We are going to become limited by power in our quest for digital super intelligence. This is a structural issue we have in the US. This is America's Achilles heel. China is going all in on energy production, and it's epic. Meta is, you know, worth $1.8 trillion today. They got $70 billion in cash. These offers of $100 million, or their acquisition offers on companies—it really is a winner-take-all mindset in this.

The natural dynamic is winner takes all because the AI becomes self-improving very, very soon. The biggest threat to Meta is that they fall way behind on AI. We're in the middle of probably the greatest drama in human history here, which is why everyone should be tracking these moves closely. These numbers are so unprecedented, but they're completely justifiable given the impact. Now that's a moonshot.

Ladies and gentlemen, welcome to an episode of WTF on moonshots. I'm here with my moonshot mates, Salem Ismael. Uh, Sem, I'm calling you the emperor of exponentials, cuz that's just who you are. And Dave London, the alchemist of AI. How's that for a title? We need one for you, Peter. All right, Peter, you have to be something epic. How about the humongous bungalongus of abundance? Uh, not sure I like that. I like what Dean came and said on stage. He called me the hope. The pope was hope. That's awesome. Yeah, my mom liked that. She's watching all of my abundance, you know, abundance videos and the whole show on stage, and she writes back, she goes, "Pope of hope." I love that. Thank Dean for me.

All right. We have a lot to cover today, and as always, uh, our goal here is to deliver you the real news—you know, the news that's going to impact you, the news that's changing every industry, every family, every country right here, right now. So rather than watching the 6:00 news, join us on this epic mission. Deliver, you know, a compelling, you know, hopeful and abundant future. All right, buddy. Buddies, let's jump in.

So, let's talk about all things AI. Another epic week. Uh, every week is just accelerating. It feels that way. Uh, let's kick it off with uh this conversation. Uh, this is from Elon, and I'll just read his tweet. Uh, he says basically, "We will use Grok 3.5. Maybe we should be calling it Grock 4, which has advanced reasoning to rewrite the entire corpus of human knowledge, adding missing information and deleting errors and then retraining on that new corpus." So uh, first of all, we've got this like name escalation, right? So, we're going to, you know, GPT-5 and then Gemini 2.5 through soon Gemini 3. I think Elon feels behind on Grock 3.5, numerical warfare.

Yeah. Dave, what do you think about this idea of retraining Grock 3.5 on a new corpus corrected by AI and getting rid of human errors?

Yeah, that that specific idea is actually low-hanging fruit and and a real big win, but it's it's one of many big wins. I mean, the rate of change of what we've seen in the models in the last two weeks since last time we talked is just mindboggling. And you know, an experience everyone needs to have is if you if you pick up either a Gemini 2.5 Pro or uh GPT-4 voice mode and just talk to it as you're driving in a car for like an hour or two hours. That's something you couldn't do a month ago. And now you can do it, and it's engaging. And if you if you draw a line between a month ago and today and you look a month into the future, it's going to replace a lot of what you do in terms of media. It's just so incredibly engaging all of a sudden. So I think what what Elon's talking about here is, look, the training data, you know, believe it or not, the actual original training data for these models had a Reddit subreddit in it that's called microwave. And the microwave subreddit has a series of M's, just goes for thousands and thousands of lines, and then at the end it goes beep. So that gets scraped and gets thrown into the training data. A lot of crap. Like, okay, there's a lot of crap. And I think, you know, Elon might actually be referring to a lot of his own tweets with with Donald Trump here. Like, okay, well, if we get rid of that crap, then the neural net has a much easier time learning what really matters. So uh, this is this is part of a long list of low-hanging fruit uh that's right in front of these training algorithms. So you're going to see really rapid improvement just from the obvious, including including this.

See what could possibly go wrong if AI rewrites the corpus of human knowledge? You know, I've been watching a few videos of uh Yuval Harrari talk about, oh my god, AI can now program itself and program things, and he's going to go nuts on this type of concept where if you can edit history, right, where do you end up? Where do you draw the line? How who decides what's accurate or not?

In the beginning, there was AI. Exactly. Exactly. God said, "Let there be AI?" And then everything followed from there. Right. um, this this really has will pose some huge philosophical challenges. Now on the plus side, there's there are so many gaps. There's so many flawed narratives where history is written by the winners of all the epic battles and wars in the in the past, and therefore we can balance out that viewpoint a little bit and get a little bit more reality into it. That'd be great. But there's a very dangerous line here, and and I think it's the right thing to do. It's going to cause a lot of consternation.

Yeah. So, we're expecting Grock 3.5 any day now. Uh, you know, it was promised in May, then delayed into early June, what is today? We're recording this on June 26th. So, uh, he said by the end of June. He's got 4 days left. But even if it's July, it's going to be epic. Can't wait to try and play with it.

All right. Um, I'm going to play this video also from Elon. And, uh, the subtext here is, "Super intelligence may happen this year or by the end of next year." All right, let's listen.

I think we're quite close to digital super intelligence. It may happen this year. If it doesn't happen this year, next year for sure. The digital super intelligence defined as smarter than any human at anything.

So here we've got the issue of definition, right? What is AGI? What is digital super intelligence? Dave, you and I recorded an episode; we'll be sharing shortly with Eric Schmidt uh going deep into digital super intelligence. His prediction is uh a little bit more, you know, I would say pessimistic, but you know, it's the next 5 years on his timeframe, but what is it, you know, do you still have the confusion that I do when people are popping back and forth between AGI and ASI?

Yeah, that because no one's really locked down a clear definition, but I think Elon gave a very, very clear definition in that presentation just for that reason: AI that can do anything better—any intellectual task better than any human. That's the hardcore definition. And he's saying by the end of next year, which is, you know, the soonest date that people are saying, but he's very close to the uh to the progress. So, you know, he has every reason to be right.

Yeah. No, I would not doubt his timeline. I actually went on to ChatGPT and Grock and asked them both for a definition of AGI versus ASI. Can I share that with you guys?

Mhm.

So, so ChatGPT says AGI is a machine capable of understanding, learning, and performing any intellectual task that a human can do across domains with reasoning, adaptability, and autonomy. And then it says ASI—this is ChatGPT—is an intelligence far surpassing the best human in every field, creating uh with creativity, problem solving, decision-making. Grok says AGI is an AI capable of performing any intellectual task that a human can do with general problem solving, and ASI is AI surpassing human intelligence in all intellectual tasks. Even these definitions sort of blur the line, you know, but I go I I go on my classic hobby horse here because we have no idea what we're talking about when we talk about intelligence. Um, and so I don't need to get into that trope again, but but let me suggest this, right? The minute you can prescriptively, if you want to define a something like this, you have to define what you mean by it. And the minute you can prescriptively describe a task, an AI or robot's going to be much better than you anyway. So the work that then comes down to what what's the task prescriptively saying that and it be smarter than any human being. That's a different kind of a model. Here's where I'd like to see it do. You know, you have Kepler uh couple hundred years ago one day making an intuitive leap that maybe the moon is affecting the tides and makes a massive intuitive leap that then can be backed up with scientific and experimental evidence. That's the kind of thing that if if AIs can do then so you start tickling at the edges of what we mean by intelligence because we have emotional intelligence, we have spiritual intelligence, etc. There's the end of my rant.

Well, and I think that's going to happen. I mean, one of the predictions is we're going to start to see math, physics, chemistry, biology getting solved by uh these advanced AI models in the next two to five years. I mean, this is what our friend Alex Wezener Gross keeps on hitting on—we're going to solve math in the next 12 months.

Yeah. I think it's important to stay out of the philosophical debate if you want to succeed with AI and focus on the capabilities within swim lanes. And because the reason Elon Musk is saying, look guys, I'm talking about AI that can do literally any human intellectual task better than any human. He's just trying to create awareness and motion because people are underreacting so badly in so many areas. But I think as Alex Wisner Gross is saying, it gets miles ahead in areas like math and and code writing where it's not data constrained and it lags behind in areas like biology where it needs the full cell simulator to make forward progress. And so the rate of progress is going to be hugely different in these different swim lanes. The exact date when it can do any intellectual task versus any other human is going to be like a blur that comes and goes and you know whether somebody was right down to the minute or not. Nobody will care a year later, but we'll care a lot about the the impact on society and all these different use cases. So, I think going down that path of saying here's a vector or swim lane, that's a really good way of framing it. Uh, but when you throw out general words like AGI or ASI or whatever, that's when I go a little bit nuts. But the swim lane thing, I can totally vibe with that.

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All right. Um, I love this video. I asked the team to cut it. This is from Jeff Cloon, who's a DeepMind advisor. Uh, the title here is "The first AI may be—I mean the first ASI may be the last ASI." So take a listen to this.

It is a world in which the first AI is the last AI, and the creation of the first ASI suppresses the creation of ASI worldwide. Then that organization—whoever they are—has a decision to make, and that decision is we just invented—effectively—if that thing is aligned to them and will obey their commands. We just in effectively invented a god. Do we want to sit around and let those people over there also invent a god? That nobody talks about as much as they probably should is how quickly things might get nationalized. If you are the the premier or prime minister or head of state of a country and somebody—a company within your borders—creates a super weapon, a superpower, effectively a god, do you nationalize that? Do you start giving them orders? Do you make them run everything by you? Are you going to let them just like run as a normal company? Like, I that seems very unlikely to me.

So just wow, right? I mean, I can very much imagine that. In fact, I just read a book with my son Jeff um called *After On*. Actually, second time I've read it, and it tells a Silicon Valley story of the first ASI coming online and it is basically taken over by the government and it is basically the last ASI cuz it suppresses other AIs around the world. It's a great story.

Dave, what do you think about that?

Yeah, well, hey Same, we have our side bet, and this really weighs in my favor. Look, the the natural dynamic here is winner take all. And you're going to see later in this podcast the amount of competitive pressure on these, you know, foundation model companies to get the best talent, the amount they're willing to pay is mind-blowing. Well, why is that? Well, because the natural dynamic is winner takes all because the AI becomes self-improving very, very soon. So, uh, the the observation in that video is right on target. And the only force that's going to, you know, in our first slide here, we're saying, look, if if the data that goes into these is one view, one point of view, and it's self-fixing, but it will filters out other points of view, that could be terrible. And so the only way you're going to have a variety of these, and you know, America thrives on a variety of competitors in any given market, a variety of viewpoints, that that has to come through some kind of regulatory framework. It's not going to happen with the natural winner-take-all dynamic. So, this is a this is a great wake-up call video, and I completely agree. Salem, winner take all.

Um, I think the I'm not sure about the winner take all. I'll go with I'll stay with my bet on that one. So, Dave and I will continue. I It'd be great to have a Polymarket on this, by the way. Let's do it. But but the the idea that when something like this emerges that it might get nationalized is 100% true. There's no way that's not going to happen. While these—and I think this is what the governments are doing right now. They're just watching their various uh folks work on stuff and they're going to jump uh down their throats the minute something like—nationalization may take a different flavor. It may be the government buying a significant share. Um, we're going to we're going to talk about what the government's doing in AI in—I don't think it's going to be like that. I think it'll be just like, "I'm sorry, we own that. It's a military potential." Boom. And and you're you're you're you've lost uh kind of—

Yeah.

Well, I think that's going to happen, and I wouldn't—from what I've seen with governments, there's no way they're not going to do that. They almost have to do it in order to uh prevent other people from getting there or if they think they're getting there first. The bigger picture might be where—what if you have a particular worldview uh can you—what do you do with that when you have ASI? Because I have a view—I have a feeling that ASI is going to strip past the limitations of a particular worldview very quickly. And so then what do you do?

Right. Yeah.

All right. Well, let's let's—I have the next—the next—let me let me just build on that for a second. Here's what I think will happen. U some ASI—call whatever we want to call that—will emerge. A national government um uh call it Kazakhstan will kind of go, "We need to own that. Okay. This is our worldview. ASI, please operate on this worldview, and then let's get everybody else to align with this worldview." Um uh and the AI in about three seconds is going to go, "Their worldview is so limited, right, that this doesn't help at all," and it skips right past all of that. I don't think once—I think once you have ASI, it's outside the potential for control for anybody for sure, and it maybe this is like the modality of religions taking over and setting a worldview around the world. Yes, you have to relate to it in that way, except that religions are, you know, they're based on absolute unverifiable truths or assumptive truths. Uh, like Mary was a virgin or Muhammad was the last prophet or Jesus or the son of God or whatever. And an AI—any kind of AI half its worth—would skip past that assumptive truth in instantly and go, "There's no evidentiary basis for that." I don't think I don't think there's much of any chance that the US is going to nationalize a single AI company and say, "This is our national AI." I think that if you look at the way the defense department works, you know, some things like uranium and plutonium refinement are nationalized, but you know, all the missiles, inertial guidance, defense systems, those are all private sector companies that that work for the government. That's that's going to be the likely outcome in AI as well in the US, maybe not in China, maybe not in the Middle East, but certainly in the US.

Well, we're going to find out in the next few years. I think that's the the key point here. By the end of next year, clearly. By the way, Jeff looks more like an AI in that than anything—any video I've seen in a long time.

All right, this next story is one I want to dive into. Uh, it the title here is "Meta try uh to buy Ilya Sutskever's $32 billion AI startup and now planning to hire its CEO." We'll get into this in a moment, but I just want to I want to pass a theory by you. So, how does Ilya get a $32 billion valuation? Right. So he's basically goes out, he pitches Andre Horowitz—his investors are Andre Horowitz, Sequoia, DST Global, which is Yuri Milner, Alphabet, Nvidia, Lightspeed Ventures. I mean, like the AAA list of investors, and he raises uh what was it? $6 billion of capital on a $32 billion valuation. How do you do that without any product uh or any tech to show? And I have a theory. Here's my theory. You ready?

Okay.

Yeah.

Yeah. We just saw the presentation on the first ASI, his last ASI. He goes in and he says to these venture funds, "Listen, I know how to build an ASI that will blow away the other other AI companies. It will be a safe ASI cuz here's my strategy. And because it's the first, it will be the last." You believe him, and as a venture fund, you have no other choice than to invest in that company at whatever valuation he offers you—he offers it to you.

How do you think about that?

Uh, I think that's exactly right, and I think there's another another point which is that clearly the true great neural architect people—the Ilias, the Miro Maradis—are not intimidated by the progress that's been made at OpenAI, Grock, and Google.

Mhm.

And that's an amazing fact by itself. And when you look under the covers, the research teams working on this are 10, 15 people. They're not 10,000 people. uh, and the innovations are still piling up, you know, where there are still 10x improvements out there. And so, undoubtedly, Ilya, having been an architect right in the middle of this, is saying, "Look, I know how to 10x this." Uh, and and I'm not afraid of the big guys. And and actually, the actions at OpenAI are are kind of reinforcing that. OpenAI is racing to control the consumer experience with, you know, buying windsurf, you know, for coding and having the the voice mode and trying to get everyone—they're trying to be like Google and have a huge user base installed, and they're succeeding by the way—and succeeding wildly. Yeah. um, because you know, just competing as a foundation model is not is not necessarily defensible, and so it's not just Ilya—it's Mir and then also some other things bubbling up out of MIT that are getting huge valuations because they're very likely to work, and and so I think that's the other kind of—

Underpinninging this, we're in the middle of probably the greatest drama in human history. Here's why everyone should be tracking these moves closely: these numbers are so unprecedented, so much bigger than anything in history, but they're completely justifiable given the impact. And so more people should be getting involved and reacting and contributing, and you know, not being intimidated, because Mirror is not intimidated, Ilya's not intimidated, and the investors coming in to invest in Ilya are not intimidated. Billion dollars a day.

Sim, do you remember the meme that came out when Ilya left OpenAI, or you know, staged the revolt? It was like, what did I see? Do you remember that? And now I want to know, is "What did I pitch?" the new meme? What do you think about this $32 billion valuation? Did you know, does he have an ASI in the bag and he's racing out in front? I think this conversation kind of nails it, right? If you're in front of investors, they don't know. They're kind of trusting you to know, and the fact that they kind of have a confidence-based approach to saying we can beat the other models is huge. And I think Dave's assessment is right. OpenAI is now focused on how do you get to the biggest consumer share in this, and they will go after those other white spaces that are there, and there's a lot of white space. So applying this in all sorts of areas becomes hugely important. But my big question for this is: how do you do this safely? That's my question, and I'd love to understand what did he say to investors that gave them the sense that this could be done safely, because that's the foundation of his approach, right? We're going to make AGI that's safe. I'm curious how he's going about that. Yeah, all right.

The other side of the story here is that Meta is trying to buy talent left, right, and center. Let's take a listen to this video. All right. OpenAI CEO Sam Altman has some strong words for Mark Zuckerberg on a new podcast, criticizing Meta's recruitment methods and even its level of innovation. Dear Droposa with more, it's cutthroat out there. Brian, you're right. Yes. I mean, critical words may be an understatement. So, Sam Altman, on his brother's podcast, he says that Zuckerberg is offering $100 million sign-on bonuses to poach top OpenAI talent. Keep in mind those kind of bonuses, they don't have cliffs. They don't vest over a number of years. $100 million just to get on board. Nothing stopping talent from leaving in what is already a revolving door of talent in AI. Uh, See, did you get an offer of $100 million from Zuckerberg yet? No, but can I please be an intern at one of those companies and maybe I'll get a $20 million signing bonus? It's insane, right? So, so here are the numbers, just to put this in context. Meta is worth $1.8 trillion today; they've got $70 billion in cash. So if you think of it that way, these offers of $100 million, or their acquisition offers on companies—'cause Meta tried to buy SSI first—it makes sense. I mean, the biggest threat to Meta is that they fall way behind on AI. Dave, what's your calculus here?

Yeah, there's so much. Um, well, first of all, I don't believe for a minute that it's $100 million to join, no vesting, no retail. You can't just join and quit the next day. There's no way that's true. I don't know where that fact came from, but um, but look, these numbers again, you see professional athletes getting numbers like this, but other than that, it's unprecedented in human history. But it's hugely justified if you get one of the key research talents at this inflection moment in the competition toward ASI. So it does make a lot of sense. I don't know if the choices of who to go after are necessarily right. You know, we heard on our tour through San Francisco two weeks ago, Peter, that the Llama 4 really does suck. And it's kind of embarrassing. And I know Mark tried to save it with a podcast world tour there, but but look, if it sucks, it sucks. Doesn't mean that they can't catch up in a heartbeat, though, because you know, a couple tweaks in the algorithm and suddenly you're back on top. And so you get the right people who know exactly how to try the next experiment the next week. And it's worth a lot more than $100 million. It's worth many billions, if not a trillion. And so I think that's the bet that they're making. And this isn't the only one. There's a lot more of these going on. Yeah. So there's a $70 billion war chest, and it's really a winner-take-all mindset in this. They're willing to do whatever it takes to move forward. Here's a—

Yeah. Can I game this out a little bit? Yeah. So if we go back to the previous conversation, I think what Ilya has figured out is how do you use AI to tweak itself, and that then gives you a very, very fast iteration path to what you're trying to do. And if the investors believe something like that, then they go, "Wow, if he's figured that out, then nothing will stop that from being the winner." I think you're right about that. Um, now regarding this particular thing, you know, we when WhatsApp was bought for what, $18 billion, everybody laughed at Zuckerberg, right? And thought this is nuts, this is unprecedented, etc., etc., but it was actually a hugely important and relevant bet. So given the past success in throwing money at this and going after it, you can see that he can see the market is that big, and this is pennies in the bucket, pennies in the dollar in terms of the potential outcome. Yeah, I would never bet against Mark for exactly the reason you just said. He can act unilaterally and quickly, and he's aggressive, and he's super, super smart. And so what is interesting, though, is the other thing we learned on our tour through San Francisco two weeks ago is there is a mass exodus of AI talent out of Meta. So then Sam saying, "Hey, they're trying to buy everybody back for $100 million bucks," like, well, dude, you just took everybody, so you know, it's fair game. But the question I have is: why were they leaving in the first place? And why did Llama 4 not come out the way they wanted it? And so we'll dig in on that. I'll try and try and get to the bottom of exactly what's going on there. But the tide is—throwing money at it is one way to turn the tide, and it will. So you know the story here again: Meta tried to buy SSI. They were rebuffed, and now they're trying to hire Daniel Gross, who's the CEO of SSI, and Nat Friedman, who's been on our, you know, stage at Abundance 360. Again, he's out shopping, and he just made an acquisition. He hit the Neiman Marcus store for AI, and he basically bought our friends at Scale AI. Alexander Wang also was on stage with me a couple years ago at A360. $14.8 billion for 49% of a non-voting stake in Scale AI.

Dave, you know, the IPO markets are just beginning to open in the tech and AI space. The acquisition markets are getting hot. You're deploying Link XPV's venture fund and companies out of MIT and Harvard. How are you seeing, sort of, the acceleration, because it's been a relatively closed IPO and acquisition market over the last, you know, five years? Does it feel like it's opening up now? I'd say as of last month, it's wide open. Yeah. I mean, these deals are unprecedented, huge deals. The core IPO is way up. Circle is way up because it's the way that agents can transact with each other. Um, so yeah, the Yahoo moment clearly happened. The door is wide open, and the deals are still concentrated among, you know, the top, the Magnificent 7, but you know, Jamie Diamond sees that, Bank of America, everybody else sees that. So their banking teams are spooling up. Everyone's getting ready. It's going to be just like 1997-98 all over again. That would be great, much bigger. So also, you know, a couple—I don't know if people care, but the structure of the deal is really important. And I know a lot about the topic. If you can cut it out of the podcast if people don't care, but this is the deal structure of the future. The 49% acquisition dodges Hart-Scott-Rodino. So the deal is closed the day you sign it. You don't have to go through the six-month torture waiting cycle of DOJ review, and it does skirt the edge of the rules. But the rules are bright line. So, and there are two parts to it. 49% is not a controlling stake, so you don't have to report. The other part is it's a non-voting stake. There's another threshold of 19.9% or 20% ownership, that's right, where you have to consolidate financials, but because it's a non-voting stake, you dodge that rule as well. So you're like, well, okay, but do I really own the company? Well, then you look at the contractual structure, which isn't disclosed. You know, there's no public disclosure of the underlying agreement. And that agreement probably says we own all the intellectual property, and you know, if you don't work your ass off, you have to come clean windows at Mark's house, and you know, a whole bunch of things like that that really effectively make you own the company. And I also know that the investors in Scale are distributing the capital. So it's not disappearing into the corporation; it's going to the shareholders and getting distributed to the investors in the company. So it's truly an acquisition.

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So, Salem, I'm curious. You know, you and I both have spent time with Yan LeCun, who previously was heading AI at Meta, and now Alexander Wang comes in. Alexander, I guess, Dave, he was a freshman at MIT, dropped out after his freshman year to start Scale AI, becomes a—Was he the youngest billionaire out of MIT? Oh, yeah. Yeah. Yeah. By far. And now he's going to—I wonder if Yan is going to stay on at Meta. So any thoughts there, Sel? I think, well, clearly there's a changing of the guard there, and whatever they feel they're deficient in, they're trying to leapfrog, and they're doing it very, very aggressively. Something that I love about Scale AI is it's really attacking the heart of the problem, which is tagging of data, and if you have that, you can solve the garbage-in, garbage-out problem in a really powerful way, and then it means you can use much better models—the models you use become much—you can use lesser models because you have much better data. Yeah, I think Yan LeCun, just to bring it back to that, and he's a super brilliant, sweetheart guy at the center of this all, but he's had a much more conservative point of view on AGI and ASI. It's the same with Jeff Hinton. Yan is kind of in that camp of being—everybody needs to slow down and be really, really careful of what they're trying—what we're about to unlock here. Yeah, I think Mark, right? Yeah, Mark is an engineer at heart. All these guys are engineers at heart. They're not trying to buy an AI philosopher. They're not trying to buy—you know, a lot of the people that are the senior AI leaders from the big labs are saying, look, there's something fundamentally missing from these transformers. They're not actually reasoning; they're just brute-forcing their way to intelligence. They don't want to buy that. What they want to buy is, I know how to make this algorithm work on a million concurrent GPUs. I know how to change the algorithm so that it stays synchronous across all this massive amount of compute. I know how to actually deploy the transfer—al—you know, algorithms that the swiggloo isn't working. We need to go back to ReLU—like stuff like that—that's in the minds of these mid-20-year-old geniuses. That's what they want to buy. And so what's interesting to me is normally the older, you know, kind of highly successful, you know, Eric Schmidt have all the money, and the young people have all the brainpower, but here the young people have the brainpower and now they suddenly have a lot of money, too. So that's a new thing in the world as well. So it'll be—

Well, speaking about brainpower and money, Masayoshi Son, one of the old-guard investors, has pitched a trillion dollars. He wants to replicate Shenzhen scale within the US. Let's take a listen to this video talking about $1 trillion worth of investment out of SoftBank. Put that into context for us. A trillion dollars, and he wants to recreate a kind of Shenzhen in the US, potentially alongside TSMC, of course, the foundry, and of course Samsung as well. You would imagine that OpenAI would have a piece to play, as would ARM as well, that is moving closer into data centers in terms of their CPUs aligning with AI accelerators. So it hits that and it ticks that box in terms of Trump's ambitions. But we do need to find out where the capital is coming from, where the spending is coming from, and whether indeed they can get the talent and the engineers not just to build all these projects but actually to operate them as well, which has been a constraint and a bottleneck in the US. So have either of you guys been to Shenzhen?

I've been there a few times. Oh, really? Selena years ago. Yeah. I mean, it's changed in the last five years. I mean, I was there between, you know, 2014 and 2019, and it was an incredible hotbed. I mean, it was an engine of innovation. The old—the mindset there was 996 was the best lifestyle you could have: 9:00 a.m. to 9:00 p.m., six days a week. And you know, people talk about trying to replicate stuff. There was a lot of entrepreneurs creating varying new ideas out of there. But it was basically a convergent mecca for technology, and the idea that Masayoshi Son wants to rebuild that here in the US, I find that fascinating. Thoughts? Yeah, I think part of that vision doesn't align. You know, when we were at OpenAI, one of the questions I was asking D. Scully is, you know, the talent pool, the computer science talent pool in Boston is about 20 times bigger than in Silicon Valley, and it's also not nearly as picked over. Why doesn't OpenAI open an office in Kendall Square, just like Google did and Microsoft did? And the answer is, yeah, we would do that, except the timeline to AGI is so short that we're going to have a multi-billion-dollar or multi-billion-person AI workforce before we could even finish the building and populate it. You're like, "Okay, that's that's a pretty interesting insight." Wow. Blows my mind. Yeah. So then you're like, "Okay, well, Shenzhen, that's a huge number of people, buildings, uh, you know, but is that timeline going to line up with the Elon Musk video that we saw a minute ago?" So, you know, I think the constraints here are electrical power and chips and not so much building a huge city that's all working on—on the 60s, buddy. Digitize, dematerialize, democratize, demonetize, you know, and disrupt. Yeah.

And here's—this is a chart near and dear to your heart, Dave. Cursor, the fastest SaaS growth in history, $500 million of ARR in under three years, blowing away Anthropic and Uber and OpenAI. Talk to me about this. Well, this is so inspiring for the teams in the office at Link Studio. So you know, Link Studio now, we have 26 teams—MIT, Harvard, Northeastern—and this team—these are these are startup companies that are being incubated at Links. Yeah, I mean, they're exactly—and they're culturally just like Cursor, you know, like three, four, five best friends from school. Brilliant, but never operated a company before, building something with AGI or AI that's groundbreaking. And so they see a company like this thriving and hitting a huge valuation. But also, you know, back when this happened in the internet era, you got huge valuations, but the companies were very fragile because they didn't have a huge amount of revenue. These companies, $500 million of revenue. The margins on that must be astronomical. And so they're raising a lot of money at a big valuation, you know, greater than $10 billion-ish, but they can actually operate profitably, you know, on one day's notice if they want to because they're not headcount intensive. So these are like the best companies financially that we've ever seen in history. And then the timelines are just laughable. Like two years to get to $500 million of revenue. How many Cursors are out there in the next couple years? Dozens. Dozens. It's actually constrained by the number of teams, not by the number of opportunities. So it's fascinating, right? We got constraints on electricity, on chips, and on the smartest entrepreneurs who take this forward—for at least for the moment. It's humans that are constraining.

Well, I mean, the difference in the vibe around Boston versus anytime I've ever seen is just so blatantly obvious and palpable. You just need to walk around. But everywhere you go, everyone's like, you know, just talking about Scale AI, talking about Cursor. These are these are, you know, their fellow alumni that they actually knew. Yeah. And so, you know, the jealousy factor is a great motivator. It's really an amazing time. See, and these are all exponential organizations, all EXOs; they have an MTP. They're using community effectively; they're building developer communities; the engagement levels are really great. They've gamified, in many cases, what they're trying to do. It's phenomenal to watch. We predicted this in the book, right? We said we're going to have just an continuing increase in the velocity and scale and speed. I mean, this is surprising even to us at some level because the speed of—I mean, $500 million ARR in this time scale is just unbelievable. I do agree with Dave. There's a lot more coming down the pike on this, and these curves are just going to get more and more vertical. The teams is a really intriguing problem. How do you find the right teams? And I'm wondering if you could use an AI solution to find teams that can then be put together and thrown together for this. That would be a really interesting problem. Dave, can you do that? I mean, you know, one of your billion-dollar—one of our billion-dollar investments is Merkore, that is all about, you know, finding and hiring, but is that for the general employee ver—I mean, what are the attributes of the founding team that you're looking for?

Yeah. Great question, and you know, we study that all the time. We quote the Fred Wilson rule a lot. We call it the Fred Wilson rule. Fred didn't call it; he's the Union Square Ventures founder, MIT alum, most successful venture capitalist of all time numerically. Keeps a low profile, so we don't talk about him every day, but Fred Wilson is really a god of the industry. But what he says, you know, as he gets older is, I always invest in teams of three or more best friends who write the code themselves, meaning they're technical. They're really technical, all three of them or more, and I trust them. And if they pass those three filters, I invest even if it's the stupidest idea in the world, because because they'll change the idea much more quickly. You can't change friendships, you can't change relationships, you can't change yourself overnight, but you can change your idea overnight. And once you get them into an ecosystem of other people that have great ideas, you know, take them out to Silicon Valley, introduce them—

To Eric Bolson, take them to HAI, take them over to OpenAI headquarters, run them through Google. You know, we're doing all that with these teams now. Then they come back home and they're they're enlightened, and they always have good ideas at the end of that road trip.

Let me hit on one of the points there. I mean, people say, why should they be best friends? Why should they be around? You know, having had a relationship for a number of years, you just saw uh these large companies like Meta and Google and OpenAI are just raiding companies and stripping out the talent. And if you've started a company uh with some stranger that you don't know, and it's been six months, and someone gives you a huge signing bonus, you're going to leave. But if you've started a company with your best friends and you've got a long history, you're not going to abandon them. I think that's exactly right, that that's the number one failure mode actually for for companies, is that uh somebody fails because you'll always succeed in the end if you stick with it. Uh, and so you're ex- the way you characterize this pivot. Exactly right. A dozen times, and you'll look, you know, name any one of these companies that didn't pivot at least once. You know, going back to PayPal and every one of them, you know, pivots at least once. And so that's just part of the journey. But when you pivot and then someone says, "Oh, I give up. I'm leaving," That's what that's what ends up killing the company.

So also, the way I've been phrasing it for many, many years uh is more true than ever before. Imagine that you're on an international flight and you're sitting right next to somebody in a middle seat. The way you feel when you get off that flight, that's the way it's going to feel when you're doing a startup together. So, you know, if it's you and me and See flying, we're going to come off that plane energized because we've been talking about everything in the world for hours, like, you know, eight, ten, twelve hours. Not only that, we'll have infected the three rows around us to all get into a conversation.

Yeah. Walk out with more employees than you started with.

Yeah. Yeah. You know, Selma, when we had Singularity University's uh uh graduate studies program, the GSP going, and we were starting companies that had a 10 to the 9th plus mission, right? Impact a billion people over a decade. Uh, and we were starting companies. It was around the same exact time frame uh that Y Combinator was getting going. And the failure mode I think was that we thrust, you know, a hundred uh you know, alpha males and females into a room independent of each other and said, "Start a company," and that was very different than Y Combinator where teams came in with an idea already and that glue pre-existing with something that they're all passionate about. I think is uh is a super differentiator for for investments, and if you look at the track record, the ones that did succeed were the ones that became friends uh and stuck together over time. The one thing we did do was created lasting friendships that were lifetime long. Uh, and so if you look back, a lot of those alumni have gone in and started working together for where they found affinity, not necessarily on the teams that team formation is a critical one, and that early chemistry is really important.

I remember this whole conversation reminds me of Yosi Vardy who kind of single-handedly created the Israeli startup scene. Yeah, and he sold ICQ to then became AOL Instant Messenger for like half a billion dollars back. I remember, and and he did something amazing. He basically went to founders in in Israel and said, "If you're a good guy and you have integrity, I'm giving you 50K. That's the bar." Um, and then he just trusted them, and he would check their integrity and their character very carefully. And then he just give them money. And he invested in something like 400 startups. Uh, and the outcome of those has been a little bit like the Fred Wilson type where it's just been off the hook. So the the team and the individual that you're betting on is everything in in this type of Salem.

You're so right. And you reminded me of something that's really really important. Peter, remember when we went over to Israel to Tel Aviv to Startup Nation to try and figure out why the startup success rate is five times higher there than anywhere else on the world per capita than anywhere else on in the world? And there are a lot of reasons, but a lot of it comes back to everyone has to do their military time, and there's a huge amount of bonding, you know, just marching through the desert together and suffering together, and that creates these lifelong friendships. Then you go to college and you appreciate it a lot more, and then you start your company while you're in college. Um, and so they're a little older but a lot more bonded when they're going through that experience. But if I port that back to the US, you know, MIT is absolutely thriving like I've never seen before in terms of startup success. But Danielle Ruse, you know, who runs Seesale at MIT, biggest AI lab in the world. She has two daughters. One went to Harvard, one went to MIT. Her Harvard daughter was constantly at MIT for the parties. And nobody thinks of MIT as a party school, right? Like why would you? But actually, when you're there, it has an immense amount of bonding. Part of it is because the way it's set up with the living groups and the fraternities and sororities. Part of it is because the school is so freaking hard. And that's like the Marines. You cannot get through on your own. Those problem sets, you know, all night long with your best buddies trying to get through.

Just a plug here for Waterlue, which is the MIT of Canada. Um, we had the same thing. You couldn't get through unless you collaborated really closely with a bunch of other fellow students, and that created lifelong friendships.

Really great point.

Yeah. Well, if anyone's listening out there in school administration, you know, Harvard has a little bit less of that bonding culture because school's so stupidly easy. Um, you know, everyone says it, Mark Zuckerberg, Alex, everybody says it. Um uh and and it also hard to get into, harder to fail out of.

Harder to fail out.

Yeah. And then Stanford has become even worse. Stanford is, you know, if you talk to the students there, they're like, "Where the hell is the the crazy fun bonding culture?" But one of our Harvard guys in in the lab uh decided he was going to open a window and and and do a rock climbing drill on the second floor down to the first floor on the brick wall. And so there were cops all over the building and security guys running around and they're like, "Dave, why are the cops all over the all over the building?" I said, "Guys, let them let them be. This is this is what they need. They need to bond. They need to they need to blow off steam. They need to be a little crazy. This is what's going to create the success in the long run. But, you know, we also can't have the cops here every day. But but uh but this is this is the culture that is ultimately going to thrive because they it's kind of lacking on the Harvard campus and they need to create it." And so they are they are self-creating it.

All right. This next slide from Andre Harowitz uh is pretty epic. Uh, it's labeled "What's working means in the era of AI apps." GenAI startups are shattering growth records. Dave, this must make you feel pretty amazing.

Yeah, this chart's a little a little hard to read, but if you look at the top quartile, you know, it looks like they raised less money, but they actually raised it much more quickly. So, if you look in the bottom right corner, pre-series A dollars raised 3.1 million. That means they were very very capital efficient getting to 8.7 million in in revenue run rate. So this is what I was saying earlier. The fundamentals of these companies are so good compared to the internet era. I mean, very capital efficient, great ARR, and this is accelerating really quickly now cuz did you see that uh you know, one of our companies Farsight was talking to JP Morgan as a customer and nothing was happening for months, you know, just unresponsive. Then Jamie Diamond sent an email to everyone in the entire company, every manager saying, "If someone is trying to sell you AI, you better buy it or at least listen right now because this is," and all of a sudden they called back. They JP Morgan actually reached out to Farsight and says, "Okay, we want to talk. Get over here right now." Uh, so that's going to happen now across you know much of most of the Fortune 500, all of the mid-market. So this will get even more traction very quickly.

Now I just I love these numbers are extraordinary, right? uh you know, AR of uh 8.7 million time to a series A in five months.

Yeah.

Um, extraordinary. I mean, those are crazy good numbers, but then look at the cursor number from the prior slide. 500 million in two years.

I mean for sure.

I mean, it makes look weak, right? You look at the bottom quartile there though, right? They raised 10 million in in series A and in six months or twelve months they brought back a third of it. That's an still an amazing number.

It's a great point, Salem.

Yeah. 3 million in 12 months would have been top decile three years ago. Here it's bottom quartile. That's a great point.

Yeah. An acceleration of the acceleration.

Um, here's a big story in AI. This past week, the Trump administration is launching AI.gov. They're hoping to launch it on July 4th. I hope they hit it. Uh, and I just want to dig into this a little bit uh for those who've been frustrated by the government. This is a project being led by a Tesla engineer by the name of Thomas Shed who's leading the team. And the idea is can the government use AI across federal agencies, the GSA, DOT, you know, FDA, DOE, FAA, all of these agencies which have been, you know, sublinear in their existence at best. Uh, and let's chat a little bit about about this. So GSA, right, which is General Services Administration, it buys everything for the government. Uh, they could use AI to optimize procurement, uh you know, get vendor performance, automate contract analysis, really you know eliminate fraud. DOT is going to be predicting flight delays, analyzing real-time vehicle data, helping support infrastructure like roads and bridges in advance. Wouldn't it be great if they could predict where the potholes are and get those fixed? DOE about optimizing grid uh grid ops, forecasting demand and supply. The FAA, we're going to see a story on this about automated drone traffic management, uh, weather avoidance, and just, you know, as a pilot, the the FAA's air traffic control system is a bloody, you know, 1950s mess. And then, of course, we've we've spoken about the FDA uh using AI to enhance drug uh device approvals, faster clinical protocols, optimizing food safety. I mean, if there's one part of the world that needs optimization with AI, it's the government.

Yep. Thoughts?

You have a great road map for how this works, too. I think Palanteer and AWS. Uh, because because everyone was worried about, you know, how is the government going to interact with cloud computing? You know, there's a huge privacy issue here. And is the government going to start building their own data centers and build their own cloud? And obviously, they don't know how to do that. So then Palanteer and AWS set up secure clouds, private clouds for the government, and that became the roadmap. So now with AI, it's like, well, I obviously can't take all my government documents, tax returns and everything and dump them into Gemini or into chat GPT. Like how's that going to work? So so now if explain to people why why you can't why you shouldn't do that, why you can't do that. Well, first of all, there's no compartmentalization. So it gets pulled into the training data with everything else. you know, everyone asking about what time's a soccer game gets pulled in with someone's tax return, goes into the training data. Then somebody else who queries chat GPT says, "Hey, what a pay Peter Diamandis' taxes look like." And it just answers. So, so that's not going to work. Um, so yeah, all kinds of concerns like that. Uh, but it's going to be figured out in the private sector and it's going to be sold to the government as compartmentalized AI modules. Uh, there there's a lot of questions around whether departments can pull information and share their AI. So those are really tricky conversations, but I guarantee none none of the ideas are going to come from the government out. What'll happen is mandates will come out. This what the state of New York just did. You know, the the governor of New York said, "You know what? We need a gigawatt of nuclear power." Okay, any ideas on how to do that? No, I'm just saying make it happen, and then every private sector genius can propose a way to do it, and then they'll just approve one of them, and that's what'll happen. So the same will happen with AI here. So hopefully the big AI companies are aggressive in building up their government services operations or they bless some other third party like a Palanteer type or or a new startup to go and become that that entity. But that's that's the only way this can actually happen. And God knows we desperately need it, right? AI can solve so many government problems so quickly.

Yeah. See, you've been working with governments around the world with your EXO hat on. Speak to this, please.

I have so much to say here. Okay, three quick points. One, um, most note that most government processes are prescriptive, and the minute you have a prescriptive repetitive process, you can apply AI to it and totally change the game. So I think that's a huge area. Second about um a few years ago I was asked to give a talk at the Republican National Leadership Convention, and the title of my talk was going to be "How do you drop the cost of government by 10x," and you could do it easily using some of these technologies, blockchain, AI, etc., etc. Uh, the third point, I'll give a specific example. If you were applying for a wind uh turbine approval in I think it was in Colorado, it was taking like two years or three years to get approval for that, right? And then they brought in a a programmer who put in a on a a Google maps where are the electrical mains, where are the water manes, where the what are the flight paths, and they were able to reduce that two-year approval time to 30 seconds. And that's just the smallest example of how you can do this across the board. And we've mentioned some of these already. It's going to be a game changer. I can't I'm so excited about the potential government applications of this.

I love it. I love it. And it and it is.

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Okay, back to the episode. Uh, here's a related story. Uh, the US Army appoints Palanteer Meta OpenAI execs as lieutenant colonels. Uh, this is a special unit created uh to support the government. Uh, fascinating. I'm going to give some names here uh because they were they were published. The employees include the Palanteer CTO, uh, Cheyam Sankar, uh, Meta's CTO, uh, Andrew Bosworth, uh, Kevin Wild, uh, the OpenAI's chief product officer. Kevin's going to be joining us on this podcast in the next, uh, for that.

Yeah. And and Dave, you and I had an amazing meeting with with Kevin up at OpenAI headquarters. And then Bob Mcgru, former OpenAI chief revenue research officer. So I find this absolutely fascinating. Um, sort of indoctrinating and uh and actually they they made it super fast. There's no uh no required uh you know, traditional training, no boot camp for these uh for these individuals. Uh, what are your thoughts?

Peter, you didn't read the quote there. The uh the backlash quote.

Okay. Uh, the appointment of uh lieutenant colonels in the US Army followed the creation of a special unit created for rich big tech mavens seeking military leadership roles. This is like exactly what you're always saying. You know, everything turns into a drama whether it needs to be or not. That's just the nature of social media. I mean, this is one way that the government can bring in extraordinary intelligence that they could never hire. They could never recruit otherwise. I mean, this is sort of a part-time military service to make sure that the US government and the US military uh have access to the brightest minds.

Yeah, exactly. And then I don't know the other guys uh personally, but Kevin Wild we know and guy brilliant.

Perfect guy.

Yeah, absolutely. And you know, is is somebody going to just naturally join the army as a private, work their way up, and end up being aware of how to use AI to solve government and military issues? No. That's not that's not likely to happen. So, go get the best guy on the planet. Uh, he's absolutely the right guy. I mean, just just he, you know, he's he's a physically impressive manager. He can he can actually move mountains while still being the nicest, sweetest guy on the planet. And he knows exactly how this stuff works. Like, this is just great for everybody. I don't know. I don't The negative spin here is nutty. I think that this is a great example of a human being plus AI because as they bring AI to help in these roles, it's going to be totally transformative. You of course have the monster immune system response uh with people going, "Well, you can't do that unless you've worked your way through the ranks," etc., etc., and people have a thing, but I think this is a this is a great application um this reminds me of the big problem of around leadership training right and we we have we've spent decades and dozens of of hundreds and thousands of books lit written on leadership training and then about a few years ago it turned out the best leadership training in the world was World of Warcraft um and and the fact that technology can outstrip this age-old human kind of institution is unbelievable, but it's there. And I think that added to what these guys can do, plus bringing technology and their mindset to the mix. This is where I think it'll have the biggest impact is they'll bring that mindset to and hopefully infect the rest of the armed forces with it.

Yeah.

All right. Uh, talking about sort of breakthroughs in AI, I love this. My, you know, hats off to DeepMind continually to push new capabilities out that support all of humanity. So, this is a DeepMind uh algorithm supporting better tropical predictions uh for cyclones. Um, let me just play the video here. It's no sound, but let me give the uh the data. So, it's it's a five-day track prediction uh that averaged 140 km closer to the actual storm path, right? It's the difference between hitting Florida and, you know, and Georgia or Virginia. Uh, this was trained on 5,000 cyclones over 45 years. Uh, here are the numbers on impact. Uh, there's about $1.4 trillion in economic losses for cyclones over 50 years. And I'm excited about this thoughts.

Yeah. Yeah. I mean, it it's it's you know, there's a there's a piece of AI folklore called the bitter lesson which basically anytime you throw a lot of data and a lot of compute at one of these algorithms, you're likely to get a great outcome. You can sit there and stare at a wall trying to think through how to do it with differential equations for three years. You're not going to compete with the big data approach. And uh this is a great case study. I'll bet the people working on this got it cranked out in a very short period of time with just a couple of people. Yet, it's far more effective than anything that's been done over, you know, 50 years of weather research. So, there's so many of these around. It's it's just the benefit to humanity if we if we coordinate it and wrangle it correctly is

Just immeasurable. And is a great is a great example. Selma, what are your thoughts here?

Um, I label this as nothing to see here. Um, and I don't mean that in a negative way. This kind of thing should be com—well, this kind of thing should be completely expected. Right? You take an ancient data set where we had human beings trying to hand-plot these things, which are not—never going to do that well—and now you throw, uh, AI at it, plus the rich data set that's very bounded, and we know exactly the history. Of course, it's going to come out with a much better thing, and thank god, uh, thank god, because look at the predictive ability now going forward—huge impact. But I think we should take this as—we should expect like a thousand of these is coming out in the next year or two or three.

I, I, I agree. These would have been great X-prizes as well, and I've been pushing for this. You know, I think DeepMind is an extraordinary company under—under Demis Hassabis—and they're creating these kinds of assets to support humanity is really in their—their DNA, in their culture. Uh, I can't wait for an earthquake prediction X-prize or an earthquake prediction algorithm, right? I mean, if you could predict an earthquake with a—instead of like 30 seconds or a minute—with 10 minutes or 30 minutes, getting people into safety, uh, would be huge. I mean, one of the—

Wait, can I just drill in on that? That's a perfect example. Like, we know animals can sense this early. Exactly. The data is there. The data is there. We just have to get the right kind of algorithmic approach to it. And that's an area where I would expect to see a breakthrough in something like that for whether—and then when it happens, everybody's going to go, "Oh my god, this is unbelievable." But we should expect things like this. In fact, we should take areas and go find them—find areas where we have—we know what the answer could be. We know definitively it's possible—and then put AI against that. Yeah, my guess is we'll see earthquake prediction, uh, algorithms within the next two years, if not sooner.

Here's an interesting, controversial, uh, thought on this. Imagine if you could—d—you could control the direction of a hurricane. So you—instead of having it hit Miami, um, you steer it down into Central America. You go, "Oh my god, why would you possibly do that? That's terrible." You know? Well, so if you hit Miami and the cost of the impact there is, you know, $50 billion for that—and the government of Costa Rica says, "Listen, uh, you pay us $20 billion and you can land the hurricane here." Um, an interesting arbitrage on geography. Crazy idea. Uh, we have people that control—control the path of these things. Do you know the mechanism that they'd use for that?

Uh, I mean, butterflies. Butterfly effect. I think you'd use lasers and heating the atmosphere. Maybe it's—uh—it's magic voodoo dust. I don't know. I mean, I can just see the—the other side of that coin, right? Hey, Mr. Trinidad, you—maybe you want to pay us some money so that we make sure that hurricane doesn't hit you. And you get into all sorts of crazy outcomes. But if you can measure it, you can impact it. And, uh, I—I find this again huge and interesting implications.

Okay. Um, our next story here comes from Mattel and OpenAI. They've announced a strategic—strategic collaboration. Uh, I've talked about this forever. Super excited. Your toys are going to become, you know, super intelligent with GPT-5. So your—your Barbie doll, your Hot Wheels, your American Girl—I know that—see, that you—in part—in particular like the American Girl dolls. Uh, Thomas and Friends. Sorry, buddy. That's okay. You've uncovered my deep secret. Uh, I think this is going to be a boom for the toy companies. And I mean, this is going to enable rapid, you know, early education of our kids. That's the area I'm really excited about because the feedback loop—as you have interaction with these toys, you'll learn a lot about the child—and we can use that to—for understanding learning behavior, uh, guard rails that you could implement where their motivations are. You could—I think it's so exciting because we'll get more data about young children than we could ever gotten before.

Yeah, I was a little surprised OpenAI wanted to touch this one. Um, it—it's really clear when you're talking to the AI voices now that they're within a year going to be just crazy engaging, super—super friendly, and a lot of kids are going to prefer talking to AI all day than to talking to real friends. And I, you know, there's good and bad that comes along with that. I—I kind of—I've loved every minute of raising my kids. Uh, and I—I hate to see that change in any way, but it's clearly coming soon and it's inevitable. The other part, Dave, is sparking their kids' imagination, right? When you're—when you have to make up what your Ken doll or Barbie doll is saying. Um, that's critical for fostering early curiosity and imagination.

It is. And—and you have the echo chamber risk on the other side of that. So if it's done right, it's an educational gold mine and the kids are happy—and you know, a lot of schools are terrible. So you're—you're alleviating, you know, a lot of that. So if it's done right, it's—it's incredible. Uh, if it becomes an echo chamber, then you know, you can see where it can go bad in a real hurry, too. That's why I'm surprised OpenAI wants to touch it because when you start talking about kids, you really got—you cannot make a mistake, right? You got to get it right.

Yeah. There was a friend of mine that had a product called Moxy, which was an AI robot, and it was mostly being used for young kids with educational, uh, challenges, right? Uh, neurodiverse kids, in which case—you know—creating a best friend and helping them open up and communicate—there's real value there. What happens when you AI-enable Chucky? That'll be interesting—a whole new set of movies coming out.

All right, let's jump into a little bit of AI and education. Um, these are some scary reports that came out—so this is in Time magazine—"ChatGPT may be eroding critical thinking skills," according—according to a new MIT study. Dave, did you—did you track this?

Yeah. Well, only because you put it in the slides, I—I said, "I better understand what's going on here. This sounds really—really important." So, I—I dug up the—the research and—and read it. Um, and it's—it's nothing surprising if you think about how Waze works, right? A lot of people don't know how to drive anywhere unless they turn on Waze. Like—like places they go every day, they still could not get there without turning on Waze. So, it becomes a crutch really—really quickly. So that's what's happening here with writing, you know, where you would have thought through all the underlying topics in order to write it—because the AI is filling in the blind spots. You're just—you just don't really understand what you—what you just wrote. But it's not—it's not at all surprising. You know, it's that when you write it up and put it in a headline, it—it opens your mind to what's going on, but when you read the paper, you're like, "Oh, duh. Of course, this is exactly how it's going to work."

Yeah. This is—uh—some of the data. Uh, I don't know if you want to use this to recount what—what the study said.

Yeah. Well, no, it's—it's really straightforward. If you—if you write a document yourself and you have to think through every single word of it, that time that you put in means you can then recount what you just wrote with incredible accuracy. So, you know, the—the failure rate on the top line shows your quoting accuracy of what you were just talking about. So if you use AI to write the same paper and then you immediately ask you—"Hey, what was Shakespeare's favorite toy?"—like, "I have no idea"—well, you just wrote it down—"Like, oh, did I?" You know? So—so that's 88% failure rate, uh, if you use ChatGPT versus 11% if you're using Google—meaning you're actually looking up the data—then you're composing it. I mean, when you're doing the writing, you're doing the research and doing the writing—you're effectively training your own neural net, uh, and the data is being deposited in your, you know, uh, in your brain. Uh, it's—it is scary. Uh, it's going to become a crutch in terms of—of thinking. Uh, and it's going to get a lot worse. I didn't read it as all bad, though. I think that the—you got—you got the work done a 100 times faster in the left column.

Sure. So, your neural net actually didn't have time to retain every little detail. Even if—I don't know if—if society's going to move 100 times faster, we're not going to retain every detail. It's just that simple. So yes, you, as a teacher, you could say, "Look, the kids are not really learning the stuff," but as a person moving through life, the kids are covering a lot more terrain. Isn't that more important? So there—it's a mixed bag. You know, it's not—it's not all bad.

See, good or bad? What are your thoughts?

I have—I have an 80/20 approach. 80% unnerved, 20% will navigate this. So, the 80% is—I actually saw this with Milan, my 13-year-old. Um, he was writing an essay and he just used ChatGPT to write the essay—and he clearly had no memory of that essay. He would have fallen completely into these buckets, right? And so, when I saw this slide, I was like, "Whoa, this reminds me completely of what Milan just went through—and he has no cognitive framing for what he wrote in that essay," okay? Because he used the—the AI to help. And so, there's—now the other side of it is—it's happening much faster, etc., etc. I think the key question is—how do you effectively train kids on critical thinking into the future? And a—a guest we might want to think about is Nicole Drysdale, who's actually solved this problem and has found a way of teaching critical thinking into kids in a very active and a very accelerated way compared to where we do it. The—the last point I'll make is that—um—I remember seeing a study that 52% of the CEOs in Silicon Valley are—are liberal arts majors, right? Which is—the—the ability to think in different ways is a critical factor of success in leading a tech company. And that's really—I find that really interesting. Paul Graham has a different—different spin on that—that the liberal arts major succeeding is more tied to their desire to not do irrelevant difficult things and get to important topics—and it's just an easier way to get through.

It's a good filter.

It's a good filter. It's a good filter either way.

Yeah. Dave or Selma, I don't know if you saw Andrew Ng's, uh, presentation at the AI startup school. Um, I showed it to my son Jet yesterday—trying to incentivize him about vibe coding—which—which Andre came up with. He put out the tweet that went viral defining vibe coding. Uh, and—and my son's reaction was—"I want to learn how to code, not just vibe code." Right. So I'm curious what you think about that because you know the concept—right now—is English is the new coding language—but there's a lot of value in fundamental coding. So what are your thoughts, Dave?

Oh my god, so many thoughts on this. I—I have a little story. Amazing experience this week. I don't know if you want to—want to hear it.

Um, I do want to hear—of course you do want to hear it.

It was incredible to me. You remember—you know—right when I got out of MIT—went to MicroStrategy—came back to Boston and started my first company, DataSage. Yeah. Our very first product was using neural networks for handwriting recognition. Okay. And so I took the backprop algorithm, you know, read the raw research paper, all the differential equations—said, "I got to try and code this up on real-world hardware and assembly language." From the day I started on that journey until we productized it was four years of coding.

Wow.

Uh, and then that turned into a few million of revenue—and then we just skyrocketed from there. It—all a billion-dollar exit when—

Did you say you coded up in—Did you say you coded up in assembly?

Well, we had to because—so—so you know, we—we started out in a high-level language—but you needed to squeeze every—myip—you know—every flop out of these processors to build anything scalable enough to work. So you know, we invented quantization, you know, which is now all the rage to try and shrink the parameter size—anything to get another 2x performance out of these things—just to make it work in a real-world use case. And so it's a lot of hard work. So then this week, uh, on Monday, I said, "I wonder how long it would take me to recreate that four years of work." And so—no joke—and I'm absolutely not exaggerating—it took less than an hour to vibe code it from scratch to the exact same pro—even the demo—you know—the demo—you know—graphical interface I put on it—vibe-coded the entire thing in under an hour. Now it's not entirely apples to apples because there's a ton of open source out there that—you know—the vibe coding can pull in. So just—just to be fair, but in terms of—getting broader point is—is the broader point is well made though.

Yeah.

Yeah. Four years down to an hour is just like mind-blowing what you can do. Now your son is exactly right. Spend some time looking at the code, writing some raw code. You—you don't realize how much faster you are until you try and do it the old way. And so it's a really—really important to get that experience, you know. So let me—let me give you the end of this. He went off and wrote a short story, um, kind of full without any help, etc., etc.—and it was mind-bogglingly good. I couldn't believe that—I thought he used an AI to write the short story—but it was really—really good. I think we're in this golden era—like—like right now—the AI can do almost anything for you—but it's not creative yet. And so you still have to think—the—the human component is still by far the most component. Now, I don't know if that period of time will last forever, but right here, right now, such a golden era where you're empowered, but not, you know, not demoralized or crushed. You know, you're—it's—it's just such a wonderful next couple of years, and you really got to take advantage of it.

All right, next topic here is AI and job loss. Um, this was a Stanford survey revealing which jobs AI would most likely replace. They surveyed 1500 workers and AI experts. 69.4%—4%—want AI to—"Let me focus on high-value work," unquote. And 46.6% want it to take on repetitive junk. So that—that's kind of obvious. Um, we'll put this study in the show notes. Uh, but, you know, here's the occupations most likely be automated: No news here—bookkeepers, payroll clerks, data entry, insurance claim processors, software roles, tax preparers, public safety, telecom. Uh, Dave, Selma, any thoughts?

Well, high-level thought is—look, everybody needs to become a user of AI to get ahead of this. And this—the—the study would say, "Wow, it looks like bricklayers are going to be immune for a while," but you're not going to go and become a bricklayer just because, you know, you got three more years of—like—it doesn't—doesn't really give you any actionable, you know—"Robots are coming for that job, too."

Yeah.

Exactly. So, don't—don't do that. Just—just start using it every day, understand it, and—and ride the wave. And let's—let's double down on that. If you're listening to this podcast and AI sounds fascinating, uh, you're not a—a power user, how do you start, Selma? What do you start with?

Oh, just take a task that you're trying to do and go—"AI, how would I do that task?"—and then say—"Do it for me"—and give it the raw data and watch it just go. It's—uh—it pretty much is that easy. And I love the point you made, Dave, earlier, which is—I do use ChatGPT, uh, voice interface—and when I'm doing my red-light therapy or taking a sauna—whatever the case might be—or driving—I'm having a conversation on whatever subject is—I'm curious about. Uh, and it's extraordinarily educational and fun to have this back and forth with an AI—saying—"Well, I don't understand that term—could you dive in?"—or—"What's the data that backs it up?"—or—"When did that happen?" I mean, just being able to have a continuous, you know—it's—what a childlike—childlike memory or, you know, experience of—why—why digging deeper. That's exactly what you should do. And—and, you know, get out of the media rut. I know Peter, you say this a lot, but, you know, we have the internet now. You can actually watch useful media like this or—or, you know, study KJ Hardrich and his—his podcast. He's—he's phenomenal. Um, watch Lex Fridman, watch Dwarkish Patel—but while you're doing it, if you don't understand anything, have either Gemini 2.5 Pro or ChatGPT-4 open and just talk to it, right? While you're listening to the podcast, stay out of the mainstream media. Like, do not listen to the Rockstars—sports broadcasting, whatever. It's—it's going to distract you and suck you in. You need that time back—and—and use that time this way. It's—once you're into it, it's just as much fun, but much more useful.

Can I make a couple of points about that last line? Let's note that, uh, a lot of those roles are being done because people have to do them, not because they want to do them. Right? It's—it's grunt work done repetitively, etc., etc. And it's perfect. It's a perfect area. I was really happy to see that a large number of folks—40—whatever percent—said, "I want to take all the repetitive tasks"—because nobody wants to be doing that anyway. And now we can automate a—a lot of that side of it. And just a quick point on the bricklaying thing. I remember showing a drone at Singularity University a few years ago where you had drones working in cohesion to lay bricks on a wall—and the drones did it in like no time flat—cuz they didn't have—it was—it's—we know exactly where the—the bricks need to be laid. It's totally prescriptive. Off you go.

Yeah.

This is a story from The Guardian: "Amazon testing humanoid robots to deliver packages." Took them long enough, right? Um, this is—we see in the image here—Agility's Digit Robot. I'm gonna have the CEO of Agility at the Abundance Summit with their robots. Actually, I'm gonna have four or five robot companies at the Abundance Summit in March this year. Uh, you can learn more at abundance360.com. Uh, but I was a little alarmed when—when you read—"It's going to spring out of the van." That's—it's going to be a little unnerving when that starts happening. My two—my two dogs are already freaked out by the postman. What the hell are they going to do? I mean, come on, guys. We're going to have autonomous vans driving around, uh, where robots do the last 10 meters of delivery to your doorstep. Uh, and it's just going to drop the cost of this. So we're going to see, you know, drone delivery of products. We're going to see, you know, van—autonomous van and robot delivery of products. This is happening. There's no question about it. It's a when, not an if.

Agreed.

Right. And so the question is—when—when do you predict, Selma?

Uh, I'd say middle of next year because the technology is all there. They just have to get—there's probably some regulatory stuff to get through which might slow it down, but the technologies—potential is now there—now.

Yeah, the technology is there. I think the humanoids are inspiring everybody. There's no surprise here. But—but you know what people don't talk about as much as the robotics that are doing nano surgery, micro surgery—are unbelievable. Uh, and also the robots that are crawling through pipes, cleaning things, you know, getting into sewer systems. Those—those are also taking off. They're not as sexy as the humanoids, but—but it's all happening concurrently—and it's just, you know, tremendous benefit for humanity.

Yeah. I want to make a point about humanoid robots. You know, we've had this long discussion—I'm tired of your point you're making.

Hold on, hold on, hold on, hold on. I thought of a great real-world example of—of—of my octopus idea, which is—which is—you've got a human robot. How

Many times, when you're doing something, do you wish you had a third arm to hold the garbage bag open, or whatever? So, can we please have these humanoid robots have three arms? No, we'll just have two robots with four arms. Um, anyway, so but here's interesting, right? We're going to see these companies stack resources. So, you know, I would not be surprised to see Tesla get into delivery services, right, with autonomous vehicles and Optimus robots. We'll see, obviously, here Amazon and Agility. Um, we'll see other companies coming coming together on this, but a full stack in the physical world.

Uh, let's talk about robo taxis. Big news since we spoke last on June 22nd. Uh, the Tesla uh, robo taxi launched in Austin, uh, with a flat fee of $4.20. Elon loves his 420 over and over again. So, Robo Taxi is now live. Uh, here is Elon uh at Tesla headquarters in Austin. And here's a quick video of what a fan had as an experience in uh robo taxi. Thoughts? Finally, he's done it. I mean, I think it's the biggest one of the biggest markets uh, you know, that Tesla is going to experience. We've seen Kathy Wood predict as a multi-trillion dollar marketplace. Tesla will have been known as a car manufacturer. It will be known as a humanoid robot and uh and autonomous, you know, robo taxi service delivery company. Thoughts, gentlemen?

Um, so two quick thoughts. One is never bet against Elon. I've learned that through my massive investment portfolio suffering over the last decade. Uh, I think the second observation is uh the the these cars are technologically quite inferior to the Google Waymo taxis because they don't operate in heavy rain. They're limited by human-level sight, and that's a problem, I think, in the long term. He may get some buzz out of it, but he's going to have to upgrade the LiDAR for this to be really workable on the other side of that. He could just be waiting for LiDAR systems and all that to hit the cost curve where it becomes cheap enough, and then you just flip over to that. Well, you know his thesis, right? If a human driver can drive with just his or her eyes, in fact, with one human eye, then from first-principle thinking, an autonomous car should be able to drive with a couple of cameras. And that's basically that's great, except LiDAR can see five cars ahead. So, uh, I you why not give it superhuman skills? Yeah, why not give it? You could do it. Why not do it? And yes, it's much more expensive for now. I think his he went down a philosophical route of going away from LiDAR. And I think that's going to I think you end up with an inferior product. But if it's workable and it works well enough, that's fine. I mean, listen, I drive with my, you know, my Tesla's autonomous mode all the time, and it does perfectly. The only time it ever stops working is when it catches me picking up my phone and looking at it, and it beeps at me. Otherwise, it's extraordinary in the rain. That part surprised me actually. I didn't know, you know, when we were driving together a couple of weeks ago, the inward-facing camera is new to me. It's like actually watching your behavior and then adjusting. I was like, "Wow, that's a little—" I'm looking out the window to the left, it sort of like beeps at me. If I pick up my phone, it beeps at me. It's like really annoying. I have my I've kept my 2017 Tesla Model S for exactly that reason. There's no inward camera, so it's great. I've now driven that car just to flip to the other side of this. I've now driven that car four times up and down the country from Miami to New York or Toronto. So, I've become a bit of an expert at the highway.

Sm: Have you heard about this thing called an air? You know what? I load up with five of my favorite kebabs. I arrange 40 conference calls. The car drives itself 80% of the time, and it's free to do that, and I arrived more refreshed than when I left. I mean, it's phenomenal.

All right, let's take a look at this next one. So, Tesla faces protests in Austin over Musk's robo taxi plans. Protesters claim Tesla's uh FSD, full self-driving, has been linked to hundreds of crashes, including dozens of fatalities. Um, so let's look at the data here. One second. Um, here it is. Number of accidents uh per million miles. And without any question, listen, humans are terrible drivers. We are distracted constantly now with, you know, at least one cell phone per car. We are terrible control systems for two-ton cars going at high speed.

Can I give throw out a quick data point here?

Sure.

About in 2011, I think it was, there was a 3-day outage in BlackBerry services around the world. Nobody could send text messages for 3 days. The accident rate in Abu Dhabi dropped 40% during that three days. Okay, that was then. Today, you look at anybody driving, they're looking at their phone. It's we're we absolutely should not be driving as human beings.

I I I agree. I mean, we're going to see an extraordinary uh increase in safety. I mean, just the idea of a 16 or 17-year-old uh driving a a couple of ton vehicle at 60 mph through the streets with very little experience and their phone distracting them should scare the daylights out of everybody.

Well, this is this is America's greatest Achilles heel actually is that we're we're responsive to uh sympathetic stories that are statistically rounding errors. And it's it's actually the uh or wrong or wrong.

Yeah.

Sometime well look at the state of the union address. You know, somewhere along the way it changed to let me call out four or five people in the crowd here and tell their personal stories. You're like, well, how do I know if that's just like that could be one in a trillion for all I know. But yeah, that's okay. I'm just trying to sway a bunch of voters toward the what I'm trying to get done here. But we're ridiculously, you know, swayed by that. And if you look at that prior slide, you know, yes, hundreds of fatalities from self-driving, like, well, hundreds relative to what? And you know, you you put your statistician hat on, you're like, this is clearly better. But, you know, some of these are really, really tragic. And if it's all captured on video, which everything is now, it can sway opinion. And this is where if America is going to lose to China or to some other, you know, state, it's going to be for this reason.

Yeah.

It's it's the same the same concept when people hear about an airplane accident. Oh my god, I'm I'm fearful of flying. It's like, have you looked at the accident rates in cars? I mean, you know, flying is still the safest mode of transportation. 1.2 million people a year die in car accidents around the world every year.

Yeah.

Well, hey, nuclear power, let's we will come to that later, I guess. But that's another case study. And we will.

So, here's uh an important news bite from this past month here in LA. Five Waymo vehicles were torched in downtown LA. Uh Waymo paused service in LA, Limited, San Francisco, Austin, Phoenix, Atlanta. And the question is, is this the beginning of the Luddite revolt? Right. So are people, you know, are you know, people are responding against uh against uh all of the technology, and and here's an image of the Luddite Revolution from uh 811 through 816. And I have some data I want to share with you guys on this cuz I think it's uh it's worth noting and I want to talk about it. So, the Luddite Revolt over that 5-year period was a series of protests by English textile workers against the mechanization of the industrial revolution, particularly against automated looms that threatened their jobs and wages. Sounds familiar, right? Uh, named after the mythical Ned Ludd, the movement began in Nottingham and spread across the UK. Workers fearing deskilling and unemployment amid economic hardship from the Napole from the Napoleonic Wars destroyed machines and organized raids at night. The revolt involved thousands. The British government deployed 12,000 troops to suppress it. Sounds familiar. Uh, and here we go. Quote: machine-breaking became a capital crime in 20 in 1812, leading to 17 executions, dozens of hangings, um, and the movement was crushed by 1816. Thoughts?

Well, this is the classic immune system response, right? Um, in a slight twist note, I note when I read this up, the Waymo cars were actually called to that spot so they could be attacked. So the AI is watching those people carefully for future retribution. Um, but I think this is the general backlash of technology against society. What we don't understand we fear, and what we fear we get angry at. We try and destroy.

Yeah.

I should insert a picture of the picketers that are in front of OpenAI. You know the security guys have cleared them all out now, but if you pull one off the internet it's uh very Luddite revolt looking.

Yeah.

And I I think we're we are without question going to have a revolt, uh you know how often and where against which companies. I mean we haven't really started to see job displacement truly occur, but when it does hit, and I think we'll be seeing it uh significantly in the next 2 to 3 years, until we figure it out on reskilling and, you know, uh other other mechanisms.

Can I give the positive spin here of of course we have no more looms, we we no it's that it's the fact that we've seen this um kind of displacement fear throughout history, and we always survive it very, very well, and on the reskilling which everybody's like, oh my god, how are we going to reskill, note that we have AI to help reskill everybody, right? And so you can pick your passion and go, I want to be reskilled in that area, and you'll get a really good uh potential work. Note also that we're near full employment today and have been for a while, so we actually need a little bit more buffer in the in the labor market than we have today. So those are my positive spins, and I also understand the negative. I am curious uh what rules and regulations the government will put forward. I don't think it will become a capital crime. I do think we'll see troops again deployed on things like this.

Um, this was just arm the Waymo cars with little machine guns so they can defend themselves.

Fight back.

Uh, this was a scary story. Two children shot uh while in a Waymo here in Santa Monica at Second and Broadway. This is actually like a probably a mile from my home. Uh, two teens were shot, Armen Tarso, non-life-threatening, now stable in hospitals. Uh, I think violence against tech. I don't know if you remember all of the scooters here in Santa Monica, Sim, if you were here at that time. And uh and the scooters, people sort of raged against the scooters cuz they were blocking sidewalks. They would like literally throw them into the middle of the street. They would decapitate them. Uh, I think we're going to see when we see Waymo robots or not way more robots, when we see o, you know, Optimus robots and figure robots on the streets, I I think we're going to find them in various positions hanging from trees. Thoughts here?

We are, but I think this is really just part of the shift. I mean, they probably called the Waymo to try and get away, and there was probably some sort of gang violence involved in this, something like this.

Yeah.

Okay. This was the slide uh about Waymo versus Tesla. Uh, and here's a tweet. The downfall of Waymo began yesterday. This is on on this was tweeted on June 23rd about the launch of uh of Elon's robo taxi. So, people need to understand the Waymo car is not cheap. It's a $200,000 vehicle. It's got 29 cameras, five LiDARs, six radars uh versus robo taxi. And Elon has held to his first-principle thinking: there shall only be cameras. Uh, but this would be a great Dave Salem bet. Dave, do you have a particular preference on which one would would not win this?

Yeah.

Uh, yeah. Peter, you know this topic far far better than than I do. My bet, knowing what I know, is that it'll be about a a 70/30 split. There's always two or three vendors in any given market in the US. It always stabilizes at that for antitrust reasons. Tesla will grab the lead now uh cuz they put a bigger investment into the the neural chips. Um, on the other hand, you know, Google's got incredible technology. So, but if I had to bet right now, I'd say 70% of the market goes to Tesla, 30% goes to Waymo, it stabilizes.

So, I'm 50/50 because I always prefer better technology, but you have the uh never bet against Elon problem on the other side.

You know, here's the here's the issue. It's a huge capital expense that Waymo will need to uh to roll out to do this nationwide. Elon's got a different option. You buy a Model Y, you turn on self-driving, it drives you around, you're going on vacation for a week, you tell your car to go off and earn your revenue. So basically, the capex is covered by the consumer, and it becomes a revenue engine for you. So you'll buy a couple of these and just have them go out there. So he's going to populate millions of these cars across the country at no capex to himself. So if you apply that model, which is essentially the exo model, which is assets on demand and you don't own your own assets and you let other people self-provision these assets, etc. Uh, that will win hands down because it'll scale much much faster than Waymo trying to own its own cars, which it has to.

This is directly connected to our other side bet, which is you remember last week uh Elon and Trump finally break up, now they'll hate each other forever. I was like, "No, no, no, no, no, no, no. One, this might be totally made up. You know, they might be just trying to make PR for themselves. It wouldn't surprise me at all. But two, if it is real, which it probably is, they'll kiss and make up in no time." That was my bet.

Yeah.

Anthony Scaramucci is going to join us back on this pod to talk about uh how the administration. He was eerily eerily accurate last time when we after inauguration we asked him how many how long will this bromance last, and he said I think 30 Scaramucci or something like that, and it was really near dead on almost to the day, so we got to respect his views next time.

Yeah.

Yeah. Well, look, the government needs space launches, and Elon needs regulatory approval of that really good idea. You know, you buy your car and then you lease it back to be a robo taxi. It's just a really good idea.

Let's hit a couple other quick ones. Uh, this is uh flying cars and drones. Uh, we've seen the Trump sign an executive order order on drones and flying cars and supersonics. Uh, really important for these drone systems to actually work. Uh, you need to enable beyond visual line of sight mode. Um, and we're seeing uh the US government support five regional eVTOL pilot programs. Super excited about Archer Aviation here in LA to serve the Olympics in 2028. And uh the other point here is they're enabling supersonic travel by scrapping outdated overflight bands. So you know the uh supersonic jets of the Concorde could not fly over the domestic US because the sonic boom uh and uh changing providing FAA waivers in particular because you know a number of companies have come up with mechanisms to actually avoid or absorb the sonic boom, but this is going to accelerate uh aviation as it should. I mean, there hasn't been that much change in aviation for the last 50 years. It's been incredibly slow.

Yeah.

I I was wondering if all the uh, you know, privatization of space travel was also going to lead to breakthroughs for, you know, out of the atmosphere hypersonic travel cuz you know I don't know if you remember Steve Kishi was working on that. I know way too much about this. It's it's just really tough. I mean the amount of energy and to build something that's going to go skip across the upper atmosphere uh and there have been many companies uh who have died on that on that uh mission statement and and billions invested. Uh, the closest thing right now is Starship going spaceport to spaceport, but it's still expensive.

um, here another competitor we know about uh we know about uh uh three or four of the companies out there providing eVTOL services. This is Whisk. It's been selected by Miami uh to launch in that location. So watching out for Whisk in Miami. Uh, I don't know if I want to talk about uh these eVTOL flying cars at all, Seem, but they're coming. uh you know, interesting, you know, Dave, when we spoke to Eric Schmidt about this, he was not a believer in eVTOLs.

Yeah.

I mean, I think I think it was a a relative thing, you know, there's so much change going on and so much of it is so impactful and um I I don't think it was like, yeah, I don't believe in this. It was it was like, look, aviation, we have helicopters now, we're going to have, you know, four-prop electronic versions of them. So what? Like, well, the so what to me is that they're self-flying, self, you know, self-driving. That that to me is is really, really a big deal. And they're much safer, too. Um, so I do think it is a big deal. But he he's like, "Yeah, but relative to space and AI, is it a big deal?" And he was like, "Nah, not really." Uh, for me, this is one of the most exciting technologies we could have.

Okay.

Can I explain why?

Sure.

But you're still driving your Tesla everywhere.

I am, but I just I just love it. That's that's fine. I'm allowed to do that. By the way, I have a Porsche Macan electric also, and it's like maybe the best car I've ever driven, but it's not way way better than my 2017 Model S. It's marginally better. So, that's really profound to say uh how much further ahead Tesla was than all the other car makers in many, many areas. But, let me go back to eVTOLs for a second.

Okay.

I think this totally changes the game. Why? Because um uh real estate that's hard to get to is priced very uh low and it's scarce, and therefore we pay a lot of money for that little um um waterfront property on a lake somewhere because there's not that many of them. Well, now you can get to all sorts of places you can't get to by road. It's going to make an abundance of or a really beautiful plot high up on a mountain side that you can't get to by car. Now that becomes viable real estate, and we turn real estate from a scarcity problem into an abundance problem, and I think that's incredibly exciting for the future. Uh, there's huge economic implications for this. Uh, not just to mention uh many of us fly around a lot and how how much of a nightmare is the damn commute into the city and just having a drone corridor uh from Kennedy airport into Manhattan would just change the game.

Yeah, for sure.

And that is coming. Uh, we've seen this with Joby, with Archer, now with Whisk. You're gonna get commute from downtown uh Manhattan to JFK in one of these vehicles, right?

Yeah.

In Sao Paulo, it's 2 hours to get to my helicopters are the only option you have if you are like not the safest. So these are safe and solid and and I think they be start become really um a big deal. Tourism destinations. I mean the list just goes on of the broad effects this could have. This is hugely exciting to me.

Yeah.

Every day I get the strangest compliment. Someone will stop me and say, "Peter, you have such nice skin. Honestly, I never thought I'd hear that from anyone." And honestly, I can't take the full credit. All I do is use something called One Skin OS1 twice a day, every day. The company is built by four brilliant PhD women who've identified a peptide that effectively reverses the age of your skin. I love it. And again, I use this twice a day, every day. You can go to onskin.co and write peter@checkout for a discount on the same product I use. That's oneskin.co and use the code peter at checkout.

All right, back to the episode. I want to jump into the next subject, which is uh timely and critical, which is the demand for energy from AI systems and a little bit of a look at US versus China. I think people need to understand we are going to become limited by power in our quest for digital super intelligence. Uh, so how are we going to power this revolution? So China is rapidly scaling up on nuclear. Uh, they're you know it's their equivalent of a Sputnik moment. So China aims to surpass the US by 2030 in nuclear. I mean the numbers are staggeringly uh incredibly um you know pessimistic here. The US only added two reactors uh

This century. I mean, two reactors, you know, over the last 25 years. 94 total in the US versus China's 58. China is building a reactor, uh, every 52 months. The US licensing alone takes 10 to 12 years.

Yeah. Crazy.

Yeah. You know, this is the reason I love doing this podcast, and I look forward to this so much because I, you'll, your team will dig up a topic that I really need to study, and then it'll come into the deck, and I'll be like, it's just so fascinating to me to dig in on these things, and you're, it's just so fun to talk about it. A lot of these things, like, you know, this are so obvious, and this is America's Achilles heel; like we cannot act on long-term thinking and long-term investing. Our investment cycle is 3, 4, 5 years at the most. Our election cycle is 8 years, four years or 8 years. And we, we can't think about 10 years in the future. And so it's killing us. It's absolutely killing us. But the data in these next couple of slides is mind-blowing.

You. Yeah. I mean, we're going to talk about nuclear in a future podcast with some of the CEOs in these industries. But, you know, generation one nuclear power plants no longer exist. Uh, generation 2 plants, uh, are still out there. Um, including what we saw with Fukushima and 3 Mile Island. Those were the dangerous plants. Uh, generation three have been the plants that have been really manufactured over the last 30 years. And then generation 4 are the plants that are currently, uh, have been designed, are fail-safe. It's kind of nuclear plant I'd put in my backyard. But the time frame for these plants, for developing them, is insanely long, right? We're talking like, you know, if you wanted to start today, it would take you 10, 15 years. And that's why Three Mile Island is being recommissioned because it's already, uh, it's already approved from a government regulatory standpoint.

It's crazy. It is totally crazy. Um, I've got a, I'm really, really angry about this one in a, in a, I'm trying to be constructive here, but we know that solar scales. Uh, China is going to have more solar. Let's get to that. Let's get, that's our next topic here. Let's, let's go to the next slide.

Wait, you got muted. You muted. I don't know if you muted yourself or muted. I get it. I'm just really mad. I was going to swear, and I thought better cut off the mic before I swear.

All right. So, here's, I'll let you take the lead here. Uh, China is winning the race to become a type one civilization. In other words, a civilization that harnesses all the power hitting the earth and the sun. By 2030, China will have the ability to build an entire US worth of power generation, uh, from solar and storage alone every single year. Look at this chart, Sem. Talk to us about this.

You go, Dave.

Let me, let me just gather myself. No, this chart is, I added the, the gigawatt axis on the left there because who the hell talks about terawatt hours per month? What the hell is that metric? But anyway, gigawatt is a better way to look at it. But this is actually, uh, gigawatt actual utilization. They actually created about 700 gigawatt of solar panels last year, 2024, and deployed 250 gigawatt of peak capacity. After the, the hillsides covered with solar. We, we covered that on a past podcast. It's insane. They're just rolling this out, building capacity and distribution.

Yeah.

Yeah. I mean, just for context, the US total capacity energy production is 1.2 terawatts. So, 1200 gigawatt. Uh, and so, you know, peak actual utilization is more like, you know, 3/4 of a terawatt. Um, so, so you're like, yeah, half of what the US creates they created in solar panels in 2024 alone. Just solar panels in 2024.

Yeah.

All right. So, they have an advantage because they've got all the rare earths, and they can use those for solar panels and, and build out. They're going to add more solar than the entire US energy output in a little while. So, that's going to be crazy. Um, it blows my mind that we are putting restrictions and not extending tax credits for solar and other stuff here in this country. We need to unlock that in the biggest possible way and let private sector go nuts on this and put government subsidies there instead of government subsidies on oil, which is what we do today. It's the stupidest energy policy we could possibly have. I mean, I'm fine with all energy needs to be, you know, made available. But where do we invest on growth? You know, uh, solar is available today. You know, the numbers are,

Can I just share a couple of points here?

There's enough energy that hits the earth in one hour to provide the global energy needs of the entire year. So, one year worth of sun hitting the earth provides global needs for the entire year. All right. So, uh, here are some additional numbers. Global solar capacity, uh, reached 1, uh, 1300 gigawatt by 2024. About 1% of global energy need is being provided by solar. It's estimated that if you cover just .1% of the earth, about 150,000 kilometers with 20% efficient panels, that would generate 200,000 terawatt hours annually, exceeding current demands. So, how big is 150,000 km? It's about the size of South Dakota. I've never been to South Dakota. Uh, but if it were covered by solar panels, it'd be giving us a huge amount of energy.

So yeah, the, the, the problem with solar for data centers and AI fundamentally is the good thing about AI is you can move it to the power. You know, take the data center. That's, that's a huge advantage. The bad thing is you need those chips to be running 24 by 7. They depreciate really, really quickly. They're very expensive. The chips cost 10 times more than the power. You're not going to let them sit idle if it's raining out. So, solar has the, the, the horrible flaw of being intermittent. And so it's, it's really good if you can store it, but the cost of lithium to store the solar when there's, when it's cloudy and raining is about five times higher than the cost of the solar panels. So, if you want to become the world's first trillionaire, find a way to store huge amounts of energy cheaper. There is a way, and you, we're going to be talking to Bill Gross, the CEO of Ideal Lab, right? And he's been using gravitational storage, which is, we'll talk about that, rather than storing into batteries, you use the energy during the day, a portion of energy to move a large weight vertically, and this was done, has been done with water for, for ages, but you move a large weight vertically, and then at night the weight gets pulled down by gravity, and in a generator generates electricity. So, it's efficient, it's available, and it works.

Can I throw out some, some thoughts here?

Sure.

So, um, in 2016, we crossed an inflection point where it became cheaper to build a solar gener power generation facility than fossil fuel, and almost all energy and generation since then has become has been solar because of that. Um, in 2019, we hit a more important inflection point, which is that it became cheaper to build solar than to, to build and run solar than it was to build, sorry, it became cheaper to build and run a solar facility than just run a fossil fuel facility. So, the capex and opex of solar are now cheaper than the opex of fossil fuels. Right? That's a crazy inflection point. Meaning we, we don't ever need to build a fossil fuel thing again. We should just be building solar. The utility storage problem has been solved at scale, as you've said, um, at large scale, this is very easy; you just pump water up a hill to an artificial lake and use hydro at night on the way down, right? It's a little clunky, but it's very workable until battery technology or energy vault type stuff that Bill Gross is along doing comes along, so this is a really a known problem; we should be going full out for this, the, I think it was 100 miles by 100 miles to power the whole of the US was Elon's calculation, the one I saw was 2% of the Sahara covered with solar panels gives you enough power to cover the whole world's energy needs. Distribution is a challenge, but just that visual is a really killer visual. It's absurd that we're doing what we're doing.

Here's the chart, uh, Elon that, uh, was posted. Elon's tweet is solar is 100% of energy long-term, right? No question. This is what's going to drive humanity forward. Uh, and here's a chart that basically reads it took eight years for solar to go from a 100 terawatt hours to a thousand terawatt hours, and then just three years to go from a thousand to 2,000 terawatt hours. You can see that super exponential growth curve, you know, exceeding hydro, coal, gas, nuclear, wind.

Yeah, pretty amazing.

Yeah, I really like pumped hydro is very, very efficient, but you need a, you need about a lake the size of Loch Ness to move up about 300 meters and come back down to store enough energy to power a huge data center. So, that's, that's a lot of water. Bill Gross has, Bill Gross has solved that, right, with these gravitational towers. Basically, you, you pump huge, uh, you know, multi-ton bags of dirt up into like an elevator shaft into a large building or up the hillside if you're near a mountain, right? Uh, and he's got this working today. He's got huge contracts. We'll be talking to him about that. I think storage, uh, can be solved. Uh, and I'm hoping, in fact, AI is going to help us with new technology for, for,

Yeah, that's exactly what I was going to say. You know, if you're a material scientist or, or a chemical engineer, I'm pretty sure with AI's help in a couple of years or, or maybe even this year, come up with a reversible chemical reaction that's completely self-contained that stores huge amounts of energy, use the solar to drive the reaction one way, and then when it's cloudy, run the reaction the opposite direction. And if you come up with something that's, you know, 10, 20 times more energy dense than a lithium battery, which seems very viable, you're going to be a trillionaire.

Yeah. So, just, you know, figure that out. Use AI to help. I, I, we a couple of years ago, we tried to design an X-prize around this, um, and the numbers were, get off-grid solid storage 50 times cheaper than it is today, which is viable from,

Here's another tweet from Elon: Solar power in China will exceed all sources of electricity combined in the US in three to four years, in three to four years, it's a wake-up call, um, China is going all in on energy production, Uh, and it's, it's epic.

I have one more thing to say about, I have one more thing to say about this. I, I think this China, US stuff is a little overhyped. I don't think we'll have that much of a, I think it's a stocking. But I think it's a great, it's a great,

Yeah, I agree. But it's a great comparator. I don't think it, there's real deep conflict there.

No, there's not. There's just,

But what it does is it shows the US what is possible.

Yeah.

Yeah. And to Dave's earlier point is, is this is a structural issue we have in the US where, uh, we have four-year election cycles, and we have no mechanism to look at 20 years and say this is the water, healthcare, energy we need over a 20-year period. We need to solve, and you know, you know, running our venture funds, you know this acutely, but you, you make an investment, investors want to see liquidity, you know, within four or five years. They don't want their money to be sitting out there for 10 or 15 years. In China, they know they'll still be in power. They think they'll still be in power 20 years from now. If you look at the date they said, you know what we need to be the world's biggest manufacturer of solar panels. So it's about 2004 or 10 or somewhere around there from that date to you have the factories up and running and you have the production, and then also, you know, when there's a recession, you got to keep cranking. So, just keep the engine running because you know you got a 20-year view, 30-year view.

Yeah. We just can't do that structurally in the US. Um, and that's why we get so far behind in nuclear and solar and some of the other long-term trends. And that is our fundamental Achilles heel.

Hey folks, Lim here. Hope you're enjoying these podcasts. And this one in particular was amazing. Um, if you want to hear more from me or get involved in our EXO ecosystem, on the 23rd of July, we're doing a once-a-month workshop. Tickets are $100. Uh, we limit it to a few people to make sure it's intermittent and proper. And we go through the EXO model. What we do there is we basically show you how to take your organization and turn it into one of these hyper-growth AI type companies. And we've done this now for 10 years with thousands of companies. Uh, many of these use the model that we have called the exponential organizations model. Peter and I co-authored the second edition a couple of years ago. So it's 100 bucks, June, July 23rd. Come along. It's the best $100 you'll spend. Link is below. See you there.

All right. Last subject for us, gentlemen. Crypto. I always have to have a little crypto in the conversation. We've seen, uh, Bitcoin over the last couple of weeks dip down below 100K and resurrect itself up to 107. Predictions, uh, See that I'm seeing still hold that we might see 200K by the end of this year. Uh, I still remain all in and massively enthusiastic.

Are you?

Uh, big time. I'm, I heard Michael Sailor say Bitcoin will get to 21 million a Bitcoin. Uh, I'll be happy when it gets to a million a Bitcoin. That'll be perfectly good enough, I think, for most people, cuz that'll just put it at the level of gold, which is infinitesimal anyway. Um, as in terms of global asset class, but I think there's a bunch of things happening that are making this move very hu, very, very, uh, that'll start to accelerate this. I heard Freddy May and Fanny Mack are looking at or approving mortgages backed by Bitcoin. That'll be a huge thing. So, it's starting to get systemic approval, and then things go crazy.

Yeah, for sure.

Uh, I love this. Uh, this comes from our, our friend Brian Armstrong at Coinbase: Earn up to 4% Bitcoin back on every purchase with a new Coinbase One card. Uh, I love this. I'm going to switch over from my AMX to this.

How about you?

Big time.

Yeah. Dave, thoughts?

Uh, I'm really excited about the next story. Actually, I want to,

All right. Well, let's go to the next story here. Uh, Dave's holding his powder.

Okay. Yes. Circle internet group goes public and explodes, goes exponential.

Mhm. Yep.

Yeah. So, uh, two, two parts of the story. One of them is Jeremy Aair, who's, who stuck with this for so many years, and he deserves every bit of his, his success, um, for just, just grinding it out. You know, it's always tough to be an entrepreneur. He had to grind it out, uh, over a long period of time with regulators all over him and, you know, different administrations and people going to jail and like, what a persistent story. But anyway, the reason this is so, so important is because agent-to-agent transactions can be done in either Bitcoin or dollars now. Oh, and you can move back and forth seamlessly. The old method, the Swift network, the interbank, you know, trading network is great if you're trying to move a million dollars to Hong Kong because it's only like a buck. Terrible if you're trying to do a penny microtransaction with another AI agent. Crazy. So, this solves that problem. And you, because the current pricing model on AI is subscription fees. You give me 200 bucks a month or 20 bucks a month flat. But that's crazy, right? The utilization gets throttled because, you know, they, if you're trying to write code or talk to your AI, it'll, it'll slow down every now and then. Why is that? Cuz there are too many users online. Like, well, why can't I just pay for what I use as I go? Well, it's because we didn't have Circle. So, the whole AI economy needs to now move to these micropayments, and this is what's going to enable it. And that's why the stock is up so much.

Yeah, I've been texting with Jeremy. Uh, super impressed, congratulating him on this exponential growth. The IPO goes out at $31 a share and peaks at $300 a share. Extraordinary, right? These are the IPOs that the entrepreneurial market needs, uh, to fuel sort of the opening of the doors wide open. Um,

See, thoughts?

Um, I want to just, uh, echo the kudos here for a slightly different reason, which is, um, one of the big issues in the crypto world has been trust, and you have a lot of scam artists and a lot of shers, and can you actually deliver trust, and Jeremy over a long period of time has demonstrated rock-solid, stable, trustworthy environment, and that's not, and easy to do in the environment where everybody else is in the United States, and so huge kudos there within the US, uh, you know, territory of law if you would, which is super important. So, you know, Circle internet group is a financial technology founded in 2013. It's a stable coin pegged one to one for the US dollar, and it's going to enable, as you said, Dave, uh, you know, my AI agents to go and transact microtransactions, uh, and it's finally going to enable what is, what has been the full promise of the internet, uh, not just data, not just video, not just words, but a financial layer, and I can't wait,

Can I say one thing about, can I say one thing about stable coin?

Yeah, sure.

It's, it's awesome to have this pegged against the dollar, but once you have something, there's so many natural assets on, in the ground and out in the world, ing, when you can peg a stable coin against, say, real estate holdings or something like that, when that becomes possible, as long as the trust again needs to be there, uh, you're going to unlock unbelievable amounts of capital flow. One of my friends is actually contracted, I can't say the details here, with a government who has large gold deposits underground, and they've gotten a contract where they're going to, uh, peg a token against the gold in the ground and not dig it out. Wait until the technology for being able to extract it more environmentally friendly is there. But, you know, that's an extraordinary thought that there's so many assets that could be, uh, sort of connected to a token or a stable token.

Yeah, it's a great, it's the, the missing ingredient actually, and kind of the trifecta of digital transactions because Bitcoin has become a great store of wealth. Uh, but it's, you know, there's no guarantee that it's stable. The dollar is guaranteed to go down in value, right? We just print more dollars every year. So, you don't want to have a huge balance sitting in Circle for a long period of time. So, what people will tend to do is park their money in Bitcoin. Then when, if they want to transact in dollars, move it over to Circle, it's all seamless, do your microtransactions in Circle, then come back to Bitcoin. But what if you want something tied to something incredibly stable like real estate or gold or whatever? Well, doesn't exist yet, but that would be the trifecta of the, you know, the, the crypto circle.

All right, Moonshot mates. What an extraordinary couple of weeks since we spoke last. Um, I mean, there's so many other stories I can't wait to cover with you guys, uh, in the next week or two ahead. Uh, any travels coming up for you guys?

See, are you, are you orbiting the planet again?

I just came back from my 100th birthday party of a grandparent. Uh, Lily is one of Lily's grandmothers, which was unbelievable. Uh, not going anywhere for a bit. Um, I think I'll be seeing you soon, Peter, at the end of, um, uh, July in Utah, maybe. So, we'll talk separately.

That's great.

Yeah. Dave, how about you?

Yeah, we have our, We're going back to see Kevin While very soon, uh, in San Francisco. Hopefully, the sooner the better as far as I'm concerned. Uh, and then, uh, at OpenAI headquarters, right? Mega event.

Yeah, OpenAI headquarters. Our mega event, uh, on September 9th. Uh, Google agreed to host the, the pre-party at their HQ. So, that's going to be,

So, I'm basically going to be going back to San Fran over and over, and that's why I need that hypersonic plane. I just want to, want to get back and forth a lot.

All right, dear Moonshot mates, have a fantastic weekend and, uh, excited for next week. See you guys.

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Meta’s 15 Billion Dollar AI Bet & The Race To ASI w/ Salim Ismail & Dave Blundin

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