Thursday's Diet TBPN

Summary

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TBPN Podcast Summary

Episode: Thursday's Diet TBPN
Date: November 14, 2025
Hosts: John Coogan, Jordi Hays
Notable Participants: Jason, Tyler

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Episode Overview

This episode of TBPN dives into the ongoing turbulence around OpenAI, the changing economics of the tech sector due to rising debt, the sustainability of AI’s growth, and sector-specific news including Meta’s expansion and security updates from Anthropic. The hosts frequently question mainstream narratives, probe financial engineering behind big tech projects, and highlight concerns about both AI hype and long-term viability. There is a sharp, conversational tone punctuated by irreverent asides, data-driven skepticism, and sharp observations about the state of technology.

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Key Discussion Points & Insights

1. Debt Comes to Tech: The OpenAI Effect

Timestamp: 00:00–07:30

• OpenAI’s AI Buildout Boom: Jason discusses a “new seriousness” as tech firms, particularly AI players, take on debt at massive scale—unlike the simple equity-fueled risk-taking of the past.
• Tech now resembles oil & gas: The analogy of “data is the new oil” is explored in a financial context: tech is increasingly resembling the heavily indebted, capex-heavy oil industry.
• Notable Quote:

  “With the 1.4 trillion of backlog that OpenAI has… there is this worry that maybe the level of indebtedness could be risky. […] it feels like with tech suddenly talking about backstops, these are much more serious consequences than ‘a startup raised some money and it didn't pan out.’” (Jason, 00:44)

• Data’s real value: Hosts critique the “data is oil” analogy, noting most data is worthless, and refining (AI) is needed to extract value.

2. Data Center Financing: The Meta Hyperion Deal

Timestamp: 06:31–09:41

• Meta’s Manhattan-sized data center: Breakdown of a $27B deal where private debt finances Meta’s “Hyperion” Louisiana data center. Unusual structure: Meta receives $3B upfront, financed by the asset manager Blue Owl, rather than spending its own capital.
• Private credit vs. traditional banks: Contrasts between private debt players like Blue Owl & traditional banks (e.g., JP Morgan) and debates about systemic risk in increasingly opaque debt markets.
• Notable Quote:

  “You would expect that when… it’s a $27 billion deal… Meta went down, they spent $27 billion. […] No, they got paid $3 billion.” (Jason, 06:46)

• Flashpoint: Jamie Dimon’s "cockroach" remark about hidden risk in private credit, rebutted by Blue Owl’s CEO.

3. OpenAI Growth & ChatGPT Slowdown

Timestamp: 09:41–15:22

• Signals of deceleration: Tyler and Jason analyze CFO Sarah Fryer’s comments suggesting a slight decline in ChatGPT usage, possibly linked to content restrictions in August.
  • OpenAI plans to loosen these for adults in December to stimulate engagement.
• Growth reality check: Despite enormous user numbers (800M), sequential growth appears to be slowing. The hosts compare ChatGPT to other AI platforms, noting that “saturation” may be setting in.
• Notable Quotes:

  “There’s been early warning signs.” (Jason, 10:00) “If you get a digital guy, that’s pretty powerful because guys can do a lot of stuff.” (Jason, 13:40)

• Benchmarks & product upgrades: Hosts mock the lack of transparency in 5.1 releases and joke about being “in love with” certain AI model versions (14:26).

4. AI Bubble & Survivability: Zuckerberg’s Perspective

Timestamp: 16:01–17:55

• Zuckerberg’s internal Q&A: Zuck divides AI camps into optimists (superintelligence in 2-3 years), moderates (by end of decade), and pessimists (2030s). Meta, with strong cash flow, can weather a burst bubble; smaller, unprofitable startups like OpenAI are more exposed.
• Hot take: Prediction that only “large caps survive”—Microsoft buys OpenAI, Google nabs Anthropic, Tesla takes XAI.
• Employee churn & liquidity: High OpenAI turnover as employees cash out options, with the podcast speculating on what motivates talent migration within frontier AI labs.

5. AI Promise vs. “Real Economy” Penetration

Timestamp: 18:36–20:19

• Disconnect between AI and daily life: Multiple hosts note how basic business tasks (e.g., doctor’s office forms, paper receipts) still lag decades behind, suggesting AI’s integration into the broader economy will take decades.
• Quote:

  “General SaaS really does not… has not permeated as much of the economy as people think.” (Jason, 18:50)

• Field switched from 'explore' to 'exploit' too early: The field may believe it's reached a plateau prematurely.

6. AI Stock Volatility & Sustainability Fears

Timestamp: 20:19–21:48

• Wall Street unease: AI-related stocks fluctuating as growth decelerates, compounded by massive infrastructure spending outpacing current revenue (OpenAI: $1.4T projected spend vs. ~$20B annual revenue).
• Public skepticism: Altman addressing spending concerns publicly; the hosts joke about “beta bubble boys” and internet memes.
• Quote:

  "AI stocks have swung downward as doubt rises about sustainability and payoff. Perfect isn't good enough and any sign of weakness is a disaster." (Jason, 20:19)

7. Security, Asset Management, and Industry News

Timestamp: 21:52–end

• Anthropic fends off Chinese state-sponsored attack: Espionage campaign targeting tech and government, using AI models like Claude in the process; the blog post reads as both chilling and unintentionally humorous.
• Michael Burry’s retirement: Michael Burry liquidating Scion Asset Management, which hosts joke is a classic "top signal."
• Vine revival: Jack Dorsey backs “Divine,” a new version of Vine with 10,000+ old clips and an AI ban, reviving nostalgia and skepticism.

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Notable Quotes & Memorable Moments

• On Data Value:

  “Lot of data is worthless.” (Tyler, 02:59)

• On Tech's New Financial Complexity:

  “The fact that you're walking through that math is very different than what the venture capitalists in 2000 were doing.” (Jason, 05:09)

• On Infinite ‘Digital Guys’:

  “If we have infinite workers, that's like insanely bullish.” (John, 13:31)

• On AI’s Real-World Penetration:

  “I filled out a piece of paper at the doctor's office last week too.” (Jason, 18:45)

• On AI Industry Hype:

  “Recent history suggests that the gloom won't last. But… there is far more AI computing infrastructure spending than there is AI revenue, a gulf widening by the day.” (Jason, 20:47)

• Lighthearted Dismissal:

  “The White House last night tweeted, we are so back in all caps. What was that? What did that mean?” (Tyler & Jason, 21:48-21:52)

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Timeline of Important Segments

| Timestamp | Segment Description | |------------|---------------------------------------------------------------| | 00:00–04:03| Debt arrives in tech, data as oil metaphor | | 04:03–06:33| Lending for data centers vs. traditional asset models | | 06:33–09:41| Meta’s Hyperion, Blue Owl, and private credit vs. banks | | 09:41–13:03| ChatGPT’s growth slowing, content restriction repercussions | | 13:03–15:22| Model updates, benchmarks, and user engagement | | 16:01–17:55| Zuckerberg on AI bubbles, survivability, and sector M&A | | 18:36–20:19| “Real economy” lag, explore/exploit, talent churn | | 20:19–21:48| AI stock swings, spending/revenue gulf, Altman’s defense | | 21:52–22:40| Anthropic, cybersecurity, Chinese hacking attempt | | 22:40–23:26| Michael Burry closes Scion, market reflections | | 23:26–24:06| Vine revival (“Divine”), podcast sign-off |

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Tone & Style

• Language: Irreverent, data-savvy, skeptical, and openly speculative. Regular in-jokes about “digital guys” or “beta bubble boys” intermingle with deep analysis.
• Approach: Hosts blend market data, industry gossip, high-level financial analysis, and humor in a conversational and fast-paced format.

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This summary captures the full arc of discussion, focusing on the acceleration of debt in AI infrastructure, Meta’s innovative financing, slowdowns in ChatGPT’s growth, AI’s limits in real-world adoption, and the ever-present uncertainty in the tech and financial markets. Essential listening for those tracking the intersection of technology, finance, and the shifting realities of the AI boom.

Transcript

[Jason]

There is a bunch of breaking news, the big news out of OpenAI, of course, the OpenAI show continues. Sarah Fryer had some comments about ChatGPT's growth potentially slowing and it's unclear. It's not in decline, it's maybe deceleration. We'll have to dig into that. It had me thinking about, about debt and I was thinking about just the fact that the debt has come to, to tech for the first time really. And this was sort of my take and I'm a little bit, this is an area that I know the least about. And so I was doing some research, learning a different, learning about a different industry since it's just so abstract. Like we keep going back and forth on the, on the debt is coming to tech narrative as like it's very scary. We live through the global financial crisis and there's a lot of jitters when debt is around. It's like, oh, you could get wiped out, you could blow up. The backstop comes in. It just feels like all of a sudden we're talking about things with a much more serious consequence than like, oh yeah, a startup raised some money and it didn't pan out and it was a zero and it wound up being a write down. Even when Theranos blew up, it was only equity holders that were lost. It wasn't this entire industry. And it didn't turn into this like systemic issue. Right. But now it feels like with the 1.4 trillion of backlog that OpenAI has kind of opened up across a whole bunch of different deals, there is this worry that maybe the level of indebtedness could be risky. The level of risk in the system, the level of investment in the system could be something that's bigger than just, oh, if you're in this one name, you're taking a big risk. Now it's maybe like, hey, we're all taking a risk. And if we're talking about backstops, at least data is the new oil. And back then in 2006, his point was he was working as a data scientist at Tesco, which is this British grocery store. I don't know if you know this story, but he was working at this British grocery store chain and his point was we have all this data on a customer is in the rewards program. We see that they buy a Thanksgiving turkey before Thanksgiving. We see that they buy this type of paper towels or this type of milk or whatever. We have all this data, but we don't really do anything with it. The data is not valuable. We need to refine it much like oil into gasoline. And once we refine it into gasoline, then we can do things like targeted advertising. And so it was basically just a generic call to action for taking data science seriously. People have been saying data is the new oil for I guess, two decades now. And it never really sat that well with me because unlike oil, data is not perfectly fungible. So one tranche of data is not equivalent to another. Like Reddit is clearly very valuable since it kind of provided the backbone for GPT3. All the analytics data that flows out of some mobile game is basically A.

[Tyler]

Lot of data is worthless.

[Jason]

A lot of data is worthless.

[Tyler]

All oil has at least some value, essentially.

[Jason]

I mean, I guess there are different levels of crude, right. There are different grades. And I was actually trying to play out the metaphor more and I was wondering, can we get to a place where, you know, so we can wring intelligence out of raw data like the oil, and the result can be low octane gasoline, kind of like midwit, you know, level like slop, an AI slop, or it can be jet fuel, like a deep research report that's actually pretty great, or some code that's really reliable and really useful. But it all depends on the processing methodology. But the more interesting data is the new oil. Take that I don't think was considered in 2006 is that maybe the tech industry is going to look like the oil and gas industry soon. Like, I was looking up what, how much debt is in the oil and gas industry. It's over a trillion dollars of debt. It was 2 trillion, like, you know, a decade ago and then it went down and then went up. And it's like it's all just a function of like, how much oil and gas is going on, what are the new projects, how big are the projects, how much debt goes in.

[Tyler]

The difference is that if you identify oil in the ground and you figure out how much it's going to cost you to extract it and how long you think you'll be able, like basically estimating, like how much, how much oil is actually available.

[Jason]

Yes.

[Tyler]

In this site.

[Jason]

Yeah.

[Tyler]

Then you can lend against that pretty predictably because you know that the price of oil is going to fluctuate. But in general, as long as it's in, in some range, it will be like a profitable operation to pull it out of the ground. And I think it's a little bit easier to lend against that than GPUs. Today the big debate is around depreciation schedules. And we have a sense that a data center that has power and basically a box with a lot of power will be valuable in the future. But if you're, if a lot of the cost of a new Data center is GPUs, it's harder to gauge on what the value of those GPUs will be in four years than than it is. Okay. It will this oil like production site still be producing oil in five years? I think that's a bit easier to answer and easier to lend against.

[Jason]

The fact that you're walking through that math is very different than what the venture capitalists in 2000 were doing. Like Google was like the most pure play, just beautiful software business. So Google from 2001 to 2004 grew from 86 million in revenue to 3.2 billion in revenue and net income over that period went from 10 million to 400 million. And that includes stock based comp. So they were still making 400 million in profit with the stock based comp. Googlers made a lot of money, they gave away a lot of stock. And so it didn't look like an oil business. There was not this big capex build out. There was not this big. Even this crazy R and D phase, there was just not. There wasn't that much capital that went into Google before it became this monster cash flow machine. It was sort of an infinite money glitch. It was this beautiful algorithm that was just discovered and it was so elegant and it just produced this monopoly insane like growth rate for so long. But for a long time like tech just meant take a bet on a company and it's either a zero or a trillion dollars or something like that. And so it's a lot different. And I wanted to dig into like the actual structure of one of these deals. You remember the Hyperion release. Zuck went on threads and announced that he was going to be building a 5 gigawatt data center. It was going to be as big as Manhattan.

[Tyler]

It's like somewhat of a Manhattan project.

[Jason]

Somewhat of a Manhattan project, exactly. The crazy, crazy thing about that deal. So he spins up the, he puts out the announcement post on threads, says hey, we're going to build this 5 gigawatt data center campus. It's going to be online in a few years, it's going to be as big as Manhattan. And he shares some of like where it's going to be, how many racks are there going to be square footage, stuff like that. But he's basically just announcing that like hey, the project's financed, we're ready to go on this. You would expect that when, that it's a $27 billion deal, you would expect that, okay, Meta went down, they spent $27 billion. It's worth it. They're going to. No, they got paid 3 billion. They got paid 3 billion. And the reason is because Blue Owl financed it with external debt. And they are basically paying Meta upfront for the right to have them as a, as a tenant, as a leaser for a very long time. And so you have this massive data center project that's going to be paid for even if it's not producing any valuable toke. Zuck's still going to, he's not just going to default and be like, yeah, take the company. No way. He's going to pay. And so in exchange for that, they had 3 billion upfront. This feels deeply important to the current AI buildout boom. The tech story, it feels like an entirely new piece of the puzzle to understand where this technology is going. And I don't feel equipped to understand it at all. Private asset star Blue Owl has been flying high. Is it too close to the sun? So the article says, suddenly Blue Owl Capital is everywhere. This past Tuesday, the upstart alternative investment firm with an aptitude for private credit announced a financing deal for Meta Platform's $27 billion AI data center in Louisiana. That is Hyperion that I was mentioning earlier the week before at the PAC C I S Alternative Asset Summit in Los Angeles. Blue Owl's Co CEOs Co CEO Mark Lipschitz called JP Morgan Chase's CEO Jamie Dimon Cockroach, warning about risk in private credit an odd kind of fear mongering. So basically, private credit has been growing a ton. We've talked about this a few times. Aries is massive now. Blue Owl is really big and, and there's basically been this little bit of a fight emerging between where the debt is coming from. Do you do private credit or do you go with the traditional bank route? And so Jamie Dimon, at least I'm pretty sure he's going head to head against Blue Owl in a bunch of these deals. Jamie Dimon was cautioning investors about potential risks in the credit market by invoking a proverb, when you see one cockroach, there are probably more. And so he was referring to recent lo loan defaults, such as the bankruptcy of auto parts maker First Brands and subprime lender Tricolor holdings, as warning signs of broader credit issues. So Dimon noted that JP Morgan took losses on some bad loans and implied that trouble in one corner of the credit market could mean undiscovered problems elsewhere, implicitly casting doubt on the booming private credit sector. And so Mark Lipschitz fires back and he says, I guess he's saying that there might be a lot more cockroaches at JP Morgan. During a recent private call, OpenAI's investors asked about external signs that ChatGPT's growth is slowing.

[Tyler]

CFO Sarah Fryer this the external signs were, I think like App Store data. There was some data out of Europe. Oh yes, yes, yes, that's right, that's right. And it was hard to read into the European data because Europe, Europeans, they don't work ever. No, I mean it was coming off of summer. Right. And, and you know, Chat GPT is.

[Jason]

Popular with students, but European summer hasn't ended yet. There's been, there's been early warning signs. Well, yeah, walk me through some others.

[Tyler]

So I can walk through Alex's coverage. Sarah Fryer held private quarterly earnings call with the company's biggest investors. As usual, the numbers she shared were mostly up into the right. But behind the strong top line figures, a quieter question hung over the call. Was ChatGPT's momentum starting to slow? During the Q and A portion of the call, sources say Fryer was asked to reconcile ChatGPT's meteoric growth and weekly users from 250 in September 2024 to over 800 million now with external signs that the app's growth has slowed in recent months. Close followers of OpenAI's business have been whispering about these sign from research firms since late summer, but this was an opportunity for company backers to hear directly from leadership on the matter. After telling the investors to take third party estimates with a grain of salt, Fryer acknowledged a chink in ChatGPT's armor. She said time spent had declined slightly in response to, quote, content restrictions the company rolled out in early August. She then referred to the loosening of those restrictions that CEO Sam Altman has said will be implemented for adults in December. So, and Sarah says and OpenAI expects the decline in time spent to reverse. And so I don't think them announcing that they're getting into erotica is a sign of strength. Felt like something that you that they would do in order to stimulate growth while they get a bunch of other monetization online. Right. So like commerce ads, et cetera. The reason I reacted strongly to it was that there had been messaging, you know, around the same time of I don't want to be in a world where we have to decide between curing cancer and free education for the world.

[Jason]

Yes.

[Tyler]

And so then at that same time deciding we're going to do erotica.

[Jason]

It was very weird timing. It was very weird timing that those two statements like came out one after another. OpenAI has decelerated revenue before because they, I think they tripled and then they went to a doubling or they went, or they were quadrupling and then they went to a, to. To a tripling. And so they actually decelerated in 2024 and then they re accelerated in 2025. And so I was kind of saying, like, well, you know, there's a good chance that you could see deceleration in the future. It's happened before. Like, to be accelerating forever is basically impossible. But it would be interesting to track exactly how, how ChatGPT's growth is slowing. There certainly feels like there's just a.

[Tyler]

Level of saturation a month over month change in total visits to leading genai tools. ChatGPT is at the bottom of a list that includes Gemini, Deepseek, Perplexity, Grok, Claude, copilot, and Meta AI. The key difference here is that like, ChatGPT is so much bigger than these other platforms. They could still be adding more users on a per user basis than these other tools, even if their growth is slower.

[Jason]

Like Meta is not accelerating. Top line, top line users, they have like 3 billion users. Like no one's expecting them to accelerate. Top line users, maybe like randomly, one quarter, they accelerate, but not continually. And so, I don't know, it just feels like an odd thing. It's going to be very funny when LLMs plateau around 120 IQ and what we've created is just a digital guy, not a God.

[John]

This doesn't make any sense. If we have like infinite digital guys, that's like literally a guy is just like a worker. Yeah, if we have infinite workers, that's like insanely bullish.

[Jason]

He didn't say it's going to be. It's going to collapse the economy when we just get a digital guy. He said it's going to be funny. And I agree. If you get a digital guy, that's pretty powerful because guys can do a lot of stuff.

[Tyler]

You need a guy for everything. Yeah, that's. Middle class has apps.

[Jason]

Yes.

[Tyler]

The wealthy have guys.

[Jason]

Tyler, did you get a chance to read Fiji Simo's latest blog post, Moving Beyond One size fits All?

[John]

Yeah, Nothing, I would say super substantive in it. I think with the, with 5.1 they.

[Tyler]

Were like, we made our digital guy faster, better.

[Jason]

I mean, it is, it is crazy following this company so closely because in here there's a line that says with more than 800 million people using ChatGPT, we're well past the point of one size fits all. And 800 million sounds amazing. Except I feel like I heard the 800 million number like two months ago and I feel like they have been accelerating so fast you would expect them to be at 950. 900, exactly. And so the fact that they're repeating the 800 number is like.

[Tyler]

They're like, sorry, we can't add a third of the United states every month.

[Jason]

ChatGPT is officially in its Fiji Simo phase. If you're wondering why the upgrade doesn't come with benchmarks, have fun. Rune says you're you are confidently wrong about the internal dynamics of this. It could be better summarized as an infra cleanup. And NIR says the source for my top tweet is Fiji's blog post from today, when which discusses the release and its goals. I don't really know what else to say. Is there hunger for benchmarks anymore? I might actually take the other side of this here. I like that they're getting away from benchmarks. I wish they didn't do a 5.1. Just make it better and don't do a release and certainly don't tell people.

[Tyler]

Because what if because you're not in love with a specific version.

[Jason]

John I'm in love with 5. I'm in love with 5. Rune, bring back 5. I don't like 5.1.

[John]

When GPT4, like T4, like not 4 or anything. When that was the best model, they would do updates. They wouldn't like, say, oh, this is a new model.

[Jason]

Yeah.

[John]

And people could definitely tell. Oh sure, like, okay, they released the model. It's worse.

[Jason]

So you think putting a version number actually helps, like, fight back against that?

[John]

I think it's more. It's just like easier for people to tell it that it was actually a change when they're noticing something that they've been depending on.

[Tyler]

Yeah, yeah. Sources say that sources say.

[Jason]

Okay.

[Tyler]

Sources says that sources say CEO Mark Zuckerberg joined an internal employee Q and A and shared a warning about the AI bubble. First, he shared a breakdown of how different players from startups to big tech names like Meta should think about timing their bets. He described three camps in the industry, optimists who see superintelligence emerging within two to three years, moderates who expect breakthroughs by the end of the decade, and pessimists who think it'll take well into the 2000 and 30s. Each outlook, he said, dictates how aggressively a company invests. Then he expound expounded on a version of the answer he gave me recently. In our last interview, he noted that while unprofitable startups like OpenAI and Anthropic Risk bankruptcy if they misjudge the timing of their investment, Meta has the advantage of strong cash flow. He also made the point that while big tech has historically been relatively debt debt free compared to large companies in other sectors, the AI infrastructure race is leading Meta and its peers to start using leverage in a more normal way relative to their size. Like he told me in September, Zuckerberg acknowledged to employees that Meta's market cap could suffer if his timing is wrong and the bubble bursts. But the message was clear. We'll have the balance sheet to survive and emerge stronger than most on the other side. Super Dario was quoting that and said the obvious end game in the next two to three years is that Microsoft acquires OpenAI, Google acquires Anthropic and Tesla acquire acquires XAI. Only the large caps survive.

[Jason]

That's a nuclear hot take. In contrast, OpenAI employees stayed for two plus years sold $6.6 billion of equity last month. Many hit the $20 million cap. Morale and vibes are high, but so is the turnover rate. New OpenAI hires are often shocked by how many slack accounts get deactivated each day. There are dozens or perhaps a Couple hundred. X OpenAI XAI, Google, DeepMind researchers Founding companies in the current climate and this was talking about the simple answer. The liquidity of anthropic options is the worst among those frontier yeah, this is.

[Tyler]

Talking about how a lot of people have been leaving various labs, less people have been leaving Anthropic. And so Liang Chen is saying the.

[Jason]

Simple answer would be interesting is if is if companies started offering liquidity in the form of annuities. But I don't know. There's some way to deal with this. Like if you don't get employee liquidity, they'll leave for something else. They'll just go somewhere else that pays them a higher salary. If you give them too much liquidity, they'll leave and start new companies. Very, very tricky to manage the team. But that is the nature of these companies.

[Tyler]

One of my strongest beliefs is that it's going to take 20 plus years to get AI penetrated into the real economy. I filled out a piece of paper at the doctor's office last week.

[Jason]

I filled out a piece of paper at the doctor's office last week too. I finally realized why Docusign has so many employees. Because you need to go to every doctor's office in person apparently for decades to get them to use online form filling technology like General SaaS really does not has not permeated as much of the economy as people think. There's a company that makes paper receipts that's worth $20 billion. $20 billion. There are fax machine companies. The fax machine industry is still over a billion dollars still in my opinion. The entire AI field switched from explore to exploit two years early. Everyone convinced themselves no, this isn't the case. Look at our exploration and it's like watching someone go on a 50 foot walk and find a cool tree when the entire continent is still covered in fog of war. Now that the terrain seems known, it should be harder to convince yourself. I suppose this makes sense given a lot of people hint at being good as gone as soon as they have enough money. But no, not me. I've been gone for ages already. Weren't we talking about this yesterday? This idea of where will the next innovation come from? Where will the next breakthrough come from? Will it come from any of the Will it come from Xai?

[Tyler]

Will it come from DeepMind? Yeah, it's really tough right now. You can stay in a university system and be a student and be taking on debt, or you can go work at a lab and make have a good shot. At least if you did this a few years ago, have a good shot of making $20 million in a few years. And it's hard to give up that kind of opportunity.

[Jason]

This Wall Street Journal article has given more context on the AI boom says the AI boom is looking more and more fragile. AI stocks have swung downward as doubt rises about sustainability and payoff. Perfect isn't good enough and any sign of weakness is a disaster. This is what's happening. It's like you double revenue and your stock trades down. It's very, very odd.

[Tyler]

But everything core weave who again is the only NEO cloud in the platinum tier semi analysis is down 45%.

[Jason]

Recent history suggests that the gloom won't last. But the shakeup serves as a strong reminder that the early years of AI pose a challenge for investors. Companies at the heart of the of AI are now talking about years, plural of all major investments still ahead. There is of course real reasons to worry about the sustainability of the boom chief them is that there is far more AI computing infrastructure spending than there is AI revenue, a gulf widening by the day. OpenAI says is planning to spend $1.4 trillion in the next eight years, but is only pulling in around 20 billion of annual revenue today. Has the mood become that? CEO Sam Altman felt the need last week to defend the company on X, saying the spending was understandably causing concern. Wow. He says he understands your concerns. Jordy, if you're down today, you're a certified beta bubble boy. You literally bit upSANDISK WTF. Alternatively, you can call yourself a bad beta bitch.

[Tyler]

The White House last night tweeted, we are so back in all caps.

[Jason]

What was that? What did that mean?

[Tyler]

What? What did they mean by that? In what way were we back? In other news, Anthropic disrupted a highly sophisticated AI led espionage campaign. The attack targeted large tech companies, financial institutions, chemical manufacturing companies and government agencies. We assess with high confidence that the threat actor was a Chinese state sponsored group. I guess they were using Claude. I think is.

[John]

Yes, I think they were using Claude code actually.

[Jason]

Weird.

[Tyler]

They said they were vibe coding espionage.

[John]

Yeah, it was pretty funny. I read through some of the blog posts and it was like some of the interactions of like the hackers and it was like this is what they were saying to the model. They're like, okay, good job Claude. But I think this part is wrong. You can see like the actual transcript. Very bullish for Anthropic.

[Jason]

Michael Burry appears to be shutting down Scion Asset Management. He said, dear investors, with a heavy heart, I will liquidate the funds and return capital but for a small audit slash tax holdback by year's end. My estimation of value in securities is not now and has not been for some time. In sync with the markets. With heart, with heartfelt thanks, but also with apologies, I wish you well in your future investments. I do suggest investors contact my associate pm.

[Tyler]

Did he really. Did he really quit right before the market started correcting? Is this one of those, like, you know, 90%. 90% quit right before. 90% of gamblers quit right before. Apparently this they finally called the top correctly.

[Jason]

Yeah, it does seem odd.

[Tyler]

I mean, his memory will live on through meme images from the big short. Vine is being rebooted under the name Divine, with funding from Twitter's former CEO Jack Dorsey. The app plans to feature more than 10,000 previously archived vines and does not allow AI generated content.

[Jason]

That's remarkable. There have been so many vine revival attempts. Elon was talking about bringing it back at one point. I believe the founder of vine was talking about bringing it back and did a number of different projects. There was a project called V2. We will see you tomorrow.

[Tyler]

Can't wait.

[Jason]

10Am Pacific.

[Tyler]

Sure.

[Jason]

Goodbye.