The Cournot Equation, Micron’s $200B Bet, Hollywood vs. Seedance 2.0 | Diet TBPN

Summary

TBPN Podcast Summary

Episode: The Cournot Equation, Micron’s $200B Bet, Hollywood vs. Seedance 2.0 | Diet TBPN
Date: February 18, 2026
Hosts: John Coogan & Jordi Hays

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Overview

In this lively episode of Diet TBPN, John Coogan and Jordi Hays dissect the interplay of oligopoly dynamics in AI labs, explore massive capital bets shaping tech infrastructure, and riff on the fast-blurring lines between Hollywood and AI-generated talent. With notable references to game theory, recent headline-grabbing investments, and the legal/cultural shockwaves of tools like Sea Dance 2.0, the hosts and guests bring sharp analysis with plenty of signature irreverence.

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Key Discussion Points & Insights

1. The Cournot Equilibrium & Oligopoly in AI

Timestamps: 00:25 – 05:26

• Titles & Meme Discourse:
  The hosts joke about tech circles' tendency to humorously frame topics as under-discussed, referencing "Why is no one talking about Marc Andreessen?" (00:39).

• Cournot Model Explained:
  Tyler explains the Cournot equilibrium—how in markets with few players (e.g., AI labs), firms compete on capacity and investment rather than price, each reacting to rivals’ moves (01:20).

  "If there's only a few players in a given market... and they aren't competing on price, they will compete on supply, and they'll try to predict what their competitors are doing..." — Tyler, 01:20

• AI Labs as an Oligopoly:
  The hosts compare AI labs' behavior to this model, noting how companies like OpenAI, Microsoft, and AWS seem obsessed with each other's moves, triggering an arms race of compute and capacity investments.

• Healthy Inference Margins:
  While the cost of serving (inference) is profitable, the constant race to build bigger models (R&D) means current AI leaders aren't posting profits.

  “The Cournot equilibrium comes when a small number of labs, an oligopoly, effectively choose supply at the frontier level and then the market clears at a high price for frontier access.” — Tyler, 03:55

2. AI Commoditization and Bertrand Competition

Timestamps: 05:26 – 06:56

• Commoditization Risks:
  If AI models converge in capabilities and become indistinguishable, competition could shift to pricing battles (Bertrand competition), lowering profits and resembling cloud hosting market dynamics.

  “The Cournot equilibrium comes when … market clears at a high price … but at some point, it becomes a commodity and you switch over to Bertrand competition.” — Tyler, 05:26

• VC Strategies:
  VCs now bet across multiple AI companies, anticipating no single “winner takes all,” but a handful of competitive players with high barriers to entry.

3. Special Guest Clip: Dwarkesh Patel & Dario Amodei

Timestamps: 07:17 – 09:55

• Economic Model of AI Labs:
  Dwarkesh outlines the industry as one of a few differentiated players with high gross margins, but where R&D investment outpaces near-term profitability.

  “Each model makes money, but the company loses money. The equilibrium I’m talking about is … where the country of geniuses in the data center … has equilibrated more.” — Dwarkesh Patel, 09:16

• Future Stability:
  Once development pace stabilizes and compute arms race slows, the market may reach a more sustainable equilibrium for profit.

4. Game Theory in Pop Culture

Timestamps: 09:55 – 13:16

• A Beautiful Mind Clip:
  The hosts use a scene from “A Beautiful Mind” to riff on game theory principles—Nash equilibrium and the limits of pure self-interest—connecting it to the competitive maneuvers in today’s AI landscape.

5. AI and White Collar Work Automation

Timestamps: 13:42 – 16:00

• Software Engineering as Unique:
  Dwarkesh asserts software engineering is uniquely automatable because all its context is in the codebase. The hosts debate whether enough context for other jobs is digitally captured.

  “My take was, it’s possible that a lot of the full context needed to do the job … is in fact logged … in the final product, in decks or spreadsheets or decision logs…” — Tyler, 14:07

• Limits for Creative Work:
  Video editing, for example, remains hard to automate due to the lack of transparent decision logs compared to code repositories.

6. Industry Investments: Adani, Micron, Memory Bottlenecks

Timestamps: 19:15 – 22:37

• India’s $100B AI Infrastructure Bet:
  Adani Group’s major commitment is lauded, but timing (2035) is questioned in the context of fast AI timelines.

• Micron’s $200B Memory Expansion:
  Memory chip supply is now central to AI progress; Micron’s audacious investment dwarfs even national-level initiatives.

  “Micron is spending 200 billion to break the AI memory bottleneck … Just this one company is like, yeah, we're going to spend twice as much as India.” — Tyler, 20:34

• Supply Crunch Impact:
  Ripple effects include delays to major hardware like PlayStation 6, highlighting the wider consequences of AI’s hungry infrastructure demands.

7. Hollywood vs. AI: Sea Dance 2.0 and Talent Rights

Timestamps: 22:37 – 29:55

• Open Source Drama:
  The rapid saga of Claude Bot/OpenClaw reflects intense, meme-laden competition over open-source AI tools, with billion-dollar acquisitions and community drama.

  “It's pretty wild that you can just vibe code an open source first project to make 40 billion in a couple months.” — Tyler, 24:39

• Hollywood’s Response to AI-Generated Talent:
  The SAG-AFTRA union issues a strong statement condemning ByteDance’s Sea Dance 2.0 for enabling unauthorized voice and likeness replication.

  “SAG stands for the studios in condemning the blatant infringement enabled by ByteDance's new AI video model Sea Dance 2.0.” — Jordy, 26:45

• Industry Pushback and New Frontiers:
  While superstars may lean in (digitally scaling themselves), concerns center on new talent and the risk of studios creating artificial actors for better economics.

  “At the same time you’re thinking, okay, my name and likeness is now infinitely scalable…but the question becomes new talent…” — Jordy, 28:14

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Notable Quotes & Memorable Moments

• On AI Industry Dynamics:
  “Everyone’s trying to figure out how far to push it. There’s … the Cournot game of chicken around, who will invest the most and advance the frontier.” — Tyler, 13:20

• On Video Editing Automation:
  “All these decisions, they sort of get chronicled, but they don’t get neatly organized the way a GitHub log does … So maybe two years, another $5 billion does it. But it's coming.” — Tyler, 17:49

• On AI-generated Hollywood:
  “If you’re already an A-list massive superstar … you may actually see some stuff like this and actually be like, great, I’ll be able to shoot a movie in a week from LA.” — Jordy, 28:14

• On Meme Language & Community:
  “The looks max lingo is really—it feels hilarious. I do wonder the half life. I think it’s over, it’s gotta be toward the end of this boom.” — Tyler & Jordy, 25:35

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Important Segment Timestamps

• Cournot Equilibrium & AI Oligopoly: 00:25 – 05:26
• AI Commoditization vs. Oligopoly: 05:26 – 06:56
• Dwarkesh Patel & Dario Amodei Clip: 07:17 – 09:55
• A Beautiful Mind/Game Theory Clip: 09:55 – 13:16
• AI Job Automation Debate: 13:42 – 16:00
• Adani & Micron Investment: 19:15 – 22:37
• Open Source AI Drama (Claude Bot/OpenClaw): 23:23 – 25:46
• Sea Dance 2.0 & Hollywood v. AI: 26:43 – 29:55

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Tone & Language

The conversation maintains TBPN’s signature mix of rapid-fire analysis, friendly banter, and insider tech humor—with numerous callbacks to memes and irreverent anecdotes. The hosts keep the discourse accessible while dropping advanced economic and tech concepts, perfect for seasoned observers and curious newcomers alike.

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Summary

This episode deftly surveys the shifting tectonics of AI, from economic theory in practice to the new reality for cloud-scale infrastructure and creative industries. With massive bets, meme-fueled rivalry, and ever-blurring boundaries between code, culture, and celebrity, Coogan and Hays pull no punches in keeping the future in focus—and always just a bit tongue-in-cheek.

Transcript

[Tyler]

It's the Year of the Fire Horse and.

[Jordy]

And we get to celebrate it twice. Because I think we. I remember we talked about it at the beginning of the year. But the Chinese New Year did not start until today.

[Tyler]

It's Lunar New Year. Right. Worshipers burned large incense sticks on Monday outside a temple in Hong Kong to mark the Lunar New Year, which falls on Tuesday. People around Asia celebrate the start of.

[Jordy]

The Year of the Horse in the Ultradome. It's the Year of the Horse.

[Tyler]

Every year. Every year, I think. So everyone is talking about the Cournot Equilibrium, at least Dari Amade and Dwarkesh Patel are you and me and some folks on the timeline, we're going back and forth and basically trying to get to this question.

[Jordy]

I feel like we should give the context on this, on the titling strategy, because we call the run of shit. Like we'll title an essay. Why is no one talking about the Cournot Equilibrium? Because this one guy had this super viral ad like a year or two ago and the title was why is no one talking about Marc Andreessen? We were laughing about it so much. Because he's one of the most talked about.

[Tyler]

Oh, yeah.

[Jordy]

Investors in venture.

[Tyler]

He's a Midas List constantly. He's written essays.

[Jordy]

Everyone's talking about, like been viral.

[Tyler]

Million.

[Jordy]

And he's someone.

[Tyler]

So many podcasts.

[Jordy]

Yeah. He's someone that everyone in the industry has an opinion on already.

[Tyler]

Totally.

[Jordy]

He's not like a Midas lister.

[Tyler]

Yeah, yeah.

[Jordy]

Up there. Not a lot of people. It's like everyone's talking about.

[Tyler]

But in this case, the basic idea is that if there's only a few players in a given market, you can think about any specific market, lemonade stands or whatever. And they aren't competing on price, they will compete on supply. And they'll try to predict what their competitors are doing and then respond accordingly. And this is really, really relevant to the AI Lab discussion because you can tell that even though all the leaders of the AI lab say, I don't think about the competition, I don't talk about the competition. I'll use general terms. They're all obsessed with what everyone else is doing. And they think about it constantly, very clearly. And if someone's buying 10 billion of compute over here, they're a counter with eight over there, try and jump to 12, and everyone's sort of keying off of each other. You know, Microsoft pauses, AWS goes all in. There's all these, like, horse races. It's why semianalysis exists and provides great. You know, cross functional data. Outside of tech. There's this, there's this discussion that I see that's always funny to me where people would be like, the price to earnings ratio.

[Jordy]

Ryan says they don't want you to talk about the prices.

[Tyler]

They don't want us to talk about it. They don't want us to talk about it. For sure. There's this discussion. I saw one person say the price to earnings ratio for OpenAI and Anthropic is just simply too high. And I was like, earnings? These companies are losing money. They don't have a price earnings ratio. Divide by zero.

[Jordy]

This is going to blow your mind.

[Tyler]

Yeah, it's so much worse than you think. They're not making any money. The other side of things is the inference factory. So this is essentially a manufacturing business. You have variable costs, so GPUs, power, engineering overhead, and then your revenue is subscriptions, API usage and enterprise contracts. And so when you just look at inference, you see positive contribution margin. And we can see that because we can compare the cost to inference. A model of the GPT5 class size or the Opus 4.5 size, you can see what does it look like to run an open source version of that model on commodity hardware. It's way, way cheaper than what you pay to Anthropic or OpenAI. So they must have good margins. And everyone sort of agrees at this point that inference margins are in fact healthy. The question is, how do you balance those two pieces and when do you risk over investing? And that's sort of this Cournot game of chicken that everyone's playing. The Cournot equilibrium comes when a small number of labs, an oligopoly, effectively choose supply at the frontier level and then the market clears at a high price for frontier access. So choosing supply in this case means how many data centers get built, how many GPUs get ordered, but also how much low latency capacity is allocated to the top tier. So right now, OpenAI just did the Cerebras deal. There's Claude Fast and there's a whole bunch of different modes that will deliver faster inference and how many of those fast queries you get. How much of the best chips are allocated to a particular tier that you're paying for is an economic question. For the labs, there's a ton of developers and knowledge workers who are happy to pay hundreds of dollars a month or more, but they always want the best available model. This is most people in executive roles in startups. Yeah, I got my $200 a month subscription I'll pay 250 or 100 or whatever, couple hundred bucks and it just makes me better at my job. I just do whatever I need to do. But don't give me the old thing. I want the best. I want to know that the hallucination rate is as low as possible.

[Jordy]

1% of the time it makes a career ending mistake. So having a product, not just an API business, gives you leverage because at some point the models are smart enough where you don't need to train them. You don't need to train a model that is 4% better because people are still coming to your application and having a good product experience, right? Yes. So historically one of the critiques to Anthropic's business was that they have to just be on this constant, constant fly sort of hamster wheel of training the best model because they have an the majority of their business is this API business. They're not an aggregator yet swap it out for a smarter model. That said, they have cloud code now which gives them some more leverage over the market.

[Tyler]

And the really interesting thing is that Dario is now talking about being near the end of the exponential or maybe producing like the final models because we've talked to a few people about this, but it's very unclear if, if it's possible to create like a super intelligence that's like 5,000 IQ. It might just be they get good at all knowledge work and they can answer all tasks. But it's like the digital guy at that point it does commoditize and you drop out of Cournot equilibrium and you become more customers are more aggressive about switching to cheaper models to cut costs because the frontier is now commoditized in the entire backlog. Everyone is at the frontier basically. And so in that scenario you switch over to Bertrand competition, which doesn't really mean that profits go to zero. But there is more competition and it looks a lot more like the hyperscaler cloud market, which is I think what people have been sort of signaling towards. And also it sort of explains why a lot of the VC firms are getting in multiple companies because they don't think it's going to be winner take all anymore. They think it's going to be much more oligopolistic for the long term and there will be competition between the major three or four labs and it will be much more about how can you marshal enough supply, create a huge barrier to entry. Like you and I could start an AWS competitor tomorrow, but it's going to be extremely expensive to bring up Data centers that just serve web apps everywhere, let alone AI stuff. Right. Building all those data centers. You're thinking what I'm thinking. You're thinking. You're thinking. I was, people are saying, when does.

[Jordy]

I was talking with my buddy, my buddy Ben on Sunday. We both live in Malibu. He was thinking of just getting some chips and setting up Malibu Inference.

[Tyler]

There we go.

[Jordy]

Just, just the name alone. It sounds like you could get at least, at least Malibu is Malibu Inference.

[Tyler]

It's really funny.

[Jordy]

Would, would be a beautiful name for, for a neocloud.

[Tyler]

Yeah. Let's play the clip of Dwarkesh Patel and Dariel Amade discussing the economics of AI labs.

[Dwarkesh Patel]

Like we have a, you know, let's just imagine we're, we're in like an economics textbook. We have a small number of firms. Each can invest a limited amount in, or like each can invest some fraction in R and D. They have some marginal cost to serve the margins on that. The gross profit margins on that marginal cost are very high. Because inference is efficient. There's some competition, but the models are also differentiated. There's. Some companies will compete to push their research budgets up. But like, because there's a small number of players, you know, we have the, what is it called in the Cournot equilibrium? I think is what the, what the firm equilibrium is. The point is it doesn't equilibrate to perfect competition. With, with, with, with, with, with, with zero margins. If there's like three firms, if there's three firms in the economy, all are kind of independently behaving, behaving rationally. It doesn't equilibrate to zero. Help me understand that. Because right now we do have three.

[Jordy]

Leading firms and they're not making profit.

[Dwarkesh Patel]

And so that's a good question. Yeah. What is changing? Yeah. So again, the gross margins right now are very positive. What's happening is a combination of two things. One is we're still in the exponential scale up phase of compute. So basically what that means is we're training. Like a model gets trained. It costs, you know, let's say a model got trained that costs $1 billion last year, and then this year it produced $4 billion of revenue and cost $1 billion to, to, to, to, to inference from. So, you know, again, I'm using stylized number here, but you know, 75, these are my numbers.

[Tyler]

I'm just picking random numbers.

[Dwarkesh Patel]

Gross, gross margins and you know, this, this 25% tax. So that model as a whole makes $2 billion. But at the same time we're spending $10 billion to train the next model because there's an exponential scale up, and so the company loses money. Each model makes money, but the company loses money. The equilibrium I'm talking about is an equilibrium where we have the country of geniuses. We have the country of geniuses in the data center, but that model training scale up has equilibrated more. Maybe it's still going up. We're still trying to predict the demand, but it's more leveled out.

[Tyler]

There is another fun clip that we should watch from A Beautiful Mind. Jordy, have you seen A Beautiful Mind?

[Jordy]

No.

[Tyler]

It won the Oscar for best picture. I believe it's about the mathematician John Nassau. Have you seen A Beautiful Mind?

[Dave]

I have not.

[Tyler]

Wow. Unk status over there.

[Jordy]

You would have. Inversely. I was walking on the beach with Senra, and we walked by an incredibly famous. One of the top movie directors of the last probably 10 years.

[Tyler]

Really?

[Jordy]

And Senra was like, do you see that? And I was like, see what? It's a guy with a dog.

[Tyler]

That's hilarious. I feel like that your beach tours have been really star studded lately. This is a different from the previous one you mentioned, correct?

[Jordy]

Yes.

[Tyler]

Wow.

[Jordy]

Yes.

[Tyler]

That's remarkable. Well, let's pull up the clip. This room of beautiful mice.

[Eric Lyman]

Nash, you might want to stop shuffling your papers for five seconds.

[Jordy]

Is that Eric Lyman?

[Tyler]

Yes, it's Eric Lyman in the. In the ramp biopic. We got. We got. We got our cast right here. Oh, this is the original, like, looks.

[Max]

Maxing movie moving in slow motion.

[Tyler]

Will she want a large wedding, you think?

[Eric Lyman]

Should we say swords, gentlemen? Pistols at dawn?

[Ash]

Have you remembered nothing? Recall the lessons of Adam Smith, the father of modern economics.

[Eric Lyman]

In competition, individual ambition serves the common good.

[Jordy]

Exactly.

[Eric Lyman]

Every man for himself, gentlemen. And those who strike out are stuck with their friends.

[Ash]

I'm not gonna strike out.

[Eric Lyman]

You can lead a blonde to water, but you can't make a drink.

[Max]

I don't think he said that.

[Eric Lyman]

All right, nobody moves. She's looking over him, right? She's looking at Nash.

[Ash]

Oh, God. All right, he may have the upper hand now, but wait until he opens his mouth.

[Tyler]

I think this. This is very, very stylized and completely apocryphal. Like he definitely thought of this theory, but not at a bar.

[Max]

We block each other. Not a single one of us is going to get her. So then we go for her friends, but they will all give us the cold shoulder because nobody likes to be second choice. What if no one goes for the blood? We don't get in each other's way and we don't insult the other girls. That's the only way we win. That's the only way we all get laid.

[Tyler]

So he's describing the prisoner's dilemma, Adam Smith said, where everyone must work together.

[Max]

This result comes from everyone in the group doing what's best for himself.

[Eric Lyman]

Right?

[Max]

That's what he said. Incomplete. Incomplete.

[Tyler]

Incomplete. Okay, incomplete.

[Max]

Because the best result would come from everyone in the group doing what's best for himself and the group.

[Ash]

Ash, this is some way for you to get the blonde on your own. You can go to hell.

[Max]

Governing dynamics, gentlemen. Governing dynamics. Adam Smith. Who's wrong?

[Eric Lyman]

Here we go. Careful, careful.

[Max]

Thank you.

[Tyler]

Anyway, very fun.

[Jordy]

Dave says just joined the stream. We watching a movie.

[Tyler]

Yeah. Lots of game theory going on in the, the, in the AI wars right now. Everyone's trying to figure out how far to push it. There's a fair amount of risk. There's still the courno game of chicken around, who will invest the most and advancing the frontier. But the end state looks a lot more durable than pure model commoditization and the perfectly competitive situation that many were predicting a few years ago.

[Jordy]

Buco Capital says, I thought Dwarkesh had a good point that software engineering is the only job where the full context needed to do the job is available to an AI agent via the code base. And I didn't think Daria had a good answer for why automating other jobs will be as easy. This got a bunch of a lot of people kind of reacting, kind of disagreeing generally that all of the full context needed to do the job is available. But I do think something we need to figure out.

[Tyler]

Yeah, we were debating this because there was a post that was just sort of like a wojack reaction that was just making fun of this. And it wasn't clear if they were saying that like that they were agreeing or disagreeing. But basically my take was, well, it's possible that a lot of the full context needed to do the job of a lot of different white collar jobs is in fact logged. It's just logged in the final product, which is like a deck or a spreadsheet or a decision, and then a whole bunch of emails, a whole bunch of slacks, and then a whole bunch of zoom calls that's recorded. And so yes, if you're running a business where a lot of work gets done in smoky bars late at night and you know, back alley deal, making sure that's going to be harder to automate. But in the world where it's someone sitting in front of a computer and there's a screen recorder running. Like you should be able to pull up most of the context at the same time. You can't just snap your fingers and go back and get every decision that was made in the 80s that allowed coca Cola to become a dominant soda maker. But you can, you literally can with.

[Jordy]

Linnets just being like knowing the calls being recorded and used. Train something to replace them. They're just like, I'll tell you offline. I'm not in speak.

[Tyler]

Speaking this secret in Record Golf this weekend.

[Jordy]

Debate around the posture.

[Tyler]

Dwarkesh.

[Jordy]

Dwarkesh. His posture was.

[Tyler]

He's been at the gym a lot. He looks fantastic. And I love this sweater. The crew neck works really well. The pushed up sleeves is a particular choice. Didn't translate into that. Chad Wojack. But he looks fantastic here. A lot of fun on the timeline looking at the looks. Mogging or whatever. The looks maxing. I don't even know frame mogging. That's the.

[Jordy]

He kept bringing up the example of a video editor saying, yeah, but when will the models be good enough to edit videos? Well and pick out moments and give me two years and another 500 billion. We've tried every tool there is. They can't do it yet.

[Tyler]

Tricky. I don't know. I don't know what's.

[Jordy]

And it's not even that we're not trying the tools to replace the people on our team. We're trying to make them have higher output.

[Tyler]

One interesting thing is that there aren't a lot of open source, like premier profiles. Like I've edited a ton of videos for YouTube. There's a whole bunch of cuts in there. What I cut out, what I didn't. You could have that record, but it's not stored in GitHub. Like it's just. You can't necessarily train on it. You can train on the final product and. And understand, but you don't understand what actually got left on the cutting. Cutting room floor. There's this whole concept of like kill your darlings. Like when you're in the edit, like you need to be cutting more. You're like, ah, I like that shot. It's so cinematic, so cool. But does it actually advance the story? No. So you cut it down. I was watching the Matrix this weekend and there's this amazing shot of when Neo and Morpheus are going to visit the Oracle and they reach for the doorknob and the doorknob has this perfect reflection and the reflection shows Neo and Morpheus and they had to do this crazy VFX shot to hide the camera in what looks like Morpheus's coat. Because if you point a camera at a mirror, you see the camera and you don't want to see the cameraman there. That ruins the shot. And so they did all this crazy stuff to cover up the camera. And I'd seen the behind the scenes and been like, wow, that's really impressive. And in my memory I thought it was like, oh, it's such an important shot. They probably lingered on that for like five seconds to really let it sink in. Like they're, they're pulling a trick on the audience. It's beautiful. It's like half a second. And they did all this work and then they knew that, like from a storytelling perspective, you don't want to hang out and watch a picture of a doorknob for five seconds. And so all these decisions, like, they sort of get chronicled, but they don't get neatly organized in the way that a GitHub log does with. With pull request discussions and what happens. So it'll be, it'll be difficult. So maybe two years, another $5 billion does it. But it's coming, so we'll, we'll keep monitoring it.

[Jordy]

And Reid says, horses don't stop, they keep going.

[Tyler]

Wait, did he actually say that?

[Jordy]

Yes.

[Tyler]

No way.

[Dave]

Yes.

[Jordy]

In response to 2026 being the year of the horse.

[Tyler]

I love it.

[Jordy]

One of the greatest lyrics of all.

[Tyler]

Time, originally to explain the joke. It's a Young Thug song and the actual lyric is hustlers don't stop, they keep going. But it sounds like horses. And so people put horses don't stop, they keep going. And they show the AI generated image of the horse bench pressing. And it's incredibly inspiring.

[Jordy]

There's a Young Thug songs that are hard to fully decipher.

[Tyler]

100%.

[Jordy]

Let's hit the size gong for this. Pennsylvania Girl Scout, 6 years old, breaks record selling 87,000 boxes of cookies. She's unstoppable.

[Tyler]

Unstoppable. How much is that?

[Jordy]

What's the ARR estimating? That it's somewhere around $600,000 of sales at only 6 years old. Really incredible stuff. Heartwarming.

[Tyler]

That's awesome.

[Jordy]

India's Adani group to invest 100 billion in AI infrastructure.

[Tyler]

We gotta hit the gong again.

[Jordy]

Hit it again. The Indian boost to the country's ambitions to become an AI power. India's Adani Group and energy and logistics giant said it would invest $100 billion to develop large scale data centers by 2035. The largest such commitment in India so far. Tyler, what do you think about the timing here? Is this going to be too late? Are the clankers going to like is 2035, how are we looking there? That's singularity.

[Dave]

Yeah, I'm very bullish on the clankers coming pretty early. So, you know, time will tell, I guess we'll see.

[Jordy]

I cannot wait to pull up this clip.

[Tyler]

It is a big number that I feel like a lot of countries have been teasing big numbers, but this is.

[Jordy]

Yeah, they're kind of mogging. Macron.

[Tyler]

Yeah, this is like a really big number. You see a bunch of like multibillion dollar deals, multi billion dollar releases. But this is like serious, serious, serious investment. So, you know, good news.

[Jordy]

Micron is spending 200 billion. Congratulations for setting the biggest number Micron. Micron is spending 200 billion to break the AI memory bottleneck. For decades, memory chips were low margin commodity products. Now the industry can't make enough to satisfy data centers hunger.

[Tyler]

Just this one company is like, yeah, we're going to spend twice as much as India.

[Jordy]

Micron Technology is the largest American maker of memory chips. The tiny slices of silicon that store and transfer data and help power everything from smartphones and car computers to laptops and data centers. Micron is rushing to add manufacturing capacity to avert the biggest supply crunch the memory industry has seen in more than 40 years.

[Tyler]

Did you hear that the PS6, the PlayStation 6 is now delayed because of memory shortages. 2029, pretty, pretty big delay to 2029. They really don't refresh.

[Jordy]

You just created a trillion gamers. No, seriously, I think adding insult to.

[Tyler]

Injury to the gamers might, actually gamers might rise up. They might be an important voting block. A lot of them are, a lot of them are of age to vote and a lot of them would rather have new gaming hardware than, you know, necessarily AI slopping the feed. They're like, yeah, I can't afford the new PC that I wanted. What do you think?

[Dave]

I don't know. I mean I feel like this says a lot about how good the PS5 is, right? Because they can like afford to just like postpone the psx. Like what games?

[Jordy]

Oh, now you don't want technological progress?

[Tyler]

Wow.

[Dave]

I wanted to go to the data centers. I don't, I don't care about like the next game graphics. Have like, have they gotten that much better in the past, like five years? Like yeah, maybe, but it's like, yeah, for the actual gameplay. Is it that important if like the.

[Tyler]

Actual pixels are realistically a Lot of this stuff should be moving to the cloud soon if it's not already. And then if you're running in the cloud you can upgrade the hardware and in theory you should be able to run like a gen AI upresing pass to make it more photoreal. And I feel like that's going to be where more of the juice is squeezed out of the graphics than just continuing on the traditional path of more pixels, more ray tracing. It'll be make a really beautifully designed video game that works really well, really tight deterministic interaction so it's satisfying and then give it a, give it a layer.

[Jordy]

We got to have like a RAM trader on the show. Really somebody that's in the thick of of deal making in this space. Moving on. Lucas Shaw was on a tear over the weekend reporting on the Warner Brothers Paramount conversations. He says this morning Warner Brothers is going to resume talks with Paramount after two months of rejecting them playing mind games. The company still says it's committed to Netflix, but needs to find out just how much the Ellisons will offer. He originally reported on this Sunday but it's being confirmed today. Again, we kind of knew this was going to happen if the Ellisons had been saying we're making a. We're giving you a big number but it's not our biggest number. It's not our best and final. So no surprise here.

[Tyler]

Let's flip over to Claude Bot. Kent Dodd says name's the thing. Claude Bot Plod asks for a rename. Renames to Openclaw. OpenAI buys it. Legendary couple weeks. No confirmation on buying. It's an open source project. They're keeping it open source. There's a whole bunch of different dynamics here.

[Jordy]

Dave Morin Reading is going to step in to I believe run the foundation that will kind of steward the open source project. And then Peter's obviously joining OpenAI. I'll take this day off to figure out this whole Open Claw thing. Every entrepreneur on President's Day weekend, we've talked about this on the show before. Long weekends are really good for AI progress and AI diffusion.

[Tyler]

Petition for 3 day weekends to speed up AGI timelines probably would work for sure. Fumblegate did anthropic fumble.

[Jordy]

Open Claw Will Brown says honestly crazy that Openclaw sold for 1 billion. Like he's really the first solo $5 billion founder. Time will tell if it's worth 15 billion that OpenAI spent on the acquisition, but it's pretty wild that you can just vibe code an open source first project to make 40 billion in a couple months. Now.

[Tyler]

It really, really nails it because everyone jumped immediately to a billion immediately off of nothing. Off of nothing. Off of like one rumor. It's very, very funny. Who knows? Alex Cohen breaks it down for Gen Z. If you're wondering what happened today, Claude was mogging OpenAI for weeks. Then this Jim cell dev ships Claude bot which was the fastest growing open source thing ever. Absolute looks max for the whole ecosystem. Anthropic tries to dairy goon him with legal Dev renames to OpenClaw. OpenAI slides in like a void pulling chad with acquisition interest. OpenClaw gets acquired by OpenAI. Now Anthropic is getting jester gooned by the Entire timeline and OpenAI is Giga maxing off their fumble. Open Anthropic could have just let them cook him cook. Instead they went full moid and got out framed by the jester maxers at OpenAI. The looks max lingo is really, it feels like hilarious. I do wonder the half life. I feel like it's.

[Jordy]

I think it's over.

[Tyler]

It's gotta be towards the end of this boom. But the rise of the kick streamers is certainly the story of the year. Certainly the story of the year.

[Jordy]

What did Claude do?

[Tyler]

What did Claude do?

[Jordy]

Pentagon has said that Anthropic will pay a price. There was reporting last week that Claude was leveraged in some way during the Maduro planning. The planning of the Maduro raid. I was imagining in my head Daario as Walter White in the suv just being like watching the logs and seeing Pete Hegseth running a deep research report on Maduro. Who is Nicholas Maduro? He's just like, no, no, don't do it. Yeah, very, very unclear how it was used, but a lot of pushback. SAG, AFTRA, what happened? Put out a statement on CDANCE 2.0 and it's not a comment, it's a statement. The Chinese, now the Chinese have been quivering in fear ever since.

[Tyler]

Oh no.

[Jordy]

SAG came after them.

[Tyler]

What'd they say?

[Jordy]

SAG stands for the studios in condemning the blatant infringement enabled by ByteDance's new AI video model Sea Dance 2.0. The infringement includes the unauthorized use of voice and likenesses. This is unacceptable. And undercuts the ability of human talent to earn a livelihood. It is kind of interesting that just in this statement they're admitting to saying like it's so good you're going to make it impossible for our members to earn a living. Which doesn't actually.

[Tyler]

It says undercuts, undercuts say eliminates CDANCE.

[Jordy]

2.0, disregards law, ethics, industry standards and basic principles of consent.

[Tyler]

Hit that. Responsible AI development demands responsibility. That is non existent here. Completely correct. Some of the Sea Dance videos are insanely infringing. It's just like, wow, it's Larry David. Beginning of the end, says Growing Daniel.

[Jordy]

Disney, also, as expected, sent a cease and desist letter to Bytedance over Sea Dance 2.0. It's crazy. I wonder how Bytedance will actually react to this pushback. Obviously they expected it.

[Tyler]

Yeah.

[Jordy]

They know that they're not abiding by a number of different US laws. Whether or not they care is another thing. Yeah, like if you, if you make an AI version of Andrew Huberman and you get in a fresh ad account, you can probably start spending money before the Huberman Lab team finds out what you're doing.

[Tyler]

I would disagree. I think Rob's on top of it. I think he's goated, so. But anyone else, any other team would be cooked.

[Jordy]

I don't know. I mean, he might respond faster than the others, but this is certainly happening. So this is interesting. If you're already like an A list massive superstar, I think you see some stuff like this and you're actually like, great, I'm going to be able to shoot a movie in a week from la. I'm not going to have to travel to these insane exotic locations and spend a week in the desert filming all these clips. So if you're like a Timothee Chalamet, this is maybe like, yes, you're worried for the overall industry, but at the same time you're thinking, okay, my name and likeness is now infinitely scalable. I can still like restrict the supply to some degree. Right. I'm not going to tell any movie studio, hey, you can make a movie with me, whatever. You're still going to kind of restrict it. The question becomes new talent that's emerging, trying to build their brand. At what point do studios say we're just going to make a character, we're going to make a new actor out of thin air, place them across different movies, build them up over time. You could imagine. I don't think a company like CAA would do this because all their talent would be like, what are you doing? You're taking our job. But I could imagine a group trying to make like a lil Mikaela style actor that you build up over time. One thing that we'll find out is how much does the actual actor's real life matter in the context of their career. Like if Timothee Chalamet is dating Kylie Jenner. Does that, like, increase his appeal on the big screen?

[Dave]

Yeah.

[Jordy]

And I would say yes, probably.

[Tyler]

Right?

[Jordy]

There's so much fixation on the lives of all this talent.

[Tyler]

I can't wait to tune in tomorrow at 11am sharp, Pacific.