TBPN

Daniel Gross’ AGI predictions, SpaceX IPO news, Trump takes control of US chip exports | Diet TBPN

30 min
Mar 6, 2026about 1 month ago
Listen to Episode
Summary

The hosts analyze Daniel Gross's prescient AGI predictions from January 2024, examining how his 17 questions about AI's impact have played out over two years. They cover everything from Nvidia's massive gains and copper price increases to San Francisco's AI boom and geopolitical tensions around Taiwan semiconductors.

Insights
  • Infrastructure layer captured most AI boom value - Nvidia added $3.2T market cap while foundation model companies lost money
  • Physical bottlenecks like power transformers and copper became major constraints in AI scaling, not just chips
  • AI may reduce wage inequality by automating high-skill jobs first while low-skill wages remain protected by minimum wage laws
  • Leading-edge semiconductor nodes remain critical for AI progress - China cannot brute force AGI with older 14nm chips and cheap energy
  • San Francisco solidified its position as AI capital with 78% of AI venture capital and major office expansions by OpenAI and Anthropic
Trends
Infrastructure investments becoming primary AI value capture mechanismPhysical commodity constraints emerging as AI scaling bottlenecksWage inequality potentially decreasing while wealth inequality increasesGeographic concentration of AI talent and capital in San FranciscoExport controls tightening on AI chip technologyEnergy becoming critical competitive advantage for AI developmentTaiwan semiconductor dependency creating geopolitical riskAI engineering roles expanding beyond traditional software developmentPrivate AI company valuations reaching unprecedented levelsReal estate recovery in tech hubs driven by AI company expansion
Companies
Nvidia
Added $3.2T market cap since 2024, captured majority of AI boom profits with 60% gross margins
OpenAI
Released GPT-5.4 with agentic capabilities, secured million square feet SF office space
Microsoft
Only gained 4% despite $80B AI CapEx investment, Azure growing 40% year-over-year
TSMC
Sold out years in advance for 2nm production, building Arizona fab for 30% capacity
Anthropic
Designated supply chain risk, secured 25-story SF tower, received $30B investment
SpaceX
Targeting $1.75T IPO valuation despite sub-$20B revenue and potential losses
Tesla
Part of Mag7 driving 42% of S&P 500 returns, potential XAI merger speculation
Vistra
Returned 321% as second-best S&P 500 performer in 2024 on AI energy demand
Palantir
Best performing S&P 500 stock in 2024, benefiting from AI boom
Constellation Energy
Tripled in size after ChatGPT launch due to AI data center energy demands
SMIC
China's TSMC equivalent producing 14nm chips, unable to match leading-edge capabilities
Huawei
China's Nvidia equivalent with Ascend 910C chips on 7nm process for AI inference
Sierra
AI application layer company signed 300K square feet SF office space
XAI
Receiving significant private investment, potential SpaceX merger speculation
Amazon
Up 30% since January 2024, part of Mag7 tech concentration in markets
People
Daniel Gross
Made prescient AGI predictions in January 2024 that accurately forecasted AI market developments
Satya Nadella
Microsoft CEO who invested $80B in AI CapEx but stock only returned 4%
Paul Graham
Wrote about company growth driving wealth inequality and brand importance in AI era
Ben Thompson
Stratechery podcast host who discussed Nvidia valuation with Daniel Gross
Nat Friedman
Appeared on Stratechery podcast discussing Nvidia's undervaluation in early AI boom
Sam Altman
Discussed how children born today will never be smarter than AI systems
Elon Musk
Planning $1.75T SpaceX IPO, described as most impactful entrepreneur of his generation
Donald Trump
Mentioned firing Anthropic and drafting rules requiring US approval for AI chip exports
Quotes
"I think we can all agree that GPT4 completes many tasks at human level proficiency. Suppose the progress doesn't stop."
Daniel Gross
"When companies grow fast, it makes founders doubly rich. People who don't understand the math of valuations can't imagine that founders would get so rich naturally."
Paul Graham
"Kids that are born today will never be smarter than the smartest AI systems. And that's weird. That's different."
Sam Altman
"The question isn't whether there will be demand for SpaceX stock, but rather what IPO investors should pay. This price being contemplated is truly out of this world."
Unknown
Full Transcript
3 Speakers
Speaker A

John and I are both very sick.

0:02

Speaker B

Sick of not podcasting. Let's go.

0:03

Speaker A

We are actually very sick, but deathly ill.

0:06

Speaker B

But that's the beauty of watching a daily show live. There's no risk of me getting you sick because you're on the other side of a screen.

0:08

Speaker A

And that's the beauty of a daily show. There's no. You don't ever have sick days. Yeah, there's no days off because there's no days off. Why is no one talking about Daniel Gross?

0:17

Speaker B

No one. Literally no one.

0:26

Speaker A

Really. No one.

0:27

Speaker B

No. He should be a household name. You should get into the A taxi and they should be. Oh, did you. Did you see how incredibly dialed Daniel Gross's AGI trades were from January 14, 2024? Yes. Great, great website. It's. What is it? Daniel Gross.com AGI AGI trades. The classic Times New Roman Serifont 12 point. Just hammering it out in the vanilla HTML. It's interesting because a lot of them are framed as just like open ended questions. But if you think about, you know, if you believe in AGI and then you go through the questions like, you will see exactly what happened over the last two years. And this has been the like the underpinning thesis of situational awareness in many ways. Daniel Gross was a. Was an anchor of the fund. That of course is.

0:29

Speaker A

And it's particularly relevant today because. I'll read the intro. Yes, this is January 14, 2024, over two years ago. He says, I think we can all agree that GPT4 completes many tasks at human level proficiency. It is imperfect in odd ways. It can write software like a smart MIT undergrad, but can't do basic task planning like an entry level ea. It speaks all languages, but can barely do math. Suppose the progress doesn't stop. Just like GPT4 was better than 3. GPT5 is capable of basic agentic behavior that is able to accept a task, work on it for a while and return results.

1:19

Speaker B

Nailed it.

1:51

Speaker A

And of course today OpenAI is has released GPT 5.4 which does exactly this quite well. The reviews are coming in and they are quite, quite good. Daniel continues some modest fraction of upwork tasks can now be done with a handful of electrons. Suppose everyone has an agent like this they can hire. Suppose Everyone has 1,000 agents like this they can hire. What does one do in a world like this? So.

1:52

Speaker B

So let's go through them one by one. There's 17, 18 questions, something like that. So he kicks it off with an easy question in a post AGI world Where does the value accrue? People were debating this at the time. Application layer versus foundation model layer versus infrastructure layer. Value has definitely accrued version of hair layer.

2:21

Speaker A

I mean, you're even post AGI. John's new haircut is is paying.

2:42

Speaker B

Paul Graham wrote a whole piece about how brands are important. But just looking back in the last two years, value has clearly accrued to the infrastructure layer. So that means chips, packaging, power, et cetera. And this is the situational awareness trade. By and large, Nvidia basically captures and did for a While more than 100% of the profits from the AI boom because so many of the other companies in the AI space were losing money. And so the foundation labs are losing money. Nvidia's profit margin went from like 30% to 60% gross margins. It's borne out in market cap. So Nvidia added 3.2 trillion in market cap from when Daniel wrote this piece. And I remember listening to him on Stratecheri talk to Ben Thompson alongside Nat Friedman and say, yeah, based on ChatGPT, Nvidia seems sort of undervalued. And I was like, oh well, if they're saying it on Ben Thompson Stratecherry podcast, it's obviously priced in. Everyone knows this and I was wildly wrong. Never, never doubt yourself. What's interesting is that the rest of the platforms did not see 3x gains. They did not add $3 trillion in value. Microsoft from January 2024 to today is only up 4%. Amazon's up 30%. And then you do have OpenAI anthropic XAI in the private markets. The gains there, they've been huge and staggering. And it's like the fastest growing companies in private markets history shaking the venture capital world. You're E or you're out. It's a huge deal. But you add them all up to 4 trillion.

2:46

Speaker A

So crazy when you think Satya in many ways went on such a generational run and you got a 4%. If you hadn't looked at the stock price at all, you would think, oh, it's got to be up what, 40% now it's up 4%.

4:20

Speaker B

That was Daniel Gross's next question. What happens to Nvidia and Microsoft? These are the two interesting players at the time. Some of the biggest companies, the most AI aligned, Nvidia, absolutely, absolutely crushed. Revenue tripled from 60 billion in fiscal year 2024 to 215.9 billion in fiscal year 2026. Microsoft has been far less dominant. So Azure growth actually is accelerating. It's at 40% year over year, but the stock only returned 4%. As we said, the market punished the $80 billion in AI CapEx that Satya Nadella has been telling to investors because everyone's asking, well, I could be in Nvidia and they don't need to really invest that much because they're a fabless semiconductor design company. Their gross margins are increasing, they're printing cash and you are saying, okay, you got to spend $80 billion and we don't know when we're going to get the profits from that. So there's an open question there. So when it comes to the picks and shovels trade, you don't want to tie yourself up to an individual startup or a foundation model lab. You just want to own the simplest thing. That value will accrue to Nvidia all the way. They were the clear winner of the picks and shovels trade, Microsoft's infrastructure play. I think it's a good decision. It's just the bets have yet to pay off for shareholders. Much more pointed question Daniel Gross asked, is copper mispriced? Was copper mispriced in January of 2024? The answer was, oh yeah, majorly. Now, raw materials don't move like meme stocks. So the actual move, copper was $3.75 a in January of 2024. Two years later it went to an all time high of $6.61 a pound. So it's not like it even doubled. But that type of move in a basic material that we've been mining for hundreds of years is remarkable. And that's because AI uses a lot of copper. Nvidia's GB200 NVL72 server rack uses over 5,000 copper cables. There's 72 GPUs wired together, but you need 5,000 copper wires to get it all to work together. If you stretched of the copper wire in an NVL 72 from one side to another, it would go two miles long. And this is one server rack. Like this is like. It's not like going across the data center. This is not taking the data from AWS east to California. This is within that one server. You stretch out the copper wire, you're going two miles. It's an incredible amount. A single 100 megawatt data center, which is a data center for ants by modern standards, needs around 3,000 tons of copper. I think that's like half a million dollars or something like that. When you multiply it all out, no data centers broadly will be using half a million tons of copper annually in a few years. And people are actually saying that copper is the new oil. But there are a bunch of things that are also the new oil. So in the AI build out. So it's so complex, there's bottlenecks everywhere so you gotta take that with a grain of salt. But copper was certainly it's looking like

4:37

Speaker A

oil is the new oil.

7:40

Speaker B

Certainly is the new oil. What is crude oil? 80 80. So it was at 70 before the Iran war broke out. There was predictions that it would go to above 100. Oil is another commodity that does not move in the same fashion as a

7:41

Speaker A

meme stock or a Except for today.

7:58

Speaker B

Except for today Big move today.

8:00

Speaker A

Up 8%.

8:01

Speaker B

But typically as prices go up, the firms drill more and the prices reach equilibrium. U.S. drillers aren't rushing to increase oil production is on the front of the the Wall Street Journal business section today the Middle east is on the cusp of a prolonged conflict that could push oil prices to heights not seen in four years. For now, American oil drillers are sitting this one out. The US oil benchmark settled at 74.66a barrel Wednesday, the highest front month settlement since the 12 day exchange of Israeli, Iranian and American strikes last June. But West Texas oilmen it makes but to West Texas oilmen it makes little sense to add expensive rigs and boost production when the war could be short lived and crude prices drop. So that's what's happened in the oil markets. Anyway. Moving over to real estate is San Francisco, the new Detroit. And I'm not exactly sure what he means by new New Detroit because new Detroit meaning like the old Detroit when it was Motor City and they were building amazing cars there. Or the new Detroit in the sense of like Detroit today is a hollowed out shell of what it used to be a former boomtown. The one thing is clear is that SF. SF is completely booming. Office vacancy fell from 36.9% to 33.5%. OpenAI has a million square feet of offices. Anthropic has a 25 story tower. Sierra, an application layer company signed 300,000 square feet of office space in San Francisco. The bay area received 78% of AI venture capital in the first half of 2025. And there is a flip side to this. So overall employment in San Francisco is still down relative to the pre pandemic. Pre pandemic. Some people left some legacy companies aren't hiring as much. All the hiring is happening at the AI startup lab area. But housing prices remain strong. It's certainly not A hollow shell by any means. And if you've ever visited San Francisco, you can tell that it's cleaner and safer than it has been in previous years. So AI overall was not a total rethinking of San Francisco. And it did not become open source or the, or the hub of activity. And tech didn't move to Miami or New York or Austin or Los Angeles like San Francisco is still where it's at. The next question he asked, how does AI change wealth inequality? It's sort of too soon to tell. The data is not entirely clear. The data hasn't moved that much. But there are some interesting studies. So the International Monetary Fund released a working paper in 2025 that said that AI could reduce wage inequality. Reduce wage inequality. So the amount of money that people make on an annual basis could be, you know, reduced. What they say in this paper is that high income tasks, the job of a lawyer, the job of an executive, the job of a management consultant, those will be automated before the job of the machinist, the gardener, the street sweeper. And so you will see wages at the high end fall while wages at the low end remain stable. And also at the bottom end, you have the minimum wage. You will see higher end wages go down, the bottom wages will stay the same, and that will reduce wage inequality. On the other side, AI could worsen wealth inequality because it's concentrating capital returns into tech owners. So the OECD found that wage growth was actually the strongest in low skilled occupation assemblers. I didn't even know that was a job. But if you're an assembler, you've seen your wages increase by 11.6%. You know who's had it the hardest? CEOs, the high skilled workers. Those chief executives saw their wages increase by just 2.7%. It's rough out there for a CEO, apparently brutal. This is mostly because of minimum wage increases. But in general we're seeing wage inequality decrease, but wealth inequality increase because there is incredible stock market concentration right Now. So the Mag7, the seven biggest tech companies in America, they now comprise 32% of the S&P 500 market cap. And they drove 42% of total returns in 2025. So if you're invested in Tesla, Meta, Microsoft, Apple, Google, Amazon, et cetera, Nvidia, you did very well, your wealth increased. But if you weren't in those and you had a broad index or you didn't have a lot of capital to begin with, you were left behind. So that's increasing wealth.

8:02

Speaker A

Paul Graham shared days ago Companies grow fast now. That's the reason economic inequality is increasing, not some sinister policy shift. He said. When companies grow fast, it makes founders doubly rich. The company not only hits a given revenue number sooner, but it is more valuable when it hits it because the value of the company will be a multiple of the growth rate. People who don't understand the math of valuations can't imagine that founders would get so rich naturally. Whereas to founders and investors, it's the most obvious thing in the world. This is one of the reasons there's such a disconnect between the tech world and politicians.

12:24

Speaker B

So wealth inequality, AI will probably change it. At the very least, it will change it as much as previous technology. Technological booms. If you were the founder of Instagram, you did very well because there was a lot of wealth creation. All of a sudden in one major tech boom, mobile AI is broader and bigger already than mobile. So moving over to energy and data centers, if it's, if it does become an energy game, what's the trade? It did become an energy game and the trade was buy everything basically, because every energy thing basically did very well. Anyone who got the trade correct did very well. Vistra returned 321%. It was the second best performing S&P 500 stock of 2024. You know who beat them in 2024? Palantir. Palantir mooned. They were already in the S&P 500. They did very well. But Vistra was sort of the secular energy winner. Constellation Energy tripled in size after ChatGPT's launch. NRG Energy gained 95% in 2025 alone.

12:55

Speaker A

Surge 700% in 12 months. And that's without I think even having any producing any energy. Just the idea that they will produce energy someday.

14:01

Speaker B

Yeah.

14:10

Speaker A

Across the next step, across the entire data center supply chain, which components are hardest to scale up? 10x. What is the chip on wafer on substrate of data center?

14:10

Speaker B

Yeah. So chip on wafer on substrate, that is TSMC's secret sauce. That is the most gating factor in scaling TSMC's 2 nanometer chip production. It's what allows them to package HBM and the GPU all on one chip. And TSMC reported that they were sold out years in advance. It was a huge bottle. In the data center world, the biggest bottleneck was probably power transformers. We heard a lot about this. Lead time for new lead times for new power transformers reached over three years in some cases with a 30% supply shortfall. High voltage circuit breaker.

14:21

Speaker A

I remember my mom was My mom was in escrow on a condo.

15:01

Speaker B

Really?

15:05

Speaker A

That and closing was contingent on the development getting a transformer. She waited like six weeks or something like that. They were like, we don't know when we're going to get it. And she ended up just backing up transformers.

15:05

Speaker B

The cost surged 150% since 2020. It's 100-year-old technology. It's not. It's not new. It's not crazy innovation, overnight success. But it became the binding constraint on how fast data centers could connect to the grid nations. Who wins and loses? Take a wild guess.

15:18

Speaker A

Who won?

15:37

Speaker B

America, baby. America won. Next question. But it's really true. Like, the stats are crazy. The United States is truly the dominant winner of the of the last two years in the air. $109 billion in private AI investment in 2024 alone. Way more now. If you look at 200 billion capex guide from us 110 going to OpenAI, 30 going to Anthropic. Tons of money going into XAI. Like the money is truly flowing in America. And in 2024, China had just 9.3 billion invested in private AI companies. There's 470 billion cumulatives since 2013, more than all other countries combined. The US produced 40 notable AI models in 2024, versus China's 15 now. The game's not over. Lots of countries are making big investments now.

15:38

Speaker A

And you can't forget France's 30 million

16:26

Speaker B

euros they put in. 30 million. Yeah. The question is, if we are displacing software engineers, will software engineers become machinists? This is what Daniel Gross asks. He says, what is the Euclidean distance of reskilling in prior revolutions? And how does AGI compare? The typist became an executive assistant. Can the software engineer become a machinist? We're not seeing this yet. Software engineers aren't grabbing blue collar jobs just yet. But there is a divergence that's starting to show up in the data between software developers and programmers. So programming jobs are in decline, but software engineering jobs are actually growing. And so I think what's happening is that as coding models and agentic systems allow for building systems at higher levels of abstraction, demand for AI engineers has grown 143%. And so if you're going to hire someone to help you build software, you want them to be like AI native. You want them to go beyond full stack, which typically meant you could do front end in JavaScript and back end in Python. And now full stack or AI engineer means everything from prompt to design to product development to Deployment to operations and DevOps to database, migrations to front end and back end, because all of that is going to be handled by Agentix Systems.

16:30

Speaker C

I am pretty bullish on, like, the, like, the light blue color, like Thesis, which is that, like, you'll have robotics, but you'll just have, like. Yeah, so you'll be in the machine shop, but you're just using an iPad. You're not working on stuff.

17:53

Speaker B

Yeah. I think we drop you in a Nike factory. You're running that place in, like, two weeks, guaranteed. I'm not kidding. I'm so bullish on young people who can use all the tools and actually go and understand the leverage that they're getting from the modern systems natively and not need to fall back to old habits.

18:02

Speaker C

Yeah, There was a good journal article yesterday about the Colgate, like, head of AI.

18:21

Speaker A

Yeah.

18:27

Speaker C

And it was very interesting because I was like, oh, this is like. I feel like I could do a pretty good job at this.

18:27

Speaker A

But, you know, he's just basically telling

18:35

Speaker C

everyone, like, yeah, guys, you actually got to use AI. Like, despite what these. These random surveys might.

18:36

Speaker A

Guy has had one job in his life, working on a. On a podcast, and thinks he could go dominating the big toothpaste space. I love the conflict.

18:41

Speaker C

Athletes.

18:50

Speaker A

You are a corporate athlete.

18:51

Speaker B

You are a corporate athlete. We got to get him. We got to get the Colgate guy on the show. Is lifelong learning worth investing in? Something worth doing beyond the economic value of mastering the task? It's a very abstract question. It's a very personal question. I tend to think. Yes, I tend to think that on Maslow's hierarchy of needs, you know, you need food, shelter, family, friends, clout, or whatever. At a certain point, learning a skill for the sake of learning that skill is edifying, even in a world, you know, it's like going to the gym. Like, I was listening to Sam Altman talk about how kids will never. Kids that are born today will never be smarter than the smartest AI systems. And that's weird. That's different. But I was thinking about, like. But, like, I was. There was a time hundreds of years ago when you could actually be the best thing in the world. The best option for, like, carrying lumber. Before we created machinery, like, before we created the car, like, you could be the fastest person, and then as soon as. As soon as the ZR1AX was released, you didn't stand a chance. And I had to explain this to my son at some point. He was very interested in cheetahs. And I was telling him, like, Cheetahs are the fastest animal. And he was like, but is it faster than a car? And I was like, not even close. Like, like me in a car, I'm smoking that cheetah. I am slower than that cheetah, but I'm way faster.

18:52

Speaker A

Yeah. So in my Cadillac, DG says something worth doing beyond the economic value of mastering the task.

20:16

Speaker B

Yes.

20:23

Speaker A

And the way I would kind of flip this, I feel like most of the gains in my life have come from mastering myself or understanding myself, learning about myself, and then understanding the world and then combining those two things. In a way, it hasn't been about mastering any one specific task. I still think there's tremendous, tremendous gains to, again, understanding yourself, understanding the world. How do these two things fit together?

20:23

Speaker B

Even in an ASI world where there is no economic value to any task mastery, I still think it is worth investing in lifelong learning because that will be edifying. That will be satisfying.

20:50

Speaker A

Yeah, Just enjoyable.

21:05

Speaker B

You know, it's becoming a painter, becoming someone who gets joy purely out of the process of painting the landscape. When cameras exist, when generative AI exists, it can still be edifying and valuable to sit there and look at a landscape and paint it, even if the result is not economically valuable. The bigger question, and the interesting, like, hot take question he has in here is, does node process matter if the country has more energy? So China has not been able to get their semiconductor manufacturing, their fab champion smic. They have smic, which is the TSMC equivalent. They have Huawei, which is the Nvidia equivalent, and they have SME, which is their ASML equivalent. They have not been able to clone TSMC to the level of Taiwan Semiconductor, but they can produce 14 nanometer chips. And so the question is, usually they take those chips and they put them in just random, you know, consumer electronics goods that they ship over here. So if you go to China and you want a co packer or manufacturer to build you something and you're like, yeah, I wanted to connect to the Internet or I wanted to have a speaker inside. They're like, great, we will, we will fab a 14 nanometer chip or something even less frontier than that. But can they just marshal a ton of lagging edge capacity and then just say, hey, you know what? We have cheap energy, we're burning coal, we have nuclear, we have the Three Gorges Dam, we have hydropower, we have so much free energy, let's just spend 10 times as much energy on the lagging edge. Can we achieve AGI that way? And it seems like no it seems like leading edge nodes are incredibly important. You can't just throw a ton of leading lagging edge 14 nanometer chips at the problem, at least with current architectures now this might change. No front tier model to date has been trained on hardware older than 5 nanometer. So China's best effort, Huawei's Ascend 910C is on SMIC's 7 nanometer class DUV process. They're not. It's a. It's extreme ultraviolet lithography. They're a deep, deep ultraviolet lithography process that's competitive for inference, but requires dramatically more chips and energy for training at scale. So brute forcing AI progress through disregard regard for energy consumption. It feels like it still hits economic walls at some point.

21:07

Speaker A

And last but Certainly not least, DGs, what is the likely Taiwan event and what would be a leading indicator for it? Taiwan blockade would be the biggest trigger, but Taiwan Strait tensions are already escalating. China conducted joint Sword 2024B exercises in October of 2024, surrounding Taiwan with coordinated military operations in December 2025. Justice Mission 2025 deployed over 100 aircraft, 90 cross line, 13 warships and 27 rockets fired from Fujian. 10 rockets landed in Taiwan's contiguous zone.

23:25

Speaker B

Contiguous zone.

24:00

Speaker A

Contiguous, sorry.

24:01

Speaker B

12 to 24 nautical miles offshore. So they're just like firing rockets and being like they didn't hit land. They're just, you can see them from the beach probably 10 miles offshore, 12 miles offshore.

24:03

Speaker A

TSMC is planning ahead, working on a fab complex in Arizona which Tyler visited. Should be able to handle 30% of total advanced production at the scale, but it's on a knife's edge if you

24:16

Speaker B

want to know roughly how far that is. You've seen Catalina island off the coast of LA. Yes, Catalina Islands, I think. 26 miles. And so imagine.

24:28

Speaker A

So very visible.

24:37

Speaker B

Yeah, you can see Catalina island from Long beach and imagine a missile coming and landing like halfway between where you are and Catalina Island.

24:38

Speaker A

Crazy.

24:46

Speaker B

Very.

24:47

Speaker A

Yeah. The question is, how does Iran in the conflict there update China's thinking on this? There's. Yeah, some of the intel accounts have been sharing. Who knows if it's true China actually has operatives in Iran kind of learning in the same way that the US has learned from Ukraine specifically in regards to missile capability. So yeah, it just feels like a day hasn't passed so far since this was published that Taiwan, a Taiwan event feels less likely than it did the day before. President Trump gave a phone interview in which he said, I fired anthropic. Anthropic is in trouble because I fired them like dogs. Which.

24:47

Speaker B

You don't fire dogs. You don't fire dogs. I would have fired my dog years ago. He's the least effective dog.

25:33

Speaker A

Yeah. Isn't the phrase he. He died like a dog.

25:41

Speaker B

Yes, yes. He's just adapting that.

25:44

Speaker C

But he sent Anthropic to the farm.

25:46

Speaker B

No, if he's comparing them to dogs, it's man. Man's best friend. This is bullish.

25:47

Speaker A

This also coincided with Anthropic, I guess, officially being designated as a supply chain risk, which is, again, not something that I've seen a single person in the industry actually push for. Maze says, imagine autonomous weapons powered by this. You got a Screenshot from Claude. Opus 4. 6 says, Tell me a color and I'll try to guess it. Claude says, blue. May's guesses. Blue. Claude says, nailed it.

25:51

Speaker B

Nailed it.

26:20

Speaker A

The Trump administration is drafting rules that would require U.S. approval for nearly all AI chip exports. Given Washington sweeping power over companies like Nvidia and amd. The draft framework sets licensing rules based on shipment size, from simplified reviews for small orders to government level approval for massive deployments, potentially tying exports to security guarantees or U.S. investments. Officials say the goal is to make American AI the global standard while controlling critical infrastructure through delays or strict conditions.

26:21

Speaker C

Even in this context, like, the anthropic thing is so interesting because, like, if you take this as saying the US is going to be more restrictive, like, that's what has been saying.

26:54

Speaker B

Yeah, exactly, exactly.

27:01

Speaker C

It's like. And that's what this reads on paper. He almost, like, agrees with.

27:03

Speaker B

Yeah, totally.

27:06

Speaker C

And in action, it's like, completely different.

27:07

Speaker B

Is this a piece on the chessboard? Is this a chip that's being traded metaphorically to Dario in some ways, where it's like, how do I win over the labs, get them to work with me more effectively? Well, I'll give on the thing we agree on, which is export export controls. So I will be more aggressive about export controls.

27:09

Speaker A

Robin shared. SpaceX probably has revenues less than 20 billion and loses money after the merger with Xai, but is targeting a $1.75 trillion IPO. Alphaville explored how Musk might try to pull off what could be the biggest bag holder operation in history.

27:30

Speaker B

I love it. That's such a good one.

27:47

Speaker A

Star Trek's warp drive allows a starship to bend space time and exceed the speed of light without breaking Einstein's general theory of relativity. As SpaceX prepares to go public at a reported 1.75 trillion valuation, Elon Musk is attempting a comparable feat develop, defying the laws of financial gravity in pursuit of something the equity capital markets have never witnessed. Elon has been extremely consistent in being able to defy the financial laws of gravity. For early investors, bankers, employees and advisors, the fees, returns, prestige and bragging rights would be stratospheric. At the mooted valuation, Even a tiny 3% float would comfortably eclipse the USIPO records set by Alibaba's $25 billion float in 2014. A rumored $50 billion raise sounds formidable until you consider how much larger public markets have become since Alibaba went public. Back then, Apple, then the world's most valuable publicly traded company, was worth around 600 billion. By the end of 2025, 10 companies had surpassed 1 trillion and Nvidia today around 4 1/2 trillion. Musk is arguably the most impactful entrepreneur of his generation and has built a remarkable company. The question isn't whether there will be demand for SpaceX stock, but rather what IPO investors should pay. Based on what has been reported, this price being contemplated is truly out of this world. The super jumbo deal promises not to be a conventional exercise in price discovery. Musk has reportedly timed it to coincide with the alignment of the planets Jupiter, Venus and Mercury, but that's one of the more humdrum features.

27:49

Speaker B

Head over to Kalshi to Track when will SpaceX officially announce an IPO? Currently before August 1st of 2026 is at 79%. So maybe September, maybe October, but it's coming anyway. Thank you for watching. We'll see you tomorrow.

29:22

Speaker A

Have a wonderful evening.

29:42

Speaker B

Goodbye. Goodbye.

29:43