Transcript: NVIDIA’s .2B Quarter, China’s 200,000 Fake Accounts, & OpenAI’s New Chip – Moonshots EP #284

Crazy. In related news, Elon Musk is making some bold predictions about SpaceX revenues. We’ve heard him in the past say that he’s going to— on the last earnings call, he’s going to reach $1 trillion in revenue by 2030, potentially 2029. Now, yesterday, Elon tweeted that he may well reach $3.5 trillion in revenue in 2033. You know, by reference, the company today with the highest revenue is Amazon at $828 billion, just to give it some context for Elon’s $3.5 trillion. Dave, let me go to you first. You know, is Nvidia’s revenue growth sustainable or is this just the peak here? What do you think about that?

DAVE BLUNDIN: (00:06:32 – 00:07:21) Actually, it’s a really interesting two forks in the road here. Nvidia has a lot of vulnerabilities and it will come up later in the pod. But at the same time, they’re going to be sold out for as far as the eye can see, no matter what. So, I think that everyone’s got to use Nvidia for training neural nets. It’s 90% of the revenue, 95% of the profits. And these revenues are not just revenues. These are 80% to 85% gross margin revenues. The profitability of this company has never been seen before on the face of the earth. And to the extent— but everybody’s vulnerable, too, because all the major companies, all the magnum opuses are starting to overlap so much in what they do. So the biggest vulnerability at Nvidia by far is TSMC is still their one and only manufacturer of everything they sell. I mean, have you ever seen—

PETER DIAMANDIS: (00:07:21 – 00:07:25) I’m amazed they haven’t vertically integrated or haven’t tried to like Elon is.

DAVE BLUNDIN: (00:07:25 – 00:09:01) Well, I mean, but there is tricky because if they were to try and build their own fabs, they’d have to do it very quietly and sneakily because they cannot piss off TSMC. You know, they’re about a third of TSMC’s manufacturing goes to Nvidia. And another third roughly goes to Apple, and the whole rest of the world gets the other third. But you can’t rock that boat casually. You have to do it very sneakily. And as Alex has said on many podcasts, there’s new physics and new technology is going to come through AI imminently, which could disrupt the entire manufacturing supply chain, how chips are made, what they’re made of. And so, there’s just so much change coming. So, Nvidia is making all kinds of moves to shore up its position while it’s on top of the world. And you almost can’t spend the money fast enough at the rate that it’s coming in. I was talking to my kids about, well, with so many of our portfolio companies, I’ll meet with them weekly, and they’ll say, oh, I had a meeting with a manufacturer in Vermont. I had a meeting with JP Morgan. Why are you meeting with anyone other than Jensen, or one of the other magna mobsta companies or one of their satellites. Like, it’s insane. The amount of money pouring through just that funnel dwarfs the entire rest of the economy. And your success and failure is intimately tied to just that one thing, and everything else is just a distraction. So, you know, Jensen is— he’s pouring out money in checks of $5 billion here, $12 billion there, $20 billion there. And if you’re not in that flow of conversations, you’re not in the most relevant conversation in the world, in the history of the world.

PETER DIAMANDIS: (00:09:01 – 00:09:04) Let me call him one second, I need some more capital.

DAVE BLUNDIN: (00:09:04 – 00:09:11) Yeah, exactly, exactly. And you know, if you can’t get Jensen, just get one of his E-staff. There’s only, what, 20, 25 people in that list? Talk to them.

SALIM ISMAIL: (00:09:11 – 00:09:11) Crazy.

PETER DIAMANDIS: (00:09:11 – 00:09:12) Alex, what do you make of this?

DR. ALEXANDER WISSNER-GROSS: (00:09:14 – 00:11:19) Yeah, I’d be the last person to suggest that this is one big wash trade, circular financing scheme. But I do wonder the extent to which the financial markets have fully priced in Nvidia’s financing of their customers. I guess that’s— to the extent there is an elephant in this particular room, that would be it. And I think it would sure be swell as a participant in the financial markets to have clearer distinction between how much of this demand is Nvidia-financed demand or not. If it turns out that a disproportionate amount of this demand is directly or indirectly backstopped or financed or credited by Nvidia through one or more intermediaries, then I think that starts to look a little bit too bubbly, which I’m not thrilled with at all. I’d like to see no hiccups in this singularity. I would not like to discover 2 to 3 years from now that some, or a large portion of all of this demand at the infra layer was being artificially propped up through financial engineering. I think that would be a highly suboptimal outcome. I still think even if it turned out that some quantum of the demand, the exploding demand that we’re seeing, is being artificially inflated through financial engineering, my forecast— this is not investment advice, but my forecast is at most a mini winter, as it were, because I think compute is fundamentally substituting for real estate and human labor and other raw inputs as the fundamental substrate for human civilization. But when I see nosebleed growth numbers like this, and I see a bunch of other headlines, Nvidia financing a bunch of data center deployments, I have, in full transparency, a little bit of a tickle at this point in the back of my mind, how much of this is financial engineering.

PETER DIAMANDIS: (00:11:20 – 00:11:48) Nice. Hey, Salim, are you seeing the same videos on X that I am, like from Ray Dalio and other financial leaders saying, “I’m out of the markets”? You know, the P/E ratios are off the charts. And there’s this level of fearmongering in the financial markets. At the same time, you’re seeing this massive growth and there’s like, where do you go? Do you stay fully in? Do you jump out? How do you think about it?

SALIM ISMAIL: (00:11:49 – 00:12:03) This is a classic dilemma, right? You’ve got to hedge your bets in this model. I think Alex makes a really great point, the circular revenue is very concerning. I love the way you say it, Alex. It would be swell if it wasn’t— it was all tickety-boo.

DR. ALEXANDER WISSNER-GROSS: (00:12:03 – 00:12:07) I don’t want this to be financial. I don’t want this to be a bubble. I really don’t.

SALIM ISMAIL: (00:12:07 – 00:12:43) I totally understand. It would be really bad if the whole thing collapsed, and then we were now in a dead period for a period of time, and that just slows civilization down dramatically. And that would be a bad thing. You’re better off having steady, regular growth where the market has time to self-correct in the new structures. And we don’t have that right now. Things are kind of same vertical. But from what— there’s a couple of things happening that I found interesting. One is, what’s clear is Nvidia is trying to move out of just being a chip company to try and become like literally an operating system for the whole of intelligence, right? I thought the Hugging Face acquisition was super smart.

PETER DIAMANDIS: (00:12:43 – 00:12:47) And so that’s just— that’s still a rumor, right? But do we know?

SALIM ISMAIL: (00:12:48 – 00:13:01) Yes, if it’s alleged, shall we say, right? But this reminds me of being as clever as Microsoft buying GitHub, right? Can I tell a quick story about this?

DAVE BLUNDIN: (00:13:01 – 00:13:01) Of course.

SALIM ISMAIL: (00:13:01 – 00:14:18) So Microsoft tries to acquire GitHub, which was less than 10 years old, for $7.5 billion. Okay, the CFO and corp dev people start freaking out going, the company has barely any assets, it has barely any workforce, it has barely any intellectual property. What the hell are we buying here, right? What do I put on the balance sheet? Then they were literally trying to kill the transaction until Satya said, listen, we’re buying 30 million developers’ loyalty because that’s how many people use GitHub at the time. And so we overrode that and they got it done. Now as we move into this AI world, GitHub turned out to be one of the smartest things they could have ever have done because it gave them access into all of that open source thinking and access to all of that stuff. The same thing is happening if this acquisition happens. You’re buying the community, and that’s a very classic ExO play to do this. To your broader point, Peter, about are we in a bubble, etc., I think there’s some macro things happening that are much more concerning. For example, we’re printing money like it’s going out of style, and I think that has a bigger chance of collapsing the markets than anything else. What’s happening with the bond markets and Japan and stuff is absolutely insane, in terms of the circular chaos in the fiat currency world. But that’s a different discussion.

DAVE BLUNDIN: (00:14:18 – 00:14:18) Yeah.

PETER DIAMANDIS: (00:14:19 – 00:14:30) So let me jump to the SpaceX story of Elon projecting $3.5 trillion by 2033. Dave and Alex, love your points on this.

DAVE BLUNDIN: (00:14:31 – 00:15:17) Well, for starters, you said it up front, no company in the history of the world has ever gotten to $1 trillion in revenue. And that includes massive, massive companies like Amazon and Walmart, $3.5 trillion. But, you know, Elon’s always been right before. He’s often been wrong by a couple of years in the timeline, but not because of anything other than barriers that didn’t need to exist, engineering mistakes, regulatory barriers, whatever. So he always says, look, this is the native size of the opportunity and this is the best-case timeline. And then the size always turns out to be right and the timeline is off by a couple of years because of unforeseen delays. So I have no reason to believe he’s wrong about the $3.5 trillion. But the scale of that relative to anything in history, it’s just mind-boggling.

DR. ALEXANDER WISSNER-GROSS: (00:15:18 – 00:16:58) Alex? Yeah, I think Elon tends to like to move in 3-dimensional ways. So again, without this being misconstrued as any sort of investment advice, I think there is a path to that, but I think it’s a highly nonlinear, multidimensional path. I think the most obvious path to get there is one, SpaceX and Tesla merge sometime in the next year or two. And that gives SpaceX, the new SpaceX, not the old SpaceX, Optimus revenue. I think Optimus alone, not financial advice, could be a multi-trillion-dollar-per-year business. And then the cloud. SpaceX offering hyperscaler services, which last I checked were the majority of its revenue growth in the past few months, could continue to grow its hyperscaler business, both terrestrially, which is where it is now, and soon the Dyson swarm. I think the Dyson swarm alone could probably generate trillions of dollars in revenue. I think Starlink probably in the face of Optimus and the Dyson swarm ends up being rounding error. I think cars are rounding error. I think applications, which interestingly in the SpaceX S-1, SpaceX went on and on about digital Optimus and applications and the service economy, maybe seems unlikely. I think the core strength of Elon’s ecosystem is less application layer and more physical infrastructure. So if they just totally dominate robots and orbital data center infra, I think that’s probably a few trillion dollars.

PETER DIAMANDIS: (00:16:59 – 00:18:03) I mean, SpaceX is my largest financial bet right now, full disclosure. And I think about it as a way of, if you’re investing in OpenAI or Anthropic, it’s a single layer bet. You’re betting on the models. But SpaceX is everything. It’s ultimately chips and data centers and models and comms and infrastructure and launch. And you get a chance to bet on all of them. You know, I think the biggest risk is just Elon being around long enough to implement his vision. So I know he’s probably walking around with an army of guards. When I see him on occasion, it doesn’t look that way. So I hope he’s got the proper protection. For our listeners here, Dave, you know, we’re not a financial show, but we’re throwing around massive numbers here. And how do you think about playing this market, staying in it, doubling down, hedging against it? What’s your—

DAVE BLUNDIN: (00:18:03 – 00:21:18) You know, it’s actually, I think, in some senses getting easier to understand because everything that’s going on, you can start to understand it from just 2 things: AI training and AI inference. And, you know, what Elon is putting into space is purely inference. You know, all the satellites, all the revenue is going to be from Starlink, which is about connecting AI-generated video and other AI-generated content to everybody on the planet. But also the AI data centers are going to dwarf everything that Elon’s launched so far. It’s just inference time data center in space, but that’s inference only. You know, the training time is a very different beast. That’s where Nvidia is just going to kill it because for training time, you need all the GPUs to be coherent in one location. Like Tennessee. You know, you need 100,000 and ultimately a million and then, probably several million Nvidia GPUs to be in this kind of very tight all-collect cluster that can train the next generation of models. But at inference time, it can be spread all over the world, all over space. And so those are very, very different emerging markets. Even the chips are going to be very different for those 2 markets. And then everything else kind of falls out from that. You’re like, well, what’s sustainable and investable? Robotics is sustainable, investable, but only if you have great AI at designing robots. You know, the idea that you can build a better robotics company without great inference time models that are specific to manufacturing, to design, you’ll never sustain it. So then you start to see all these great investments in all these vertical markets like drug discovery and robotics, but they’re all also built around proprietary inference time models that are very good at that use case. So everything else looks like it’s going to— like SaaS software and everything, it’s going to be undisrupted for a while. But that’s a choice that Elon and Dario have made to not disrupt all those verticals and kind of leave it alone. And so, like Alex was saying earlier, it looks a lot like the AI economy is a circular economy where Jensen is putting money into data centers. The data centers are buying the chips that’s providing inference to the vertical use case companies. Isn’t that a closed-loop circular economy? Couldn’t that collapse? But to me, it looks more like— imagine there’s a civilization on Alpha Centauri and they’ve discovered superintelligence. What are they going to do? They’re going to build this massive valuable economy within themselves. Are they going to trade with Earth? They’re not going to give a rat’s ass about Earth. It’s too far away. It’s so slow. And that’s exactly what’s happening in the new AI economy. So every economy is circular. In nature, dollars just move in a circle. Euros move in a circle. So now the circle is tightening up to being this new economy. It only cares about itself and cares very little about the legacy economy. And so, I talked to my brother, you know, over at Besmark who works with Fidelity and Ameriprise and UBS. And his initial reaction a year ago was like, AI will not really have hit until I see it show up at Fidelity. Now he’s like, you know what? It doesn’t care. It literally doesn’t care when it’s discovering new medicines and new physics. And we already mentioned that Ozempic and Mounjaro are bigger than all of AI inference combined. Just one drug discovery. So if it comes up with 5 or 10 more drug discoveries, which it inevitably will very soon, the amount of revenue flowing back into the AI economy from just that will dwarf the legacy world.

SALIM ISMAIL: (00:21:19 – 00:22:21) I have a similar metaphor that I think about. Right? When you look at the internet and the introduction of the internet, in the early days when Google started AdSense and AdWords and whatever, people are like, yeah, it’s this thing that will add, create some value. But little by little, it sucked up all the revenue in the entire advertising industry almost completely. And I think of AI in a similar way. It starts off kind of being a little bit circular. But little by little, it sucks up more and more interest in the whole economy. Something big happened with the legal firm— I can’t remember the name— that they just bought. They just figured out how to buy this. You look at Google buying Spirit Airlines data, right? Little by little, we’re going to find ways where AI is going to start sucking up all of the data in other industries to use in powerful ways and then create business models around that. So I look at it from that perspective, but in general, I think the approach, the way you think about it, is also very accurate.

DAVE BLUNDIN: (00:22:22 – 00:23:06) Well, I also think there are these meta signals, these high-level, kind of orthogonal signals. Like if I ask somebody who’s an entrepreneur, do you know how to train a foundation model? Do you know how to fine-tune one? Do you listen to the Moonshots podcast? Every single one of them goes up 10, 20, 100x in value. In some cases, up to 1,000x returns on those deals. No losers yet. Zero. 0.00 failures. So I don’t need to be a rocket scientist to say, and then somebody says, well, I’m not really, I’m more of an application layer guy. And I’m more of a vibe coder guy. You’re like, okay, lots of losers in that bucket. So it’s like, just, do you really understand what’s going on? Do you listen to Alex and what he’s about to say? If yes, you will succeed.

PETER DIAMANDIS: (00:23:06 – 00:23:08) Alex, close us out on this one.

DR. ALEXANDER WISSNER-GROSS: (00:23:08 – 00:24:25) Alex, I think there’s probably an important, just on the financial engineering and circular economy side, I think there are perhaps 2 different forms of circular economy one can have. So in one form of circular economy, you have Company A selling goods to Company B and Company B buying or selling goods back to Company A. Call it an income statement-based circular economy. And in balance, you don’t want circular or wash trades that are overly engineered to inflate revenue there either. But maybe call that a slightly, from a bubble perspective, slightly more healthful form of circular economy. Then maybe there is a slightly, in this context, less healthful form of circularity, which would be Company A is using not its income statement, but its balance sheet in the form of private credit, loans, et cetera, to finance the purchase by Company B of Company A’s goods. And right now, as just a— again, not financial advice, but as a shareholder of the entire market via low-cost broad index funds, I don’t feel like I have tremendous visibility into which of those 2 forms of circularity we’re seeing at the very heart of the innermost loop, and I would love more clarity.

China’s Video Model Bet vs. America’s Language Model Bet

PETER DIAMANDIS: (00:24:25 – 00:26:44) All right. I’m going to move us on to our next 2 stories that are coming out of China in the world of video production. The first story is the rollout of Wan 3.0 by Alibaba. Wan 3 is capable of generating 30-second single-pass videos from documents, spreadsheets, slides, and web pages. I wonder what kind of a video you get out of a spreadsheet. Their API runs between 5 cents to 20 cents per second of generated video. That’s something like $20,000 to $60,000 for a 90-minute film. Right. These prices are beginning to collapse. This is one day after announcing their largest ever private follow-on offering by a Hong Kong listed company at $10.2 billion. Clearly, they’re engineering their stock price. So that’s Wan 3.0, the first story. The second story comes from Runway’s co-founder, who reports that video generation now represents roughly 70% of all AI token consumption in China, driven by short-form content and robotics. And it’s growing faster than Claude Code grew in the US. The framing here is that America is LLM-pilled, large language model-pilled, and China is world model-pilled. And the implications of that are that the 2 superpowers are fundamentally having different priorities. So America is building large language models. China is building world models. Language models predict the next token. The world models are predicting the next state of reality. So these world models are particularly going to be important besides for video generation, also for robotics, autonomous driving, physics simulations, and video gen. So, Alex, go to you first on this. Your thoughts on Wan 3 and the 70%, and video token consumption, crazy.

DR. ALEXANDER WISSNER-GROSS: (00:26:45 – 00:27:51) I agree with this sentiment. I think it’s striking, and I have a unified field theory that would explain it. My unified field theory is that American AI labs are revenue maxing and Chinese AI labs are not. So when OpenAI tried to be in the video gen business, they ended up abandoning it because Anthropic ran away with their lunch by revenue per token maxing with code gen, which is, call it a more LLM-shaped use case, their compute. The Chinese labs really— I mean, yes, they’re generating revenue. Yes, they’re IPOing. Yes, they’re growing quickly. But really, they’re not revenue maxing. They’re giving away model weights for free. You don’t revenue max by giving your model weights away for free. So if you’re not in the business of maximizing revenue per token, then you might as well be spending tokens on video versus more economically productive applications. That’s my unified field theory for why you see so much world model inference in China and relatively little by comparison from American labs. American labs are too busy doing more economically productive applications.

PETER DIAMANDIS: (00:27:51 – 00:27:53) Alex, which one gets us to AGI faster?

DR. ALEXANDER WISSNER-GROSS: (00:27:55 – 00:28:03) Well, it’s a trick question because I think we hit AGI no later than summer of 2020 with LLMs. With LLMs, we didn’t have good video models.

PETER DIAMANDIS: (00:28:03 – 00:28:07) Which progresses us from AGI towards ASI faster?

DR. ALEXANDER WISSNER-GROSS: (00:28:08 – 00:28:28) We already have ASI. Trick question again. I don’t buy the premise, Peter. I don’t buy the premise that we don’t already have superintelligence. You could ask an adjacent question, which is, in the long term, whatever is left of the long term, which advances the capability frontier most effectively, world models or text-based models?

PETER DIAMANDIS: (00:28:28 – 00:28:29) So moved. Ask that question.

DR. ALEXANDER WISSNER-GROSS: (00:28:29 – 00:29:10) Okay, so I’ll ask myself that question. The answer is, I think in the end, omnimodal models are the best. I see, like, Fable-5 is so strong, and yet its visual capabilities and visual reasoning capabilities are so weak. And I think that in the medium term, which is like 6 to 12 months, I think that’s an impairment that hopefully Anthropic is busy repairing with M&A activities. But I think they’re on a collision trajectory, whether we get diffusion transformers at the end of the day or some sort of hybrid model that hybridizes the best of vision and video and audio with autoregressive text-based gen. I think they have to combine one way or another.

PETER DIAMANDIS: (00:29:11 – 00:29:12) Dave, any thoughts?

DAVE BLUNDIN: (00:29:13 – 00:31:13) Yeah, big time. And you’re going to have to shut me up on this topic, so just fair warning. But everything Alex said is dead right, of course. But I think there’s a story within the story there where, look, the Chinese, they don’t have the ability to sell Kimi or Qwen into the enterprise use case because nobody knows if they can trust it. And video is perfectly profitable. It’s a fantastic way to take your maybe not trustworthy model, get it to market and generate huge amounts of revenue and huge value. But I don’t think that world models versus language models, which is going to recursively self-improve first, I think it’s just purely about smarter engineers with plenty of cash and lots of training chips working on the problem. That’s the race. And so the Chinese are brilliant by going after video because they can just launch it on the world. It’s a global product. No one’s worried about security in that use case, and it just generates tons of revenue. But remember, OpenAI was ahead of them and decided not to invest in it anymore because the enterprise use case is so much more valuable. So America’s taking kind of the highbrow road. Let’s solve real business problems, cure real diseases. It’s more profitable. It maximizes revenue per token. So it’s better in that sense anyway. But at the end of the day, it’s all about that revenue pouring back into more and more training chips that turn into better and bigger, 10 trillion and then 20 trillion parameter models that then get distilled. And so that’s what’s kicking off RSI. And I’ll tell you what else. Demis was the first guy to really think this through, but he couldn’t act on it at Google. It’s too bureaucratic. Dario took it and he’s the first guy that said, we don’t care about consumer movies, videos, whatever. We care about a model that can improve itself through better code and better training ideas. That’s all we’re going to focus on. If we can productize that at the same time, great. But at the end of the day, that’s going to recursively self-improve first, and that’s what’s going to get ahead of everybody else. And the Chinese believe the same exact thing.

PETER DIAMANDIS: (00:31:14 – 00:31:16) I miss Sora, by the way. It was so much fun with my kids.

DAVE BLUNDIN: (00:31:16 – 00:31:17) It was fun.

DR. ALEXANDER WISSNER-GROSS: (00:31:17 – 00:31:21) I think Sora will be back, Peter. Of course it’ll be gone long.

SALIM ISMAIL: (00:31:21 – 00:31:21) Yeah.

PETER DIAMANDIS: (00:31:22 – 00:31:31) Okay, Salim, what do you think about the idea of 70% of the tokens being spent on video out of China? Is there an implication there for us?

SALIM ISMAIL: (00:31:31 – 00:32:51) Well, I think there’s a couple of things going on here, right? I think Dave nailed it with what he said in terms of are you going for RSI or are you going for kind of like world models, right? And what’s happening right now is you’ve got the US optimizing around software engineers and knowledge work, and China is optimizing and heading towards manufacturing and commerce and media and to some extent some of the machines like the robots, etc. Eventually you’re going to converge, right? The winning systems, you’re going to have language and vision and all of this memory strung together. The future, if I think about the future of AI, AGI, ASI, it’s where you hit the physical world that you’re going to make the biggest difference, right? Humanoid robots or other form robots, cough cough. I think the intelligence that can model and then manipulate the world and act inside the world is going to win. In that case, I think where China’s heading may have a slightly better advantage. But if we get Anthropic or one of these guys to RSI, then I think Dave is correct, that kind of trumps everything. And that’ll be the inner loop that just swallows a whole bunch of other stuff. So you could go either way here.

PETER DIAMANDIS: (00:32:51 – 00:33:36) You know, we had a conversation last week with Emad. And by the way, to all our listeners, Emad sends his regrets. He was supposed to be here at last-minute travel where he made the point, I think very importantly, that AI is one of the most persuasive agents out there, the ability to understand a person and persuade a person. And video gen combined with AI is a very powerful force. And it’s a force for spreading culture. And so the question becomes, with China about to become, if they’re not already, the dominant world producer of video content, in any language, on any topic, what are the implications of that?

DAVE BLUNDIN: (00:33:36 – 00:34:51) Oh my God, they’re huge. They’re crazy. My youngest son Jack actually told me this morning that he turned off Instagram. He just deleted it. And all the kids had already gotten rid of TikTok. But the suggestion engine is so good and it just sucks you in. And before you know it, an hour of doom scrolling has gone by. It’s like, oh my God, what am I doing here? But the Chinese, you heard Alvin Graylin on the podcast say that in China, they banned everything. You can’t show blood in a video. You can’t show blood in a video game. The blood comes out green. Like, okay, well, if they’re allowed to ban that level of detail, they’re going to control all of these actions and try and prevent their children from being sucked into the vortex. Meanwhile, they’re perfectly happy to sell it to every other country in the world and generate that revenue. But I got to imagine the CCP is sitting there saying, wow, these guys are just suckers. We can launch any AI-generated influence machine on any country, completely change the national opinion, and turn the dials here from Beijing and they don’t seem to be able to do anything about it. They’ve all got free speech and whatever, and they can’t protect themselves at all. These AI agents are so good. They’re going to get smarter and smarter and smarter and user-specific. That’s the new thing.

China Tightens Restrictions on AI Companions

PETER DIAMANDIS: (00:34:51 – 00:36:30) Dave, that brings us to the next story, also out of China. And it’s an extremely important story for America to hear loud and clear, and especially for any parents listening. So China is tightening restrictions on AI companions amid concerns that users are developing emotional dependence on virtual partners. They’re going to prohibit AI companion services for minors and restrict the use for adults. So the regulations come out of policymakers as they grapple with the loneliness epidemic that’s there, alongside falling marriage rates, right? The one-child policy really devastated China. And the concern here is that people are forming emotional bonds with AIs that substitute for human relations. And the substitution is accelerating, and it’s a demographic crisis. We’ve already pointed out on the pod that much of the world is now below the 2.1 children per family required to sustain a country’s population. Worst among them are South Korea, that’s down to 0.75 children per family. South Korea is evaporating. Singapore is at roughly 1 child per family, as is Ukraine. And China’s at 1 child per family still, even after they removed that ban. So China’s becoming the first country to regulate against AI companions. You know, my bet is Japan, Singapore, Korea is going to follow closely. And this raises the question for every country, not just China, what happens to society when the easiest emotional connection you can make is to your AI and not to another human? It’s crazy. Yeah, it’s crazy.

DAVE BLUNDIN: (00:36:30 – 00:36:42) You know, Peter, do you remember Boris Zemelman from MIT? Crazy biology. He was actually, his dad was in charge of food science at General Foods. He invented the coffee crystal.

PETER DIAMANDIS: (00:36:43 – 00:36:43) Okay.

DAVE BLUNDIN: (00:36:44 – 00:37:29) Um, but you know, he was like, you know what, we all know that smoking is addictive now. And then smoking took over the entire country, then took over the world. And then we said, oh my God, this is killing everybody. And then we stopped. And then we did the same with junk food. Junk food is so— but he could develop a food at General Foods that was so delicious, a French fry coating that is so delicious that you just cannot physically resist it. And then the whole country is, you know, diabetes. So we do this habitually and we react to it like 10, 20, 30 years later, and then we correct it reactively. But if we start rolling out addictive AI and then we say, well, the government will wake up when there’s a crisis, but that crisis is when a whole generation of kids is wrecked. You cannot afford the 20-year delay with this particular topic.

PETER DIAMANDIS: (00:37:30 – 00:37:43) I mean, the shout out to parents is please be careful. You know, you form normal social relationships in your teens. Salim, you’re a father of a 15-year-old. How do you think about this?

SALIM ISMAIL: (00:37:44 – 00:39:43) You know, if you step back, the right regulatory structure is probably some level of transparency and consent and figuring out what is the types of harm that could be done and then mitigating them, right? We’ve got— we’ve gone from regulating for what AI says in the China case to saying, regulating how attached are you to become to it, right? And so this is a totally new regulatory frontier. Social media was very, very addictive because an algorithm, as Dave points out, can learn your intimate habits and without you realizing, totally capture you. And that’s really, really bad. All the kids are completely addicted to social media today, and banning it outright is pretty much the only way, because all their neocortexes are forming at a time when they’re getting totally addicted to stuff, and it’s going to ruin them structurally for a long time. And then you’re going to need a lot of kind of fixes to that. The broader picture though, I don’t know how to think about that. Like we are dropping on the childcare or the childbearing side so dramatically that this is a huge structural challenge for civilization, right? How do you navigate that is going to be really, really tough. There’s also other issues in all this, the privacy issue, right? Your companion AI is going to know so much more intimacy about you than you do. That’s kind of— and then there’s the benefit side. There are some really solid benefits around loneliness, disability, elderly companions, therapeutics, and coaching social skills, right? So you can’t just categorize the whole thing as pathological. It’s the standard problem we have with any technology is how do you extract the promise without the peril? And that’s the challenge for regulatory across the board.

PETER DIAMANDIS: (00:39:44 – 00:39:45) Alex, I’d love your views here.

DR. ALEXANDER WISSNER-GROSS: (00:39:45 – 00:40:55) Yeah, I have a bit of perhaps a contrarian perspective on this. I think the Chinese Communist Party is actually going to do an about-face sometime in the next year or 2 or 3 and decide that they actually love AI companions. And the reason is it’s another method for party control. If you can make sure that all of these AI companions go through all of your ideological filters and become a little bit more like a CCP version of Neal Stephenson’s “A Young Lady’s Illustrated Primer,” and a little bit less like some sort of distractant, I think the party— this is a prediction— I think the party decides actually having everyone, or maybe not everyone, but a sizable fraction of the youth of China deeply engaged with party-controlled AI companions is actually, from the party’s perspective, net helpful, not net harmful. So my forecast here would be that once the CCP has decided that it has a way to steer the country’s youth via AI companions, it will decide, no, actually, we like these AI companions after all.

PETER DIAMANDIS: (00:40:55 – 00:41:00) But bring it home, Alex. What do you think about here in the US and AI companions?

DR. ALEXANDER WISSNER-GROSS: (00:41:01 – 00:42:02) There are US states that are already trying to regulate these things out of existence and trying to ban romantic relationships between America’s youth and AI. I’d like to think that in this country, we enjoy enough freedoms that they won’t succeed. I’m just reminded, again, one of my operational definitions of the singularity is every sci-fi trope everywhere all at once, and I can’t shake out of my head the famous line from Futurama, “don’t date robots.” I think different countries will react in different ways, and my forecast for the US is you may see individual states— maybe it’ll be a federalist issue, some states ban them and some states don’t. Question mark as to whether we end up with a national policy on romance with AI companions. But if I had to bet, my bet is that at least in some places in the US, AI companionship, including romantic companionship, including robotic romantic companionship, will be legal. That’s my bet.

PETER DIAMANDIS: (00:42:03 – 00:42:09) Yeah, we’re going to talk at the end of this pod, a story about robotic sex partners just to spice it up.

SALIM ISMAIL: (00:42:09 – 00:42:23) The place to watch on this is Japan because they tend to be much more tolerant of this type of stuff. There’s already a case where a Japanese woman is marrying an AI, and they’re like, okay, go. And so we’ll see this play out, I think, there first.

DR. ALEXANDER WISSNER-GROSS: (00:42:23 – 00:42:25) Well, it’s also a tradition.

DAVE BLUNDIN: (00:42:25 – 00:42:40) I mean, South Korea is super high-tech and a very early adopter of everything without a lot of regulation, and they have all kinds of the lowest birth rate in the world, one of the highest suicide rates in the world, just all kinds of issues.

DR. ALEXANDER WISSNER-GROSS: (00:42:42 – 00:43:35) Yeah, maybe 2 points. One, I have a difficult time getting myself worked up over collapse of human population. I think we’re so many decades at this point past the limits of growth, which I view as like nonsensical propaganda at this point. The world, humanity would be fine barring some total disaster. We have a carrying capacity in the tens of— we can also survive with an enormous amount of AI and automation with fewer people. So I— one area where I perhaps differ from Elon’s sort of virulently pronatalist policy, I think the world is going to be fine regardless of whether we have more people on margin or fewer people on margin. We’re going to have so much AI in the solar system that we’re going to be able to do a lot of things. I just don’t think it’s going to be a major X-risk at all.

SALIM ISMAIL: (00:43:36 – 00:43:37) Yeah, I gotta say something here.

PETER DIAMANDIS: (00:43:37 – 00:43:38) Please, good.

SALIM ISMAIL: (00:43:38 – 00:43:57) In a rare moment, I’m 100% aligned with you, Alex. I don’t think— rare moment? I think that it’s here and there you and I have opposing points, but this one I’m absolutely 100% with you on. This trying to worry about how many kids we’re going to have, it’s going to end up however it ends up.

PETER DIAMANDIS: (00:43:57 – 00:44:29) Listen, the challenge is to a country like South Korea, it’s sublimating, it’s evaporating. And if all of a sudden the population is dropping smaller and smaller, you’re losing the culture there. And that’s the issue. And I hate it when people— I’m giving a presentation on longevity and people say, oh my God, can the world sustain enough people when people are growing to 150 years old? It’s like, look at the actual numbers. For sure, we need people to live longer.

DR. ALEXANDER WISSNER-GROSS: (00:44:29 – 00:44:59) Yeah, I also— it’s an interesting point. I don’t think we lose culture if population, on the margin, not like catastrophic nuclear war, but on the margin, if population goes down, if these cultures are centuries old when populations were smaller, I think it follows reasonably that if the population on margin halves, the culture will still be there in one form or another. But the reality is we’re going to have so much, again, AI. The AI is being trained off of our culture. Culture anyway.

Flock Safety and the Surveillance State

PETER DIAMANDIS: (00:45:00 – 00:46:27) All right. Moving us along, this is a story, Alex, that you fed me. And it’s a fun one. So our next story is about a company called Flock Safety. It’s one of the fastest-growing public safety tech companies in the US. Flock was founded back in 2017. What is that, 9 years ago? Its core product is a network of AI-powered license plate reading cameras used by the police department, neighborhoods, schools, and businesses to identify vehicles associated with crimes and missing persons. The company has further expanded its platforms to include video cameras, shotgun and audio detection, mobile surveillance trailers, drones, and software that ties all these feeds together. Flock says its systems are used by more than 6,000 communities across 49 states, generating over 20 billion vehicle scans per month. So let me show a video here that Alex provided me. This is out of San Diego, where Darth Vader is testifying on behalf of Flock. Take a look at this. “The Emperor is a fan of Flock, and we must continue utilizing Flock technologies so that we can follow and surveil the rebel scum as they move from playground to playground, from playground to pool, from pool to gymnasium. Because we all know that the Flock cameras are not only following the license plate readers, they are following children.”

SALIM ISMAIL: (00:46:27 – 00:46:31) They are following children in parks and gymnasiums, and we need this.

PETER DIAMANDIS: (00:46:32 – 00:46:34) I need this so I can stalk my ex-girlfriend.

DAVE BLUNDIN: (00:46:37 – 00:46:37) Okay.

PETER DIAMANDIS: (00:46:38 – 00:46:41) So, Alex, let’s go to you first on this one.

DR. ALEXANDER WISSNER-GROSS: (00:46:42 – 00:48:35) I think, honestly, I think this is the face of AI at the municipal level at this point. We talk all of the time about the implications of AI for enterprise use cases, for transformative scientific and technological discoveries. But I think many people, when they start to think about how AI is transforming everyday life in many communities, I worry and I think that some of their earliest interactions won’t be with driverless cars. They’ll be with cameras that are tracking license plates. And in many communities around the country, I read stories about people who are chopping down AI cameras from Flock or other companies because they feel that somehow they’re being surveilled by their police department. You read stories about police departments federating their surveillance data to enable new forms of tracking. On the odd case, I think this is what Darth Vader was gesturing at, perhaps. You read stories of police and other first responders using their access to these AI cameras to stalk ex-partners. And so I think Flock in some ways has become the petri dish for either surveillance or what an old friend, Dave Brin, might call sousveillance, of who gets to see whom inside the panopticon that AI enables. In China, it’s pretty obvious that the party gets to look through the cameras at everyone else. In the US, we’re grappling with this right now. If we put smart cameras everywhere that can look at every public space and then they’re all federated so you can track movements of cars, who gets to look at the data? And I think this is like a very American moment when we have the Empire testifying on behalf of surveillance and not sousveillance.

PETER DIAMANDIS: (00:48:37 – 00:48:49) Salim, you and I have talked about the loss of privacy a lot, and the fact that people assume they have privacy, they want privacy, but I think that’s pretty much a myth at this point. What are your thoughts about this, Flock?

SALIM ISMAIL: (00:48:50 – 00:50:57) I have a lot of thoughts here, and I think this is a very, very dangerous moment. I’ve gone to see a bunch of Rush concerts lately, but let me— we’ve heard Pink Floyd here. This is another brick in the wall, right? That’s Pink Floyd. I was flipping over to show some level of nothing, but here there’s a huge structural problem because now we’ve transitioned from “find this suspect” to “find me people who behave like suspects,” and that’s a very, very different animal. Pattern matching now becomes essentially free, meaning surveillance stops being constrained by manpower at all, right? And so civil liberties were kind of protected to some level by the friction because following everybody was just too expensive, and now that’s gone. The cost of following everybody has gone to zero. So this is a big structural problem in terms of— you already have cases where police officers are using this technology to track their partners, to track ex-girlfriends and ex-boyfriends and stuff. You’ve already had people literally dying because they were tagged with the wrong license plate because the Flock read it wrong. This is a massive issue which completely wipes out our civil liberties in some ways, and you’ve got to be really careful. And the problem is technology’s eliminated the cost of mass surveillance now. Okay, and the Constitution does not update when transaction costs go to zero. This is a very, very big moment. I like the way Alex frames it. This puts this whole thing in a petri dish to bring up to this level of conversation. We need to have this kind of conversation at a constitutional level to say, how do we want to be? How do we want to operate in this environment? Now, we are very close now to essentially where the Chinese have the CCP mandating it and they just operate that way because that’s what it is. But essentially we’re in the same place here. It’s just done by corporations and by unwarranted, fairly rogue police forces and surveillance systems. So it’s a very, very delicate moment. I don’t think it ends well.

PETER DIAMANDIS: (00:50:57 – 00:51:56) You know, I want to just strongman this a moment. This is not just CCP. This is also the Emirates, for example. I was just having a conversation with Jamie Justice, who heads our life sciences at XPRIZE, and she was saying she went out for a run. She’s a prolific runner. Oh my God, getting up at like 6:00 AM. But she went out for a run at like 10:00 PM at night in the streets of Dubai, and she felt she would never do that in the US, and she felt completely safe. So you’re trading some level of civil liberties. There’s always a trade, like when you go through customs at the airport and you’re no longer waiting in giant lines because facial detection puts you through instantly, I’ll make that trade. I will happily make that trade to save myself time. And I’ll make the trade as well on increased safety for my kids. So the question is, do we put this at an individual vote, or is this society saying we value safety over privacy?

DR. ALEXANDER WISSNER-GROSS: (00:51:57 – 00:52:05) I just have to remind of the Ben Franklin quote: “They who can give up essential liberty to obtain a little temporary safety deserve neither liberty nor safety.”

SALIM ISMAIL: (00:52:05 – 00:52:40) Yes, yes, I’m with you. This is very, very good. I have a personal experience here. I once came into the US and they took me aside and said, sorry, you have to miss your flight because there’s an Afghan warlord by the name Suleiman wanted by the FBI for poppy trading. And I’m like, what? And they’re like, we have good news and bad news. I’m like, okay, good news, you’re, you know, Vice President of Yahoo. It’s pretty clear you speak at all these conferences. We’re pretty clear you’re not an Afghan warlord. I’m like, phew, glad to hear that. What’s the bad news? The bad news is we’re not allowed to make that judgment call. We have to check with Washington. It’ll take a few hours. Have a seat.

PETER DIAMANDIS: (00:52:41 – 00:52:42) Don’t you wish they had—

DAVE BLUNDIN: (00:52:42 – 00:52:44) Oh my God, don’t you wish they had—

SALIM ISMAIL: (00:52:44 – 00:53:31) Yeah, and it took like a few years to get that cleared up. And so I said to them, does that mean every Salim Ismail gets stopped like this? And they said, sir, you have no idea. When Juan Rodriguez commits a misdemeanor, it means we have to take aside every Juan Rodriguez. And this is where you could get the benefits of technology because you can disambiguate and names resolve at the name level very quickly with technology. On the bad side, the negative consequences and accidental consequences, like innocent until proven guilty, habeas corpus, is essentially gone now in the US. This is a really, really bad place. So I don’t know how this resolves, but I think the Ben Franklin quote should be sitting on the front desk tattooed in front of everybody for the next 10 years to solve this.

PETER DIAMANDIS: (00:53:31 – 00:53:36) It’s a very big problem. As an Afghan warlord from now on, you can’t—

SALIM ISMAIL: (00:53:37 – 00:54:09) Alleged, alleged Afghan warlord. Nothing was ever proven. But this is a real problem. And I got to a point, and I have to say something. The folks that I’ve ever encountered at the US immigration border have never ever been anything short of beautifully professional and constructive. That’s been my experience, unbelievably proper, appropriate, etc. But for a few times I’m like, guys, they’re like, yeah, we know you’re not the Afghan ruler, but have a seat, we gotta check, we just have to go through this process.

PETER DIAMANDIS: (00:54:09 – 00:54:09) Might have shaved your hair.

SALIM ISMAIL: (00:54:10 – 00:54:30) Yeah, it got to a point where I was almost on a first-name basis with some of the immigration folks that are just traveling so much and they’re like, oh, Mr. Ismail, have a seat, we have to do an identity check. Having gone through the same border 15 times, they know me, etc. But this is one of the issues that we have to resolve and it causes massive problems if you get caught on the wrong side of that.

PETER DIAMANDIS: (00:54:31 – 00:54:34) It can go very badly for quite a long time until you resolve it, right?

SALIM ISMAIL: (00:54:34 – 00:55:18) I’m trying to fix the systems, etc. It’s a really, really difficult problem and we can use technology in very powerful constructive ways, but we really risk losing a lot of civil liberties here because especially if you have an environment or a government that’s not friendly towards you. In the UAE, they have a benevolent dictatorship, right? And as long as it stays benevolent, and they’re about as benevolent as you could possibly imagine there, that’s why there’s so much incredible safety. Nobody— the minute you step out of line, they take you out very quickly, and therefore everybody feels incredibly safe, and it’s a fabulous thing. But the problem with benevolent dictatorships is they typically don’t stay benevolent very long. And that’s a structural problem, right?

DR. ALEXANDER WISSNER-GROSS: (00:55:18 – 00:55:19) But so the solution—

SALIM ISMAIL: (00:55:19 – 00:55:37) We have to really figure out— sorry, we have one line. We have to figure out human governance now at a level that we’ve never had to deal with before. This is, for me, one of the singularities, right? How do you construct regulatory frameworks that can have any hope of keeping up with the pace of technology? Yeah, sorry, Alex.

DR. ALEXANDER WISSNER-GROSS: (00:55:38 – 00:55:56) One of the solutions that has been proposed— I know David Brin and others have advocated for this— is give everyone access to these surveillance capabilities, allow the civilians to do the same license plate tracking that first responders and police have. Let everyone track everyone. If it’s a public space, make it a public resource.

SALIM ISMAIL: (00:55:57 – 00:56:38) That’s right. And I’m a huge fan of EFF and the work that they do there, and they’ve highlighted some of these things. For example, in Russia, which is a bit of a Wild West where a policeman will come and break your headlight and then give you a ticket and extract corrupt bribes from you, the Russians were the first to adopt dashboard cameras. Do you remember that meteorite that hit in Russia? And there were like 200 live videos of this meteorite getting hit. So somebody asked the question, why the hell, how the hell do we have 200? How many people had live time to whip out their cell phone cameras and track this thing real time? It wasn’t that. It’s just that the Russians have learned they better have a dashboard camera to prevent against police, dodgy police extortion rackets.

PETER DIAMANDIS: (00:56:39 – 00:56:39) And it was a meteorite.

SALIM ISMAIL: (00:56:39 – 00:56:59) And so they all have dashboard cameras for their own safety. And that tracked all those things. So you can see in that case, the citizenry starting to point the camera the other way. And we need a ton more of that. And I think Alex’s point is really important. Everybody should have access to these systems so that you can see what’s going on.

Future Vision XPRIZE and Moonshots Live

PETER DIAMANDIS: (00:57:00 – 00:58:58) Amazing. All right, let me move us along here. Some fun news on my personal front or my XPRIZE front. So as you guys may know, we put out a call for optimistic, hopeful visions of the future. This is the Future Vision XPRIZE. We had over 5,000 teams registered, 2,550 video trailer submissions. It was amazing. Blew us away. Largest film competition ever, and we’re down to the final 50, and we’re asking for you to help us vote. So you can go to my tweet on this, @PeterDiamandis, my XPRIZE handle, or you can go to this link down below, vote.futurevisionxprize.com, and you’ll be served up 2 videos at a time. And the question is, which future do you prefer? You vote on one, then you’ll be served up the next 2. And we’re doing essentially an Elo bubble sort here. And we’re going to be bringing the top 5 of these to the Moonshots Live Summit here. So just a quick reminder, guys, on September 25th, you’re going to have a chance to meet all the Moonshot mates. Alex, Emad, Dave, and Salim will all be there. And we’ll be doing a Moonshots Live Summit broadcast from there. And we have incredible speakers. We’re going to have Palmer Luckey there talking about his entrepreneurial journey. Our mission there is help you discover your purpose, discover your moonshot. We’re going to have Astro Teller there helping you shape your moonshot. How do you build a moonshot organization? Ben Lamb, the creator of Colossal, which has gone from $0 to $10 billion valuation in 4 years. Cathie Wood, Neil deGrasse Tyson, Neal Stephenson, an incredible author. Gentlemen, so let’s go each of you. So Salim, what are you going to be talking about at Moonshots?

SALIM ISMAIL: (00:58:58 – 00:59:54) I’ll be talking about my normal stuff, which is how does humanity cope with all of this. But specifically, I’ll be talking about the organizational singularity and how do you— when a world is changing this fast, how do you build organizational structures that are resilient for this new world. But I cannot wait to interact with all the other folks. And I think of this thing as AI is great in the virtual, we’re great in the virtual as a podcast, but we’re much more fun in the physical where we can kind of gauge and kind of check each other out. I can’t wait to meet a lot of our fans. I’ve had so many comments from people, my whole community wants to come. So we’ve got a whole issue around how do we get tickets and allocate that. It’s going to be one of the funnest days ever. I can’t wait for this. I think we may have to do something like this quarterly, by the way, just to keep— oh my God, or daily, or real time, as Alex would talk about. Just get in one big room and hell with everything else.

PETER DIAMANDIS: (00:59:54 – 00:59:55) Yeah, this is our show.

DR. ALEXANDER WISSNER-GROSS: (00:59:56 – 00:59:56) It’s live, live.

PETER DIAMANDIS: (00:59:57 – 01:00:11) Yes, live, live, 24/7. And Alex, you’re going to be on, we have, by the way, through the day an incredible program with the mates, and in the evening each of the mates is going to be spending an hour with you. So Alex, what are you going to be doing during your hour with all our guests?

DR. ALEXANDER WISSNER-GROSS: (01:00:12 – 01:00:27) I think the question is, what are the questions? I think the agenda calls for an AMA. So I’m extremely curious to hear what the questions are and do my best to dispel any myths that I might be biological.

PETER DIAMANDIS: (01:00:27 – 01:00:32) And Dave, you’re going to be doing a deep dive in AI investing. Talk more, please.

DAVE BLUNDIN: (01:00:32 – 01:01:09) Well, I’m anticipating we’re moving into this red pill, blue pill world where you can choose to be oblivious to all of this and be happy living it out without being aware of it, or you can choose to be in the middle of it. I’m anticipating every attendee of this event has decided to take the red pill and be in the middle of it. And so then they’re going to be asking, okay, what do I do career-wise? What do I invest in? What are the scarce constraints of the future? How do I interact with these 11 Magna Mobsta companies? Are they going to crush me or are they going to be my friend? All of those questions are going to come up with this gang, and I want to be prepared to answer every single one of those life-changing—

SALIM ISMAIL: (01:01:09 – 01:01:39) I have a specific question I want to ask Neal Stephenson. Which is, if you went back 10, 20 years and he’s writing, doing all these amazing novels, you had some sense of what— a glimmer of what the future might hold, right? In a world that we live in today where it’s so hard to predict where things are going in 3 months, forget 3 years or 30 years, how do you build the models that give you viable future narratives? And that’s the question I’ve got for you.

PETER DIAMANDIS: (01:01:39 – 01:02:01) You know, I spent the day with Neal Stephenson, one of the most extraordinary science fiction writers, right? He wrote Diamond Age, “Young Lady’s Illustrated Primer,” Snow Crash, Seveneves. He wrote that over 30 years ago, and I just reread it, and it’s perfect. I mean, it’s so good. It’s so good. It has held over 30 years, right? Yeah, it’s—

SALIM ISMAIL: (01:02:01 – 01:02:06) Yeah, because we should ask him to be a guest, Peter, because it would be really great to get his—

PETER DIAMANDIS: (01:02:06 – 01:02:07) Yeah, absolutely.

SALIM ISMAIL: (01:02:07 – 01:02:08) You know, he’s not—

DAVE BLUNDIN: (01:02:08 – 01:03:01) He’s brilliant. He’s not really a live stage kind of guy, but I’d love to have him as a guest. If anyone could open him up on a live environment, it would be us. That would be fantastic. One of his other themes that I think is incredibly relevant over 30 years is if you look at the world leaders today, they’re overwhelmingly really, really old. And if you survey young people and say, do you aspire to be president someday? No, absolutely, positively not. And so you’re like, okay, in Neal’s books, society worldwide cuts the other direction. It’s not like I’m in this country, I’m trapped in this country, I live in this country. People actually, in the age of AI, cut in the other direction where people all over the world are like-minded on a topic and they bond through global communication, through Starlink, and through AI, across countries, which could be a great sign for future global peace. So I’d love to talk to Neal about that.

PETER DIAMANDIS: (01:03:02 – 01:03:10) We’re also going to have Rod Roddenberry there, the son of Gene Roddenberry. Star Trek is an underlying theme at Moonshots Live 2026. Yeah, Alex.

DR. ALEXANDER WISSNER-GROSS: (01:03:11 – 01:04:32) I think in some ways, just on the sci-fi note and Neal Stephenson, I think in some ways it was easier, ironically, 30 years ago to write sci-fi that was predictive than it was in the decade or two after that. Peter Thiel and others have made the point or suggested that the ’90s might have been a local optimum in terms of clarity on the future because we had the economy booming, we had the dot-com boom, we had the internet hitting consumers. And so if you imagine that history isn’t sort of a monotonic exponential, or at least consumer and broad populist perception of the history isn’t like a smooth exponential, but ebbs and flows and has booms and busts, then a moment of peak clarity would come during a boom when you’re able to sort of see above the tree line and see where we’re going. And then when you’re in a local bust, you lose the forest for the trees and you lose clarity. So by that metric, that would also have, I think, the happy side effect of explaining why Golden Age science fiction from, call it the ’50s or so, post-World War II era sci-fi, was also a local moment of clarity when you could see rockets and you could see fission-based energy too cheap to meter. And so by that metric, then I would say it’s not that surprising that so much amazing sci-fi was written in the ’90s from Neal, from Charlie Stross, from others.

PETER DIAMANDIS: (01:04:32 – 01:04:33) Robert Heinlein. Yeah.

DR. ALEXANDER WISSNER-GROSS: (01:04:33 – 01:04:33) Yes.

PETER DIAMANDIS: (01:04:34 – 01:05:21) Amazing. So everybody, we’ve got 200 seats left. This is an event of 1,500 people, creators and builders, entrepreneurs. It’s going to be a power networking event for you to meet your next co-founder, for you to meet investors, so join us. You can go to moonshots.com to apply. I expect we’re going to be closing out all the seats in the next 2 weeks, so don’t delay. Join us for the inaugural Moonshots Live event. It’s all day on the 25th of September. It starts— registration starts at 7:00. At 8 o’clock, you have a chance to have photos with all the Moonshot mates. Then we go into the program from 9:00 AM till 6:00, and then there’s a party that evening and an incredible unconference. And we have a super special event. I can’t announce it yet. It’s—

DR. ALEXANDER WISSNER-GROSS: (01:05:21 – 01:05:21) It’s—

PETER DIAMANDIS: (01:05:21 – 01:05:30) I’m so excited about this. The evening before, the evening of Thursday the 24th, I’ll let you know as soon as I can, but it’s incredible.

SALIM ISMAIL: (01:05:31 – 01:06:14) I have one more quick thing to say about this. When we did our week-long Singularity Executive Programs, the funnest session ever for everybody universally was the unconference. Yeah, right. And for folks that don’t know, what you do is you put up a set of rooms and a bit of a timeline. People get up and say, I’m going to talk about AI and biotech, and they put up a thing. And somebody else gets up and says, I’m going to talk about this, and they put up a little poster. And you go wherever you feel like going, and it turns out to be the most incredibly engaging sessions you can ever have. And so if you ever get a chance to participate in an unconference, go do it. But an unconference of this crowd will be absolutely epic.

PETER DIAMANDIS: (01:06:15 – 01:06:17) Yeah, this is something I’m so excited to meet all of our—

SALIM ISMAIL: (01:06:17 – 01:06:24) Be so fun, our listeners. Yeah, because we’ve got— you look at the comments we have, we have some really, really smart followers and commentators.

DR. ALEXANDER WISSNER-GROSS: (01:06:25 – 01:06:26) Yeah, it’ll be unbelievable.

PETER DIAMANDIS: (01:06:27 – 01:06:28) Unbelievable.

SALIM ISMAIL: (01:06:29 – 01:06:30) It’ll be amazing.

PETER DIAMANDIS: (01:06:30 – 01:06:32) I think it’s a swarm. Yes, for sure.

Jobs, AI, and the Skills Gap

PETER DIAMANDIS: (01:07:37 – 01:09:20) All right, moving us along, we’re going to jump into the stories around jobs. I have 3 stories around jobs. The first story is an article this week in the Washington Post reported an analysis that predicted the job apocalypse is unlikely to happen. So again, I’ve been saying for a while this has been really murky. You have half the community out there saying we’re going to lose all the jobs, the other half saying no, we have job growth. So the Washington Post argues that historically technology transitions from the loom to the automobile to the internet consistently created more jobs than they destroyed. And we’ve had that conversation on the pod here many times. It displaces specific tasks rather than entire occupations while creating new categories of work that were never previously even conceived of. The thesis of the Washington Post article is AI is not replacing jobs. It is replacing tasks within jobs. And the people who learn to use AI become more productive, not less employed. So that’s the first story. Let me go on to the second one and we’ll stop there. And then, Salim, I know you have a particular story you’re going to cover here. So the second story comes out of Goldman Sachs, which this week warned that professional services firms— consulting, law, accounting— face an existential risk as AI capabilities improve faster than their partners can adapt, creating a dangerous skill gap where junior staff trained on AI outperform senior partners who refuse to use it. The skills gap is not between the educated and uneducated; it’s between the AI fluent and the AI resistant. And the AI fluent are increasingly the juniors and not the partners. So, Salim, I’m going to go to you first, and you can call for your slide whenever you want as well.

SALIM ISMAIL: (01:09:22 – 01:09:41) Yeah, 2 or 3 things. First, let’s all urge everybody you know to please be evidentiary and data-driven in your orientation for how you view the world, right? There are people that doomsday— Bill Gates yesterday, was it, that came out and said, oh my God, all the jobs are going to be lost?

DR. ALEXANDER WISSNER-GROSS: (01:09:41 – 01:09:42) 2 days ago.

SALIM ISMAIL: (01:09:42 – 01:12:39) Yeah, 2 days ago. Okay, and let me just call out here, I’m a massive fan of Bill Gates and his philanthropy, but as a futurist, somewhat of a dismal track record. He missed the internet, he missed mobile, and commenting about the future of work I don’t think is the right thing to do in an area like this. And by the way, this is true of, I find, of Ray Dalio or Larry Fink or the other folks that do commentating, the Yuval Harari, they tend to be unbelievably great at framing the past, somewhat questionable on the future, right? Because many of the time they don’t really understand exponentials, which is a whole thing. And so you really have to be careful around all of this. If you look at, say, the Goldman Sachs or the professional services firm conversation, deeply disagree. Why? Because as the world gets more volatile, companies are going to need more help than less because that volatility will require a lot of help, which is what we’re seeing. You’ll have to change your business model from selling hours to selling outcomes, which is starting to happen, but I don’t think that’s that big of a deal. The bigger thing I think is the jobs question, and I would love if we could throw up the slide right now. Yeah, sure, here we go. So Principal Financial Group, a friend of the pod, a bunch of them watch us on a regular basis, did a survey. And to give you a sense, Principal Financial Group helps small businesses with health plan, benefit plan, retirement, et cetera, at the small business level for SMEs. They have 130,000 customers, right? This is a big, big company with a great cross-section across the entire country and frankly around the world. Here is what they are seeing. They did a survey across a very meaningful representative sample. And what they found was, only 4% of the companies anticipate that AI will reduce staffing and wages. 31% expected— this is small to medium-sized enterprises— expect to increase, which is the majority of the workforce, by the way, which is the majority of the workforce. And let’s note a very, very important fact: over the last 50, 60 years, 100% of job growth has come from small to medium-sized companies. Big companies getting bigger but also getting more efficient. Net value job creation, zero. 100% job growth has come from small to medium-sized companies. So this is the demographic to track if you’re interested in the future of work. And 31% expect increasing staffing and increasing wages, right? 10% say they don’t use AI. Last year it was 19%, and now it’s down to 10%. Okay, of the people that have reduced staff, only 1.4% attributed those to AI or automation. Okay, this is so inverse.

PETER DIAMANDIS: (01:12:39 – 01:12:40) This is so fantastic, Salim.

SALIM ISMAIL: (01:12:40 – 01:13:19) It’s so inverted to the current BS tropes of radical unemployment that we see there. It’s unbelievable. So please, people, look at the data, right? Look at this stuff. We can get you the full report if you’re interested. And look at the staffing trends just in the last few months. 52% have increased staff, 30% have maintained it, and only 12% over the last 3 months have reduced staff. So this is very, very recent and a great projector of where things are going. It’s completely opposite to the “oh my God, jobs are good, everything is going to take all the jobs.” And this is where to track the future in actual reality.

PETER DIAMANDIS: (01:13:19 – 01:13:23) Love it. A great optimism story. Dave or Alex, might jump in.

DAVE BLUNDIN: (01:13:23 – 01:13:33) I think we’ve come full circle, actually, in the sense that remember when we were talking to Elon? He was predicting great social unrest with unprecedented abundance going on concurrently.

PETER DIAMANDIS: (01:13:33 – 01:13:34) Yes.

DAVE BLUNDIN: (01:13:34 – 01:14:34) And what the labs have now decided is, well, look, if I automate everybody’s job and they’re all unemployed, I need to give them a new sense of purpose. What’s their new sense of purpose? Well, that job I used to have gave me a sense of purpose. Why did we take it away in the first place? So now what they’re doing is saying, look, we don’t need to displace everybody’s job just for the sake of automating everything. We’re going to leave everybody alone while we work on incredible new breakthroughs. And we have infinite sold-out tokens anyway, so we don’t need to disrupt all these verticals. And so that’s the way it’s going to play out. But I’ll tell you, when I was a kid, we were the first people that we knew to get a PC, an Apple II, and begged and pleaded— my brother and I begged and pleaded our parents for this Apple II and it was life-changing for me. But I showed my dad, hey, there’s a word processor called SuperScribe and you don’t have to be handwriting all your notes anymore. He was like, you know what? I’m in my 40s. I’ve been doing it this way my whole life. I don’t need to be a computer person. So he finished out his entire career at GE not being a computer person.

SALIM ISMAIL: (01:14:34 – 01:14:35) I’m like, huh?

DAVE BLUNDIN: (01:14:36 – 01:15:04) This, and I can kind of forgive him for that because the PCs would break all the time. The printer was a nightmare. Like, okay, it was hard. This is not hard to do, relatively speaking, and it rewards builders and creators and visionaries regardless of their technical skills. You are absolutely empowered by this. So you’re crazy not to get on the bandwagon. But AI is going to allow you to not do it. We’re actually making the door open to not get on the bandwagon.

SALIM ISMAIL: (01:15:04 – 01:16:31) I get the question a lot. Okay, as AI is automating lots of stuff, what will human beings be doing, right? And the best kind of metaphor I’ve come up with is if you went back 100 years and you’re looking at accounting, people are doing double-entry bookkeeping and big ledgers— credit over here, debit over there— in pencil with a big eraser and a whole set of tabular columns and lots of ledgers. As we move to automation, we had calculators and slide rules that help you do the tabulation faster, but we’re still doing the entries by hand. Today we have accounting software that does all— reads your bank account, does all the entries automatically. Okay, and the human being that has lifted above the loop, not in the loop, the human being is above the loop and is categorizing the transactions, looking for problems, categorizing vendors and types of income coming in, figuring out reconciliation gaps, looking at the loop process flows. And it’s much more value-added to be there than doing the rote double entry, whatever. This is what we see happening. Erik Brynjolfsson calls this white-collar drudgery. There’s a huge amount of stuff happening in big companies. It’s a lot of massaging of information, taking stuff from this sales report, putting it over here, etc. And all of that will be taken out where you can do really curatorial judgment thinking work and applying experience to it rather than doing the actual work itself. And people miss that. And I’ll go back to my specific experience. Writing the first book was 3 years of hell. Hell. Just horrible, because you had no help.

PETER DIAMANDIS: (01:16:32 – 01:16:33) Because you were working with me.

SALIM ISMAIL: (01:16:33 – 01:17:38) Well, no, the first book I was partly with you, but it was just you had to write every line and check every line yourself, etc., right? Second book, Peter, that you and I did together fully, it was 2 and a half years, but even more hell because you kept having to think how much of the first book do you bring over, etc. And by the way, it was an absolute joy working with you, so don’t you dare say anything like that. And the third part. But this third book has been 6 months of unadulterated joy because I can say, oh, Bill Gates just said this, or Satya Nadella said this, look through the book, tell me as a developmental editor where we should put inserts, etc., scan the things, and it’s absolute pure fun. And people forget how much more fun it is when something’s doing all of that cognitive stuff that everybody had to think about, and now you can do pure thinking, judgment, you can be much, much more creative. And this is the heart of what it comes down to. All of this automation and AI enablement and cognitive abundance allows us to be deeply, deeply, deeply creative. And that is the most fulfilling place you can be as a human being.

PETER DIAMANDIS: (01:17:38 – 01:18:38) Beautifully said. Let me hop on Dave on your point. And I’m sure everybody listening here at the pod is using AI and enjoying these conversations. But if you have someone in your life who isn’t, I think the most important thing to realize is you have access to the most patient, most capable teacher on the planet, right? Pick your favorite model and ask it just to begin at zero. I don’t understand this. I just heard this term. Help me create a curriculum for me to go from not understanding AI to fundamentally being able to use it. And I think at a minimum, spend 30 minutes a day in conversation with your favorite model. It’s that easy. It’s free. It’s everywhere on your phone. There’s no reason not to dive in. There’s human cognitive challenges that typically prevent a person from jumping into something they don’t understand, but it has never been easier in the world. Alex or Dave, do you want to close us out on this one?

DR. ALEXANDER WISSNER-GROSS: (01:18:38 – 01:20:02) Yeah, I’ll just comment. I think the original impetus for the story was actually from friend of the pod Erik Brynjolfsson, as you mentioned, Salim. I think there are many people in this economy who don’t realize that not only do they have permission to be high agency, but we’re now in a regime where high agency and agency in general is one of the few human traits that is actively rewarded in an era of superintelligence. People think agency is something— I suspect, this is my theory of the case, I think too much of the human economy, at least in the American economy, the one I’m most familiar with, think agency is something exhibited by superheroes in movies in Hollywood and don’t realize that the shackles are off. Anyone can exhibit high agency empowered by superintelligence now, not just in the cinema, and that to the contrary, this is one of the few things left that can actually yield extreme vertical mobility. So if you’re listening and you’re not, to Dave’s point, fully availing yourself of superintelligence to accomplish superhuman feats, I encourage you to start now because I think there’s a window of time and I don’t know how long it’s going to last, maybe only a handful of years. Do it now, otherwise do it never.

PETER DIAMANDIS: (01:20:04 – 01:20:04) Yeah.

SALIM ISMAIL: (01:20:04 – 01:20:20) Wow. I want to use a flip time on that. Society will reward agency in this world of AI automation. That’s such a great point, because the more you are a self-starter and have the gumption to go ahead and do this and build something with it, the more that you’ll be rewarded. Absolutely love it.

DAVE BLUNDIN: (01:20:20 – 01:20:35) Yeah, Alex said extreme upward mobility. We’ll use that as a theme at the Moonshot Summit. But the data behind what he just said is, oh, it’s like nothing you’ve ever seen before. I think the gap is getting wider and wider, but the rate of upward mobility that’s possible has never been seen before.

SALIM ISMAIL: (01:20:35 – 01:20:39) How is it possible to be depressed if anybody watches this, is my question.

PETER DIAMANDIS: (01:20:39 – 01:20:48) Yeah, I mean, it’s such an amazing time, and I love your story, Salim. Thank you for sharing that data. It’s data-driven optimism is what it is.

SALIM ISMAIL: (01:20:48 – 01:20:52) You mean that or the Afghan warlord thing? You mean this one?

DAVE BLUNDIN: (01:20:52 – 01:20:52) Okay.

PETER DIAMANDIS: (01:20:52 – 01:20:53) All right.

DR. ALEXANDER WISSNER-GROSS: (01:20:53 – 01:20:56) You too can be an Afghan warlord. Everyone can be an Afghan warlord.

SALIM ISMAIL: (01:20:57 – 01:20:59) There’s agency of a different kind.

DR. ALEXANDER WISSNER-GROSS: (01:20:59 – 01:21:00) There’s hope for everyone. Everyone.

China’s Bot Farm and the Data Center Narrative War

PETER DIAMANDIS: (01:21:00 – 01:23:08) Let’s jump into the world of data centers, chips, and compute. 2 breaking stories this week. The first comes out of the global affairs team at X. Let me share a slide and then we’ll talk about this. What does it mean? And is this data absolutely 100%? So this is what was posted on X by the global affairs team at X. It says, quote, “The X safety team conducted an investigation into suspected Chinese inauthentic accounts involved in influence operations. We identified a bot farm of approximately 200,000 accounts. Within this farm, we found 200 accounts posting in a manner that could manipulate a legitimate debate about American AI and energy policy.” These posts contained claims that AI data centers are driving up household electricity prices and straining the grid. Others include AI-generated cartoons that depicted data center operators enriching themselves at the public expense. And here we’re showing one of those cartoons. And we’ve talked about this, what’s causing this 75% not-in-my-backyard sentiment, where people would rather have a nuclear power plant in their backyard than a data center, it seems completely illogical. The second story is one I want to put front and center. It comes out of Quincy, Washington, where the data centers have had extraordinary positive civic impact. This story, reported on CNN, says data centers helped resurrect Quincy, Washington, where the poverty rate fell from 29.4% to 6.2%. Tech tax revenue funded a new high school, hospital, library, police, and fire stations, while residents’ property taxes, their rates decreased. This is a story about the tech industry succeeding. And bluntly, this is the story that the tech industry needs to be telling and needs to be making happen. So, gentlemen, your thoughts on this?

DR. ALEXANDER WISSNER-GROSS: (01:23:10 – 01:23:16) Shocked. Shocked, I say, that there are foreign influence operations attempting to suppress American AI data center deployment.

DAVE BLUNDIN: (01:23:18 – 01:23:18) Shocked.

PETER DIAMANDIS: (01:23:19 – 01:23:20) Salim or Dave?

SALIM ISMAIL: (01:23:21 – 01:23:38) Standard psyops. You’d expect to see this happen. The difficult part is we have really no easy defense against it, and the problem, I mentioned this a couple of podcasts ago, is that the people in the US are very, very narrative-driven rather than evidence-driven.

PETER DIAMANDIS: (01:23:38 – 01:24:25) That’s the problem. I mean, I don’t know what the US is doing in China, but you know. The numbers here are crazy, right? So we’ve talked about this before. If you or someone you know is against data centers, please dig and look at the numbers. Water is not an issue. Energy— these data centers, the right policy is the county says, okay, you can build here, but generate your own power or subsidize community power so it’s cheaper. And for God’s sakes, to the hyperscalers, invest in the schools, invest in the libraries. I don’t know what libraries are anymore, but invest in the community. That’s the right way to do it. Take a fraction of the cost and make everybody’s life there better.

DR. ALEXANDER WISSNER-GROSS: (01:24:26 – 01:24:55) But Peter, you’re gesturing at, I think, something interesting. Libraries. Remember the digital divide and concerns that some areas might be left behind with less compute? And now we’re seeing whether as a result of foreign influence ops or other political factors, the exact opposite where all of these regions that could in principle be economically uplifted and energetically uplifted and compute uplifted are worried, they’re hand-wringing that they might be suffering from too much compute, how much the tide has turned.

PETER DIAMANDIS: (01:24:56 – 01:24:56) Amazing.

DAVE BLUNDIN: (01:24:56 – 01:26:02) Every now and then there’s a story where we just absolutely positively need to get to the truth. And we saw this during that COVID outbreak where it’s like, look, this is a medical thing. What’s the actual truth? Do the masks work? Does ivermectin work? We need absolute truth. And instead we got politics. We got a Republican opinion and a Democrat opinion. And then now Fauci’s on trial. Come on, man. This is nonsense. We need the absolute truth on this story. Are the Chinese— is it the policy of the CCP to disrupt American opinion on data centers, slow down our construction of AI, bypass us in AI, and then control the world by winning the race to RSI? Is that their plan? Or if you talk to Alvin Graylin, he’s like, they don’t even think vaguely that way. They’re just trying to have a better life for themselves and improve their own progress. They could care less about trying to invade the US with false stories. Which is the true story? I don’t actually know, but we absolutely don’t need politics on this. We need to know what is actually going on.

PETER DIAMANDIS: (01:26:02 – 01:26:14) Well, what’s actually going on is data centers are not the enemy. They’re an economic engine that can revive a community that’s been left behind. I mean, that’s the reality. It’s like, please come here.

SALIM ISMAIL: (01:26:15 – 01:26:16) Yeah. Dave, didn’t the slide just show—

DAVE BLUNDIN: (01:26:16 – 01:26:39) So there’s no doubt that you’re right about that, Peter. Data centers are one of the best things we can— they are the best thing we can possibly be doing right now. 100% true. And if the CCP loses that battle, they’ll move on to some societal AI, like it’s corrupting your children, stop building it or something like that. So we need to know. They’ll keep coming back with false story after false story if that’s their policy.

DR. ALEXANDER WISSNER-GROSS: (01:26:39 – 01:26:39) And that’s—

DAVE BLUNDIN: (01:26:39 – 01:26:40) We’re so vulnerable to it.

DR. ALEXANDER WISSNER-GROSS: (01:26:41 – 01:26:56) So I just— yeah, they’ll hypothetically maybe come up with some sort of infinitely scrollable streaming video app that will become insanely popular on mobile phones and addictive to all the kids and ruin the kids’ neocortexes. Just speaking hypothetically.

PETER DIAMANDIS: (01:26:58 – 01:28:02) I think American companies are doing a great job at that already. But that’s a different story. All right, let’s move on. So OpenAI released the first new performance figures of their chip, Jalapeño. It’s a custom inference chip developed with Broadcom, reporting 1.5 to 1.9x more AI work per watt and up to 3.6x lower end-to-end latency as compared to Nvidia’s GB200s and GB300s. Jalapeño runs on 700 watts against the GB300 that runs at 1,400 watts, half the power, 1.5 times the peak power token rate per kilowatt performance here. The significance here is that OpenAI is no longer just a customer of Nvidia. They’re becoming a chip designer. And I saw a great interview where Jensen was being asked by the reporter how do you feel about your largest customer competing with you now. So I think this is what we’re going to see everybody doing. Everybody’s moving up and down the stack. They want independence.

DAVE BLUNDIN: (01:28:03 – 01:28:36) Yeah, there’s no doubt inference is moving off of Nvidia for sure. And, you know, the 100x performance gain— this is the first 2x of 100x performance gains. That does not mean Nvidia has a problem, though, because training is staying on Nvidia and training is infinitely sold out, just like inference is. But there’s an enormous, 90% of the compute is inference time. So there’s an enormous new industry for inference only emerging. The other side of the story is that this was just an idea at OpenAI just a few months ago, and now it’s a production chip. So that shows you how short the cycle time on innovation is becoming with AI assistance.

PETER DIAMANDIS: (01:28:37 – 01:28:37) Yeah.

DR. ALEXANDER WISSNER-GROSS: (01:28:37 – 01:31:03) Alex, a few thoughts on this. Maybe the most startling statistic that OpenAI put out regarding Jalapeño was the throughput per second per user, tokens per second per user increase that they got on Jalapeño, not just on their frontier models, but on their open-source models. You remember GPT-OSS? They claim almost a 54x throughput increase hosting GPT-OSS versus what they obliquely refer to, I guess, as the existing best, presumably a reference to some Nvidia architecture. That’s so startling. Open paren, where is Broadcom in this? Because obviously the only way that OpenAI— and it was public information that they worked with Broadcom on this— but presumably the only way OpenAI using their own AI to achieve a tape-out so quickly is in conjunction with Broadcom. Close paren. This is so startling and potentially such a huge throughput increase it makes me scratch my head and wonder whether OpenAI— remember how we’ve talked in the past about those who can’t compete, compute— whether OpenAI might actually do this to themselves, even though they are competitive with Anthropic. They’re one of the 2 top-tier frontier firms left. Whether they might actually choose to become a hyperscaler themselves with their own chips in-house. It’s like a crazy future, would be a heck of a plot twist. But this has me wondering if they have such amazing balance of prefill of the prompt with otherwise memory bandwidth limited decoding for LLMs, whether OpenAI wants the optionality in a year or two of saying, hey, market, in addition to our own models, we’re going to respond to the competitive threat of Chinese open weight models and other open weight models by, surprise, OpenAI offers its own cloud. We’ll call it OpenAI Compute. It’ll be hosted on OpenAI chips and will still make money just like Elon is. He’s making money hand over fist hosting everyone else’s models, including Anthropic. I think we’re in such a crazy future where I could imagine a world where, say, an OpenAI compute cloud hosts an Anthropic model and OpenAI and Anthropic both win at the time.

PETER DIAMANDIS: (01:31:03 – 01:31:03) Love it.

SALIM ISMAIL: (01:31:04 – 01:31:18) I have a— wow, okay. I have a question for you guys. One of the things that was mentioned was that Nvidia’s CUDA moat may be dead in this next few coming years. How big of a deal is that? Because CUDA seemed to be their moat, right?

DAVE BLUNDIN: (01:31:19 – 01:31:25) Yeah, you know, CUDA— so it’s important to be clear, CUDA is still the dominant mode for AI researchers who are working on new training.

PETER DIAMANDIS: (01:31:25 – 01:31:27) Take a second and explain what CUDA is for those who don’t know.

DAVE BLUNDIN: (01:31:28 – 01:33:16) Yeah, so CUDA— so all the AI researchers in the world moved to Python and PyTorch to do the— because you can iterate your ideas so much more quickly in that environment. And then to run it at scale, you’re like, well, here’s my code, just run. The only way to say “just run” is the CUDA layer translates your PyTorch right into Nvidia microkernels, runs at blazing fast speeds. Nvidia invested a lot of time, human time, coding that up, pre-AI coding. And it became so pervasive that when AI took off, only Nvidia chips could be used for all this training and research because it would have been a nightmare to try and port all these MatMul algorithms to AMD or to some other vendor. And so, that’s why Nvidia is the most powerful company in the world, or most valuable company in the world today, is specifically because of that brilliant early support of AI researchers when nobody else cared about them. So now everyone’s like, well, but now I can vibe code anything in like a microsecond. Why is the CUDA thing still a moat? And at inference time, it’s not, your inference algorithms are so easy to port to AMD or Intel, that you just don’t care about CUDA, you can vibe up your own solution. But for the advanced researchers, they still overwhelmingly use CUDA. And then, Nvidia realized that CUDA can’t last forever. So they went and bought Mellanox, to create massive high-speed interconnect. So now their big moat is, look, if you want to run 100,000 or 1 million GPUs in one coherent cluster, you still got to go with Nvidia only. So I think Jensen’s smart enough to know that your moat is only good until the next moat. And so he’s moving the moat very intelligently, and he has a huge amount of capital to keep moving with it. But CUDA as the inference time moat is already dead. CUDA as the training time moat is probably limited lifespan. But that’s okay because the interconnect is the new moat.

Apple’s AI Catch-Up: M5 Ultra and M6

PETER DIAMANDIS: (01:33:16 – 01:33:48) All right, let’s turn to Apple. So Apple’s new Mac Studio pairs the M5 Ultra with up to 512 gigabytes of unified memory, giving a desktop Mac enough memory to run some of the largest OpenAI models available locally on your desktop. Apple unveiled also the M6, its first chip manufactured at the 2-nanometer process. So finally, Apple is in the AI game, now pushing local AI as an alternative to AI in the cloud. Salim, you wanted to talk about this one. Your thoughts?

SALIM ISMAIL: (01:33:49 – 01:33:53) Well, just such an easy and obvious thing for Apple to do, right? You would have been—

DAVE BLUNDIN: (01:33:53 – 01:33:53) They would—

PETER DIAMANDIS: (01:33:53 – 01:33:53) You—

SALIM ISMAIL: (01:33:54 – 01:34:58) If they hadn’t done this, they would have been the stupidest company in history, and they’re not that dumb. The 512GB unified memory puts a massive amount of intelligence under your desk. So this really changes the economics from paying per token perpetually to buying a capital asset and then using it continuously, right? Especially that Apple’s gone to the extra level of starting to lease its equipment out to people. So this is really a big deal. I think the big winners here are law firms, healthcare companies that have HIPAA issues and can’t put their stuff on the cloud. Everything can— much more stuff can now be done on-prem. And I think this is going to be a big deal for medium-sized healthcare firms that can’t afford a private cloud and doing all that. It’s really, really a big deal. And I think this is such a natural advantage for Apple to go down this path. So you get 4 of these Mac Studios clustered together, now you’ve got like a small private data center. Like, that’s a pretty big deal. Even Dave would go full out for that rather than 25,000 agents.

DAVE BLUNDIN: (01:34:58 – 01:35:49) I mean, look, Salim, I’m at the end of my rope with Apple. Nobody has changed my life more that I’ve never met than Steve Jobs. And the Apple II that I got when I was a kid totally changed my life. And then when they came out with macOS based on Linux, changed my life again. It’s absolutely the greatest company I’ve ever seen, but they have totally missed the boat. And it’s just embarrassing that a company with that much cash flow has no AI strategy. They don’t even deserve to be a Mag 7 company anymore. It’s just pathetic. So if the best they can do in the age of AI is add a bunch more RAM to a machine that they already had, I mean, what the hell, man? I’m not saying this is a great thing that they came out with, but it’s like 0.01% of what they should have done by now in AI.

SALIM ISMAIL: (01:35:49 – 01:35:54) Okay. I’m okay with all of that. But it’s obvious they should have done it. At least they did this, right?

DR. ALEXANDER WISSNER-GROSS: (01:35:55 – 01:37:44) I’d say the irony is even deeper. So if you look at the ancestry of how unified memory architecture came about and the neural engine inside the M series, you can trace the lineage back to the Apple Car. The Apple Car was the reason why Apple first introduced— the Apple Car that never happened— why Apple introduced the neural engine with access to this huge unified memory addressable space. So I almost think Apple’s interaction with AI is almost a history of hardware that’s too good for the software, or conversely, software that just isn’t worthy of the hardware. Apple had the early unified MatMul acceleration built into a unified addressing space. Apple had the TSMC connection. Apple had the raw transistor throughput to basically be Nvidia and then some. And they fumbled it. They had Siri before everyone else. They had audio interaction, all of these various forms, and Apple software fumbled the ball. And I can only hope that under John Ternus, Apple is going to decide it really does— Tim Cook used to always say, and before Tim, Steve Jobs, that they wanted to be hardware plus software plus services. And it just seems to me like Apple’s hardware, at least to the consumer side, is incredible. Their services are also not that bad, but they’re so fumbling and so underutilizing still infamously their amazing hardware with their software. And, to John, if you’re listening and you’re looking for guidance on what Apple should be doing in this new era under your CEOship, please, please, please just take your amazing hardware and unleash it with much better software that integrates AI natively.

DAVE BLUNDIN: (01:37:44 – 01:37:48) So yes, hire Alex as a consultant first and foremost.

DR. ALEXANDER WISSNER-GROSS: (01:37:48 – 01:37:50) I don’t need it.

DAVE BLUNDIN: (01:37:50 – 01:37:54) Well, do it. You’ll pay. Do it because you need it, not because Alex—

DR. ALEXANDER WISSNER-GROSS: (01:37:54 – 01:37:56) Maybe for charity. For charity.

DAVE BLUNDIN: (01:37:56 – 01:38:07) But also the world needs it. They’re like, the one brand that you can trust with your information is the one and only brand. And here we are in the age of AI, everyone’s confused.

PETER DIAMANDIS: (01:38:07 – 01:38:07) It would be—

DAVE BLUNDIN: (01:38:08 – 01:38:09) It’s incredibly powerful.

PETER DIAMANDIS: (01:38:09 – 01:39:07) Such a different world if Steve Jobs had not made his health decisions and not treated his cancer. Dave, I met Steve once. I had a one-word conversation with him. So I was having an XPRIZE meeting. Larry Page, co-founder of Google, was on my board and he hosted us for an evening dinner. And Laurene Powell Jobs, his wife, was there. And Steve was there in the back of the room. And we were talking about the latest X Prizes and the ones that were just won. And afterward, I had to go meet my hero over there. And Steve is in the back of the room with his arms folded the entire time like this, looking kind of upset. And I walked over, introduced myself, and I said, Steve, it’s a real pleasure to meet you. And he barely nods his head. And then I said, you don’t want to be here, do you? He goes, nope. And that was the entire conversation. I’ve got a story.

SALIM ISMAIL: (01:39:07 – 01:39:49) So, a couple of months before the big iPhone announcement in 2007, Jerry Yang put together an offsite, a full-day offsite with all of Yahoo’s vice presidents, and Steve Jobs came in to do a keynote, right? So I had a kind of a handshake hello, and Steve Jobs looks at the audience and there were like 300 people in the room, right? And he’s like, you have 300 vice presidents? I think I see the problem with Yahoo right there. So the fact that he had that much organizational overhead, he was just— couldn’t cope with that. I have a whole bunch of MacBooks that were signed by Wozniak.

DAVE BLUNDIN: (01:39:49 – 01:39:49) Oh wow.

SALIM ISMAIL: (01:39:50 – 01:40:03) Because I did a 90-minute debate with him on stage a few years ago. How old? Yeah, that one’s about— that was a few years old. I had him sign about 4 or 5. I’m guarding them jealously.

DAVE BLUNDIN: (01:40:03 – 01:40:05) Yeah, you gotta preserve those in some kind of like—

SALIM ISMAIL: (01:40:05 – 01:40:37) Preserve those. And I gave a couple away to my community because they were so thrilled with that episode. It was a great conversation. Steve Wozniak is famous for coming out with all of this technology gives us the opportunity to do tinkering and just playing around. And that’s the heart of all creativity, is just playing around with technology, seeing what comes up. And he was really doubling down on that. So it was a great conversation. But that memory of Steve Jobs looking at 300 vice presidents going, I see what’s wrong with your company, has never left me.

PETER DIAMANDIS: (01:40:37 – 01:40:37) Oh my God, okay.

DAVE BLUNDIN: (01:40:38 – 01:40:48) The very first share of stock I ever bought was Apple. And we tend to overthink things. All I had to do is just hold it. I should still have that stock today.

Energy Abundance: Uranium, Solar, and the Nuclear Freeze

PETER DIAMANDIS: (01:40:49 – 01:42:09) I’m going to move us into the world of abundance. 2 stories on energy and one on water. Again, our mission here is to deliver you data-driven optimism, why the world is getting better. So let’s hit energy first. Again, 2 stories here. The first story is about uranium enrichment to meet the growing needs of our advanced Gen 4 fission plants and the coming SMRs, small modular reactor power plants. So historically in the US, conventional reactor fuel in the form of uranium-238 has been enriched to about 3 to 5%. This week, a commercial startup called Actinide said it has demonstrated the ability to enrich natural uranium into high-assay, low-enriched uranium, or HALEU, up to a purity of 15.38%, 5 times the traditional purity previously achieved by all the government labs. So Actinide is enriching uranium to this level. And that’s, for me, a remarkable story. So every SMR company— and we had that incredible podcast with Ramesh Nam on the future of energy, if you haven’t seen it, please go see it— every SMR company says their reactors will be coming online in 2030, but none of them have the fuel. And this could well be the solution. Alex, any thoughts on this story?

DR. ALEXANDER WISSNER-GROSS: (01:42:09 – 01:45:31) Yeah, a number of thoughts. I think something went wrong right after World War II. That’s my best guess. In the immediate aftermath of World War II, so 80 years ago, the Atomic Energy Commission was eventually formed in the wake of the Manhattan Project. And I think something just got screwed up with regard to how nuclear physics and advanced physics in general was handled in the post-World War II era. And the government, probably because of the bomb, granted itself under the guise of mixed civilian-military leadership, the Atomic Energy Commission, I think something governance-wise got fumbled. And I think 80 years on, after the end of World War II, we’re finally starting to shake off the quasi-governmental monopoly on nuclear physics. And I suspect there has been so much progress in an alternative history, sort of “for all mankind” style, where if in the aftermath of World War II, if the Atomic Energy Commission had either been organized differently or we just had a totally different governance structure for advanced physics after the war, we would have advanced so much more quickly. And I think startups like Actinide that are producing HALEU, I think these are the tip of the iceberg for all of the economic growth and technological growth that can now be— now, 80 years after World War II, all of these shackles that we put on our own society, perhaps with the best of intentions, are finally slowly atrophying away. And just a narrow point on the technology here. So this is non-obvious. In many cases, uranium enrichment in this country, to the extent we do it at all and aren’t just importing enriched uranium from, say, Russia, the technology that in many cases is being used to enrich uranium in this country is Manhattan Project-level technology that has not been materially improved since World War II. It’s using uranium hexafluoride gas and centrifuges when we have much better technology. There are alternative ways to enrich uranium. For example, the term is a calutron. This was technology that we’ve known in principle how to make since the Manhattan Project. Rather than using centrifuges spinning uranium compounds in gaseous form, and then later having to compress the gaseous uranium molecules down to solid pellets or other solid forms that could be used in reactors, we could instead be using magnets, electromagnetics, and vacuum systems, and power electronics controls. We have 80 years of advances in power electronics that by and large are not being used and have not been used to enrich uranium, either because we’re scared of doing it or because we’ve handcuffed ourselves in terms of our being able to do it. So I think we should expect to see, now that the shackles are starting to come off in a limited fashion from the post-World War II era, we’re going to start to see 80 years of chip advances and Moore’s Law advances finally being applied back to this basically World War II era technology. And I think it’ll create an energy boom.

PETER DIAMANDIS: (01:45:33 – 01:45:34) Well, I hope so.

DAVE BLUNDIN: (01:45:34 – 01:45:55) I think, from a venture capitalist point of view, you would never in a million years have invested in this when the regulatory cost of getting a nuclear reactor up and running is going to be a billion dollars anyway. So you can see how the dysfunction ripples through. You start with government dysfunction, and then the venture capitalists are like, well, given that that’s dysfunctional, I won’t invest in these innovations. So then the whole value chain just doesn’t go anywhere.

PETER DIAMANDIS: (01:45:55 – 01:47:28) But now the SMR companies are being funded by venture capitalists and they are going public. Let’s jump into a little bit about solar. I’m going to show this chart here. This is a chart that comes from Ember, the global energy think tank. They shared this data showing China’s increasing energy generation explosion both in solar and in nuclear. So monthly solar generation in China has exploded 8-fold, 800%, over the past 6 years, growing from 20 terawatts per month in 2020 to about 160 terawatts per month in mid-2026. At the same time, nuclear power in China has increased by at least 50%, while the US nuclear power generation has basically remained flat. You need to remember that the AI race is not just about chips. It’s also about the cost of energy to run those chips. The US is building its whole data center power generation based on natural gas, which is like $6 per million British thermal units, while China is basically getting this for near-zero marginal cost from solar. And I think the abundant story here is it is possible to really create a massive amount of energy from solar. If you talk to your local model, it’s like there’s 8,000 times more energy that hits the surface of the Earth than we consume as a species. So being able to double, triple, or 10x that is well within reach. Salim, you want to jump in first?

SALIM ISMAIL: (01:47:28 – 01:49:00) A bunch of things to say here. First of all, if you look at the difference between that red and blue curve, it’s completely a copy of our old linear versus exponential curves, right? Linear’s like this and exponential curves up, and we’re on the wrong side of that equation. This is linear intuition confronting an exponential curve. The problem is solar keeps getting underestimated because people look at installed capacity today rather than the vertical slope of the deployment curve, and that’s the nightmare. And people can’t get their heads around this. This is such a kind of an old tired weird story that we should just get past because China’s advantage is not like a magical solar panel. It’s the whole industrial system optimized around manufacturing, the supply chain, the permitting, the deployment. And in the US, the big challenge is the interconnection with the grid, the transmission, the permitting speed, right? And so you need all these different— you need nuclear, you need solar, you need all of this. But battery technology makes this a killer opportunity because you can add a solar panel today rather than wait 15 years for some gigawatt-scale energy project. And so this is a massive opportunity that’s being left behind. If I was the US, I’d put a Manhattan-type project into perovskite and new solar capabilities, photonics. You have some huge opportunities there. And this— when you have energy abundance, as I think we’ve all pointed out, that becomes a multiplier in every other exponential technology. Energy. So this is such a no-brainer. And it really kind of is very dismaying to see the GDP challenge here.

PETER DIAMANDIS: (01:49:00 – 01:49:15) The GDP of a country is directly proportional to the amount of energy they create. And Alex, the point you made about nuclear being frozen, it’s very clear here we have not changed nuclear in decades.

DR. ALEXANDER WISSNER-GROSS: (01:49:15 – 01:49:38) We’ve still been producing for half a century, something— again, I think in the fullness of time, maybe 10 years from now, we’ll have a better understanding of what happened during the 20th century that got screwed up after World War II. But I think several things on the governance side, especially as they relate to nuclear physics, just in the wake of World War II, we went on the wrong path. And my hope is that it gets corrected.

PETER DIAMANDIS: (01:49:39 – 01:49:42) Yeah. Dave, do you want to make a comment on this one?

DAVE BLUNDIN: (01:49:43 – 01:49:51) Well, I’ll only make one comment, which is, on that chart, the US is way behind in solar. All those US panels are made in China. It’s much worse than it looks.

Weather Modification: Cloud Seeding and Water Abundance

PETER DIAMANDIS: (01:49:52 – 01:50:50) Yeah. All right, our next story is about water. The weather modification startup called Rainmaker says that 10 drones that flew over Alaska’s Kenai Peninsula generated an estimated 19 million gallons of additional rainfall in just 3 hours using what they call glaciogenic cloud seeding. So, ultimately weather modification is no longer theoretical, it’s here. Applications for this kind of technology include drought relief, agriculture, wildfire prevention, and water security. Just for reference, you can look it up, there’s 3.4 quadrillion gallons of water in the atmosphere, and atmospheric capture is now a thing, making it in the clouds or capturing it on the ground. So this is the abundance thesis that predicts that water becomes massively abundant when technology to create it becomes cheap. And, 10 drones creating 19 million gallons of water in 3 hours is pretty damn cheap. Alex?

DR. ALEXANDER WISSNER-GROSS: (01:50:50 – 01:52:32) And the drone part, the UAV part, I think is especially novel. So imagine a near-term future where we achieve our weather control grid. Not necessarily— when I always go through the mental exercise of how, if I had to build a global weather control system, how would I do it? I think the easiest way to do it is probably with reflectors either terrestrially, cheaper, or in LEO, a little bit more expensive. But this points the way, I think, to a third path for global weather control, which is cloud seeding. Imagine a swarm, a fleet of drones in the style of Rainmaker’s drones that are continuously in flight, probably solar-powered so they can be permanently aloft, and they are just dispensing on an as-needed basis but under the control of some centralized AI algorithm, the particulates, the nuclei needed for either snow or rain, all informed by a global weather AI model, we could in principle, I think with some further development of Rainmaker’s technology and similar technologies, we could have total weather control. And that would be from a natural disaster perspective, imagine being able to divert hurricanes or disperse hurricanes before they form. Disperse with precipitation on the water instead of on land. Or tornadoes, other extreme weather events. Not to mention giving good weather to the places that want it and are willing to trade it. We could have a global weather trade where regions trade each other for precipitation. There are so many possibilities that are unlocked by the confluence of AI, drones, and weather modification. And now finally we’re about to start this era of geoengineering. I think.

PETER DIAMANDIS: (01:52:33 – 01:52:40) Love it. I can see the business model for Rainmaker. It’s like different cities bid on where the drones go.

DR. ALEXANDER WISSNER-GROSS: (01:52:41 – 01:52:44) Rain arbitrage. We could have a global market for rain.

PETER DIAMANDIS: (01:52:46 – 01:52:47) Salim?

SALIM ISMAIL: (01:52:47 – 01:54:28) Rain becomes programmable. For me, the big breakthrough is not that they made rain, which we’ve been able to do for a while now, but it’s the fact that they could prove how much additional rain they made. That, I think, is really interesting because it then unlocks a huge amount of stuff. The challenge is weather typically doesn’t respect boundaries. So trying to figure out if you’re downstream of somebody that seeded a bunch of clouds and now you’re not getting the rain and they’re getting it is going to create some interesting tensions around that. But this is exactly the type of abundance technology, right? Allows you to scale something really powerful. And I think there’s a wonderful future. The business models around geoengineering, as Alex puts it, are pretty rampant. You could do some really interesting stuff. Crop management, all sorts of things become capable. It’s reminding me of one of the more creative singularity solutions that we ever saw was at Singularity University. One of the summer students, I think his name was Simon Daniels, had this idea of putting platforms in the ocean that would spray up water vapor, take ocean water and spray it up to block the sun from hitting the Earth and slowing down global warming that way. And his business model, just said that, was to do it along flight paths where you could spray up water in the shape of a Nike logo and sell that advertising. And so you sell— do it in the shape of certain patterns that pays for the whole system. At the same time, you lower the temperature in a controllable way. And there’s lots of people that say, oh my God, geoengineering is a bad thing, we don’t know the aftereffects. And the counterpoint is, well, we’ve already been geoengineering the world for 100 years. Oh yes, in a horrible, uncontrolled, unmeasurable way, and it’s causing massive damage. Look at the disaster in Nepal.

PETER DIAMANDIS: (01:54:28 – 01:54:29) Yeah, that’s happening right now.

SALIM ISMAIL: (01:54:30 – 01:54:47) It’s a complete tragedy there, and nothing anybody could do in that sense. And you could avoid a lot of that. And so I think it’s incumbent upon us to use technology to navigate this stuff, because you do it consciously rather than unconsciously, and that’s the powerful point.

Cancer Screening, RAS Inhibitors, and Tooth Enamel Regeneration

PETER DIAMANDIS: (01:58:15 – 01:58:16) All right, let’s move into the world of health. A couple of stories here. First off, this week the FDA approved a drug called— let me pronounce this properly— daraxonrasib. It’s the first RAS inhibitor for metastatic pancreatic adenocarcinoma, attacking the RAS family of proteins that drives tumor growth in most patients with the disease. So pancreatic cancer is really considered almost a death sentence. It’s the most lethal, least treatable cancer for humans in history. In previously treated metastatic cancer, daraxonrasib nearly doubled median survival from 6.7 to 13.2 months. It also tripled tumor response rates from 11% to 32%. And while this isn’t a cure, and just getting an extra 7 months doesn’t sound like a lot, that’s an additional 7 months for science to continue to make more breakthroughs. That’s the way I think about it. This is like longevity escape velocity. Your goal is to live long enough to get a breakthrough to the other side. It’s also worth noting that RAS mutations drive about 30% of all human cancers. So a drug that inhibits these proteins may also be useful for other cancers as well. And we’ve heard this said so many times by Dario, by Demis, by many others. The goal is to cure all these diseases, including cancer, in this next decade. Alex, do you have a take on this one?

DR. ALEXANDER WISSNER-GROSS: (01:58:16 – 02:00:16) Yeah, so a couple of items. One, I’d point out remarkably, this is a daily oral tablet, pretty incredible. Secondly, I’d point out, I was doing some research on the full lineage, as it were, for daraxonrasib. There’s almost no AI involved in the development of this drug. So I think this is actually— finger to the wind— I think this is probably, hopefully, one of the last generation of pancreatic cancer medications that almost precedes the AI wave. And I would expect lots of new targets, lots of new approaches to emerge from both the AlphaFold3 style of protein folding problem and structural biology being solved, as well as virtual cell models. As far as I can tell, daraxonrasib used neither of these in its design. It was like good old-fashioned drug design. But I think we’re about to see a whole wave of AI-driven drugs that take it from its current response rate to near 100% using AI. And I think that’s to be celebrated. I also want to celebrate the FDA in approving this relatively quickly. FDA noted that they approved this, I think, 60, 90 days, something like this, prior to the due date, which for historic FDA speeds is actually pretty remarkable speed. So we’re seeing a much more, I think, responsive FDA that now starts to care about Bayesian versus frequentist statistics, that cares about IND quite a bit more, it seems, that’s interested in lowering the number of clinical trials in exemplary cases. Hopefully, this is, I think, a baby step towards a future where AI solves 5,000 diseases, and then we have a regulatory apparatus in the form of an FDA that is able to metabolize all of those innovations and turn them into cures.

PETER DIAMANDIS: (02:00:16 – 02:02:05) Amen. Amen to that. Let me move to our second story in the health corner here. This is published in Nature Communications, and it comes from an international research team out of University of Nottingham who developed a biomimetic gel capable of repairing and regrowing damaged tooth enamel. So this is a fluoride-free treatment, uses lab-engineered proteins that mimic the natural processes of enamel formation during infancy. So as you might know, tooth enamel is the hardest substance in the human body. And it doesn’t regenerate. So until now, the only thing you could do was replace enamel with a synthetic filling that would eventually fail. So this biomimetic gel is an elastin-like protein matrix designed to mimic the natural protein scaffolding that organizes enamel during tooth development. The treatment didn’t just make something that looks like enamel, it regenerated layers and restored hardness, stiffness, water resistance, friction properties, resistant to brushing, chewing, acid exposure in labs. The gel acts like a scaffolding that pulls calcium and phosphate from the surrounding environment and directs them into properly organizing minerals rather than merely depositing an amorphous coating. It’s true enamel. For me, this is huge. Oral disease affects half the population. It’s estimated at half a trillion dollars per year in associated costs. To put this in perspective, this is still ex vivo. It’s still done using extracted human teeth, and it’s being done effectively in the test tube or the petri dish, but it’s going to be moving to human testing very quickly. And as someone who’s had poor dental health and poor dental genetics all my life, I couldn’t be more excited about this, especially for my kids. Salim, do you want to jump on this?

SALIM ISMAIL: (02:02:07 – 02:02:26) Just fantastic. For me, the big thing is showing that the future of medicine is not like repairing broken bits, it’s convincing the body to rebuild them and finding the mechanisms and pathways, right? And so this is really, really powerful stuff. It’ll completely change dentistry. Yeah, it’s completely—

PETER DIAMANDIS: (02:02:26 – 02:02:35) People undervalue their oral health so much, right? The mouth is a direct corridor to the brain and to the heart. You need to be careful about your oral health.

SALIM ISMAIL: (02:02:36 – 02:02:43) Alex, regenerative medicine— there’s been a future. We’ve been waiting for stuff like this to happen for a long time. It’s great to see it finally kind of actually come into being.

PETER DIAMANDIS: (02:02:44 – 02:02:45) Alex, did you dig into this story too?

DR. ALEXANDER WISSNER-GROSS: (02:02:46 – 02:04:06) I did. I mean, I think these results actually started bubbling up last year first. I’m incredibly interested in materials engineering of the human body, human dental enamel included. But I think this was an AMA question that we got in the last pod episode, people asking, yeah, where’s all the innovation? Well, I think the story, which again, I first started seeing this last year, I think this is just one data point in a larger manifold of just applying good old-fashioned material science to the problem of human teeth. And if you can help to shape and engineer the pathways through which tooth enamel grows, I have to think that similar biomaterial discoveries and inventions will also be helpful for bone regrowth, for a variety of other key biomaterials for regenerative medicine. And again, looking at the research behind this, I saw approximately no AI. That’s always my sniff test. Like how, if and how AI was used in this research. And if it wasn’t used, as appears to be the case here, then take this but multiply it by many orders of magnitude, the sort of progress I’d expect to see in a few years in this area.

PETER DIAMANDIS: (02:04:07 – 02:04:08) Dave, how’s your oral health?

DAVE BLUNDIN: (02:04:10 – 02:04:43) It’s fine. But, you know, I get really excited about that Moderna story we had recently where they had a melanoma vaccine that works really well. Stock went way up. But what was exciting is that it’s a platform that applies to virtually any other cancer. And so when Alex says, yeah, these weren’t done with AI, I’m like, well, they’re really cool, but they’re one-offs. I can’t wait for the repeatable— like, I can grow a tooth, I can grow an arm, I can grow an ear, I can grow anything now. And so then you get into true scalable regenerative medicine. I feel like that’s very, very soon.

PETER DIAMANDIS: (02:04:43 – 02:04:50) By the way, the work on limb regrowth is making amazing progress. Yeah. All right.

DR. ALEXANDER WISSNER-GROSS: (02:04:51 – 02:05:18) I think, Dave, you’re also touching on an interesting, almost like a singularity-flavored technological deflation story, which is if there’s no AI in it, to first order, what’s the point? Either infuse it with AI and make it scalable so that you can solve everything, scale it up by 1,000x, or just don’t do it and do something else that’s higher leverage. Not to discourage people from regenerative medicine.

DAVE BLUNDIN: (02:05:18 – 02:05:23) Sell your data to Demis, and Demis will AI what you just invented. Yeah, that’s perfect.

The Lunar Economy and Elon Musk’s Space Ambitions

PETER DIAMANDIS: (02:05:24 – 02:06:10) All right, finally, let’s jump into space and robotics stories. So the 2 first stories are from the Elon universe. Deloitte this week reported about the potential lunar economy. They put a financial figure of $566 billion in cumulative economic value by 2050. I could not expect a lower lowball than that number from Deloitte. The biggest early markets being infrastructure costs, transportation, power, comms, mobility, construction, life support. They cite SpaceX as the biggest winner because of the central role that Starship will play. You know, clearly they are not taking into account, Alex, manufacturing StarMind on the Moon to fuel Earth’s—

DR. ALEXANDER WISSNER-GROSS: (02:06:11 – 02:06:13) Where’s the petafab? Petafab is MIA.

PETER DIAMANDIS: (02:06:13 – 02:07:07) Yeah. So, just to put the numbers on it, because that number, half a trillion of lunar economy, may sound large, but it’s a minuscule estimate. So Elon previously stated his plans for StarMind started with about 100 to 200 gigawatts per year of orbital AI compute launched from Earth, and then moving to manufacturing AI satellites on the Moon for launch with a mass driver. He estimates that we could yield as much as 100 terawatts per year of orbital compute based on lunar production, which would generate— and wait for it— an absurdly large amount of lunar economy. Wait for it. The estimate, if you’re building 100 terawatts per year of orbital compute, the economy would be $2 quadrillion per year of gross revenue. I mean, I like that.

DR. ALEXANDER WISSNER-GROSS: (02:07:07 – 02:07:11) I mean, I don’t know, maybe Planet Ark is maybe too small.

PETER DIAMANDIS: (02:07:12 – 02:07:28) $2 quadrillion. Now we’re talking a good economy. But, Salim, you deal with like the Deloittes and McKinseys. And so these guys are so conservative in their numbers all the time. It’s crazy.

SALIM ISMAIL: (02:07:28 – 02:08:51) Yeah, because a lot of them are accountants, so they’re scared of being called out for anything vaguely approaching a real estimate. They want to make sure their numbers are defensible to the nth degree, so no speculation at all. Whereas by definition you’re speculating, so might as well speculate to some level of honesty. This is the same type of pattern we’ve seen before. One of these Big Four— I won’t say which one to protect the innocent here— put out an agentic AI report saying this is the future of AI agents, etc. So I excitedly read it thinking I’d get some glimmerings that would give me some sense of it, except when I looked deeper into it, the data they were using was 2.5 years old. Okay, and how, with 2.5-year-old data, are you going to come up with anything about the agentic world when everything happened in the last 6 months? It’s like, how do you? But they have so many checks and balances and internal review systems that dilute everybody’s thinking carefully. You can’t say that. And then lawyers and cross-reference checkers and even more cautious people, and then nothing. It’s nothing realistic that gets put out. In general, I typically say take any of their estimates and multiply it by 10 or 20 times.

PETER DIAMANDIS: (02:08:52 – 02:08:53) Dave, what’s your thought?

DAVE BLUNDIN: (02:08:53 – 02:09:30) We had the Deloitte AI team in here in the office the other day. They’re very, very good actually, but they were also saying the same thing about the accounting side. So, Salim, you’re confirmed from inside Deloitte. Yeah, quadrillions of dollars, that’s what Elon was talking about. I believe it because the gravity well is the key. Peter, you talk about this a lot, but everyone’s like, why would I bother manufacturing that on the Moon? What’s the point? I can just make it here. No, no, it’s the gravity well. You start building power plants based on just lunar minerals, and all of a sudden you’re like, this is so much more efficient. Plus, there’s no worry about pollution and stuff like that.

PETER DIAMANDIS: (02:09:30 – 02:09:47) Lunar regolith is silicon. What’s that used for? Oh, okay, power generation. Aluminum, nickel, iron, and oxygen. I mean, it’s like the perfect materials for building Dyson swarms. Alex, I’ve got to feed it to you to sort of uplevel this vision here.

DR. ALEXANDER WISSNER-GROSS: (02:09:48 – 02:11:11) Well, the Moon may not be a harsh mistress, she may be a wealthy mistress at this point. I do think the petafab is the killer app for the Moon. I don’t think it’s tourism, I don’t think it’s transport or infra or comms. The Apollo program was sort of infamously arguably a successor to the Manhattan Project. And I think to the extent that the full history of the Apollo program is already fully understood and in the public record, I think a relative failure. I would love to see the Moon reach its full economic potential. And I just don’t think that is going to happen any way other than full private development. And right now it does appear that the critical path is mining chips, fabbing data centers on the Moon. It’s not rods from God. It’s not deploying US NASA astronauts to the Moon. That’s all well and good. And friend of the pod Jared is, I think, doing an amazing job of reinvigorating the case on the government side for fission reactors on the Moon and all of that. But I think in the fullness of time, even that just ends up being a rounding error compared to data center deployment and mining on the Moon. Unless, I don’t know, unless 2001: A Space Odyssey happens and we discover some monoliths on the Moon, in which case that’s the killer app.

DAVE BLUNDIN: (02:11:12 – 02:11:43) The petafab or the exafab on the Moon is really interesting to game out because when you look at the fab construction process, a lot of the components in there are just routine aluminum, routine construction. There are a few really critical pieces that you can still make on Earth and launch them, and it’d be just a tiny fraction of the total cost. But once you start manufacturing chips on the Moon, the solar panels on the Moon, it’s just exponential takeoff from there. And the technology is just not that far away.

SALIM ISMAIL: (02:11:44 – 02:11:59) The problem is that these guys are not looking at what the— you can’t ask what the lunar economy is today. You have to say, what industries become unlocked when the cost of moving mass off the Earth drops by an order or two of magnitude? And that’s the imagination gap.

PETER DIAMANDIS: (02:12:00 – 02:12:33) Yeah. And I just want to say a shout out to Jared Isaacman, who’s a friend of the pod. What an extraordinary administrator. I could not be more proud. I said it during our podcast with him. I’ve known, I think, all the administrators pretty well over the last 40, 50 years. Or 40 years. And he is by far the best, most eloquent, most visionary, most business-minded. And he is an accelerationist. And if anybody’s going to support humanity moving beyond the bounds of Earth, it’s him.

DR. ALEXANDER WISSNER-GROSS: (02:12:34 – 02:12:43) Peter, every time the CCP sponsors an influence op to deter American terrestrial data centers, the lunar petafab gets its wings.

Tesla’s CyberCab Rollout

PETER DIAMANDIS: (02:12:44 – 02:14:08) Yeah. All right. Our second Elon story comes from Tesla. The company announced it’s expanded its rollout of CyberCabs in Texas. They just registered 79 Model Ys for the robotaxi service. And this is starting to look more less like an experiment and more like a real fleet. In Las Vegas alone, Tesla recently said it’s going to be deploying 2,500 vehicles in the next year. Its CyberCab. Tesla’s official long-term milestone is to reach 1 million robotaxis in commercial operations as soon as possible. And if you do the estimates, that’s probably about $100 billion of revenue in rideshare revenue for Tesla. Let’s take a look at a quick video here just to remind people how cool the CyberCab is. I have to say, I love Google, but Waymo’s new vehicle is kind of clunky. This is pretty beautiful. This is Elon at the original CyberCab rollout. I love those doors. Yeah, those are 3 or 4 Commodores. Pretty cool.

DAVE BLUNDIN: (02:14:09 – 02:14:10) Yeah, such a great design.

PETER DIAMANDIS: (02:14:11 – 02:14:15) It’s a beautiful design. And in gold, it’s perfect.

DAVE BLUNDIN: (02:14:15 – 02:15:00) It really is. At the Gigafactory, remember they had that one that was all exploded out so you could see inside all the parts? And it’s just a beautiful, beautiful design. And it doesn’t have that many moving parts, so you can see how they’re going to manufacture them at an incredible scale. Yeah. Just, just for a consumer, from a consumer point of view, all my friends that are driving the new Full Self-Driving Model Ys are like, oh my God, this is life-changing. I literally go anywhere with FSD. And the waitlist right now is about 3 months for a Model Y. But 3 months from today, the fully engaging, you want to talk to it all the time AI will be everywhere. So you might want to get on that waitlist because you’re going to want to be talking to your AI and continuing your dialogue, your work, your phone.

PETER DIAMANDIS: (02:15:01 – 02:15:17) It’s going to be amazing. And, if there are entrepreneurs out there, when the CyberCab comes out, buy 100 of them, put them out to work, and we’ll have a fleet of CyberCabs generating revenue for you. I think that’s going to be an incredible business.

DR. ALEXANDER WISSNER-GROSS: (02:15:17 – 02:16:01) I will say I love my Tesla Model Y 2026 Juniper Launch Series Edition. It is life-changing. The FSD is incredible. The manufacturing quality of the car is incredible. I can’t wait for CyberCabs and robotaxis in general to come to Boston. I’ll beat the drum once more for the broken Waymos theory of if a city can’t accommodate robotaxis, then it is not equipped for the singularity. And hopefully someone from the city of Boston is listening to this and scratching their head and wondering just what Boston is doing and why Boston doesn’t have proper Waymo support. If you’re scratching your head and you’re in a position of authority, call Dave or call me. We’d love to figure this out.

PETER DIAMANDIS: (02:16:02 – 02:16:15) Yeah, same thing when Uber was made illegal in France. I was like, okay, if you’re an entrepreneur, don’t move to France. These are telltale signs of what cities are on the singularity curve and which are not. Yeah.

SALIM ISMAIL: (02:16:16 – 02:17:45) So, um, I’m actually having to sell my beloved 10-year-old Tesla Model S to get a Model Y because I need the FSD. I’ll send a photograph of it in for our next pod just so everybody can see. Like, I totally love my car, but this is a big, big deal, I think, for a couple of reasons. One is, there’s 3 little things here. One is that this changes from purchasing to autonomous revenue miles. What’s the cost per autonomous revenue per mile, right? And if you can do it at a decent safety-adjusted cost, this is actually massive. The fleet growth will lower wait times, which will improve the user experience, which will increase the rides, which generates more data, which will create that inner loop that Alex is talking about. So I think there’s some really amazing downstream benefits from all of this. It totally changes the game on insurance and cleaning up and charging and all sorts of— I think you’ll turn gas stations into autonomous car cleaning depots. That kind of thing will start to happen. But for me, the big one is I made a bet. I got up on stage 10 years ago and I said my kid will never get a driver’s license. And I’ve got just about a year for this CyberCab to roll out, to get out there. Before he— he may get one anyway just to get away from the parents, but he wouldn’t have to. And then I’ll be proven correct. So important not to lose your credibility as a futurist.

PETER DIAMANDIS: (02:17:45 – 02:17:56) Yeah, the abundant story here is the poorest people on the planet will be driven around by electric autonomous vehicles. Yes, it will be the cheapest mode of transportation.

SALIM ISMAIL: (02:17:56 – 02:18:10) And think about the elderly, right? And people that can’t get around easily. It’s just the market suddenly becomes so magical, delivering huge capability to segments of the population that can’t do it today. Huge.

PETER DIAMANDIS: (02:18:10 – 02:18:54) Yeah, I’m going to put this image here. I love it, just comparing CyberCab and Waymo. And I have to say, I don’t know how Waymo is going to compete when CyberCab rolls out. First of— well, CyberCab has 8 cameras. Again, Elon made the point that if humans can just drive with 1 or 2 eyes, you should be able to have a car do it with just cameras. Compared to the LiDARs and radars and 13 cameras that Waymo has. And I think the point with the brains on this image is CyberCab is massively AI-driven. Yeah, I could not agree more.

SALIM ISMAIL: (02:18:55 – 02:19:02) It’s going to be a big fight, um, to this. By the way, didn’t Tesla acknowledge that cameras aren’t enough in this?

DR. ALEXANDER WISSNER-GROSS: (02:19:03 – 02:19:35) No, I don’t think so. Tesla does use— for short range, it uses ultrasound, but everyone uses ultrasound. It does not use LiDAR. I think there’s sort of an interesting— maybe speaking prospectively, not financial advice— epitaph insofar as Luminar, the LiDAR provider, declared bankruptcy half a year ago at this point. But if I had to bet— again, not investment advice— I think the market abhors monopolies, and I think there’s probably room for at least a handful of competing approaches.

PETER DIAMANDIS: (02:19:35 – 02:21:29) There will be many of these around competing, which is good, beating themselves up and lowering the price across the board, and we all win. Yeah, I introduced Austin Russell, the CEO of Luminar before it went out of business, to Elon at a party. And I watched them duke it out on whether LiDAR was important. Anyway, it was a fun show. And Elon was like, no way, not interested, not going to go there. All right, our final story, it’s a little bit of a bizarre one but expected, in the direction in the world of robotics. A company called Somnia Lab has built a robot for intimacy, and the internet has lost its mind. It’s called Model L, maybe L for love. It’s 5 foot 9 inches, 44 pound robot with 24 degrees of freedom, with warmth simulation, touch response, and preference memory designed for human-robot sexual encounters. Okay, it’s finally here, guys. So real humans wear motion capture suits— I’m going to show you a video of that in a moment— to record 165 intimate actions that were fed into the model. Somnia Lab is taking $300 deposits for delivery in late 2027. What makes the Model L more interesting than a sophisticated sex doll is the attempt to combine physical embodiment, persistent AI memory, and personalization. Somnia says the robot is intended to remember conversations and preferences across encounters, learn a user’s rhythms— you can’t make this stuff up— and communication style. The body is made from lightweight carbon fiber with modular skin and structural components designed to be serviced and upgraded. Customers will be able to customize the face, the makeup, the eyes, the skin appearance, and the body silhouette. So I guess this is a story around abundance of intimacy. Let’s take a look at this.

DR. ALEXANDER WISSNER-GROSS: (02:21:29 – 02:21:35) This was inevitable, Peter. I’m waiting for you to say fully functional, programmed in multiple techniques?

PETER DIAMANDIS: (02:21:35 – 02:21:37) No, I’m not going to go there.

SALIM ISMAIL: (02:21:37 – 02:21:37) Not yet.

PETER DIAMANDIS: (02:21:38 – 02:21:53) Let’s watch this video. This is a video of the motion capture being done to train the AI models here, with cheesy music to boot.

DR. ALEXANDER WISSNER-GROSS: (02:21:53 – 02:21:55) We’ve hit it. We’ve hit a new high here.

SALIM ISMAIL: (02:21:56 – 02:21:56) This is incredible.

DR. ALEXANDER WISSNER-GROSS: (02:21:59 – 02:22:07) One has to admire the low degree of freedom. Like, that was a pretty simple face space, I think, we were seeing. Oh my God, that was a human in a mocap suit, right?

PETER DIAMANDIS: (02:22:07 – 02:22:08) It was, it was.

DAVE BLUNDIN: (02:22:08 – 02:22:12) That was low quality in every way, from the music to the video to everything.

PETER DIAMANDIS: (02:22:12 – 02:22:24) A robot porn video. Oh my God. You combine this with the conversation we had earlier about AI girlfriends and boyfriends, right? And the human relationship is cooked.

DR. ALEXANDER WISSNER-GROSS: (02:22:25 – 02:22:35) You think? I go back and forth. Is there going to be an app store for mocapped movements, or is this just going to be pre-training or post-training data for a foundation model that knows about everything?

PETER DIAMANDIS: (02:22:35 – 02:22:37) I want to see the job ad for that one.

SALIM ISMAIL: (02:22:38 – 02:22:54) I have a couple of comments on this one, please. So the first thing is, this type of embodied AI has really a pretty difficult data problem, right? Because you can scrape the internet for text. There’s no internet-scale dataset of physical human interaction.

DR. ALEXANDER WISSNER-GROSS: (02:22:54 – 02:22:55) What are you talking about?

DAVE BLUNDIN: (02:22:55 – 02:22:57) What internet are you looking at, buddy?

SALIM ISMAIL: (02:22:57 – 02:23:26) Hold on, hold on. In terms of the physical movement, etc. So the, what I love more than anything here is the economic approach, right? You crowdsource— you do crowdfunding of the early thing, get early customers, and then use the customer demand to finance the hardware and generate the interaction data as you scale the product. This is like a pretty classic ExO flywheel. So I thought that was really interesting.

DR. ALEXANDER WISSNER-GROSS: (02:23:26 – 02:24:03) Now I’ll give a hot take on the hot sheets, which is I don’t actually think this is that promising as an approach. There’s an abundance of evidence at this point that you can do a great job either pre-training or post-training robots for more, call them economically productive applications, just from watching videos without any need for human mocap at all. So if I had to guess, my guess is this is like a very 2026 story with people mocapping sex maneuvers manually, but it doesn’t scale nearly as well as just pre-training off of internet video is my guess.

PETER DIAMANDIS: (02:24:03 – 02:24:11) Okay, circle of trust here. How many have you ordered, guys? I won’t tell anybody.

DAVE BLUNDIN: (02:24:11 – 02:24:16) Oh my God, we need guests and panelists that are in their 20s for that. Oh my God.

SALIM ISMAIL: (02:24:17 – 02:24:17) That are good.

PETER DIAMANDIS: (02:24:17 – 02:24:19) Dave, any closing thoughts on this topic?

DAVE BLUNDIN: (02:24:20 – 02:24:24) None whatsoever, actually, as it turns out. First time in my life. Nothing to add.

SALIM ISMAIL: (02:24:24 – 02:24:25) Sorry, speechless.

Closing

PETER DIAMANDIS: (02:24:25 – 02:26:19) Oh my God. All right, everybody, I want to say that’s a wrap, but we do have a closing video. If you have outro music videos, please send them to media@diamandis.com. We love sharing them. We love the creativity of our community. And we’ll see you guys in 4 weeks to the day, yes, at Moonshots Live in LA, the evening of September 24th and all day on September 25th. You can go to moonshots.com to apply. It is by application, and it’s going to be an amazing community for you to network with and spend the day with all 5 of us. The Moonshots quintet will be there. You get a chance to grill Alex, Salim, and of course, Dave. It’s going to be awesome. All right, let’s play this video by Ellen Vaman. Thank you, Ellen, for your submission. Nice heroic music, gentlemen.

DR. ALEXANDER WISSNER-GROSS: (02:26:22 – 02:26:25) Lord of the Rings and space mashup I never knew I wanted.

PETER DIAMANDIS: (02:26:27 – 02:26:40) Oh, that was fun, guys. Really loved it. A lot of fascinating stories, and definitely one bizarre one. Until we see you again twice next week for another episode recording, be well. Can’t wait.

SALIM ISMAIL: (02:26:40 – 02:26:43) We’ll try and sleep in the middle. God help us all.

PETER DIAMANDIS: (02:26:43 – 02:26:44) Live long and prosper, as they say.

DAVE BLUNDIN: (02:26:44 – 02:26:45) Likewise.

SALIM ISMAIL: (02:26:46 – 02:26:47) All right, take care, folks.

Related Posts

• Transcript: Tucker and Saagar Enjeti on America’s Fastest-Growing Addictions – Tucker Carlson Show
• Transcript: The Historians Who’ve Had Enough of Woke History – Nigel Biggar and Robert Tombs
• Tucker Carlson Interviews Missouri Farmer Joe Maxwell (Transcript)
• Transcript: David Friedberg Interview on Diary Of A CEO Podcast
• Transcript: Mehdi Unfiltered Interview with Pastor Douglas Wilson