Here: AI is Solving Math, Sora Outpaces Chat-GPT & AI is Designing Chips w/ Salim Ismail, Dave Blundin & Alex Wissner-Gross | EP #201

27:37And what we're seeing is just this constant leapfrogging where everybody's just incrementally moving towards 100%. And to hit your number on price, for GPT-5 Pro, when I looked it up, it said it's$4.78 per task. And all of this stuff demonetizes rapidly. I love that the horizontal axis here is in logarithmic terms. Every chart of every good in service in our economy should be on logarithmic terms so we can watch the hyper deflation. Dave? Yeah, no, zoom in on that. When you're looking at the, if you're not driving right now, zoom in and look at the x-axis. You know, on the right side, you've got 10 bucks and then in the middle, you've got below a dollar.

28:22So it's a huge range of price points for very similar performance, you know, if you look at the peaks. So what you're seeing mostly on this chart is massive cost reduction, which, you know, makes it more accessible. So we'll talk later about some of the other innovations that are driving down that cost, but that's perpetual. All right, Alex, this one is for you. You and I have been going back and forth on text. Oh, my God, we're solving math. We've solved math. So this article in particular comes out on the heels of this. GPT-5 Pro sets record at frontier math. What does it mean and what are the implications here?

28:56Yeah, I think this is arguably the most exciting development over the past week and a half. So as a reminder, Frontier Math Tier 4 consists of math problems that professional teams of mathematicians would take a few weeks to solve. These are very hard math problems. And over the past week and a half or so, we've seen first Gemini 2.5 DeepThink and then GPT-5 Pro demonstrate breakthrough performance, GPT-5 Pro at 13 % on Frontier Math Tier 4. And Dave insisted that I make an internal recorded prediction for just to get on the record, what would it mean for math to be solved in quantitative terms?

29:37And this is months ago. And I put on the record, as Dave will, I think, attest, we can reasonably declare that math has been solved when Frontier Math Tier 4 passes 10 % scoring. So more than 10 % of the problems can be solved by a bleeding edge model. And the reason why I picked 10 % is because at some point in the logistic regression of predicting, you've solved 10%, at some point you just pour compute on and you get more results. I think we've seen this over and over again. We saw this infamously with Ray Kurzweil pointing out that you're halfway complete with sequencing the human genome once you've passed 1%.

30:1810 % is sort of my arbitrary benchmark. I predicted that we would be past this by the end of this calendar year. Christmas arrived early. Math is now on a trajectory. If you just pour more compute on, arguably with no new innovations, math will be solved, at least math as we currently know it. Okay, so when math is solved, I've asked you this before, but I just want to hit it home because it's a kind of an esoteric subject for most people. What does it mean when math is solved? What's the implications for all of our subscribers here? It's the ultimate canary in the coal mine, as it were, for solving physical sciences, solving engineering, solving medicine.

30:59If we can have machines that solve arguably humanity's most rigorous intellectual endeavor, which I would suggest is math, then everything else I would expect over the next few years, call it five to 10 years, I expect to succumb. As a tangible example, encryption is all math-based. So when you can have an AI deliver that, you can kind of get super encryption at whatever level you want instantly. And physics and material sciences, yes. Yeah. And all of the physical sciences. And conversely, as I've articulated in the past, any discipline that relies on math, at least the current math being hard, is also in danger.

31:40So it's not just learning math, it's inventing it at some point pretty quickly. Absolutely. Okay. Yeah. Wow. Yeah, I think just the implications, You know, one thing people misestimate continually is if some brilliant mathematician, human, solves a hard problem, that makes the news. But it doesn't imply that all other problems will be solved the next day. The AI version of the same achievement. Great point. In biotech, in math, in physics, in all these other areas, because it has near infinite scale instantaneously, If it can do one frontier math problem, it's very close to being able to do many and then billions just right after that.

32:23And so people need to factor that into their rate of change thinking as it cracks these different areas. Better find some more problems. This is dominoes falling and heading towards, again, Alex's words, solve everything. It's bulk discovery. And we've only seen this in narrow areas. We saw this with alpha fold three and protein folding where almost overnight we had arguably high quality protein structures for most known proteins. We're going to see bulk discovery across a number of disciplines. The other story here is we don't have a slide for this, but the Erdős problems. This is a set of order of magnitude, a thousand problems that were identified by famous mathematician Paul Erdős.

33:03AI and GPT-5 are being used to bulk solve those, and the solutions are starting to pour out. If you go to the Erdős Problems website, you'll see just in the past few days now, there are folks who are just bulk applying GPT-5 to all of these open problems, and they're getting switched from open to solved. Wow. Don't sleep. Don't blink. It's happening. All right, let's move on to this one. Open AI on building chips with AI. Here's a quote from Greg Brockman. we've been able to apply our own models to designing this chip. We've been able to get massive area reduction. You take components that humans have already optimized and just pour compute into it, and the model comes up with its own optimization.

33:47Dave, talk to me. Yeah, I love this story because this ties together so many things we've been talking about. You know, one of them is the short timeline to about 100 to 10 ,000x improvement in AI performance because of the AI self-improving. And when we say AI self-improving, a lot of people in academia are like, well, it's not that smart yet. But it is because AI self-improving is nothing more than math, algorithms, and chip designs. And it can do those point tasks. And then a lot of the academics then say, yeah, but that's not true reasoning. That's not true genius. That's not true whatever.

34:23It doesn't matter because that's all you need to do to self-improve. And so I just love this story. I also love the fact that Greg and Sam out of the original cast at OpenAI are the two guys that dropped out of college, didn't finish undergrad, and they're the two survivors. And so you take Greg, the guy that dropped out of MIT. He's designing chips now because he's a master of AI. And I don't know if you guys did any VLSI design or chip design at MIT. I did a fair amount of it actually doing neural net designs. And it's absolutely laborious. And the amount of improvement is incredible if you just had the time and, you know, 10 ,000 people to work on it.

35:01And so, you know, AI is just going to rewire and redesign and relay out the thing. And the simulators are near perfect. It's an acceleration of the acceleration. It's so cool. It is to me. I can attest to this. One of my student jobs at Waterloo was to run field tests for VLSI boards. And it was like freaking linear painstaking hell. Yeah. And so the other thing this ties in is Leopold Aschenbrunner buying Broadcom stock. And you're like, okay, I didn't see that one coming. Why is he? And of course, you can see it in his 13F filing, but now it's obvious, right? Brockman is designing chips. The chips need to go to Broadcom and then they get manufactured on TSMC.

35:40Therefore, Broadcom stock is the one that Leopold buys. And of course, Leopold was at OpenAI and knows Brockman. So it all ties together. You mentioned something that I think is important again, we hit on this sort of week on week that Sam and Greg dropped out of college to go and pursue this. And, you know, one of the things you and I've discussed, Dave, is majority of the entrepreneurs who are succeeding today, aren't the ones who've gone on to get PhDs or gone on to do graduate work, right? They're ones that have launched either just after college or have dropped out of college to go pursue it.

36:13And it's almost as if going to get your graduate degree and going very narrow into a deep, you know, it's like, I remember I was, if I was going to explain to my grandfather what I did when I was at MIT, he says, okay, you're an expert in, and I would say to him, like, look, in the dirt over there, there's this thing called this bacterium. And he goes, oh, you're an expert in that. No, no, no, I'm not an expert in that. In the bacterium, there's this thing called DNA. You're an expert in that? No. In the DNA, there's this thing called a gene. You're expert in that? No, no. In that gene, there's a promoter sequence, and I'm an expert in that, right?

36:49And so our graduate work right now is this hyper-narrow focused effort instead of being able to step back and look at reinventing an entire field. Yeah, I'll put a slightly different spin on it too, which is the people Greg's age and Sam's age that dropped out had very high situational awareness around the urgency of what's happening right now. If it were 2001, you know, and 9-11 had just happened, going and getting a PhD would make a ton of sense because the world isn't moving at warp speed during that timeframe. But the reason the undergrad dropouts and the other people just graduate and start a company right away are way overperforming is because they recognize the urgency of the moment.

37:31And they know that four years from now is just not a good choice in this moment so it's that also the brains haven't been calcified by studying that one thing that peter talked about i don't know how alex broke through all of this somehow he's like the hardest lesson to unlearn it takes a lot of unlearning yeah crazy crazy all right um let's let's move on here sora hits one million app downloads in less than five days faster than chat gpt i remember when When ChatGPT came out, I was doing a podcast. I was like, oh my God, a million downloads in five days, new world record. But something is going to beat that.

38:10Well, here it is. It's Sora 1 beating that in the App Store. And of course, something will beat this as well, probably within the next year. Dave or Salim, what's your thought here? One thing we're seeing here, I was talking to the CEO of PacFi two days ago, really thriving marketplace company. And they were asking for my advice on how to implement AI within their product. And I said, well, just ask the AI. And so what you're seeing here is more and more of what you do next is what was recommended by the last thing you had on. So if you're a Gemini user, you go with Gemini. If you're a ChatGPT user, you go with ChatGPT.

38:46But you say, hey, I want to create an amazing video. What should I do? It tells you what to do. And then nine times out of 10, you just do what it said. And so the distribution of these new capabilities is actually within the AI installed base. And that's why it's got this self-reinforcing loop. I mean, I would have expected nothing less just because the next thing will be two days and the next thing will be one day. And as Alex points out in our earlier conversation, at some point we'll get the ability to upgrade everybody at the same time and then we'll be, that's what Ray is talking about. Yeah, for sure.

39:19All right, I'm going to turn to you on this one, Alex. Samsung's tiny recursive model redefines AI efficiency. So researchers have built a mini AI model at Samsung with 7 million parameters to test reasoning ability. And this compares to models with billions or trillions of parameters. So talk me through this, Alex. I would say at a high level, remember first that this revolution, this soft or gentle singularity, if you will, that we're living through was arguably the result of just compressing information. That one of the biggest lessons I take away from how intelligence was arguably solved is just like you could take a lot of matter, and if you compress a lot of matter in a tiny volume, you get some phase transitions, and ultimately you can recover free energy, for example, via fusion.

40:10Similarly, if you take a lot of information and you compress it down into a model that has a relatively small number of parameters at some point you get intelligence out almost for free that's like a big meta lesson in my mind from from the past 10 years so there's an enormous amount of opportunity for taking large hard problems large information spaces and compressing them down not to models with billions or hundreds of billions of parameters but to models with millions of parameters i've also spoken about my expectation this is one person's speculation that we're marching toward an ultimate end state where we'll achieve like a perfect model that's like a microkernel it's like a diamond of a model that may not even be may not consist of differentiable end-to-end parameters maybe it'll only be a million parameter equivalents or a million bytes or something like that and i when i see progress like samsung's trm which which looks i i it's a it's a lovely paper if you look at the architecture sort of resembles a diffusion model in some sense.

41:13The premise is it's domain-specific. And in this case, in the case of the result you're showing, it was trained on a bunch of examples for the Arc AGI 1 challenge that we were talking about earlier. It has a notion of a scratch pad, but it's a relatively tiny model, and it rewrites the scratch pad several times and then goes back to work. It has some latent expectation of what it's trying to do and then rewrites some more times. It looks like a diffusion model if you squint hard enough at it. But I think that the big takeaway is such a tiny model achieving breakthrough performance. You know, if folks who can see the chart here, it's competing with O-class models in terms of price performance, but it only has a few million parameters.

41:55So I think— So the implications are what? You've got this on your phone. You've got this on every device. Even if it's not connected to the internet, it's able to deliver you intelligence. Oh, the implications are so much bigger than just that. Sorry, Alex, go ahead. We're going to say the same thing, I'm sure. Well, I mean, look, if you can take, you know, normally to achieve that same level of performance, you need about, you know, on the order of a trillion per number, say 700 billion, just to keep it simple. So you go from 700 billion down to 7 million. Then you can use all the rest of that compute capacity to expand it again and make it better at that domain.

42:32So if you can take a general massive model that costs a billion dollars to build and compress it down to a specific use case like protein folding or just longevity-related use case or just chip design-related use case, get all that original capability, but now you've got it in a very tiny package, then you can start training it out, reuse those billions of parameters to make it much better at that domain. And so you have this combination of many, many effective workers, many agents working on the problem, plus the ability to build back out the intelligence level with more and more data purely through this process of distillation and expansion, distillation and expansion.

43:12It's the most powerful thing in the world. And it's also really, really empowering for a whole new wave of startups. And I don't want to get too deep into it, but we could talk about this for hours. But I think this slide encapsulates the most profound idea in all of intelligence, which is, it was something that Ilya Sutskover said at MIT with Lex Friedman about, God, it must've been like seven or eight years ago, at the dawn of this wave of AI, that compression and intelligence are actually the same thing. And everyone goes, what that? That makes no sense to me, I don't get it. This is the point Alex has been making, right?

43:42Yeah, that's right. Yes, yes. And this is why Alex says intelligence is going to turn out to be everywhere. There's going to be DNA and how much is packed into a few DNA, a few genes, right? It's the same basic principle. I'm going to name this episode The Singularity Is Now. That's how I'm feeling. Okay. But here's two questions about this. Yeah. One, does this obviate the need for all the radical energy expansion, or do we just have so much compute to do that we need it all anymore? No, no, no. We're going to chew this up so fast. Okay. Because the capability is... The second thing that occurs to me is right now when we run these big LLMs, it's kind of a mainframe model.

44:18This is kind of tilting towards more client-server type architectures. Yeah, distributed. The foundation models are going to be everywhere in your pocket, in your body, and out in the cloud. Amazing. Yeah. Let's come back to that. Let's file that away because that's a... Salim, what you just said is also hugely important and profound. It's distributed training concept. Let's come back to that. All right, our next article, Diving into Anthropic, introducing Claude Haiku 4.5, which delivers near frontier coding and reasoning performance at one third the cost of Sonnet 4. Let's play a quick video here.

44:57Well, it's playing without sound and it's just showing its capabilities here. Alex, what do you think of Haiku 4.5? So I ran it through one of my, I have a suite of evals, a suite of tests or benchmarks that I throw at code gen models and classes of other models. So my favorite eval for new code gen models, and arguably Haiku 4.5 could do more than code gen, but I ask it to generate a, in one shot, a visually stunning cyberpunk first person shooter. And Haiku 4.5 was able to do that to near perfection, but critically was fast. Very, very fast model. So I maybe wall clock time 30 to 45 seconds before I had a playable Cyberpunk FPS that was lovely.

45:49That's stunning. That's nuts. Stunning. All right, congratulations, Anthropic, on that one. Moving on, here we have Google, kind of a pre-announcement, but the drums are beating in the off in the distance that Google is getting ready for releasing Gemini 3, likely this December. It turns out that Google has released its Gemini models in December over the last two years. And of course, once Gemini 3 drops, the moonshot mates are going to be there to explain what happened, what does it mean, what are the most exciting attributes in it. Any other thoughts here, Alex? It'll be interesting to see with this annual cadence how quickly all of the frontier labs leapfrog each other.

46:40I do think there have been reports of an experimental checkpoint floating around the internet, preliminary release of Gemini 3, that is really impressive if the reports are accurate. Fluent music, graphics, 3D generation. So I'm very excited to play with Gemini 3. Yeah, we're going to see that in our next slide here or listen to it in our next slide here. So purportedly, this is from Gemini 3 that it can now compose original music. Let's take a listen to this as you're sipping your coffee or driving your car.

47:29You know, it's gorgeous. What are the implications of this? What do you guys think will come out? Hold on, let me ask a question, because that just sounded like Chopin to me. And we've had for a while the ability to say, hey, play me something like Chopin, it'll play you something. There's something that's happened here. What am I missing? What I think is interesting is that this is MIDI generation. This isn't generating raw waveforms or wavelets or raw audio, as we've discussed in the pod in the past, like Suno 5. This is treating music as an almost first-class modality. There are a variety of languages like ABC notation or MIDI notation.

48:09And what I take away from demonstrations like this and others that are allegedly floating around from this experimental checkpoint is Gemini, despite whatever limitations in its omnimodal training data set, has the ability to understand music notation and music languages as a first class modality. That sort of transfer is highly difficult and non-obvious. If you've ever tried to ask like an O-class model, say in years past, to generate compelling music, it was very challenging. Well, Andrej Karpathy just kind of emerged and started podcasting again out of nowhere. And he made the point that these capabilities are using the same generic neural net design, transformer design, that the language models use and that the self-driving car uses.

48:55And so the implication of that is that, look, it's exploding into these areas purely with more data. There's no hard, heavy lift for humanity to design something new to make this work. You just put in more data and now suddenly it can do MIDI actual music creation. But that implies that there'll be something next week and next week and next week and next week. It's just as quickly as you can gather the data, it's developing these new abilities. I want to double click on that because I don't think the majority of people understand that these models, when we're hitting these scaling laws of more data, more parameters, more compute, are evolving capabilities that were never predicted.

49:35It wasn't like we tried to build these capabilities. It's like they're emergent properties as the systems are becoming more intelligent. And that's fascinating. Scary in some ways, but fascinating. And hugely important. Hugely important. Because when people see a new capability like this, they assume that some team was grinding away on it for 20 years in some basement and it just got launched. That's not the case. This is just a purely emergent capability on top of the core platform. It's like, oh, wow, look what we can do now. It's ironic, Peter. I mean, when I was an undergrad at MIT, one of my first research advisors was Marvin Minsky.

50:10And he would slap my hand every time I used the word emergent. He would say, no, that's preposterous. Emergent, using that word just means you don't know what you're talking about. And yet, ironically, decades later, in fact, we see all of these emergent capabilities. Amazing. We should do a whole episode on things they told us that turned out to be wrong. There's a bunch. That would just take too long. All right, let's go on to another property that's been announced for VO3.1. So DeepMind releases the next image video model. Let's take a look at a quick video about VO 3.1. New enhanced capabilities give you control like never before.

50:54Let's take a look. You can use a reference image. VO puts them together into a fully formed scene, complete with sound. Hello, is anybody here? You can extend your clips and transform any shot into a full scene. Reimagine any shot by adding or removing elements, from subtle details to impossible objects. VO matches scale, lighting, and shadow for real-world physics and cinematic outputs. Life with audio, using sound effects and dialogue. Just got to listen. I mean, incredible, right? So there are three critical differentiators between VO3, which was amazing in itself, and VO3.1. The first that they point out is superior audio quality and synchronization.

51:45And you could hear that when it was cooking the food in the frying pan. It's much richer, more natural. The second, which I find fascinating, is you can give it three ingredients. Like, you know, here's an image of a person. Here's an image of an object. Here's an image of a room. And it will take those three effectively and tell a story around those three, combining them. And you can give it a opening scene, like here's the starter image I want you to start the video with, and here's the ending image I want you to end it with, and it'll create a logical construct that goes between those two points.

52:20I mean, pretty amazing. Other comments on this one, please? Yeah, well, so a couple of our friends have made full-length movies now, and to do that, it only gives you a minute or two back at a time. And so you have to take the ending image and use it to stitch together the starting image. which is frustrating because you know they could do that automatically. They just don't have enough compute to keep up with all the people that want to use this. But you can do it. You can hack your way around it and make incredibly seamless full-length movies all of a sudden. And if you go back just six months ago, actually, remember 18 months ago, Peter, you had Aristotle and Plato on stage at Abundance 360 debating with each other.

52:59And if you look at all the comments from the movie crowd, the producers, the Paramount Studios crowd, they're like, yeah, but. And if you look at the list of yeah, buts, almost every one of them has been solved in less than 18 months. You know, yeah, but the characters aren't consistent from scene to scene. Yeah, but it's obviously digital and you can see the seams between the scenes. Yeah, but, yeah, but, yeah, the physics aren't quite right. The arm detached from the body. Every one of those things banged out in this, you know, less than 18-month timeline. Extraordinary. And we're going to be at the Abundance Summit this year.

53:32We're going to be diving into this again. And what's the implications for Hollywood and in particular, the creator economy, right? I've got a project, a secret project, I can't talk about it yet, but working on with Google around production of content like this. And we'll be releasing that hopefully in the next couple of months. Salim, do you want to comment on this? I don't fully understand the implications of this, except if you can go end-to-end per scene like this. then stitching together a whole movie becomes every amateur can now go full on, right? And that completely changes Hollywood radically.

54:13I guess we'll see an explosion of consumer-generated movies now with all sorts of weird plots, etc. I suspect, I don't know, but I suspect that there are many, many people all over the world that have something to say that could never get the attention of a studio or an actor before. And now they don't need it. Now they can individually put something professional studio caliber together to illustrate the point they were trying to make. I think that's going to be a crazy explosion. And what a win for YouTube, right? I mean, Google is sitting pretty because the only distribution engine for this explosion of content is going to be on YouTube.

54:52I also think with some of these models, VO 3.1 and Sora 2 Pro, for example, these are just training wheels for video-based reasoning models. I think that will generate an enormous amount of additional economic value. So generating consumer-grade video, this is wonderful. This is radically democratizing Hollywood. Excellent. But then imagine now we're about to have reasoning models that can think with images, think with videos. That's going to solve a whole bunch of transformative problems. With the associated downsize, my son just served me a suraclip of me at 800 pounds playing a video game. And I'm like, if you put that out there, people think that's me.

55:31It's going to be terrible. Oh, my God. Our next article, again, following on Alex's sort of predictions here, Gemini 2.5 and GPT-5 win gold at the International Olympiad on astronomy and astrophysics. I didn't realize that there's an international Olympiad on astronomy and astrophysics. Alex, over to you. There is, and it's quite competitive. So this is for high school students. There are international Olympiads for math and physics and computer science. I was on the computer science Olympic team for the United States in high school. This is a very competitive Olympiad. And I think this is work from Ohio State University, another lovely paper.

56:13And the authors make the point in achieving this benchmark, we're drowning in petabytes of data from astronomical sources, from automated sky surveys. And there aren't enough human waking hours in the world. Yes, to analyze it. Yeah, to analyze it. So this is more than just beating high school students at astronomy and astrophysics. This is about AI solving astronomy and astrophysics and enabling us to understand our universe. There aren't enough human waking hours to look at all the skies. I remember Gerald... Wow, this changes the game for SETI, doesn't it? I remember Gerald Soffin, who ran the Viking program back in the mid-70s, in the Dark Ages.

56:53And he said, you know, we've looked at less than a fraction of 1 % of all the data that came back from Viking. Because there isn't enough human capability to do that. And now, I mean, all the data generated, especially... We're about to have the interplanetary internet, too, right? laser links between orbiting satellites around Earth, around the moon, around Mars, with high bandwidth capability. And we're going to be able to constantly be sorting through the data and making discoveries, sort of go to sleep at night, wake up in the morning, you know, early, because you can't, you don't want to see the singularity.

57:29And critically, again, these are generalist models that are accessible to anyone. Almost anyone can access Gemini 2.5 or GPT-5. This This isn't some sort of like siloed data center that only folks who have the time and ability to purchase observatory time from the great telescopes can get. Anyone can do this. I think it's going to radically democratize situational awareness into our universe. Well, it goes, you know, using this as an analogy, anybody out there who has a large amount of data in your business, in your industry, right? It's this gold mine that hasn't been tapped yet. And so if you have that data, being able to actually feed it into one of these models to start to extract value should be your very first stop.

58:15Wait, Peter, can I just get back to something? Alex, you just said this democratizes situational awareness across many industries. Can you unpack that? Into our universe, I said. So there are publicly available petabytes of data gathered by different observatories. Historically, if we'd had this conversation 10, 20 years ago, we'd be talking about some sort of citizen science initiative, maybe people spotting, looking for interesting looking things in the sky at home. We don't need to have that conversation anymore. Now anyone can turn loose Gemini 2.5 or GPT-5 or some other frontier model with a decent inference time compute budget and say, go look for interesting things in the sky and make a discovery.

58:58It would have been 10, 20 years ago. It's remarkable when a high school student discovers a new asteroid. I understand, but how does this deliver a situational awareness into the universe? We live in a very dynamic universe. There are all sorts of interesting things going on all the time, and we're drowning in petabytes of new data all the time. 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.

59:38The Blitzy platform provides a plan, then generates and precompiles code for each task. Blitzy delivers 80 % or more of the development work autonomously, while providing a guide for the final 20 % of human development work required to complete the sprint. Enterprises are achieving a 5x engineering velocity increase when incorporating Blitzy as their pre-IDE development tool, pairing it with their coding co-pilot of choice to bring an AI-native SDLC into their org. Ready to 5x your engineering velocity? Visit Blitzy.com to schedule a demo and start building with Blitzy today. Now for our book corner.

1:00:21Favorite science fiction books. I've added one, and of course, AWG has. And Dave and Salim, I need your book entries for next week. Mine was Fahrenheit 451. Okay. It's going back. It's going back. I'll mention mine first. It's a book called After On by Rob Reed. I've read it twice. My son Jet and I have read it together once. And it's a fascinating story. It's a very fun read. It takes place in Silicon Valley. And it's really the story of the emergence of the first conscious AGI or ASI. And what is it like when something that comes online and it looks around and it sees fear? In this case, I wouldn't ruin too much of it, but the AGI is called flutter, and it hides for the first period of time.

1:01:16And it starts to then talk to certain people to understand how society and military and culture is going to feel about a superintelligence out there on the internet. It's a great story. A lot of fun. Dave, you're reading this now, you said, right? Yeah, yeah. I'm about a quarter of the way through it. It's, you know, a lot of books that deal with AI are esoteric. This is just a great, fun, awesome story that also deals with AI. So it's thick. It's a lot of words. It's a long book, but it's really good. It's really fun to read. So that's After On by Rob Reed. And it gets you thinking about what it might really be like, what could be going on right now that we just don't know about.

1:01:58Alex, tell us about Diaspora. Yeah, Diaspora by Greg Egan, I would say, is my second favorite book after Accelerando by Charlie Strauss. So Diaspora is a book about, and I'd argue it's utopian, some might disagree, but it's a book about what life after the singularity looks like. And intriguingly, it depicts a future where we don't take apart our solar system to build the Dyson swarm, where this tiling the earth motif of turning everything into data centers actually peaks and then declines. And most humans in the future of diaspora are living as uploads or emulations living in data centers underneath mountains on Earth.

1:02:37But it's a heterogeneous mix of biological humans, some who chose to remain purely biological in uploads and cyborgs. And I think it's one of the most vivid post-singular depictions that I've ever read. Big fan of the book. All right, there you go. This is all our subscribers. This is your reading assignment for the week ahead, or listening assignment, as my kids say. Dad, you don't read books, you listen to them. By the way, after on is incredible. Who has time to read anymore? We're just trying to keep pace with all the stuff that's happening. How are we going to navigate this? Yeah, insane.

1:03:13All right, let's move on to robotics. A few things coming out in the robotics world this week. The first one, super fun. This is Tesla's FSD version 14.1.2 brings on Mad Max mode. All right, let's take a quick look at this video, which is insane. So, if you're listening, what we're seeing here is someone in their Tesla Model Y or Model S, whatever it might be, and they're in Mad Max mode, they're going 83 miles per hour, but their car autonomously is weaving in and out of the car cars. like in the middle of a car chase for your favorite adventure movie. And I just imagine in the day, you know, people are in Mad Max mode.

1:04:01They're pulled over by the cop. And they say, no, no, no, it wasn't me. It was Mad Max who was driving this. Please let me go. Thoughts on this? This is nuts. How is this legal is my number one question. Well, it's not. And of course, the lab is all with the driver. but this is going to cause a lot of issues. I think you're going to see some spectacular car crashes around some of this. Well, listen, the point I think is I would rather have my FSD V14.1.2 doing this than me doing it. It's able to see, you know, with millimeter precision, how far you are from the car you're cutting off next to you.

1:04:40I think it's also ironic if you remember the original Mad Max movie was supposedly set in a civilizational collapse type scenario where energy had collapsed. In particular, there were worldwide energy shortages and sort of perverse in some sense that now we're on the verge of energy abundance at a global scale, thanks to the AI data center boom. And yet we're sort of looking back and trying to build a Mad Max, almost nostalgic retrospective while at the same time building minority report level rapid transit. it i would have called this gran turismo mode yeah let me read read the description uh from tesla when you select mad max mode for your tesla vehicle the fsd system which by the way still requires driver supervision right uh will attempt to drive more assertively faster acceleration more frequent overtakes more aggressive lane changes especially under traffic conditions i mean it's how i drive normally anyway but oh good all right the news this week uh Figure three Brett Adcock's company made the cover of Time magazine.

1:05:47I love this image best innovations of 2025 robots are coming to your home. And here we see figure three folding laundry. Gotta love it. Let's take a quick look at the video of figure three which has been reimagined for the future of labor Let's go play this video then we'll chat about it. So Figure three is here. It's got a new brand new look here. We see it washing dishes Serving food You'll be in room 23 the elevators are past the door on the right and playing at the front desk of a hotel and then delivering packages. Interesting. Very slowly. Very slowly. But fascinating figure three's changes here, right?

1:06:38It's taken on a new home ready design. We, you know, we were at one X, I'd done a podcast, I'm a full disclosure, I'm an investor in, in figure a couple of times through my venture fund. Congratulations. Yeah, no, it's, it's done amazing. They did a, We reported last week or two weeks ago that they did a billion-dollar financing at a$39 billion valuation. Of course, this is a multi-trillion-dollar marketplace for sure. But if we look at figure three versus figure two, there are five outstanding things. Number one, their new Helix AI system has a suite of sensors that make the vision, language, action much more capable than figure two.

1:07:20It's got redesigned hands with cameras in the hands, upgraded audio for voice reasoning. It's got a home-ready design. You know, it looks more soft and easy. It's taken on the same sort of look and feel as Neo Gamma from One X. And then it's a lighter chassis at 61 kilograms versus 70 kilograms and still able to lift 20 kilograms. Thoughts, Dave? 20 kilograms. It's funny because the 1X can lift its own body weight. Yeah. That's interesting. But the form factor seems to be settling in on this human but slightly smaller and soft exoskeleton and not going to hurt you. So moving a little slow, but it doesn't need to move slowly.

1:08:07It just does because it's less likely to slap you in the face that way. So they're all settling on this very similar design. So I think that's going to be the final answer. I think the most interesting design change that I saw in figure three is the palm cameras that you mentioned, Peter. So that immediately, in my mind, rhymes with Tesla vision and Tesla eschewing LiDAR in favor of pure vision. If you imagine the difficulty, sure, it has tactile sensors on the fingertips, but it's really difficult to achieve, at least at this point in time, human quality tactile sensation throughout the body.

1:08:44We have human biological meat bodies were covered in tactile sensors, humanoid robots, not so much. So to the extent that figure is able to move the future to the left by using cameras, using vision to substitute for tactile sensation all around the arms, I think it's a very clever move. And I think that in combination with vision language action VLA models, I think this is just going to be like a homework assignment for a K-12 student in a few years. Just implement a working humanoid robot using an off-the-shelf VLA model from a frontier lab, embody it. This will all be viewed as pretty easy.

1:09:21Crazy. And then the other thing announced by Brett is a price point. He wants to hit a$20 ,000 price point on this. You know, we talked in the past, we heard from Elon that, you know, cost of goods sold would be around$20 ,000 and it would be priced depending on volume. But, you know, Brett's getting very aggressive here on pricing. I think he wants to take out the competition. Brett is a brilliant engineer and entrepreneur and he's very competitive. So he's going up against Tesla and One X and is playing to win. Selene, just quickly, part of the new American dream, right? So it used to be a house in the suburbs with a car.

1:10:00And we need to add a humanoid robot, at least one to that, given that humanoid robot order of magnitude price is a little bit like a cheap car. Yeah, it's, you know, 300 bucks a month, 40 cents an hour. It's how many would you own? I mean, probably a couple. Sky's the limit. Salim, any rants on this, Salim?

1:10:26You're pre-suggesting this. Okay, a couple of thoughts. One is, I go back to Imad's comment about capital who's not needing labor anymore. And this is kind of another indicator along that spectrum, which is a very, very big outcome. The second is, you know, we took us like so long to get FSD working, almost 15 years now, almost 20 years now, with very bounded edge. The edge cases here are infinite when you have a humanoid in the home. Like what the hell, what happens when it thinks the baby is a doll or thinks it's a teddy bear and puts it through the washing machine? I don't understand how we're going to navigate all of those nuances.

1:11:12I think that's a fair analogy. I mean, it took FSD so long to get here because the AI models had to evolve to get to the point where they can work with the data in flow, the VLA models. We have those now. I understand the speed of it and the fact that it may work, but there's so many things that could happen, right? I'll use the example before of your neighbor calling up going, hey, your damn robot's charging itself on my Tesla charger. Frickin' get it off. I don't know how we're going to navigate all of those boundaries which we naturally do and maybe the broad approach of learning from each other will kind of solve a lot of this Salim, these robots are going to be smarter than any human that you possibly know they're all going to be running the most advanced models out there if they can't tell the difference between a doll and a baby or your tesla charger and your neighbors i still don't know why you can't have two extra hands okay we'll get to that finally okay how all right dave what you're gonna say uh well two things first brett brett adcock i spent a bunch of time with him backstage at your last event leader he is just awesome yeah salt of the earth he's a guy that everyone will be cheering for to win that really really makes you feel good about you know everything salim is worried about brett is the guy you want dealing with it.

1:12:38I hope I'm wrong, right? But I'm struggling to make the leap on how we navigate all those edge cases. That's all. With intelligence. The other thing is, you know, to what Alex was saying a second ago, a lot of people are saying, well, look, it doesn't have the same sensory feedback that a human hand has. You know, I've got millions and millions of neurons touching and feeling it. Yeah, no doubt that's true. But it has visual acuity and dexterity that's crazy superhuman. And so it frustrates the heck out of me when people are saying, well, I'm going to work on the smell sensor for this. I'm going to do fundamental research on it.

1:13:12All you have to do to succeed right now is glue together the obvious. For the first time in human history, we have perfect visual pattern recognition. It can easily tell your baby from a doll, easily. And it can do all these fundamental mundane tasks trivially easily, and it has a brilliant AI voice to program it. You don't have to get into coding some arcane language. You just tell it what to do. Those capabilities alone should explode technology. So I'm suffering from a gross lack of imagination here. It's possible. It's possible. Just ask your favorite LLM. I've been wrong before. Never. Rarely, but I've been wrong.

1:13:51Let's move on. We've got a lot to cover. Let's get to chips, energy, and data centers. The first data point here is something that's going to be a real challenge. So U.S. electricity prices reach all-time high. This is a spike in dollars per kilowatt. We've seen it. It was pretty level between 2014 and 2022. And we just see this asymptotic rise in energy. And this is going to hit everybody in their pocket at home. And I can imagine a situation where communities will start to say, no, no, no, you're not allowed to build a data center on our grid because we don't want to be subsidizing your AI system.

1:14:39So there's going to have to be some policy changes here, either differential pricing where consumers pay a pretty flat price and the data centers are paying for the additional required, or something has to happen here. Thoughts, Dave? Or Alex, go ahead, please. Two important caveats here. One, this is nominal dollars per kilowatt hour. So you have to subtract off inflation. So you subtract off inflation, which obviously spiked in the years following 2020, you still get a material increase in electricity price. But once you've subtracted off inflation, we're looking at real dollars per kilowatt hour.

1:15:19This is the market doing what the market does. It's signaling via prices that there's strong demand for utility electricity. And if utility electricity can't supply the thirst for energy for data centers, then we see what we're already seeing, which is data centers will have their own co-located off-the-grid NAT gas and SMR nuclear facilities and maybe eventually reconnect to the grid, which is obviously more ergonomic once the grid is available. But this, I think, again, subtracting off inflation, this is a reflection of the thirst by intelligence for the foreseeable future for energy. Yeah. And at the same time...

1:16:25canceled Esmeralda 7, Nevada's massive solar project set to become the U.S.'s largest solar project in history, capable of powering 2 million homes across 118 ,000 acres of desert land. What are they doing, Salim? Okay, so I did a little research on this. It's not as bad as it seems, right? On the surface, you read this and you go, oh my God, they're canceling solar. What a bunch of idiots. What kind of Luddite revolt are we dealing with here? I would go on a full kind of madness rant like we did last week. I think what's actually, it seems to be actually happening here is that the regulatory headwinds on such a huge project are kind of slowing it down.

1:17:04What they've decided to do is break it up into, they haven't canceled it. What they've done is said, this big thing can't go forward, break it into smaller projects and you can reapply smaller projects to do this. Now, this will still add a huge amount of timeline to it because now everybody has to go back to square one, rebuild this as individual applications, seven, I think, in total, and reapply, which will add a lot to the thing. So it's not all the headline says it is. It's not as bad as the headline says it is, but it's pretty bad. And why can't you just rush this through and get this out there?

1:17:44I don't understand. And we're accelerating nuclear, we're accelerating. Well, the administration is fond of breaking all the regulatory to do what it wants to do. Why isn't it doing this? We need the energy, as we saw in the previous slide. This makes no sense at that level. But there's a bunch of nuances and things, so I don't want to go full crazy. All right. Also this week, the U.S. Army announced the Janus Program for Next Generation Nuclear Energy. So this is deploying commercial microreactors to secure power for U.S. defense. Let's see, Alex, what are your thoughts on this? I think this is a very exciting development.

1:18:23There are many U.S. bases that are almost tyrannized by their need to ship oil. If you remember how, in part, the Pacific theater of World War II started, there was an element to which it was a blockade of oil. And I think to the extent that the U.S. Army can serve as an additional demand function for pushing forward micro-reactors, SMR, nuclear reactors in general, this is going to be a net boon for artificial intelligence. So these micro-reactors are like what? SMRs? These are smaller. Like 20 megawatts? Small fission reactors. Yeah. So it's like a fission reactor in how big a dimension? Like in a shipping container?

1:19:17I don't know the dimensions. Not sure if those have been made publicly available. Can I ask your question? is these are commercially owned and operated, right? And these are sort of like rented to military operations. Yes, that's right. I think that's super smart because it creates demand for all of that stuff. But, you know, we've been running nuclear submarines perfectly well for 50 years without any issues. Why is this such a big deal? I don't know about the fort without any issues. Why haven't they jumped to this point 20 years ago? I think that that is the elephant in the room. So, and the premise also for For All Mankind, one of my favorite television series from Apple TV +, an alternative universe where nuclear energy didn't get kneecapped in the 1970s, but instead had continued to advance.

1:20:04I think we'd be living in a very different world. Both of these slides, yeah, the answer to both questions is more politics than anything else. You know, whose idea was it originally? Okay, we don't like that person anymore, so cancel their idea and replace it with this idea. but yeah there's the the answer to like why didn't we do this 20 years ago is purely because of public backlash you know uh to to you know the perceived risk and some movies it's actually the movies are incredibly damaging to some of these you know if you sure that king from the movie was a killer yeah exactly it's like the jaws equivalent for nuclear reactors you know nobody goes in the ocean anymore all right let's move on type movies yeah let's move on so the next article here is u.s chip plant investment to outpace China, Taiwan, and South Korea by 2027.

1:20:54Alex, do you want to hit this one? Yeah, I think we're seeing the innermost loop of civilization finally recursively accelerating. So between chips... Whoa, whoa, whoa. Hold on a second. Can you just repeat that word for word? The innermost loop? The innermost loop of civilization is recursively accelerating. So So if you look at, as I tried to articulate previously, it's sort of a technology tree or maybe a supply chain of technologies. We have chips. We have energy that we were just talking about. We have robotics. We have data centers. All of these arguably form a sort of a recursive feedback loop.

1:21:32We're going to be using robots to build fabs that produce chips that go into the data centers that are powered by the energy that build better robots and so on. Why is it the innermost? because it's going straight down to the energy equation? I would argue it's the innermost because it's the most recursive and it's also the fastest improving. Yeah, the fastest loop of reinforced learning and improvement. But that flywheel, this innermost flywheel of civilization, I expect to just fly out into the rest of the economy in the next few years. It's not going to stay contained to just those four or five technologies.

1:22:09Contrary to those who are worried about some sort of like circular NVIDIA-esque economy, that's just one big wash sale. I think it's going to spread pretty quickly. And, well, listen, we're seeing this constantly with billions of dollars being deployed, hundreds of billions of dollars being deployed by all the frontier labs. It wants to be sovereign. I mean, that's the other story here with one might project reasonably into the future that just as we're seeing interest from different sovereign powers, interest in inference compute and making sure inference compute, you know, you get a Stargate and you get a Stargate, that inference compute is sovereign.

1:22:56We may reasonably see all of these other sort of core elements of this arguably innermost loop also become geographically distributed. Silicon is the new steel. possibly cool our next article here is nvidia to sell a 3999 dgx spark mini pc and this is pretty epic anybody who is playing with a pc on their desk the spark computer the dgv dgx spark mini can support models with about 200 billion parameters it's got one petaflop or a thousand tera operations per second a thousand trillion operations per second capabilities on them uh god this is going to blow away the macbook as your preferred preferred computer on your desktop all right dave what do you think about this yeah i'm going to get one for sure right away um the question i had was you know i need it dramatically more compute.

1:24:02It's obvious to me, and everybody will soon. I can't get it right now through cursor. I can't get it through the APIs. I'll give this a shot. It's not quite clear how I'm going to get it integrated into my agent world and my coding world, because I don't think that's going to be trivial, but I'll get to work on it and see if I can make it work. But yeah, the device wars are just beginning now, because there's a view of the world where you have a lightweight Johnny Ive device from OpenAI and it's connected to a massive amount of compute on the cloud. Then you've got the NVIDIA Vision here where no, bring it into your home, bring it into your office because then at least you know you've got it.

1:24:38No one else is going to take it from you right as you're producing something. It's not going to disappear. So you feel you have that feeling of like, it's mine, it's under our control. So we'll try both versions of the future, but it's very much in flux right now. But I can't wait to try it. Yeah. All right, let's jump into some of the interesting news in the economy here. This article, data centers and AI account for 92 % of the GDP growth in the first half of 2025. So our GDP grew by 1.6 % in the first half of 2025. And of that 1.6%, 1.5 % of the 1.6 % was data centers and AI, right? So now Alex's inner loop comment is making sense.

1:25:22Yeah. That was brilliant. I love that comment, by the way. This, Salim, this is just the opening act. So the opening act is we spend a bunch of our GDP on building out, you know, tiling the earth, as it were. The next act, I would predict, is transformative applications that pour out of all of these data centers that we're building that solve math, science, engineering, medicine, the works to justify all this capex. But this is the economy right now. This is divide by zero. It goes to infinity pretty fast. um i i think we're just beginning i mean we've talked about this right of the of the explosion of the gdp in the united states and to a to a large degree other parts of the world um so and we're beginning so the economy now runs on math and we've just solved math well we better find harder math or move on to to non-math problems but the question becomes if we're if we're exploding the gdp right there there's wealth being created and you know one of the big challenges is how do we redistribute that wealth right how do we have it not be concentrated part of it's going to be that the cost of living which is of great concern a lot of people right cost of living has arguably increased cause of inflation uh but it hasn't yet come down uh here are we going to see it Here's something to watch out for in this.

1:26:46If you follow Alex's kind of train of thought here, the three areas where we have increased costs are healthcare, education, financial services, because those are highly regulated. When we see major breakthroughs and demonetization in those areas, then we'll know we're winning. How's that for a thought? I think that's true. We're going to reinvent healthcare. I mean, the best healthcare in the world should be free and fully democratized. the best education in the world will be free and fully democratized. It just hasn't happened yet. Two points on this story real quick. One of them is that the spin on the story was, well, without AI data centers, the economy would be in terrible shape.

1:27:27Not true. All that happened here is all the capital and effort went into this instead of something else, because this is much more urgent. So the economy would have been in fine shape either way. But we just chose to use all of our time, money, real estate investment, everything on this problem because it's such an important and urgent problem. We're planting seeds. We're planting seeds for future growth. Exactly. The other thing is that this is where AI benefits everybody. You know, to the point you made at the front of the podcast, Peter, anyone who wanted to help Elon Musk build his data center in Tennessee and was willing to go there and help him do it could instantly double their salary because he was willing to, in the urgent race to build all this, more than willing to pay whatever it takes to get everyone to come and work on that project.

1:28:11Electricians, air conditioning, plumbers. So this is really, really democratizing the AI revolution in a big way. And it benefits any state, actually, that wants to jump on, start building data centers, is going to create jobs. This is like the second industrial revolution. It's like electrification or like intercontinental railroad. The fun stuff happens once all the infrastructure is already in place. Exactly. Exactly. We're planting the seeds that will blossom into a hole, almost unimaginable. And speaking of that, here's our next article. I found this one fascinating. The Dallas Federal Reserve is preparing for AGI.

1:28:49And so there we see here a chart in which they're making some predictions So the Dallas fed seriously considering a benign singularity By the way, we should tell them we're living through it right now Where the economy productively explodes between now and 2035, right? Everybody the next 10 years the next five years is the game You're alive during the most extraordinary time ever to be alive and you're witnessing it Which is incredible. So they actually in this graph, they look at a couple of things. So there's scenario planning. They have a baseline versus AI boosted singularity. And they have two curves, sort of one in which it's a benign singularity and things literally go into hyper-exponential growth.

1:29:37They have another one, which is a singularity extinction path, which I don't want to be thinking about. But if Shit hits the fan, and we've got real problems. So I find it fascinating that Federal Reserve is thinking about this. Yes, Salim. Two thoughts here. So this might have a second or third level impact from us because we've actually had some folks talking to these people for a while. I'm very impressed that they're doing this. This is great. This is essentially pricing exponential growth into the economy, which is amazing. Well, I think it's utterly, I posted this on our chat, but utterly frustrating and idiotic that they settled.

1:30:21They looked at these scenarios where the red line goes through the roof, the purple line, we all die next year. What we've decided is that the final impact, our best prediction, is 0.3%. It's the difference, you see those two lines that you can't even tell the difference between them? That's what we think our best guess at the final answer is. Utterly, utterly idiotic. I mean, but this is what's happening in all of our interactions with government agencies that we're having. It's the same, like, absent any idea, I'm going to forecast something incredibly timid. This is your rant from last week, Salim.

1:30:56It is, it is, it is, it is. And what they've done is gone, let's put this in to cover our bets so we don't get flamed later. Yeah, but otherwise, let's predict a marginally small increase over the next decade. But I'd like to take the positive out of this, that at least they're bringing it into the models, and then we can have the basis for fixing it later. I don't blame the people. I don't blame the people. They're in a system where they get punished for anything outside of 0.3%. I think it's very encouraging that the Fed is considering the possibility. But I would also just question, is GDP per capita necessarily the right measure for productivity?

1:31:37Does GDP properly capture productivity? Yeah, we need a new metric there for sure. This is a huge, huge conversation because when you have demonetization, GDP collapses, but everything is 10x better. So what the hell? Yeah. So Texas is really playing at a big game here, right? With Starbase there, with Tesla there, companies moving there. And so the SEC approves that the Texas Stock Exchange can ease the rules for a public listing. One of the things that powers our economy is the whole venture model, which invests in companies that then build their valuation and then build to an IPO in liquidity.

1:32:19And it's been slow and painful over the last five years. Dave, your thoughts on this one? Oh, huge amount of thoughts. I'll keep it short because I could talk for hours on this topic. But, you know, Peter, you and I have taken companies public before. The process needs to be simplified. It's arcane. It's arcane. And also what gets reported with GAAP accounting and all your 10Qs and all that, what gets reported is just a huge amount of garbage compared to just the simple, accurate truth. And so the AI version of this is going to be phenomenal where everything is reported, it's perfectly accurate, it's perfectly accountable, but it's much simpler.

1:32:59The AI can interpret it. You know exactly what you're investing in. But the beautiful thing about this is that we'll now have another choice and then hopefully a bunch of other choices other than just a New York Stock Exchange and NASDAQ. And choice is the answer. As long as there are competing exchanges, this will all get solved. But we desperately need it because the pathway to liquidity is the pathway to investment. The pathway to investment determines whether the US wins or loses the AI race against China. And so this is critically important. So important. The whole idea of all the accountants and lawyers you have to hire to take a company public is to assure that a grandma who buys your stock isn't being ripped off, right?

1:33:44It's basically, it's cover your ass across the entire process. And it should be possible for an AI system to evaluate a company and its stock and make sure that in fact, everything they say is correct and just accelerate this by a factor of 100-fold, not just two-fold. Yeah, and for a while there, you know, we thought the blockchain by itself would solve this problem and that you could raise capital through a coin offering, an ICO, and that would replace the IPO. But you do need, it just doesn't work without some regulatory guarantee. Otherwise, it can get corrupt way too quickly. So this is the perfect hybrid, I think.

1:34:20I like the general trend that we're moving from centralized systems to decentralized systems. And this, this will bring in the abundance economy in a way, because it'll allow a much better choice and markets will thrive. All right. We're going to close on health and, and a discussion about the singularity you're not going to want to miss. All right. So in our health segment here, I'm going to play a video. This is an ALS patient with a Neuralink feeding themselves. Here we can see a individual, I think it's their, third patient controlling a robotic arm and being able to, with their thoughts, pick up food and feed it to themselves.

1:35:01I mean, this is the beginning of the merger of humans and machines. It's crude. We're going to see, by the way, this year at the Abundance Summit, I'm going to be bringing two of the top BCI companies, a company that's got, you know, an order of magnitude or a couple orders of magnitude, more bandwidth connectivity between the neocortex than Neuralink has, and another one that's being backed by Sam Altman that is a brand new approach to BCI. So we are 90 % full on the Abundance Summit this year. We were selling out way before. If you're interested, you can go to abundance360.com to learn more about it, but super excited about the acceleration of BCI.

1:35:50Alex, you want to add something on this one? Yeah. First, obviously, this is transformative for people living with ALS and tremendous progress. I also think more broadly, this is the beginnings of democratizing access to our motor cortex. Imagine anyone being able to augment themselves in a variety of ways to control an exoskeleton. And also, in some sense, every sci-fi author I've mentioned in the past, I'm a sci-fi snob. Many sci-fi authors just can't resist the tendency to just extrapolate a single dimension like, oh, we get AI or, oh, you know, the apocalypse happens in a very narrow way. But actually, I think the future we find ourselves in is one where every single sci-fi scenario happens all at once.

1:36:37So we're getting AI and we're getting cyborgs and we're getting this and that. And that's a much more exciting future and present to be living in. In the next five years. We often talk about it as you're going to get Star Trek or Mad Max. And we thought it was one or the other. And it's clearly happening both. Like Ukraine, Gaza. Same world, same universe, all happening. It's the ultimate crossover. Everything, all the time, everywhere, all at once. By the way, for me, that robot ALS thing was a little bit in the ho-hum category in the sense that I would expect to see that happen. Like we expect, we should be expecting these innovations at this point.

1:37:15How quickly our expectations get re-normalized. Yes. How quickly the miraculous becomes boring. I mean, honestly. We'll talk about this more in the next section, but I remember when Singularity came out, we launched Singularity University, an article came out on CNET saying, it was being led by Ray Kurzweil, Peter Diamandis, and the noted transhumanist Salim Ismail. And I had to go look up, look the term up. What is a transhumanist? and it turns out in the definition transhumanist as a human being has augmented themselves with technology and it makes no sense to me that whole framing so we can talk about this more but you know dave you wear glasses are you a transhumanist like where do the spectrum is ridiculous on this all right let's move forward i want to i want to hit our last two articles and get into our singularity debate here so uh this article is google's ai cracks a new cancer code so So Google DeepMind developed the AI model called Cell to Sentence-Scale, generating a new cancer treatment that's never been seen before.

1:38:17AI analyzed tumors and tested 4 ,000 drug candidates virtually. Incredible. Alex, what are your thoughts? Well, my immediate thought now is that Google cracks cancer with a new modality for a sentence model. And Salim is going to say, ho-hum. what's next no this is this is I think a very important development so so the the first I think big thing to understand is the cell to sentence model this is a new modality in in some sense so we know models speak text they speak video now very popular they speak audio speaking cell and speaking cell proteomic expression is a whole new modality so Google coins this notion of a cell sentence.

1:39:04A cell sentence is a sentence of genes. So it's literally like text with a sequence of gene names ordered in descending order by how much the gene has been expressed in the cell. That's a cell sentence. So treating cell sentences as first-class citizens alongside English sentences enables you to have conversations with virtual cells. We've spoken on the pod previously about how, in principle, medicine can be solved by simply having the world's best virtual cell simulator and virtual organ simulator and virtual organism simulator, and just having questions with these simulations. This is, I think, a very, very important step, being able to have a conversation with a cell and asking it, like, how do we solve cancer?

1:39:50I'm not pulling the whole home card. This is amazing. This is really huge. I totally get where you're going. This is monstrous. Yeah, it's amazing in the narrow sense and in the broad sense. In the broad sense, it's a great example of a domain where AI can think unlike a human, you know, about, you know, things where we just don't have any intuitive intelligence because we don't live at the cellular level. The AI doesn't care. It's just data from the AI's point of view. So it gets very, very good intuition, far better than any human being. You know, so in parallel with that, you've got things like magnetic containment of a fusion reaction, very hard to visualize.

1:40:24AI just cuts right through it. And like all these other areas, because we tend to continually show those charts that benchmark, here's Gemini 2.5, here is a human doing this exact same task. But what about all these domains where people just don't operate naturally? This is a great case study to track closely. Yeah. You know, we heard recently - Is this tickling into symbolic AI? Would you agree with that? No. How would you define symbolic AI? I don't know. It makes my skin. We heard Minsky said it. You know, we heard Demis Hassabis say curing all disease within a decade. We heard Dariya Amadei talk about doubling the human lifespan in the next five to ten years.

1:41:09I mean, this is, you know, sort of the bent twig that shows us where we're heading. And I just, you know, for me, one of the most important mindsets someone can have is a longevity mindset. And it's the belief that, in fact, we're going to be heading towards longevity escape velocity, which is our next article here. We're going to be wrapping on this in a discussion of the singularity. So let me just read this out loud. Ray Kurzweil reinforces his optimism on longevity escape velocity, LEV, by 2032. So he's predicting that by the early 2030s, nanobots could connect with human brains directly to the cloud.

1:41:46by 2045 humans will reach the singularity so hitting on the first topic of reaching longevity escape velocity what is lev so for the last century most of 1900 through 2000 we were adding about three months per year that you were alive so you for every year that you're living you're extending your life for a quarter of a year the idea of longevity escape velocity is that there's to be a point that for every year that you're alive, science is extending your life for more than a year, right? And at that point, it's a choice of how long you might want to live. I have a great example. I have a friend who has a kidney problem and they're giving him the drugs to stabilize his kidney for the next few months because then the drugs will be available to solve it for another five years.

1:42:33So you don't have to solve the whole thing. You just have to solve to the next hop, right? And with all the stem cell therapies, gene therapies, we're going for three months to six months to nine months. Then we cross that threshold. We're adding more than a year to your life per calendar year that goes by. And at that point, you can live for a theoretically, arbitrarily long period of time. Yeah. And we just, I just finished my abundance longevity trip and we had 50 companies that were each contributing towards this direction and some amazing, amazing tech. It's, it's coming, it's coming so fast.

1:43:06And it's not because we've gotten smarter or have, you know, done anything linear. It's the impact of AI. Every single biologist who's driving breakthroughs is driving it on the back of AI. So the two truisms used to be death and taxes. So we're going to solve death now and taxes may be solved by crypto. So there's like, we're kind of there and nothing more to do. I want to hit on the conversation of Ray stating that we're going to have the singularity by 2045. And I'd love to get some thoughts on here. So, you know, what is the singularity by Ray's definition? I asked Gemini 2.5 since Ray was the futurist in residence at Google.

1:43:50And I said, what are the three things that connote the singularity as Ray defines it? And number one, it's non-biological intelligence exceeds biological intelligence. Well, I kind of feel like it's there now. Number two, human-machine merger. Humans become hybrids or non-biological. Again, moving there very quickly. And then three, radical transformation of the world. Biology, physics, and society beyond what we can easily predict. And this is, you know, Alex, what you speak about solving everything. So what do you guys think is, you know, the singularity? Well, I'll give you my two cents on this comment because Ray, to me, is just brilliant.

1:44:34And he predicted the singularity and he named it back in the 1990s. And his timelines and his curves and everything, he got crapped on so hard by so many people for so many years. And he's going to land it like right on the nut. And I hope that history documents it that way. I think what he's wrestling with right now is we all agree on this podcast that we're right in the middle of the singularity at this moment. And so I think he's trying to push off the date to a point in the future where people don't bother him about it anymore. I'm just guessing. And he'll just let it play out from here. Because one thing about futurists, Peter, I know you deal with this all the time.

1:45:13And when you're right 99 times out of 100, you know, Peter, remember he said, yeah, everyone's going to have a computer that's more powerful than the biggest supercomputers in the world in their pocket. And they'll be wearing it around. And now everyone's like got an iPhone and they're like, oh, is that what he meant? Huh? Well, who cares? You know, everyone knew that was coming. But they remember the one time that you were wrong. Yeah, exactly. He thought we'd have full self-driving and we'd all be in our self-driving cars today. He got hit so hard last year and the year before because we're not in our self-driving cars.

1:45:41and that's because of regulatory slowdowns, but we'll be there imminently. And it's just so frustrating to see him get picked on that way. So my guess is he's saying, look, don't bother me about singularity definitions till 2045, because it'll be history by then anyway. But we all know right here, right now, the AI is clearly self-improving. It's doing its own chip design. We saw that Brockman article earlier. We're right in the middle of the singularity as he originally defined it. It is now, the singularity is now. Alex? I think I agree with most of the prediction except for the discontinuity.

1:46:16That was that third item. So there's an intellectual strain that starts with I.J. Goode coming up with this notion of an intelligence explosion. Then I.J. Goode passes the torch to Werner Vingy, who popularizes the notion of technological singularity, then passing the torch again to Ray. I think this notion that we're going to have an intelligence explosion that somehow leads to a point of discontinuity where we can't predict what's on the other side, that's the part that I struggle with. That's a definition of a singularity. I mean, the idea that there's an event horizon and beyond which you can't see what's happening next.

1:46:54And it sort of feels like we're in the midst of continuous event horizons, right? But I also think, like, I feel maybe this is just one person's perspective, but I kind of feel like we have line of sight as to what happens next. Like, we're solving intelligence. It's well on its way to having been solved. Using superintelligence to solve math, science, engineering, medicine, a bunch of other things, solve everything. And then presumably we'll discover the nature of our universe, the nature of the trajectory of intelligent civilizations. I would expect to gain deep insight into that over the next, call it, 10 plus years.

1:47:36And that to me doesn't feel like a discontinuity where you can't see what's next. I think you have a pretty good line of sight. And I think it's such a good outcome. If you go back to the original book, that's mind-blowing original book from 1990s, the step function version of this is kind of weird in that the AI is in a box somewhere and it's self-improving itself and it finds some way to create its own nanotube-based compute. So it doesn't need GPUs from NVIDIA. It's building its own compute inside its own kind of box world. And you go to bed one night and you wake up the next day and it's like it's taken over everything.

1:48:08And that's not a good outcome in any way, shape, or form. The way it's evolving looks like a step function on any reasonable timescale. But as you're living it, it's actually manageable week to week. If you really focus, you can actually see next week's innovations coming. And you can actually benefit from it and also guide it. So it's actually working out better than you ever could have predicted. You know, plenty of risk, plenty of things we need to get on top of. But it's a great version of the singularity. Just embrace it. Can I say a couple of comments here? Of course, Liam. I would expect nothing less.

1:48:44You know, back when we had the founding conference of Singularity University, I'd never heard of you. I'd never heard of Rhea. I'd never even heard of Singularity, right? I walked in totally blank. How did you get invited to that in the first place? When I was at Yahoo running BrickHouse and heading up innovation there, I set up a relationship with NASA to do some interesting projects together. Right? Back in the old days, they had millions of satellite images. We had millions of Flickr users. Could we help tag those? My dream was, can we have a satellite hanging in our office to show that's what real innovation looks like?

1:49:18And can I tell a little snippet of an anecdote? Yeah, sure. So we used to have speakers from NASA come and speak at Brickhouse. And we had an event once where you have to imagine this event in San Francisco with 300 software developers, all with tight jeans, slicked back hair, MacBooks on their laps, white socks, et cetera. And we had this 75-year-old guy from NASA come and speak. He was where he'd worked on the lunar program, on the Apollo program. And so he did this talk, and everybody's kind of, most of the people are looking. Q &A comes along and I said, what's the biggest difference now between the space industry now and when you were, you know, working on the Apollo program?

1:49:57And he goes, huh, good question. He goes, maybe it was computers. And I'm like, what do you mean? He goes, well, we had no computers. So all information was transmitted via carbon copy paper. The pink sheet went there. The green sheet went there. The yellow sheet went there. And all of a sudden, I was standing at the back of the room and you saw these 300 developers all look up and their brains all were exploding at the same time going, how did they do what they did? with carbon copy paper sheets being passed around, right? It's like kind of an unbelievable thing. So that's how I got through the NASA discussion.

1:50:28The NASA people one day called me and said, hey, we're helping host this founding conference for a singularity university. We're bringing 70 thought leaders together, come along. So I was actually supposed to take Lily away that weekend, but it was so weird, this thing. I was like, you know what? Let's cancel the weekend. Let's go to this thing. And that's where Peter, you and I met. And this concept comes along called the singularity. A few weeks later, you said, hey, come along and help us run it. And I remember getting a call from Brad Templeton later that day. And he goes, hey, I didn't know you were a singularitarian.

1:50:59I'm like, wait, what's that? And so then I had to look that up. And what attracted me was the original thesis was we can now use technology to address grand challenges because these technologies scale naturally. And that was the most profound and interesting thing, which was the whole compelling thing about 10th and the 9th. And Peter, your vision of using these technologies to address global problems. Yeah, to positively impact the lives of a billion. The secret thing that you don't tell people is that you're trying to find more teams to work on X prizes. That's the part that you don't talk about publicly.

1:51:32Anyway, so singularity gets built. And we were talking about the singularity, which was, at that time, it was defined as the point where machine intelligence overtakes human intelligence. That was the common framing. Which we're there now. And I disagreed with it. Publicly, I disagreed with it because, A, go back to my intelligence rant. We don't know what intelligence is. There's like a dozen facets of it. And, B, my second part was what constitutes overtaking? The minute I can prescriptively describe a task, an AI robot's going to do it much better than me anyway. So it's a bit of a non sequitur.

1:52:02So kind of that tension comes along. And then Ray writes the singularities nearer and becomes more of a process. And I really like Alex's framing of it, that for us living in it, it seems normal. But when you step back in history, it's going to be this unbelievable inflection point. And this is, I think, the key part of it, where we just kind of live through it and we get there. The outcomes of it, of us being able to solve all major problems with AI now, because AI will then solve material science, etc., is the most profoundly amazing part. which is why we get so enthusiastic and bubbly excited about this and I apologize for the ho-hum cars now and then it's just that sometimes you know you get to a point where you're living this conversation you're spoiled you get spoiled you're kind of like oh yeah we would expect to see that etc and then you go nuts at the Luddites who are going well this is a bad idea and cancel the most important projects in the world I mean anyway yeah well that last point I think is if anything's changed in the last three weeks that's really palpable to me.

1:53:07It's that there's always gonna be doubters and haters and they're all over the place. But the countervailing voice to that has been Dennis Hassabis and Sam Altman and Elon Musk. But very recently, Sam has toned it down, Dennis has toned it down. And it's not because they don't believe that it's happening right now. It's because it's happening anyway and they don't need to promote it. They're doing it inside their building at warp speed and they don't need another picketer outside the door tomorrow. And so what you'll see now is kind of this kind of, hey, did things get quiet? Did things slow down as they explode inside various rooms and labs?

1:53:49The framing I like the best is that all our previous models for how the world operated break down and we need totally new models. Like Alex talked about needing new benchmarks, right? We need to formulate totally new models for where the world goes. GDP, for example, is not a workable model. And it's going to be the new social contract that needs to be reformed as well. How do people use this? How do they get their dividend from AI, whether it's reduction in the cost of all the things that they need, increased agility and their ability to build? And full disclosure here with my secret plan has been that I've been building this EXO community around the book, which is now 40 ,000 people in 150 countries speaking 47 languages.

1:54:34What we're actually doing is building kind of like a peace corps to help this transformation, because we're going to need an army of people that are practiced and versed in this model and the new models that are coming to be able to ease that transition. Otherwise, we'll end up in several hundred years of the dark ages. Yeah, you know, Salim, you, Dave, and I are going to be in Saudi in about a week, 10 days' time, and one of the projects we've been working on with IMAD is how do you use AI to provide every sovereign nation the ability to govern better, to establish policies? Because we're going to have a lot of disruptive change coming.

1:55:10You know, and all of a sudden, when people are living 30 healthy years longer, or humanoid robots are in the hundreds of millions and at 40 cents an hour, these things are going to change nation states fundamentally and their ability to rapidly adopt new policies, educate their populace, spread the wealth, if you would, is super important. So we'll be doing that. And then this coming week, Salim, I'll be with you and Imad and Eric Coulier recording a WTF episode live at XPRIZE Visioneering in Malibu. Again, if you're interested in joining us for that, We have a few tickets left for XPRIZE Visioneering.

1:55:54You can go to XPRIZE.org to learn more, and we'll put the link as well for Visioneering down in the chat. I would like to just, again, point out what Dave suggested at the beginning, that Ray will go down as—I kind of think of him not as a real person. He's like an avatar from the future. I think he proves that time travel does exist, because how the hell did he come up with this stuff decades ago, and it's proving he must be just coming from the past, from the future into the present. And I'll tell one quick anecdote. We once, you know, Ray would come and speak at Singularity. I've heard him speak maybe 60 times.

1:56:30I've never not learned something, which is really, really, really frustrating because you have to listen for that little nugget of gold. We once were able to, we once got him two glasses of wine before he did his talk. Oh, no. And nobody has ever forgotten that two-hour session where he just kind of riffed on. And it was utterly brilliant. It was there he said that language is a really thin pipe to discuss topics as complex as some of the ones we're discussing, right? And you have this unbelievable wisdom coming from and this ability to perceive decades in the future with unbelievable accuracy and accurate framing, et cetera.

1:57:06I think this is going to go, the accuracy of what he has kind of put down, and he's willing to put it down and be kind of gauged by it is going to go down in history. Amazing. That's a good note to close on. Moonshot mates, love you all. Thank you for your intelligence, your predictions, your humor. We need to get Ray to write a book. The singularity is now. Or it's come and gone. Either way. And maybe we should get Ray on this podcast with us. We should. And I think a really important comment is what Alex pointed out is like, how do we navigate this for this future? Because we can see it's coming now.

1:57:43So what does that future look like? And let's start painting that picture. All right. Have an amazing week, guys. Be seeing you and talking to you very soon. I have reading to do. Yes, you do. Thanks, Peter. Bye, guys. Thanks, guys. Every week, my team and I study the top 10 technology metatrends that will transform industries over the decade ahead. I cover trends ranging from humanoid robotics, AGI, and quantum computing to transport, energy, longevity, and more. There's no fluff, only the most important stuff that matters, that impacts our lives, our companies, and our careers. If you want me to share these meta trends with you, I write a newsletter twice a week, sending it out as a short two-minute read via email.

1:58:23And if you want to discover the most important meta trends 10 years before anyone else, this reports for you. Readers include founders and CEOs from the world's most disruptive companies and entrepreneurs building the world's most disruptive tech. It's not for you if you don't want to be informed about what's coming, why it matters, and how you can benefit from it. To subscribe for free, go to dmaddis.com slash metatrends to gain access to the trends 10 years before anyone else. All right, now back to this episode.

1:59:06Abercrombie Kids knows how to make outfitting easy. Mix and match sets are their ultimate outfit hack for fall. Their sweatshirts and sweatpants are super cozy, and they always have the cutest colors and patterns. Shop fall's easiest outfit at Abercrombie Kids in the app, online, and in stores.