Meta的150亿美元AI豪赌与通往ASI的竞速：Salim Ismail与Dave Blundin

We are going to become limited by power in our quest for digital superintelligence. This is a structural issue we have in the U.S. This is America’s Achilles’ heel. China is going all in on energy production, and it’s epic. Meta is worth $1.8 trillion today, and they have $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, which is why everyone should be tracking these moves closely. These numbers are so unprecedented, but they’re completely justifiable given the impact.

I’m here with my moonshot mates, Salim Ismail. Salim, I’m calling you the emperor of exponentials because that’s just who you are. And Dave Blundin, the alchemist of AI. How’s that for a title?

We need one for you, Peter. You have to be something epic. How about the humongous bungalongus of abundance?

I’m not sure I like that. I like what Dean came and said on stage. He called me the Pope of Hope.

That’s awesome.

Yeah, my mom liked that. She’s watching all of my abundance videos and the whole show on stage, and she writes back, “Pope of Hope.” I love that. Thank Dean for me.

We have a lot to cover today. As always, our goal here is to deliver you the real news—the news that’s going to impact you, the news that’s changing every industry, every family, every country, right here, right now.

All right, buddies, let’s jump in. Let’s talk about all things AI. Another epic week. Every week is accelerating. It feels that way. Let’s kick it off with this conversation. This is from Elon, and I’ll just read his tweet. He says, basically, “We will use Grok 3.5—maybe we should be calling it Grok 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.”

First of all, we’ve got this name escalation, right? We’re going to have GPT-5, and then Gemini 2.5, through soon Gemini 3. I think Elon feels behind on Grok 3.5. Numerical warfare.

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

That specific idea is actually low-hanging fruit and a real big win, but it’s one of many big wins. The rate of change in the models over the last 2 weeks since the last time we talked is just mind-boggling.

An experience everyone needs to have is this: if you pick up either Gemini 2.5 Pro or GPT-4 voice mode and just talk to it as you’re driving in a car for an hour or 2, that’s something you couldn’t do a month ago. Now you can do it, and it’s engaging. If you draw a line between a month ago and today and 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.

I think what Elon’s talking about here is that, believe it or not, the original training data for these models had a Reddit subreddit in it called “Microwave.” The Microwave subreddit has a series of M’s that goes on for thousands and thousands of lines, and then at the end it goes, “Beep.” That gets scraped and thrown into the training data. There’s a lot of crap.

I think Elon might actually be referring to a lot of his own tweets with Donald Trump here. If we get rid of that crap, then the neural net has a much easier time learning what really matters. This is part of a long list of low-hanging fruit that’s right in front of these training algorithms, so you’re going to see really rapid improvement just from the obvious, including this.

See what could possibly go wrong if AI rewrites the corpus of human knowledge? I’ve been watching a few videos of Yuval Harari talking about how AI can now program itself and program things. He’s going to go nuts on this type of concept. If you can edit history, where do you end up? Where do you draw the line? Who decides what’s accurate or not?

In the beginning, there was AI.

Exactly. God said, “Let there be AI,” and then everything followed from there.

This really will pose some huge philosophical challenges. On the plus side, there are so many gaps and so many flawed narratives. History is written by the winners of all the epic battles and wars in the past, and therefore we can balance out that viewpoint a little bit and get a little more reality into it. That would be great. But there’s a very dangerous line here, and I think it’s the right thing to do. It’s going to cause a lot of consternation.

So, we’re expecting Grok 3.5 any day now. It was promised in May, then delayed into early June. We’re recording this on June 26. He said by the end of June, so he’s got 4 days left. But even if it’s July, it’s going to be epic. I can’t wait to try to play with it.

I’m going to play this video, also from Elon. The subtext here is that superintelligence may happen this year or by the end of next year. All right, let’s listen.

I think we’re quite close to digital superintelligence. It may happen this year. If it doesn’t happen this year, next year for sure. Digital superintelligence is defined as smarter than any human at anything.

So here we’ve got the issue of definition, right? What is AGI? What is digital superintelligence? Dave, you and I recorded an episode that we’ll be sharing shortly with Eric Schmidt, going deep into digital superintelligence. His prediction is a little more pessimistic. It’s the next 5 years on his time frame. But what is it? Do you still have the confusion that I do when people are popping back and forth between AGI and ASI?

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

I would not doubt his timeline. I actually went on ChatGPT and Grok and asked them both for a definition of AGI versus ASI. Can I share that with you guys?

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.” Then it says, “ASI is an intelligence far surpassing the best human in every field, with creativity, problem-solving, and decision-making.”

Grok says, “AGI is an AI capable of performing any intellectual task that a human can do, with general problem-solving.” ASI is “AI surpassing human intelligence in all intellectual tasks.”

Even these definitions blur the line, but I go on my classic hobby horse here because we have no idea what we’re talking about when we talk about intelligence. I don’t need to get into that trope again, but let me suggest this: the minute you can prescriptively describe a task, an AI or a robot is going to be much better at it than you anyway. The work then comes down to what the task is prescriptively saying, and being smarter than any human being is a different kind of model.

Here’s where I’d like to see it go. You have Kepler, a couple hundred years ago, making an intuitive leap that maybe the moon is affecting the tides, and then making a massive intuitive leap that can be backed up with scientific and experimental evidence. That’s the kind of thing that, if AIs can do it, starts tickling at the edges of what we mean by intelligence. We have emotional intelligence, spiritual intelligence, and so on. That’s the end of my rant.

I think that’s going to happen. One of the predictions is that we’re going to start to see math, physics, chemistry, and biology getting solved by these advanced AI models in the next 2 to 5 years. This is what our friend Alexander Wissner-Gross keeps on hitting on. We’re going to solve math in the next 12 months.

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. 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,” is that he’s trying to create awareness and motion because people are underreacting so badly in so many areas.

As Alexander Wissner-Gross is saying, it gets miles ahead in areas like math 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. 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 a blur that comes and goes, and whether somebody was right down to the minute or not is beside the point.

Nobody will care a year later, but we'll care a lot about 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,” is a really good way of framing it. 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.

All right. I love this video. I asked the team to cut it. This is from Jeff Clune, who's a DeepMind adviser. 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 effectively invented a god. Do we want to sit around and let those people over there also invent a god?

What nobody talks about as much as they probably should is how quickly things might get nationalized. If you are the premier or prime minister or head of state of a country, and a company within your borders creates a superweapon, 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 run as a normal company? 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, called After On. Actually, it's the second time I've read it, and it tells a Silicon Valley story of the first ASI coming online. It is basically taken over by the government, and it is basically the last ASI because it suppresses other AIs around the world. It's a great story. Dave, what do you think about that?

Yeah, we have our side bet, and this really weighs in my favor. Look, the natural dynamic here is winner-take-all. You're going to see later in this podcast the amount of competitive pressure on these foundation-model companies to get the best talent, and the amount they're willing to pay is mind-blowing. Why is that? Because the natural dynamic is winner-takes-all: the AI becomes self-improving very, very soon.

So, the observation in that video is right on target. The only force that's going to—in our first slide here, we're saying, look, if the data that goes into these is one view, one point of view, and it's self-reinforcing, but it 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 America thrives on a variety of competitors in any given market, a variety of viewpoints—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 great wake-up-call video, and I completely agree.

Same: winner-take-all.

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. It'd be great to have a Polymarket on this, by the way. Let's do it.

But the idea that when something like this emerges, it might get nationalized is 100% true. There's no way that's not going to happen.

I think this is what the governments are doing right now. They're just watching their various folks work on stuff, and they're going to jump down their throats the minute something like that happens.

Nationalization may take a different flavor. It may be the government buying a significant share. We're going to talk about what the government is doing in AI.

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 you've lost it.

Yeah, well, I think that's going to happen. 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 prevent other people from getting there, or if they think they're getting there first.

The bigger picture might be: What if you have a particular worldview? What do you do with that when you have ASI? I have a feeling that ASI is going to skip 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—

Here's what I think will happen. Some ASI—call it whatever we want to call that—will emerge. A national government, 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.

In about 3 seconds, the AI is going to go, “Their worldview is so limited, right? This doesn't help at all,” and it skips right past all of that. I don't think once you have ASI it's within the potential for control by anybody, for sure.

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 based on absolute unverifiable truths or assumptive truths—like Mary was a virgin, or Muhammad was the last prophet, or Jesus was the son of God, or whatever. An AI—any kind of AI worth its salt—would skip past that assumptive truth instantly and go, “There's no evidentiary basis for that.”

I don't think there's much of any chance that the U.S. is going to nationalize a single AI company and say, “This is our national AI.” If you look at the way the Defense Department works, some things like uranium and plutonium refinement are nationalized, but all the missiles, inertial guidance, and defense systems are private-sector companies that work for the government.

That's going to be the likely outcome in AI as well in the U.S. Maybe not in China, maybe not in the Middle East, but certainly in the U.S.

Well, we're going to find out in the next few years. I think that's the key point here.

By the end of next year, clearly.

By the way, Jeff looks more like an AI in that than anything I've seen in a long time.

All right, this next story is one I want to dive into. The title here is, “Meta tried to buy Ilya Sutskever's $32 billion AI startup and is now planning to hire its CEO.” We'll get into this in a moment, but I just want to pass a theory by you. How does Ilya get a $32 billion valuation? He basically goes out and pitches Andreessen Horowitz. His investors are Andreessen Horowitz, Sequoia, DST Global—which is Yuri Milner—Alphabet, Nvidia, Lightspeed Venture Partners. I mean, the A-list of investors. And he raises, what was it, $6 billion of capital on a $32 billion valuation. How do you do that without any product or any tech to show?

And I have a theory. Here's my theory. You ready?

Yeah.

We just saw the presentation on the first ASI, the 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 AI companies. It will be a safe ASI, because 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 it to you. How do you think about that?

I think that's exactly right, and I think there's another point, which is that clearly the true, great neural-architecture people—the Ilyas, the Mira Muratis—are not intimidated by the progress that's been made at OpenAI, Grok, and Google. And that's an amazing fact by itself.

When you look under the covers, the research teams working on this are 10 or 15 people. They're not 10,000 people, and the innovations are still piling up. There are still 10× improvements out there. And so, undoubtedly, Ilya, having been an architect right in the middle of this, is saying, “Look, I know how to 10× this.” And I'm not afraid of the big guys.

Actually, the actions at OpenAI are kind of reinforcing that. OpenAI is racing to control the consumer experience by buying Windsurf for coding, having 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—succeeding wildly.

Because competing just as a foundation model is not necessarily defensible. And so it's not just Ilya; it's Mira, and then also some other things bubbling up out of MIT that are getting huge valuations because they're very likely to work. And so I think that's the other underpinning here.

We're in the middle of probably the greatest drama in human history, which is 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. More people should be getting involved and reacting and contributing, and not being intimidated, because Mira is not intimidated, Ilya's not intimidated, and the investors coming in to invest in Ilya are not intimidated.

A billion dollars a day. So, do you remember the meme that came out when Ilya left OpenAI, or staged the revolt? The meme was, “What did Ilya 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 is he 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 trusting you to know, and the fact that they have a confidence-based approach to saying, “We can beat the other models,” is huge. I think Dave's assessment is right. OpenAI is now focused on how to get the biggest consumer share in this, and they will go after those other white spaces that are there. There's a lot of white space, so applying this in all sorts of areas becomes huge.

But my big question is: How do you do this safely? I'd love to understand what he said 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. 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.

OpenAI CEO Sam Altman has some strong words about Mark Zuckerberg on a new podcast, criticizing Meta's recruitment methods and even its level of innovation. Deirdre Bosa with more.

It's cutthroat out there.

Brian, you're right.

Critical words may be an understatement. Sam Altman, on his brother's podcast, says that Zuckerberg is offering $100 million sign-on bonuses to poach top OpenAI talent. Keep in mind, those kinds of bonuses don't have cliffs. They don't vest over a number of years. $100 million just to get on board. There's nothing stopping talent from leaving in what's already a revolving door of talent in AI.

Did you get an offer of $100 million from Zuck yet?

No, but can I please be an intern at one of those companies? Maybe I'll get a $20 million signing bonus.

It's insane, right? So, here are the numbers just to put this in context. Meta is worth $1.8 trillion today, and it has $70 billion in cash. If you think of it that way, these offers of $100 million, or their acquisition offers on companies—Meta tried to buy SSI first—it makes sense. The biggest threat to Meta is that it falls way behind on AI.

Dave, what's your calculus here?

There's so much. First of all, I don't believe for a minute that it's $100 million to join, with no vesting and no restrictions. 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 look, these numbers again—you see professional athletes getting numbers like this, but other than that, it's unprecedented in human history. It's hugely justified if you get one of the key research talents at this inflection point 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. We heard on our tour through San Francisco 2 weeks ago, Peter, that Llama 4 really does suck. It's kind of embarrassing, and I know Mark tried to save it with a podcast world tour there. But if it sucks, it sucks. That doesn't mean they can't catch up in a heartbeat, though, because a couple of tweaks in the algorithm and suddenly you're back on top.

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 $1 trillion. I think that's the bet they're making. 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 really is a winner-take-all mindset. They're willing to do whatever it takes to move forward.

Can I game this out a little bit?

Yeah.

If we go back to the previous conversation, I think what Ilya has figured out is how to use AI to tweak itself, and that then gives you a very, very fast iteration path to what you're trying to do. 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. Now, regarding this particular thing, when WhatsApp was bought for $19 billion, everybody laughed at Zuckerberg and thought this was nuts, unprecedented, et cetera, et cetera. But it was actually a hugely important and relevant bet.

Given the past success in throwing money at this and going after it, you can see that he sees the market is that big, and this is pennies in the bucket, pennies on 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, he's aggressive, and he's super, super smart.

What's interesting, though, is that the other thing we learned on our tour through San Francisco 2 weeks ago is that there's a mass exodus of AI talent out of Meta. So then Sam is saying, “Hey, they're trying to buy everybody back for $100 million.” It's like, well, dude, you just took everybody, so it's fair game.

The question I have is, why were they leaving in the first place? Why did Llama 4 not come out the way they wanted it to? We'll dig in on that. I'll try to get to the bottom of exactly what's going on there. But throwing money at it is certainly one way to turn the tide.

The story here, again, is that 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 stage at Abundance 360. Again, Mark is 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 was also on stage with me a couple of years ago at A360.

The deal was $14.8 billion for a 49% non-voting stake in Scale AI. Dave, the IPO markets are just beginning to open in the tech and AI space, and the acquisition markets are getting hot. You're deploying Link Ventures' venture fund and investing in companies out of MIT and Harvard. How are you seeing the acceleration? It's been a relatively closed IPO and acquisition market over the last 5 years. Does it feel like it's opening up now?

I say, as of the last month, it's wide open. These are unprecedented, huge deals. CoreWeave's IPO is way up. Circle is way up because it's the way that agents can transact with each other.

The Yahoo moment clearly happened. The door is wide open. The deals are still concentrated among the top—the Magnificent 7—but Jamie Dimon sees that, Bank of America sees that, and everybody else sees that. Their banking teams are spinning up. Everyone's getting ready. It's going to be just like 1997–98 all over again.

That would be great. Much bigger.

Also, I don't know if people care, but the structure of the deal is really important, and I know a lot about the topic. 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 6-month torture of waiting for DOJ review. It does skirt the edge of the rules, but the rules are bright-line.

There are 2 parts to it. A 49% stake is not a controlling stake, so you don't have to report it. The other part is that it's a non-voting stake. There's another threshold at 19.9%, or 20% ownership, where you have to consolidate financials. Because it's a non-voting stake, you dodge that rule as well.

You might ask, “Okay, but do I really own the company?” Then you look at the contractual structure, which isn't disclosed. There's no public disclosure of the underlying agreement. That agreement probably says, “We own all the intellectual property,” and if you don't work your ass off, you have to clean the windows at Mark's house, along with a whole bunch of things that effectively make you own the company.

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. It's truly an acquisition.

So, Alexander, I'm curious. You and I have both spent time with Yann LeCun, who was previously heading AI at Meta, and now Alexander Wang comes in. Alexander Wang—I guess, Dave, he was a freshman at MIT, dropped out after his freshman year to start Scale AI, and became—was he the youngest billionaire out of MIT?

Oh, yeah. Yeah. By far.

And now he's going to Meta. I wonder if Yann is going to stay on at Meta. Any thoughts there, Alex?

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 that it's really attacking the heart of the problem, which is the tagging of data. If you have that, you can solve the garbage-in, garbage-out problem in a really powerful way, and then you can use much better models. You can use lesser models because you have much better data.

Yeah, I think Yann LeCun—just to bring it back to that—is 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 Geoffrey Hinton. Yann is kind of in that camp of saying everybody needs to slow down and be really, really careful about what we're about to unlock here.

Yeah, I think Mark, right? Mark is an engineer at heart. All these guys are engineers at heart. They're not trying to buy an AI philosopher. A lot of 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 1 million concurrent GPUs. I know how to change the algorithm so that it stays synchronous across this massive amount of compute. I know how to actually deploy the transformer algorithms. The SwiGLU isn't working. We need to go back to ReLU.” Stuff like that—that's what's in the minds of these mid-20-year-old geniuses.

That's what they want to buy. What's interesting to me is that normally the older, highly successful people, like 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. That's a new thing in the world as well.

Speaking about brainpower and money, Masayoshi Son, one of the old-guard investors, has pitched $1 trillion. He wants to replicate Shenzhen's 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.

$1 trillion, and he wants to recreate a kind of Shenzhen in the US, potentially alongside TSMC, of course, the foundry, and Samsung as well. You would imagine that OpenAI would have a piece to play, as would Arm. That is moving closer into data centers in terms of their CPUs aligning with AI accelerators. So it hits that and 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?

Several years ago. Yeah, I mean, it's changed in the last 5 years. I was there between 2014 and 2019, and it was an incredible hotbed. It was an engine of innovation.

The old mindset there was that 996 was the best lifestyle you could have: 9:00 a.m. to 9:00 p.m., 6 days a week. People talk about trying to replicate that, but there were a lot of entrepreneurs creating various new ideas there. It was basically a convergence 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. When we were at OpenAI, one of the questions I was asking D. Sculley was, “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 and Microsoft did?”

The answer was, “Yeah, we would do that, except the timeline to AGI is so short that we're going to have a multibillion-dollar or multibillion-person AI workforce before we could even finish the building and populate it.” You're like, “Okay, that's a pretty interesting insight.” Wow. It blows my mind.

Yeah, so then you're like, “Okay, well, Shenzhen—that's a huge number of people and buildings, 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 the 6 Ds, buddy: digitize, dematerialize, democratize, demonetize, and disrupt.

And here's a chart near and dear to your heart, Dave: Cursor, the fastest SaaS growth in history—$500 million of ARR in under 3 years, blowing away Anthropic, Uber, and OpenAI. Talk to me about this.

Well, this is so inspiring for the teams in the office at Link Studio. Link Studio now has 26 teams at MIT, Harvard, and Northeastern. These are startup companies that are being incubated at Link, and they're culturally just like Cursor: 3, 4, 5 best friends from school, brilliant but never having operated a company before, building something with AGI or AI that's groundbreaking.

They see a company like this thriving and hitting a huge valuation. But also, 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 have $500 million of revenue. The margins on that must be astronomical.

So they're raising a lot of money at a big valuation, greater than $10 billion-ish, but they can actually operate profitably on 1 day's notice if they want to because they're not headcount-intensive. These are the best companies financially that we've ever seen in history.

The timelines are just laughable—2 years to get to $500 million of revenue.

How many Cursors are out there in the next couple of years?

Dozens. It's actually constrained by the number of teams, not by the number of opportunities. It's fascinating, right? We have constraints on electricity, on chips, and on the smartest entrepreneurs who take this forward. At least for the moment, it's humans that are constraining things.

The difference in the vibe around Boston versus any time I've ever seen is just so blatantly obvious and palpable. You just need to walk around. Everywhere you go, everyone's talking about Scale AI and Cursor. These are their fellow alumni that they actually knew. The jealousy factor is a great motivator. It's really an amazing time.

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 a continuing increase in the velocity, scale, and speed. This is surprising even to us at some level, because the speed of it—I mean, $500 million in ARR on this timescale 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 are a really intriguing problem. How do you find the right teams? 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?

One of our billion-dollar investments is Mercor. That's all about finding and hiring, but is that for the general employee? I mean, what are the attributes of the founding team that you're looking for?

Yeah, great question, and 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 that. He's the Union Square Ventures founder, an MIT alum, and numerically the most successful venture capitalist of all time. He keeps a low profile, so we don't talk about him every day, but Fred Wilson is really a god of the industry.

What he says, as he gets older, is, “I always invest in teams of 3 or more best friends who write the code themselves,” meaning they're technical. They're really technical, all 3 of them or more, and I trust them. If they pass those 3 filters, I invest even if it's the stupidest idea in the world, because they'll change the idea much more quickly.

You can't change friendships, you can't change relationships, and you can't change yourself overnight, but you can change your idea overnight. 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 Erik Brynjolfsson, take them to HAI, take them over to OpenAI headquarters, and run them through Google. We're doing all that with these teams now. Then they come back home enlightened, and they always have good ideas at the end of that road trip.

Let me hit on one of the points there. People say, “Why should they be best friends? Why should they have been around each other and had a relationship for a number of years?” You just saw these large companies like Meta, Google, and OpenAI raiding companies and stripping out the talent.

If you've started a company with some stranger that you don't know and it's been 6 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's actually the number-one failure mode for companies: somebody bails, because you'll always succeed in the end if you stick with it. And so, the way you characterize this pivot—

Exactly right. A dozen times, and you’ll look—name any one of these companies that didn’t pivot at least once. Going back to PayPal, every one of them pivots at least once. 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 ends up killing the company.

The way I’ve been phrasing it for many, many years 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.

If it’s you and me and C[?] flying, we’re going to come off that plane energized because we’ve been talking about everything in the world for 8, 10, 12 hours. Not only that, we’ll have infected the 3 rows around us and gotten them all into a conversation. We’ll walk out with more employees than we started with.

When we had Singularity University’s Graduate Studies Program, the GSP, going, we were starting companies that had a 10^9-plus mission: impact 1 billion people over a decade. We were starting companies around the same exact time frame that Y Combinator was getting going.

The failure mode, I think, was that we thrust 100 alpha males and females into a room, independent of each other, and said, “Start a company.” That was very different from Y Combinator, where teams came in with an idea already and that glue preexisted, with something that they were all passionate about. I think that is a super-differentiator for investments.

If you look at the track record, the ones that did succeed were the ones that became friends and stuck together over time. The one thing we did do was create lasting, lifelong friendships. If you look back, a lot of those alumni have gone on and started working together where they found affinity, not necessarily on the teams. Team formation is critical, and that early chemistry is really important.

I remember, this whole conversation reminds me of Yossi Vardi, who kind of single-handedly created the Israeli startup scene. He sold ICQ, which then became AOL Instant Messenger, for about $500 million back then.

He did something amazing. He basically went to founders in Israel and said, “If you’re a good guy and you have integrity, I’m giving you $50K. That’s the bar.” Then he just trusted them, and he would check their integrity and character very carefully. Then he would just give them money.

He invested in something like 400 startups, and the outcome has been a little bit like the Fred Wilson type, where it’s just been off the hook. The team and the individual that you’re betting on are everything in this type of scale.

You’re so right, and you reminded me of something that’s 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 5 times higher there than anywhere else in the world per capita?

There are a lot of reasons, but a lot of it comes back to everyone having to do their military time. There’s a huge amount of bonding—marching through the desert together and suffering together—and that creates these lifelong friendships. Then you go to college and appreciate it a lot more, and then you start your company while you’re in college. They’re a little older, but a lot more bonded when they’re going through that experience.

If I port that back to the US, MIT is absolutely thriving like I’ve never seen before in terms of startup success. Daniela Rus, who runs CSAIL at MIT, the biggest AI lab in the world, has 2 daughters. One went to Harvard, and one went to MIT. Her Harvard daughter was constantly at MIT for the parties. Nobody thinks of MIT as a party school, right? Why would you? But when you’re there, it has an immense amount of bonding.

Part of it is because of 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. It’s like the Marines: you cannot get through on your own. You’re working through those problem sets all night long with your best buddies, trying to get through.

Really great point.

Just a plug here for Waterloo, which is the MIT of Canada. 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.

Well, if anyone’s listening out there in school administration, Harvard has a little bit less of that bonding culture because school is so stupidly easy. Everyone says it—Mark Zuckerberg, Alex, everybody says it. It’s also hard to get into and harder to fail out of.

One of our Harvard guys in the lab decided he was going to open a window and do a rock-climbing drill from the 2nd floor down to the 1st floor on the brick wall. There were cops all over the building and security guys running around, and they were like, “Dave, why are the cops all over the building?”

I said, “Guys, let them be. This is what they need. They need to bond. 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 we also can’t have the cops here every day.”

This is the culture that is ultimately going to thrive because it’s kind of lacking on the Harvard campus, and they need to create it. They are self-creating it.

All right. This next slide from Andreessen Horowitz is pretty epic. It’s labeled “What’s working” in the era of AI apps. GenAI startups are shattering growth records. Dave, this must make you feel pretty amazing.

This chart is a little hard to read, but if you look at the top quartile, it looks like they raised less money, but they actually raised it much more quickly. If you look in the bottom-right corner, pre-Series A dollars raised: $3.1 million. That means they were very capital-efficient in getting to $8.7 million in revenue run rate.

This is what I was saying earlier: the fundamentals of these companies are so good compared to the internet era. They’re very capital-efficient, with great ARR, and this is accelerating really quickly now.

One of our companies, Farsight, was talking to JPMorgan as a customer, and nothing was happening for months—just unresponsive. Then Jamie Dimon 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 important.”

All of a sudden, they called back. JPMorgan actually reached out to Farsight and said, “Okay, we want to talk. Get over here right now.” That’s going to happen now across much of the Fortune 500 and all of the mid-market. This will get even more traction very quickly.

I just love these numbers. They’re extraordinary, right? ARR of $8.7 million, with time to a Series A in 5 months.

Yeah. Extraordinary. Those are crazy-good numbers, but then look at the Cursor number from the prior slide: $500 million in 2 years. For sure, it makes us look weak, right?

You look at the bottom quartile there, though, right? They raised $10 million in Series A, and in 6 or 12 months they brought back a third of it.

That’s still an amazing number.

That’s a great point, Alex.

Yeah. $3 million in 12 months would have been top decile 3 years ago. Here, it’s bottom quartile. That’s a great point. An acceleration of the acceleration.

Here’s a big story in AI. This past week, the Trump administration announced that it is launching AI.gov. They’re hoping to launch it on July 4. I hope they hit it.

For those who have been frustrated by the government, this is a project being led by a Tesla engineer named Thomas Shedd. The idea is to see whether the government can use AI across federal agencies: the GSA, DOT, FDA, DOE, FAA, and all of these agencies, which have been sublinear in their existence at best.

Let’s talk a little bit about this. The GSA, the General Services Administration, buys everything for the government. It could use AI to optimize procurement, get vendor performance data, automate contract analysis, and really eliminate fraud.

The DOT is going to be predicting flight delays, analyzing real-time vehicle data, and 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? The DOE is about optimizing grid operations and forecasting demand and supply.

The FAA is going to see automated drone traffic management, weather avoidance, and—just as a pilot—the FAA’s air-traffic-control system is a bloody 1950s mess. Then, of course, we’ve spoken about the FDA using AI to enhance drug and device approvals, faster clinical protocols, and optimizing food safety.

If there’s 1 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: Palantir and AWS. Everyone was worried about how the government was going to interact with cloud computing. There’s a huge privacy issue here.

And is the government going to start building its own data centers and build its own cloud? Obviously, they don’t know how to do that. So then Palantir 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 ChatGPT. How’s that going to work?

Explain to people 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. Everyone asking, “What time’s a soccer game?” gets pulled in with someone’s tax return and goes into the training data. Then somebody else who queries ChatGPT says, “Hey, what do Peter Diamandis’ taxes look like?” and it just answers.

That’s not going to work. There are all kinds of concerns like that. But it’s going to be figured out in the private sector and sold to the government as compartmentalized AI modules. There are a lot of questions around whether departments can pull information and share their AI, so those are really tricky conversations.

But I guarantee none of the ideas are going to come from the government. What’ll happen is mandates will come out. This is what the state of New York just did. 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.” Then every private-sector genius can propose a way to do it, and they’ll just approve one of them. That’s what’ll happen. The same will happen with AI here.

Hopefully, the big AI companies are aggressive in building up their government-services operations, or they bless some other third party, like a Palantir-type company or a new startup, to become that entity. But 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. 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. Three quick points.

One, 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. I think that’s a huge area.

Second, 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?” You could do it easily using some of these technologies—blockchain, AI, et cetera.

The third point: If you were applying for a wind-turbine approval in Colorado, I think it was taking 2 or 3 years to get approval for that, right? Then they brought in a programmer who put it on Google Maps: Where are the electrical mains? Where are the water mains? Where are the flight paths? They were able to reduce that 2-year approval time to 30 seconds.

That’s just the smallest example of how you can do this across the board. It’s going to be a game changer. I can’t tell you how excited I am about the potential government applications of this.

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

Here’s a related story: The US Army appoints Palantir, Meta, and OpenAI executives as lieutenant colonels. This is a special unit created to support the government. Fascinating. I’m going to give some names here because they were published.

The employees include Palantir’s CTO, Shyam Sankar; Meta’s CTO, Andrew Bosworth; Kevin Weil, OpenAI’s chief product officer—Kevin’s going to be joining us on this podcast—and Bob McGrew, former OpenAI chief revenue research officer. I find this absolutely fascinating. They’re sort of indoctrinating them, and they actually made it super fast. There’s no required traditional training or boot camp for these individuals. What are your thoughts?

Peter, you didn’t read the quote there—the backlash quote.

The appointment of lieutenant colonels in the US Army followed the creation of a special unit for rich big-tech mavens seeking military leadership roles. This is exactly what you’re always saying: Everything turns into a drama whether it needs to or not. That’s just the nature of social media.

This is one way that the government can bring in extraordinary intelligence that they could never hire or recruit otherwise. This is sort of a part-time military service to make sure that the US government and the US military have access to the brightest minds.

Yeah, exactly. I don’t know the other guys personally, but Kevin Weil we know, and the guy’s brilliant. Perfect guy.

Yeah, absolutely. 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 likely to happen.

Go get the best guy on the planet. He’s absolutely the right guy. He’s a physically impressive manager who can actually move mountains while still being the nicest, sweetest guy on the planet. And he knows exactly how this stuff works. This is just great for everybody.

I don’t know. The negative spin here is nutty. I think 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, with people going, “Well, you can’t do that unless you’ve worked your way through the ranks,” and so on. People have a thing, but I think this is a great application.

This reminds me of the big problem around leadership training. We’ve spent decades and hundreds and thousands of bucks on leadership training, and then a few years ago it turned out the best leadership training in the world was World of Warcraft.

The fact that technology can outstrip this age-old human institution is unbelievable, but it’s there. I think that added to what these guys can do, plus bringing technology and their mindset to the mix, is where it’ll have the biggest impact. They’ll bring that mindset and hopefully infect the rest of the armed forces with it.

All right. Talking about breakthroughs in AI, I love this. Hats off to DeepMind for continually pushing new capabilities out that support all of humanity.

This is a DeepMind algorithm supporting better tropical cyclone predictions. It’s a 5-day track prediction that averaged 140 kilometers closer to the actual storm path. It’s the difference between hitting Florida and Georgia or Virginia.

This was trained on 5,000 cyclones over 45 years. There are about $1.4 trillion in economic losses from cyclones over 50 years. I’m excited about this. Thoughts?

Yeah. It’s a piece of AI folklore called the bitter lesson, which basically says that 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 3 years, but you’re not going to compete with the big-data approach. 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 50 years of weather research. There are so many of these around. The benefit to humanity, if we coordinate it and wrangle it correctly, is just immeasurable. This is a great example.

Alexander, what are your thoughts here?

I label this as “nothing to see here,” and I don’t mean that in a negative way. This kind of thing should be completely expected.

You take an ancient data set where we had human beings trying to hand-plot these things, which humans are never going to do that well, and now you throw AI at it, plus a rich data set that’s very bounded and whose history we know exactly. Of course it’s going to come out with a much better result, and thank God, because look at the predictive ability going forward.

The impact is huge, but I think we should expect that a thousand of these are coming out in the next 1 or 2 or 3 years.

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

Wait, can I just drill in on that? That's a perfect example. 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. That's an area where I would expect to see a breakthrough, whether it's something like that or weather prediction. 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 know what the answer could be, where we know definitively it's possible—and then put AI against that. My guess is we'll see earthquake prediction algorithms within the next 2 years, if not sooner.

Here's an interesting, controversial thought on this: Imagine if you could control the direction of a hurricane. Instead of having it hit Miami, you steer it down into Central America. You go, “Oh my God, why would you possibly do that? That's terrible.” Well, if you hit Miami and the cost of the impact there is $50 billion, and the government of Costa Rica says, “Listen, you pay us $20 billion and you can land the hurricane here,” that's an interesting arbitrage on geography. It's a crazy idea.

Do you know the mechanism that they'd use for that?

I mean, butterflies. The butterfly effect.

I think you'd use lasers and heating the atmosphere. Maybe it's magic voodoo dust. I don't know.

I can just see the other side of that coin, right? “Hey, Mr. Trinidad, maybe you want to pay us some money so that we make sure that hurricane doesn't hit you.” You get into all sorts of crazy outcomes. But if you can measure it, you can impact it, and I find this has huge and interesting implications.

Okay, our next story comes from Mattel and OpenAI. They've announced a strategic collaboration. I've talked about this forever, so I'm super excited. Your toys are going to become super intelligent with GPT-5. Your Barbie doll, your Hot Wheels, your American Girl—I know that you in particular like the American Girl dolls—and Thomas & Friends.

Sorry, buddy. That's okay. You've uncovered my deep secret.

I think this is going to be a boom for the toy companies. This is going to enable rapid early education for our kids. That's the area I'm really excited about, because the feedback loop, as you have interactions with these toys, will teach us a lot about the child. We can use that for understanding learning behavior, the guardrails that you could implement, and what their motivations are. I think it's so exciting, because we'll get more data about young children than we could ever have gotten before.

Yeah, I was a little surprised OpenAI wanted to touch this one. It's really clear, when you're talking to the AI voices now, that within a year they're going to be crazy engaging, super friendly, and a lot of kids are going to prefer talking to AI all day to talking to real friends. There's good and bad that comes along with that. I've loved every minute of raising my kids, and 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 kids' imagination, right? When you have to make up what your Ken doll or Barbie doll is saying, that's critical for fostering early curiosity and imagination.

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

Yeah. There was a friend of mine who had a product called Moxie, which was an AI robot. It was mostly being used for young kids with educational challenges—neurodiverse kids—in which case creating a best friend and helping them open up and communicate has real value. 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. These are some scary reports that came out. This is in Time magazine: “ChatGPT May Be Eroding Critical Thinking Skills, According to a New MIT Study.” Dave, did you track this?

Yeah, well, only because you put it in the slides. I said, “I better understand what's going on here. This sounds really important.” So I dug up the research and read it.

It's nothing surprising if you think about how Waze works. A lot of people don't know how to drive anywhere unless they turn on Waze. Places they go every day, they still could not get there without turning on Waze, so it becomes a crutch really quickly. That's what's happening here with writing, 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 just don't really understand what you wrote.

It's not at all surprising. When you write it up and put it in a headline, 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 some of the data. I don't know if you want to use this to recount what the study said.

No, it's really straightforward. 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. The failure rate on the top line shows your quoting accuracy for what you were just talking about.

If you use AI to write the same paper and then you immediately ask, “Hey, what was Shakespeare's favorite toy?” you have no idea. But you just wrote it down. “Oh, did I?” So that's a 75% failure rate if you use ChatGPT versus 11% if you're using Google, meaning you're actually looking up the data and then composing it.

When you're doing the writing, you're doing the research and the writing. You're effectively training your own neural net, and the data is being deposited in your brain. It is scary. It's going to become a crutch in terms of thinking, and it's going to get a lot worse.

I didn't read it as all bad, though. I think you got the work done 100 times faster in the left column. Sure, your neural net didn't have time to retain every little detail. Even if—I don't know if society's going to move 100 times faster—we're not going to retain every detail. It's just that simple.

So yes, as a teacher, you could say, “Look, the kids are not really learning this stuff,” but as a person moving through life, the kids are covering a lot more terrain. Isn't that more important? There, it's a mixed bag. It's not all bad. So, good or bad? What are your thoughts?

I have an 80/20 approach: 80% unnerved, 20% will navigate this.

The 80% is that I actually saw this with Milan, my 13-year-old. He was writing an essay and just used ChatGPT to write it, and he clearly had no memory of that essay. He would have fallen completely into these buckets, right? When I saw this slide, I was like, “Wow, this reminds me completely of what Milan just went through,” and he has no cognitive framing for what he wrote in that essay because he used the AI to help.

The other side of it is that it's happening much faster. I think the key question is, how do you effectively train kids on critical thinking into the future? A guest we might want to think about is Nicole Dreiske, who's actually solved this problem and found a way of teaching critical thinking to kids in a very active and very accelerated way compared to how we do it.

The last point I'll make is that I remember seeing a study that 52% of the CEOs in Silicon Valley are liberal arts majors, right? The ability to think in different ways is a critical factor of success in leading a tech company, and I find that really interesting. Paul Graham has a different spin on that: The liberal arts major succeeding is more tied to their desire not to do irrelevant, difficult things and to get to important topics, and it's just an easier way to get through.

It's a good filter either way. Yeah. Dave or Alexander, I don't know if you saw Andrej Karpathy's presentation at the AI Startup School. I showed it to my son Jet yesterday, trying to incentivize him about vibe coding, which Andrej came up with. He put out the tweet that went viral defining vibe coding, and my son's reaction was, “I want to learn how to code, not just vibe code.”

So I'm curious what you think about that, because the concept right now is that English is the new coding language, but there's a lot of value in fundamental coding.

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

I do want to hear it.

Of course you do want to hear it. You remember, right when I got out of MIT, I went to MicroStrategy, came back to Boston, and started my first company, DataSage. Our very first product used neural networks for handwriting recognition.

I took the backpropagation algorithm, read the raw research paper and all the differential equations, and said, “I've got to try and code this up on real-world hardware in assembly language.” From the day I started that journey until we productized it, it was 4 years of coding. That turned into a few million dollars in revenue, and then we skyrocketed from there. It all led to a billion-dollar exit when we did it.

Wow. Did you say you coded it up in assembly?

We had to. We started out in a high-level language, but you needed to squeeze every MIPS and every FLOP out of these processors to build anything scalable enough to work. We invented quantization, which is now all the rage, to try and shrink the parameter size—anything to get another 2× performance out of these things just to make it work. It was a lot of hard work.

Then this week, on Monday, I said, “I wonder how long it would take me to recreate those 4 years of work?” No joke, and I'm absolutely not exaggerating: it took less than an hour to vibe-code it from scratch to the exact same program. Even the demo—the graphical interface I put on it—I 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 the vibe coding can pull in, so just to be fair. But the broader point is well made.

Yeah. 4 years down to an hour is just mind-blowing—what you can do.

Your son is exactly right. Spend some time looking at the code and writing some raw code. You don't realize how much faster you are until you try to do it the old way, so it's really, really important to get that experience.

Let me give you the end of this. He went off and wrote a short story, kind of full-length, without any help, and it was mind-bogglingly good. I couldn't believe it. I thought he used AI to write the short story, but it was really, really good.

I think we're in this golden era right now. AI can do almost anything for you, but it's not creative yet. You still have to think. The human component is still by far the most important component.

I don't know if that period of time will last forever, but right here, right now, we're in such a golden era where you're empowered, but not demoralized or crushed. It's just such a wonderful next couple of years, and you've really got to take advantage of it.

All right, next topic here is AI and job loss. This was a Stanford survey revealing which jobs AI would most likely replace. They surveyed 1,500 workers and AI experts. 69.4% want AI to “let me focus on high-value work,” and 46.6% want it to take on repetitive junk.

Here are the occupations most likely to be automated: bookkeepers, payroll clerks, data-entry workers, insurance-claim processors, software roles, tax preparers, public safety, and telecom.

Dave, any thoughts?

The high-level thought is, look, everybody needs to become a user of AI to get ahead of this. The study would say, “Wow, it looks like bricklayers are going to be immune for a while.” But you're not going to become a bricklayer just because you get 3 more years. Robots are coming for that job, too. It doesn't really give you any actionable advice.

Yeah, exactly. Don't do that. Just start using AI every day, understand it, and ride the wave.

Let's double down on that. If you're listening to this podcast and AI sounds fascinating, but you're not a power user, how do you start? Alex, what do you start with?

Just take a task that you're trying to do and ask AI, “How would I do that task?” Then say, “Do it for me,” give it the raw data, and watch it go. It's pretty much that easy.

I love the point you made earlier, Dave, which is that I do use ChatGPT's voice interface when I'm doing my red-light therapy, taking a sauna, or driving. I'm having a conversation on whatever subject I'm curious about. It's extraordinarily educational and fun to have this back-and-forth with an AI, saying, “I don't understand that term. Could you dive in?” or “What's the data that backs it up?” or “When did that happen?”

Being able to have a continuous conversation—it's a childlike experience of asking why, why, why, and digging deeper.

That's exactly what you should do. Get out of the media rut. I know, Peter, you say this a lot, but we have the internet now. You can actually watch useful media like this or study KJ Hardrich[?] and his podcast. He's phenomenal.

Watch Lex Fridman and Dwarkesh Patel. 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. While you're listening to the podcast, stay out of the mainstream media. Do not listen to the rock stars of sports broadcasting, or whatever. It's going to distract you and suck you in.

You need that time back. Use that time this way. 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? A lot of those roles are being done because people have to do them, not because they want to do them. It's grunt work done repetitively, and it's perfect for automation.

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. Now we can automate 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. The drones did it in no time flat because they didn't have to think about it. We know exactly where the bricks need to be laid. It's totally prescriptive. Off you go.

Yeah.

This is a story from The Guardian: Amazon is testing humanoid robots to deliver packages. Took them long enough, right? We see Agility's Digit robot in the image here.

I was a little alarmed when I read that it's going to spring out of the van. That's going to be a little unnerving when that starts happening. My 2 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 where robots do the last 10 meters of delivery to your doorstep. It's just going to drop the cost of this. We're going to see drone delivery of products, and we're going to see autonomous vans and robot delivery of products. This is happening. There's no question about it. It's a when, not an if.

Agreed.

So the question is when. When do you predict, Alex?

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

Yeah, the technology is there. I think the humanoids are inspiring everybody. There's no surprise here. But what people don't talk about as much is the robotics doing nanosurgery and microsurgery, which are unbelievable.

The robots that crawl through pipes, clean things, and get into sewer systems are also taking off. They're not as sexy as the humanoids, but it's all happening concurrently. It's just a 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 the point you're making. Hold on, hold on, hold on, hold on. I thought of a great real-world example of my octopus idea. You've got a humanoid 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? Can we please have these humanoid robots have 3 arms?

No, we'll just have 2 robots with 4 arms.

Anyway, here's what's interesting: we're going to see these companies stack resources. I would not be surprised to see Tesla get into delivery services with autonomous vehicles and Optimus robots. We'll see Amazon and Agility, and we'll see other companies coming together on this—a full stack in the physical world.

Let's talk about robotaxis. Big news since we spoke last on June 22. The Tesla robotaxi launched in Austin with a flat fee of $4.20. Elon loves his 420 over and over again. Robotaxi is now live. Here is Elon at Tesla headquarters in Austin, and here's a quick video of what a fan experienced in a robotaxi. Thoughts?

Finally, he's done it. I think it's one of the biggest markets Tesla is going to experience. We've seen Cathie Wood predict it as a multitrillion-dollar marketplace. Tesla will have been known as a car manufacturer.

It will be known as a humanoid robot and autonomous robo-taxi service delivery company. Thoughts, gentlemen?

Two quick thoughts. One is, never bet against Elon. I've learned that through my massive investment portfolio suffering over the last decade. I think the second observation is that 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 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 worthwhile.

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 1 human eye—then, from first-principles thinking, an autonomous car should be able to drive with a couple of cameras. And that's basically great, except lidar can see 5 cars ahead.

Yeah, why not give it superhuman skills? You could do it. Why not do it? And yes, it's much more expensive for now. I think he went down a philosophical route of going away from lidar, and 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 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, when we were driving together a couple of weeks ago, that the inward-facing camera was new to me. It's actually watching your behavior and then adjusting. I was like, “I'm looking out the window to the left, and it sort of beeps at me. If I pick up my phone, it beeps at me. It's really annoying.”

I've kept my 2017 Tesla Model S for exactly that reason. There's no inward-facing camera, so it's great. I've now driven that car 4 times up and down the country, from Miami to New York or Toronto, so I've become a bit of an expert on the highway. Have you heard about this thing called an AI? You know what? I load up with five of my favorite kebabs, and I arrange 40 conference calls. The car drives itself 80% of the time, and it's free to do that. I arrive more refreshed than when I left. I mean, it's phenomenal.

All right, let's take a look at this next one. Tesla faces protests in Austin over Musk's robo-taxi plans. Protesters claim Tesla's FSD, or Full Self-Driving, has been linked to hundreds of crashes, including dozens of fatalities. Let's look at the data here. Here it is: number of accidents per million miles.

And without any question, humans are terrible drivers. We're distracted constantly now with at least 1 cell phone per car. We're terrible control systems for 2-ton cars going at high speed.

Can I throw out a quick data point here?

Sure.

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 those 3 days.

Okay, that was then. Today, you look at anybody driving, and they're looking at their phone. We absolutely should not be driving as human beings. I agree. We're going to see an extraordinary increase in safety. The idea of a 16- or 17-year-old driving a 2-ton vehicle at 60 mph through the streets, with very little experience and their phone distracting them, should scare the daylights out of everybody.

This is America's greatest Achilles heel, actually: we're responsive to sympathetic stories that are statistical rounding errors.

Or wrong. Or wrong.

Sometimes—well, look at the State of the Union address. Somewhere along the way, it changed to, “Let me call out 4 or 5 people in the crowd here and tell their personal stories.” You're like, “Well, how do I know if that's just—this could be 1 in a trillion, for all I know?” But that's okay. I'm just trying to sway a bunch of voters toward what I'm trying to get done here. We're ridiculously swayed by that. If you look at that prior slide, yes, hundreds of fatalities from self-driving—well, hundreds relative to what? You put your statistician hat on, and you're like, “This is clearly better.” But some of these are really, really tragic, and if it's all captured on video, which everything is now, it can sway opinion. This is where, if America is going to lose to China or to some other state, it's going to be for this reason.

It's the same concept when people hear about an airplane accident. “Oh my God, I'm fearful of flying.” Have you looked at the accident rates in cars? Flying is still the safest mode of transportation. 1.2 million people a year die in car accidents around the world.

Well, hey, nuclear power—we'll come to that later, I guess. But that's another case study.

And we will. Here's an important news bite from this past month in L.A. 5 Waymo vehicles were torched in downtown L.A. Waymo paused service in L.A. and limited service in San Francisco, Austin, Phoenix, and Atlanta. The question is, is this the beginning of the Luddite revolt? Are people responding against all of the technology?

Here's an image of the Luddite revolt from 1811 through 1816, and I have some data I want to share with you guys because I think it's worth noting. The Luddite revolt 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?

Named after the mythical Ned Ludd, the movement began in Nottingham and spread across the U.K. Workers, fearing deskilling and unemployment amid economic hardship from the Napoleonic Wars, destroyed machines and organized raids at night. The revolt involved thousands of people, and the British government deployed 12,000 troops to suppress it. Sounds familiar. Machine-breaking became a capital crime in 1812, leading to 17 executions and dozens of hangings, and the movement was crushed by 1816. Thoughts?

Well, this is the classic immune-system response, right? In a slight twist, I noted when I read this up that 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. 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 to destroy it.

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

I think we are, without question, going to have a revolt. How often, and where, and against which companies? We haven't really started to see job displacement truly occur, but when it does hit—and I think we'll be seeing it significantly in the next 2 to 3 years—we'll need to figure out reskilling and other mechanisms.

Can I give the positive spin here? Of course, we have no more Luddites. It's the fact that we've seen this kind of displacement fear throughout history, and we always survive it very, very well. On the reskilling, everybody's like, “Oh my God, how are we going to reskill?” Note that we have AI to help reskill everybody. You can pick your passion and say, “I want to be reskilled in that area,” and you'll get really good potential work. Also note that we're near full employment today and have been for a while, so we actually need a little more buffer in the labor market than we have today. Those are my positive spins, and I also understand the negative.

I am curious 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 deployed again on things like this.

This was just: arm the Waymo cars with little machine guns so they can defend themselves.

Fight back. This was a scary story: 2 children were shot while in a Waymo here in Santa Monica, at 2nd and Broadway. 2 teens were shot; their injuries were non-life-threatening, and they are now stable in hospitals. I don't know if you remember all of the scooters here in Santa Monica, if you were here at that time. People raged against the scooters because they were blocking sidewalks. They would literally throw them into the middle of the street. They'd decapitate them.

I think we're going to see, when we see Optimus robots and Figure robots on the streets, that we'll find them in various positions hanging from trees. Thoughts here?

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

Yeah. Okay. This was the slide about Waymo versus Tesla. Here's a tweet: “The downfall of Waymo began yesterday.” This was tweeted on June 23, about the launch 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, 5 lidars, and 6 radars versus the robo-taxi. Elon has held to his first-principles thinking: there shall only be cameras. But this would be a great Dave Blundin bet. Dave, do you have a particular preference on which one would win this?

Yeah. Peter, you know this topic far better than I do. My bet, knowing what I know, is that it’ll be about a 70/30 split. There are always 2 or 3 vendors in any given market in the US. It always stabilizes at that for antitrust reasons.

Tesla will grab the lead now because they put a bigger investment into the neural chips. On the other hand, Google’s got incredible technology. So, 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 “never bet against Elon” problem on the other side. Here’s the issue: it’s a huge capital expense that Waymo will need to roll out to do this nationwide. Elon’s got a different option. You buy a Model Y, you turn on self-driving, and it drives you around. You’re going on vacation for a week, and 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. 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. If you apply that model, which is essentially the ExO model—assets on demand, where you don’t own your own assets and let other people self-provision them—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. You remember last week: Elon and Trump finally break up, and now they’ll hate each other forever. I was like, “No, no, no, no, no, no. One, this might be totally made up. 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.

Anthony Scaramucci is going to join us back on this pod to talk about the administration. He was eerily, eerily accurate last time. When we asked him after inauguration, “How long will this bromance last?” he said, “I think 30 Scaramuccis,” or something like that, and it was really near dead-on, almost to the day. So, we’ve got to respect his views next time.

Yeah.

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

Let’s hit a couple of other quick ones. This is flying cars and drones. We’ve seen Trump sign an executive order on drones, flying cars, and supersonic travel. For these drone systems to actually work, you need to enable beyond-visual-line-of-sight mode. We’re seeing the US government support 5 regional eVTOL pilot programs. I’m super excited about Archer Aviation here in LA to serve the Olympics in 2028.

The other point here is they’re enabling supersonic travel by scrapping outdated overflight bans. The supersonic jets of the Concorde could not fly over the domestic US because of the sonic boom, and they’re providing FAA waivers in particular because a number of companies have come up with mechanisms to actually avoid or absorb the sonic boom. But this is going to accelerate aviation, as it should. There hasn’t been that much change in aviation for the last 50 years. It’s been incredibly slow.

I was wondering if all the privatization of space travel was also going to lead to breakthroughs for out-of-the-atmosphere hypersonic travel, because I don’t know if you remember, Steve Kishi was working on that.

I know way too much about this. It’s just really tough. I mean, the amount of energy required to build something that’s going to skip across the upper atmosphere—and there have been many companies who have died on that mission statement, with billions invested. The closest thing right now is Starship going spaceport to spaceport, but it’s still expensive.

Here’s another competitor we know about. We know about 3 or 4 of the companies out there providing eVTOL services. This is Wisk. It’s been selected by Miami to launch in that location. So, watch out for Wisk in Miami.

I don’t know if I want to talk about these eVTOL flying cars at all, Dave, but they’re coming. Interestingly, Dave, when we spoke to Eric Schmidt about this, he was not a believer in eVTOLs.

Yeah, I think it was a relative thing. There’s so much change going on, and so much of it is so impactful. I don’t think it was like, “Yeah, I don’t believe in this.” It was like, “Look, aviation—we have helicopters now. We’re going to have 4-propeller electric versions of them. So what?”

The “so what” to me is that they’re self-flying and self-driving. That, to me, is really, really a big deal. And they’re much safer, too. So, I do think it is a big deal. But he’s like, “Yeah, but relative to space and AI, is it a big deal?” And he was like, “Nah, not really.”

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 love it. That’s fine. I’m allowed to do that. By the way, I have a Porsche Macan Electric also, and it’s 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 how much further ahead Tesla was than all the other carmakers in many, many areas.

But let me go back to eVTOLs for a second. I think this totally changes the game. Why? Because real estate that’s hard to get to is priced very low, and it’s scarce, and therefore we pay a lot of money for that little waterfront property on a lake somewhere because there aren’t 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 really beautiful plots high up on a mountainside 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. I think that’s incredibly exciting for the future. There are huge economic implications for this.

Not to mention, many of us fly around a lot. How much of a nightmare is the damn commute into the city? Just having a drone corridor from Kennedy Airport into Manhattan would change the game.

Yeah, for sure. And that is coming. We’ve seen this with Joby, with Archer, and now with Wisk. You’re going to get a commute from downtown Manhattan to JFK in one of these vehicles, right?

Yeah. In São Paulo, it’s 2 hours to get to my office. Helicopters are the only option you have if you’re, like, not the safest. These are safe and solid, and I think they’ll start to become really a big deal. Tourism destinations—I mean, the list of broad effects this could have just goes on. This is hugely exciting to me.

I want to jump into the next subject, which is timely and critical: the demand for energy from AI systems, and a look at the US versus China. I think people need to understand we are going to become limited by power in our quest for digital superintelligence. So, how are we going to power this revolution?

China is rapidly scaling up on nuclear. They’re experiencing their equivalent of a Sputnik moment. China aims to surpass the US by 2030 in nuclear. I mean, the numbers are staggeringly pessimistic here. The US only added 2 reactors this century—2 reactors over the last 25 years. There are 94 total in the US versus China’s 58. China is building a reactor every 52 months. US licensing alone takes 10 to 12 years.

Yeah. Crazy. You know, this is the reason I love doing this podcast and look forward to it so much: 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.” It’s so fun to talk about it.

A lot of these things, like this, are so obvious, and this is America’s Achilles’ heel: 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 4 years or 8 years, and 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.

Yeah. I mean, we’re going to talk about nuclear in a future podcast with some of the CEOs in these industries. But Generation 1 nuclear power plants no longer exist. Generation 2 plants are still out there, including what we saw with Fukushima and Three Mile Island. Those were the dangerous plants. Generation 3 plants have been really manufactured over the last 30 years.

Generation 4 plants are those that have currently been designed and are fail-safe. They’re the kind of nuclear plants I’d put in my backyard. But the timeframe for developing these plants is insanely long, right? We’re talking, if you wanted to start today, it would take 10 or 15 years. That’s why Three Mile Island is being recommissioned: it’s already approved from a government regulatory standpoint.

It’s crazy. It is totally crazy. I’m really, really angry about this one. I’m trying to be constructive here, but we know that solar scales. China is going to have more solar. Let’s get to that. Let’s go to the next slide.

Wait, you got muted. You muted—I don’t know if you muted yourself or muted me. I get it. I’m just really mad. I was going to swear, and I thought it better to cut off the mic before I swore. All right, so I’ll let you take the lead here. China is winning the race to become a Type I civilization—in other words, a civilization that harnesses all the power hitting the Earth from the Sun.

By 2030, China will have the ability to build an entire U.S.’s worth of power generation from solar and storage alone, every single year. Look at this chart, Alex. Talk to us about this. You go, Dave.

Let me just gather myself. No, this chart—I added the gigawatt axis on the left because who the hell talks about terawatt-hours per month? What the hell is that metric? Gigawatts are a better way to look at it.

This is actually gigawatt utilization. They created about 700 gigawatts of solar panels last year, in 2024, and deployed 250 gigawatts of peak capacity. The hillsides are covered with solar. We covered that on a past podcast. It’s insane. They’re just rolling this out, building capacity and distribution.

Yeah. Just for context, the U.S.’s total energy-production capacity is 1.2 terawatts—that’s 1,200 gigawatts. Actual peak utilization is more like 0.75 terawatts. So you’re saying they created half of what the U.S. produces in solar panels in 2024 alone—just solar panels in 2024.

They have an advantage because they’ve got all the rare earths, and they can use those for solar panels and build out. They’re going to add more solar than the entire U.S. energy output in a little while, so that’s going to be crazy. It blows my mind that we’re putting restrictions on solar and not extending tax credits for solar and other things here in this country.

We need to unlock that in the biggest possible way and let the private sector go nuts on this. 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’m fine with all energy needs being made available, but where do we invest for growth? Solar is available today.

Can I just share a couple of points here?

Sure.

There’s enough energy that hits the Earth in 1 hour to provide the global energy needs of the entire year. One year’s worth of sun hitting the Earth provides global energy needs for the entire year.

Here are some additional numbers: Global solar capacity reached 1,300 gigawatts by 2024. About 1% of global energy needs is being provided by solar. It’s estimated that if you cover just 0.1% of the Earth—about 150,000 square kilometers—with 20%-efficient panels, that would generate 200,000 terawatt-hours annually, exceeding current demand.

So, how big is 150,000 square kilometers? It’s about the size of South Dakota. I’ve never been to South Dakota, but if it were covered by solar panels, it would be giving us a huge amount of energy.

The problem with solar for data centers and AI, fundamentally, is that the good thing about AI is you can move it to the power. You can move the data center, and that’s a huge advantage. The bad thing is that you need those chips running 24/7. They depreciate really, really quickly, and 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. Solar has the horrible flaw of being intermittent. It’s really good if you can store it, but the cost of lithium to store solar when it’s cloudy and raining is about 5 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 more cheaply.

There is a way, and we’re going to be talking to Bill Gross, the CEO of Idealab, right? He’s been using gravitational storage, which we’ll talk about. Rather than storing energy in batteries, you use the energy during the day—a portion of the energy—to move a large weight vertically.

This has been done with water for ages, but you move a large weight vertically, and then at night the weight gets pulled down by gravity and a generator generates electricity. It’s efficient, it’s available, and it works.

Can I throw out some thoughts here?

Sure.

In 2016, we crossed an inflection point where it became cheaper to build a solar-generation facility than a fossil-fuel facility, and almost all new energy generation since then has become solar because of that.

In 2019, we hit a more important inflection point: it became cheaper to build and run a solar facility than to just run a fossil-fuel facility. The CapEx and OpEx of solar are now cheaper than the OpEx of fossil fuels. That’s a crazy inflection point. It means we never need to build another fossil-fuel facility again. We should just be building solar.

The utility-storage problem has been solved at scale, as you’ve said. 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. It’s a little clunky, but it’s very workable until battery technology or Energy Vault–type systems, like the ones Bill Gross is doing, come along.

This is a known problem. We should be going full out on this. I think it was 100 miles by 100 miles to power the whole of the U.S.—that was Elon’s calculation. The one I saw was that covering 2% of the Sahara with solar panels gives you enough power to cover the whole world’s energy needs. Distribution is a challenge, but that visual is really a killer visual.

It’s absurd that we’re doing what we’re doing. Here’s the chart that Elon posted. Elon’s tweet was, “Solar is 100% of energy long-term.” There’s no question. This is what’s going to drive humanity forward.

The chart basically shows that it took 8 years for solar to go from 100 terawatt-hours to 1,000 terawatt-hours, and then just 3 years to go from 1,000 to 2,000 terawatt-hours. You can see that super-exponential growth curve exceeding hydro, coal, gas, nuclear, and wind.

Yeah, pretty amazing. I really like pumped hydro. It’s very, very efficient, but you need a lake about 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. That’s a lot of water.

Bill Gross has solved that with these gravitational towers. Basically, you pump huge, multiton bags of dirt up into an elevator shaft in a large building, or up a hillside if you’re near a mountain. He’s got this working today, and he’s got huge contracts. We’ll be talking to him about that.

I think storage can be solved, and I’m hoping AI is going to help us with new technology for it.

Yeah, that’s exactly what I was going to say. If you’re a materials scientist or a chemical engineer, I’m pretty sure that with AI’s help, in a couple of years—or maybe even this year—you could come up with a reversible chemical reaction that’s completely self-contained and stores huge amounts of energy.

You use solar energy to drive the reaction one way, and then when it’s cloudy, you run the reaction in the opposite direction. If you come up with something that’s 10 or 20 times more energy-dense than a lithium battery, which seems very viable, you’re going to be a trillionaire. Just figure that out. Use AI to help.

A couple of years ago, we tried to design an XPRIZE around this. The number was: Get off-grid solid-state storage 50 times cheaper than it is today. That would be viable.

Here’s another tweet from Elon: “Solar power in China will exceed all sources of electricity combined in the U.S. in 3 to 4 years.” It’s a wake-up call. China is going all in on energy production. It’s epic.

I have one more thing to say about this. I think this China-U.S. stuff is a little overhyped. I don’t think we’ll have that much of a conflict. I think it’s a stalking horse, but I think it’s a great comparator.

Yeah, I agree. It’s a great comparator. I don’t think there’s real, deep conflict there.

No, there’s not. But what it does is show the U.S. what is possible.

And to Dave’s earlier point, this is a structural issue we have in the U.S. We have 4-year election cycles, and we have no mechanism to look at 20 years and say, “This is the water, health care, and energy we need over a 20-year period. We need to solve this.”

You make an investment—running our venture funds, you know this acutely—but investors want to see liquidity within 4 or 5 years. They don’t want their money sitting out there for 10 or 15 years.

In China, they know they’ll still be in power 20 years from now. If you look at the data, they said, “You know what? We need to be the world’s biggest manufacturer of solar panels.” So it’s about 2004 or 2010, or somewhere around there, from that date to having the factories up and running and the production established. Then, when there’s a recession, you’ve got to keep cranking.

So, just keep the engine running because you have a 20-year view, 30-year view. Yeah, we just can't do that structurally in the U.S. And that's why we get so far behind in nuclear and solar and some of the other long-term trends. That is our fundamental Achilles' heel.

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

Big time. I heard Michael Saylor say Bitcoin will get to $21 million a bitcoin. I'll be happy when it gets to $1 million a bitcoin. That'll be perfectly good enough, I think, for most people, because that'll just put it at the level of gold, which is infinitesimal anyway as a global asset class. But I think there's a bunch of things happening that'll start to accelerate this. I heard Freddie Mac and Fannie Mae 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.

I'm really excited about the next story.

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

Yes. Circle Internet Group goes public and explodes—goes exponential.

There are 2 parts to the story. One of them is Jeremy Allaire, who's stuck with this for so many years, and he deserves every bit of his success for just grinding it out. It's always tough to be an entrepreneur. He had to grind it out over a long period of time with regulators all over him, different administrations, and people going to jail. What a persistent story.

Anyway, the reason this is so important is because agent-to-agent transactions can now be done in either Bitcoin or dollars. You can move back and forth seamlessly. The old method, the SWIFT network—the interbank messaging network—is great if you're trying to move $1 million to Hong Kong because it's only like a buck. It's terrible if you're trying to do a penny microtransaction with another AI agent. Crazy.

So this solves that problem. The current pricing model on AI is subscription fees. You give me $200 a month or $20 a month flat. But that's crazy, right? The utilization gets throttled because, if you're trying to write code or talk to your AI, it'll slow down every now and then. Why is that? Because there are too many users online. Why can't I just pay for what I use as I go? Well, it's because we didn't have Circle. The whole AI economy now needs to move to these micropayments, and this is what's going to enable it. That's why the stock is up so much.

Yeah, I've been texting with Jeremy. 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 to fuel, sort of, the opening of the doors wide open. Alex, thoughts?

I want to echo the kudos here for a slightly different reason. One of the big issues in the crypto world has been trust. You have a lot of scam artists and a lot of shysters. Can you actually deliver trust? Jeremy, over a long period of time, has demonstrated a rock-solid, stable, trustworthy environment.

That's not easy to do in an environment where everybody else is in the United States, and so huge kudos there within the U.S. jurisdiction of law, if you would, which is super important. Circle Internet Group is a financial technology company 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, my AI agents to transact microtransactions. It's finally going to enable what has been the full promise of the internet—not just data, not just video, not just words, but a financial layer. I can't wait.

Can I say one thing about stablecoins?

Yeah, sure.

It's awesome to have this pegged against the dollar, but once you have something, there are so many natural assets in the ground and out in the world. When you can peg a stablecoin against, say, real estate holdings or something like that, when that becomes possible—as long as the trust, again, needs to be there—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 that has large gold deposits underground. They've gotten a contract where they're going to peg a token against the gold in the ground and not dig it out. They can wait until the technology for extracting it more environmentally friendly is there. That's an extraordinary thought: There are so many assets that could be connected to a token or a stable token.

Yeah, it's great. It's the missing ingredient, actually, and kind of the trifecta of digital transactions, because Bitcoin has become a great store of wealth. But 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.

You don't want to have a huge balance sitting in Circle for a long period of time. What people will tend to do is park their money in Bitcoin, then, 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, it doesn't exist yet, but that would be the trifecta of the crypto circle.

All right. What an extraordinary couple of weeks since we spoke last. There are so many other stories I can't wait to cover with you guys in the next week or 2 ahead. Any travels coming up for you guys? Alex, are you orbiting the planet again?

I just came back from the 100th birthday party of one of Lily's grandmothers, which was unbelievable. I'm not going anywhere for a bit. I think I'll be seeing you soon, Peter, at the end of July in Utah, maybe. We'll talk separately.

That's great. Yeah, Dave, how about you?

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

Yeah, OpenAI headquarters. Our mega event on September 9th. Google agreed to host the pre-party at their headquarters. So, I'm basically going to be going back to San Francisco over and over. That's why I need that hypersonic plane. I just want to get back and forth a lot.