Samsung’s $70B Chip Bet, Apple Doing Nothing But Winning AI, Bezos’ New Fund | Diet TBPN
19 Mar 2026 · 31 min
In this episode of the Diet TBPN podcast, host John Coogan and his co‑hosts discuss a range of current tech and AI developments. They begin by examining Samsung’s $70 billion investment in new semiconductor fab capacity, positioning the company as a potential counterweight to TSMC’s bottlenecks and highlighting Samsung’s existing role in high‑bandwidth memory, OLED displays, and its partnership with Tesla for AI inference chips in vehicles. The conversation then shifts to the broader compute bottleneck, noting how increased fab spending is crucial for the AI supply chain. The panel moves on to Cursor’s newly released Composer 2 coding model, dissecting its benchmark results, cost‑per‑token pricing, and how it stacks up against OpenAI and Anthropic models. This segues into a deeper debate about the trade‑offs between specialized, task‑focused models and large, general‑purpose models, especially regarding cost, accuracy, and long‑term viability. A substantial portion of the episode is devoted to AI monetisation strategies. The hosts compare ad‑supported LLMs to subscription‑based models, citing ARPU figures for Google, Meta, and OpenAI, and argue that ads will dominate consumer AI revenue. They then analyse Apple’s emerging AI revenue stream, noting $1 billion in 2025 from generative‑AI apps, the App Store fee structure, and Apple’s on‑device AI strategy that avoids heavy capex. The performance of XAI’s Grok in the App Store is also highlighted. Finally, the show covers Jeff Bezos’s effort to raise a $100 billion AI‑manufacturing fund (Project Prometheus), describing its scope across chipmaking, defense, and aerospace, and its potential to reshape U.S. re‑industrialisation. The episode closes with lighter cultural asides—including a wildlife bridge discussion, a tongue‑in‑cheek comment about Rolls‑Royce, and a brief clip of Lil Wayne talking about AI music—before signing off.
Chapters
Last time we had Mark Cuban on the show, we were debating ads in LLMs. And since then we've gotten a bunch of data points about ads in LLMs. And I think that some of his takes have probably aged well. Some of our takes have probably aged well. It'll be an interesting time to reevaluate what's actually happening. There's been a lot more points.
I don't know, Jon.
We just have more evidence.
I said that ads would be fine. Well, and now the world is ending.
Yes. Here's a white pill. Samsung is investing $70 billion to advance their fab capacity. They're, they're getting back in the AI chips game. They've always been in the AI chips game. So brief history of Samsung. You probably know them from the phones, from the TVs. They, of course, are a major player in HBM, high bandwidth memory. They are a massive company, over a quarter million employees. They're close to touching $1 trillion in USD market cap. They pull in around $200 billion USD a year in revenue, maybe $250 billion this year in revenue. Really good. All that's USD. I like to Thinking USD, 'cause I'm an American. They're the global leaders in memory and OLED displays as well. So a lot of the displays that you see in other electronics, even it has a different brand name, it's still Samsung actually making that OLED display. But they're second in smartphones to the iPhone and Apple, and they're second in the semiconductor foundry business to TSMC. Semiconductors still make up 30 to 40% of their business, and they supply HBM, to NVIDIA for the H100 and Blackwell systems. So it's not like they're sitting out the AI bull market.
They're doing great.
They're participating. They are definitely participating. They're incredibly important in the AI buildout. But if TSMC is bottlenecked and TSMC is sort of risk-off and they're not going to be, you know, guiding to like insane CapEx numbers while every American hyperscaler is, well, that creates an opportunity for Samsung. And so Samsung's stepping up and they're announcing that, hey, we're gonna put another $70 billion to work on this particular business. So Tesla has been working with Samsung on the foundry side in AI for a while. So Samsung's never really been on the frontier with a direct competitor to the H100 or the Blackwell chip. That's been more of like AMD's game. And AMD also fabs at TSMC. So there hasn't really been this like neck and neck battle between TSMC and Samsung. But it's like you can do AI inference on a Samsung chip. And we know that because Tesla went to Samsung years ago and said, we need a chip that can take in pictures from the road, decide where the lines are and decide.
They want their chips with the dip.
They want their chips with the dip. And that's all you know. And that's all Samsung does too. That's all you know. And so the FSD system, if you have a Tesla, you might be familiar with like HW3, hardware 3, that has been deployed into millions of cars and it was fabbed on Samsung's 14-nanometer process, which is a lagging node. We're not in the 3-nanometer, the crazy frontier stuff, but it's working and it's on the road. And according to a US regulatory probe, there were 3.2 million vehicles Teslas on the road in America with FSD systems that were basically all running Samsung chips inside. Now, to be clear, Tesla, just like any foundation model lab company, they have training and then they also have inference. They're a little bit different than many of the labs that you know and love because they do training in a data center using what's called the Dojo chip, and that is fabbed at TSMC. So they train the system, they take all the data in from Every Tesla camera, every road, all the information that they have. Every time that there's a disengagement, that's feedback to the reinforcement learning system. It says, hey, we were in FSD mode, but then someone grabbed the wheel or someone stepped on the brakes. You made a mistake. Understand what happened to get you to that point where you made that mistake. And so that all that data gets collected in a Tesla data center, runs on these Dojo chips. They do the training and then they deploy the model onto the Samsung chips in the actual cars. So with the backdrop of NVIDIA's massive GTC news cycle They've done so much press around GTC and so many different launches. You know that Nvidia is just going to suck a lot of the air out of the semiconductor discussion this week.
Out of the clean room.
Out of the clean room. Yes. Which is recycling all of the air every 3 seconds or something like that.
Yeah, but I think this is like particularly important, especially this morning. The, I guess the CCP put something out in the last 24 hours basically saying, hey, Taiwan is going to have an energy crisis due to the broader global energy crisis.
So we need to reunify peacefully.
There's an opportunity for peaceful reunification.
But peaceful reunification, even if it was completely peaceful and all the Taiwanese people just say, hey, we want to be part of China, they all vote for it democratically. That's going to be rough for the American chip buying industry. And so having another chip on the board metaphorically to make physical chips is probably a good thing. So yeah, Samsung's been doing well over the last 5 days. Stock's up 11% during a time when the Nasdaq is down 2.2% in geopolitical Tensions continue to rise. The compute bottleneck, we know it's important. We've been discussing this constantly and it's going to be very constraining over the next few years. So every increase in CapEx in the supply chain is a step in the right direction. And so Samsung gets the first gong hit of the day. Congratulations to everyone over at Samsung on making, making a big bet.
Cursor is out with Composer 2.
Composer 2.
It is frontier level at coding, priced at 50 cents per million input tokens and $2.50 per million output tokens. It's also, they have a fast version. They say we're able to significantly improve the model quality and cost to serve. These quality improvements come from our first continued pre-training run, providing a far stronger base to scale our RL.
It's not one of these graphs that's just like, oh look, we made some arbitrary X and Y axes and like we're in the top right corner, of course, because the axes are like good and cool.
We're the only one that's good. TBPnBench is like technology podcasts that publish at least 3 hours of content every week.
Yes, yes. Naturally. Exactly.
Naturally we are the right at the top. Right at the top. And it's actually, there's no one else on there.
Yes.
But.
But yeah, I mean, this seems fair. It is a little bit odd to read this because the cost, the cost is on the x-axis and it's inverted. So the further you are to the right, the cheaper you are, which makes sense because people associate an x and y graph with you wanna be in the top right quadrant and they certainly are. And it does seem like in terms of this Pareto frontier, you wanna be on the frontier, you wanna be pushing out across every single curve. Maybe if you are interested in, Sparing no expense, you'll go with the GPT-5.4 High or Medium model and you can align Cursor to GPT. I'm sort of surprised that Opus is not doing as well on CursorBench. That feels surprising based on like the general vibes around Opus 4.6 generally, but Cursor has specific needs for specific customers. And I don't know, what else do you think is going on here?
Yeah, I mean, the cost is really big. Like this is basically like 10x cheaper than Opus. So I think also Cursar has kind of been like, not really a dark horse, like everyone knows about it, but in the coding race, it's like everyone's like, oh, okay, there's Codex versus Cloud Code. If you imagine that Cloud Code and Codex are kind of like these environments for getting a ton of like really good data for training coding models, like Cursar has had that for way, way longer than OpenAI or Anthropic. So you should imagine that like, at least, you know, in the near term, like they actually have like really, really good data that they can, you know, train these good models on. And obviously like this is a very specific model. They've said it like, you're not going to write poems with this model. It's this very like specific, almost like point solution model where it's just like—
Don't listen to them, Tyler. Write a poem with the model. PoemBench.
PoemBench. Yeah, I would be interested to know like how many sacrifices were made because it's at a certain point, like I remember talking to an AI researcher, actually a semiconductor who was saying that like he actually thinks, he actually does believe that importing like the Odyssey and like Homeric epics is key to humanoid robots learning to walk.
Yeah, well, I think like if you look back at just like the general history of like machine learning AI, like the lesson is that like big general models always beat these small specific models.
Yes.
But if you kind of zoom in on the timescale, like you can still train GLM, some open source model on a very specific task like accounting or something, and you can like, it'll climb and you can actually make it better than the frontier models right now.
At that specific thing. And especially at cost.
Yeah.
Especially at cost.
Yeah, yes. Yeah, very much so. But like on the long term, if you zoom out, what actually wins here, it seems like it's basically always going to be these big, you know, general models.
And I wonder if that's true. I mean, we talk about this a lot where the big general model outperforms the smaller model. But at the limit, like if you were to think about like a Python if statement, just like flow control that is truly deterministic, if you piped the same question of like the if statement, like is this number bigger than this number? You pipe that into 5.4, it's gonna get it right all the time. It's gonna be very expensive compared to an if statement, which takes like no compute whatsoever. But the if statement is 100% accurate.
Legendary poster SendColp says, all shits and giggles on that headline till Anthropic or OpenAI decide to cut off their access to Cursor, referencing the Bloomberg article. Cursor is taking on Anthropic and OpenAI with a new AI coding model.
Would that matter? Like at this point, if they have Composer 2 and it's a small model, but it's good at writing code and it performs well on Cursor Bench and the Cursor users are satisfied with the Composer 2 model and they do— Cursor does get their access cut off. And when you install Cursor, you roll it out to your organization, you just get Composer 2 and you know what, it's, it's, you know, maybe there's taste that wouldn't pull you towards—
Yeah, I would just say at this point right now, I don't think we have any visibility into like how much of Cursor's revenue right now is tied to using OpenAI or Anthropic models. George says, I'm hearing tons of complaints from Cursor customers at enterprise companies. A silent change put almost all models Cursor uses behind max mode. Devs who used to manage to spread out monthly credits over a month see all of it used up in 1 to 2 days.
Oh, interesting. Are furious and It does feel like there's a little bit of like an economic war here.
Yeah. And this is what came up earlier this month around the lab sort of subsidizing.
Yeah. You know who's—
they're not, they're not in an easy position, but they're such a talented team. Nikita says we're rolling out summaries for articles now. Just tap the summarize button if you want to know if it's worth your time to read it.
Yes.
And yeah, it's basically Grok, turn this into a regular tweet. I am excited about the listen button. I've had this on my commute. There's so many moments where I'm like, I wish I could just have somebody read this article.
I actually wound up doing this with a number of Will Minitis long-form essays. I would copy them, put them into Eleven Reader from ElevenLabs, and have it read it to me in sort of a silly voice. It was a good time.
Well, I was actually trying to use Grok in the X app to just take an article paste it into Grok and say, hey, can you read this to me? It said, cannot find the post.
This is a response to, you know, every article people would post, people would always say, Grok, summarize this. And now there's just a button. I recently learned that you can only ask Grok, like, @Grok, is this true? You can only do that if you're paying for X. Sort of underrated how well X has seemingly— I don't know how big the subscriber base is, but that was a crazy idea to have a paid social network.
I think it's because people are, people are deeply addicted to X. Yeah, it is very valuable to them to be on there, to participate.
Yeah.
And the paid functionality, the way that it was marketed and the way that it generally worked was like you were going to have a bad time on X. Like if X was valuable to you and you didn't pay the $10 a month, it was going to be like significantly less valuable to you, probably. you know, you might, you might, depending on what kind of business you're running or what you use X for, it might be the equivalent of like losing thousands of dollars a month of value, or you could just pay the $10. So it was a good trade.
Yeah. But it was also just, it was weird how the targeting never seemingly got dialed to the point where you could actually target the CEOs of companies who were on X. Like, I mean, you see Travis Kalanick on X, like replying to things. It's like, He's raising money. He's growing a business. There's a lot of value in advertising to him because he's going to be picking a corporate card soon, or he probably already has, or might be in that market. He might be picking a payroll suite. There's all these things where if you could deliver that to that audience, it would be incredibly valuable, and the CPM should be through the roof. But I think for privacy reasons and for a variety of other reasons and sort of like really monetizing that long tail has been very difficult across every platform. So they've just gone with scale and the products that have sold the most on social networks have been very broadly marketed. The criticism that we saw from the Oscars is always like YouTube ads are generic. It's just like for a pillow or like injury or like something that applies to every single person. But there's always this like hyper-targeted opportunity there.
Yeah. The other, the other thing is, is the paid program. With X has seemingly worked in that we know a lot of people that happily pay and have no plans to churn. But it would be a failure in the context of like Meta scale, right? I think the last reported number that I saw was something like 1 to 1.5 million paid subs at $10 a month.
Oh, on X?
Yeah. So you're talking about somewhere in the range of 100 to 200 million of like ARR. If Zuck could launch a product like that, he would just wind it down, right? Reels went from 0 to $50 billion of run rate in like a handful of years, right? That's what, that's what a home run looks like. And so I think it makes sense for X, but it certainly is not a home run from a consumer application standpoint. And they still need the, you know, the overall business.
Olivia Moore said a big story that most people are missing in the AI race for the consumer, ChatGPT versus Claude, is ads. Right now, most consumer AI revenue is coming from power users who are willing to pay high subscription costs. This currently skews positive for products like Claude, but this will not be the end state. Google makes $460 per user per year in the United States, more mostly on ads. I didn't know that their ARPU was so high. Meta makes around $250. I mean, I guess those Google ads are really, really valuable and it's so intent-driven that it makes sense. ChatGPT's ad-based ARPUs will be even higher as they will ultimately have deeper, more frequent user engagement. Even at the $460 level, monetizing everyone in the US via ads is $152 billion in annual revenue. By contrast, if you're able to monetize even 5% of the population at $200 a month subscription, which is a stretch, that's only $40 billion. That's actually a crazy difference because $200 a month subscription is like super high. Like, you know, you're talking 20 times like Netflix or something else that's, you know, premium and like really important.
Yeah, the $200 subscription at the time was crazy. Yeah. But even at that point, some of the people that were more AI-pilled generally were like, oh, it's actually possible that someday you could spend $20,000 a month.
I was like, give me the $20,000 monthly. So she says, I suspect this will be even more drastic outside of the United States where users are even less willing to pay or directly pay for subscriptions. And the earliest data from a very small rollout shows ChatGPT ads are already outperforming Meta in effectiveness. Just gets better over time. So interesting. This is an interesting story. This is an interesting story.
Apple is way behind in AI and still making a fortune from it. Let's see.
Begs the question, are they actually behind?
It might not. AI revenue is set to top $1 billion this year, reassuring investors wary of rivals' sky-high spending. And keep in mind this chart here showing gross revenue from GenAI apps as well as Apple's commission. So look at this.
The beginning of 2025 was really the boom of GenAI app growth. $400 million. Is this, is this monthly App Store revenue? Wow, they're really cooking. And then sort of a flatline.
Yeah, it's so interesting that it actually dropped.
Well, we did read that article a few days ago about how Apple has been pushing back against some of the vibe coding apps. And there's this question about, you know, where are the bounds? Obviously, Apple's had pretty strict App Store rules around adult content and, you know, what else you can do, even just the app reconstituting itself, pushing changes because they want to review every line of code that goes into the App Store. If someone's pushing 10, 20, 30,000 lines of code a day, that's a lot of code for Apple to review. Going to slow things down. So that could be a little bit of what we're seeing. Maybe they've capped out on their ability to review all the Vibe-coded apps that are flooding the App Store.
Apple is on pace to surpass $1 billion in AI revenue this year, a tidy sum that demonstrates the company's AI advantage even as it struggles to deliver an AI strategy of its own. Siri chatbot is still weak by modern AI standards. Apple does have that the other AI players don't is a dominant position making devices. However, however fancy OpenAI, Google, Anthropic, and XAI make their chatbots, iPhones are still a primary way to deliver them to customers. Uh, that means they typically pay the App Store tax, roughly 30% of subscription fees in the first year and 15% a year thereafter, though rates vary. Gen AI apps paid Apple nearly $900 million in App Store fees in 2025, almost a billion of revenue and very, very, very little CapEx. 3/4 of the revenue Apple rakes in from GenAI apps in its App Store come from ChatGPT.
Whoa.
Next at about 5% is XAI's Groq. Cooking. Here we go, Groq.
I mean, there's so many different like funnels. They did the essay competition. They did the, uh, the video competition. And I've talked to people that are just people that are in the Apple ecosystem. They're like in the Tesla ecosystem. So they're like, Yeah, I talked to Grok on my way to work. I'm not kidding.
Yeah, Grok in the iPhone App Store did $12 million last month.
Yeah. And I know, I know, like the true like AI heads will be like Grok's behind on this benchmark model or whatever. Tyler, is that a correct characterization?
Yeah, Grok did more revenue. Grok did more revenue last month than Claude in the iPhone App Store.
I've started having conversations with, I mean, I'm using ChatGPT, but I wanted to just, I wanted to get up to speed on Taiwan and the, the, the just the, like, what was the reason for the original Civil War and stuff. And so I was just having a conversation back and forth. At no point was I like, oh, it really needs to be like, you know, GPT-5.4 Pro. It's like these are things that exist just like with one search to Wikipedia or one search to any, it's probably baked into the weights of 3.5. So like if I'm just going to be like chatting with someone who's like reasonably smart, like I would say Grok is there. And so what do you think?
Yeah, but like You could be talking to someone who's really, really smart.
No, like not if you're asking like basic, basic knowledge retrieval questions that like any model is going to one-shot and just be like, yeah, but you're just describing stuff that you could just like actually Google. But I can't Google via voice in my car on the drive. And for someone who's driving a Tesla and has a Grok integration right there, they're just like, sure, like this is great.
Okay, yeah, that's fair. But like, I don't think those people have actually tried like GPT-5.4 Pro.
But I don't—
So good.
It is good, but it's slow. And truthfully, like you can fire off the exact same query to 5.4 Pro and 5.4 Fast. And if the query is simple enough, the answer will be exactly the same. Because if I ask 5.4, 5.4 extended thinking, like what is the capital of California? And it thinks for 10 minutes and it just tells me, say, Sacramento.
See, you—
yeah, there you go.
That's why you need to think. A lot of people—
I told you, I run my life on GPT-2. I hallucinate a lot.
But people have said I have the mind of GPT-2.
It's true, it's true. Anyway, let's continue. Apple's revenue from generative AI apps rose from about $35 million in January to a high of $100 million in August.
Do nothing win.
Do nothing win. Sales have fallen from their peak, partly because ChatGPT downloads have declined, according to the data. As a proportion of Apple's total sales, $1 billion is small. Yet GenAI apps are the growth driver for Apple Services business, which investors have focused on in recent years because it has grown faster than device sales and boasts higher profit margins. Apple's dominant share at the top of the smartphone market affords it another luxury: time to get its own AI strategy right. So they're making money while they figure everything else out. Apple's AI plans— plan runs counter to strategies of competitors that are spending hundreds of billions of dollars on chips and data centers to build frontier language models. Apple is spending a fraction of that, aiming instead to use all of the personal information people store on their iPhones together with the chips that it designs itself to power an on-device AI strategy. Strategy. If they can act as a toll road for providers of AI, then they'll probably end up looking good long term for not having the big CapEx overhang. I have to imagine that Apple is not capturing any revenue from enterprises, developers, Cloud Code, Codex, any of those developers. They're probably not. Even if they are winding up using like a ChatGPT subscription in Codex, they're probably setting that new subscription up on desktop.
Road on, on the, on the actual.
Yeah, but it's a toll road on consumer, which is consumer sales. All the more reason to get into ads, honestly, because Apple does not tax those.
And AI is exciting for Apple because they need, they need a new product that they can just randomly bill you like $2.99. Yeah, anytime they need a cat, like, what are you talking about, cash?
$2.99?
Like, don't, don't you get just random bills from from Apple, like, here and there.
$2.99? Like, $2.99?
Yeah, like, I feel like every time I check my email, it's like, Apple has charged you, like, some random amount for some— for some subscription. Uh, in other news, okay, Rolls-Royce has scrapped plans to go all-electric by 2030 as, quote, drivers prefer V12 engines. Would you look at that? I mean, and this is just a total shock. Total shock. Yeah, total shock.
Yeah.
Drivers totally had to experience, you know, being forced— EVs forced upon them for the last few years to know that they preferred combustion engines after all. Of course I'm kidding.
Elon has been saying the Roadster reveal will blow your mind if it has a V12.
We've been talking crazy.
If he drops a V12. That would completely break the internet. Yeah, it would be incredible.
Let's talk about this Tesla that you were following yesterday.
Oh, yes. Did you drop this in the chat already? I sent it to you. Oh, no, we shouldn't. We shouldn't. We shouldn't share the actual picture. I saw a Tesla that was a very funny mix of— it had the Anti-Elon Club on it, but also an 1199 license plate. And it was a Plaid and it just like mixed every possible political ideology together.
And it had a vanity plate that was very sci-fi. Sci-fi. So it was saying like, I do want to go to Mars, but not with Elon. The license plate basically said beam me up.
Beam me up.
So they want to go to Mars, but not with Elon. They support—
they have an incredible amount of disposable income based on law enforcement.
They enjoy high trim levels, but they do not agree with Elon's actions.
Well, maybe they work for a rival AI lab or something. And so they are extremely sci-fi, but they just don't like Elon. They just feel like they're competing with XFL.
California has now spent over $100 million on a new bridge to nowhere. It is a wildlife bridge, which I have driven by hundreds of times. I've been seeing it. I've been experiencing the traffic that it causes. I'm not against the concept of a wildlife bridge. In fact, I think it's fantastic.
It does feel like—
but it is in a concrete jungle.
This is beautiful.
Totally.
This has a lot of opportunity to actually improve the visual aesthetics of this particular part of the state.
Caleb Hammer says, bro, this state cannot be real.
Isn't Caleb Hammer—
it's very real.
Isn't Caleb Hammer, uh, he's like a finance—
yeah, he's got like the number one—
he's like the one person you'd come to to be like, should I spend $100 million in a bridge?
And it's actually, it's actually quite a bit more than 100 at this point. And the funny thing is like, it's just kind of a bridge, but it doesn't— it's, it's lacking the entrances. Yeah, the bridge. I feel like it's basically built like that.
Even just a little bit of wood to like, like smooth it out so that it looks like there's at least the going-to-be start of a, of a, of a ramp to get on the bridge. Like, the bridge looks solid. The actual center part looks solid. It doesn't feel that hard to finish this bridge. I'm optimistic. Realistic that this gets done in the next 100 years, like, top.
Apparently Colorado built a wildlife bridge for a low cost of $15 million. Oh, that's not bad. Functionally, something very, very similar. The interesting thing is apparently the bridge is in some part for cougars.
Cool.
And the wild thing is, like, on one side of the bridge, you have a bunch of, like, residential homes, and on the other side, you have a bunch of cougars. And so they're now gonna— the cougars are gonna be able to go basically hang in all the backyards. So we'll see how this goes, but I'm excited for this to be finished up.
What else is Anthropic doing? They're hiring for a policy manager who will be in charge of chemical weapons and high-yield explosives. This reads like you're going to be building high-yield explosives, which sounds like an Anduril job posting, but it is in fact for a policy manager who will be hopefully stopping people from—
No, no, no. I read this as somebody whose job it is to decide how Claude is used to create chemical weapons and high-yield explosives.
I think it's probably like this person decides like, where's the edge? If you're asking like, okay, I have a firework and I want to make sure it doesn't go off. Like, should I, you know, throw it in the trash or put it in the recycling or take it to a special place? Like Claude should answer that. But if you go to it and you ask it like, how do I build C4 or something like that. Like, there's all these policy edges where if you're talking about Counter-Strike and you say, like, let's plant the bomb, it shouldn't flag that as, okay, you're actually trying to plant a bomb. It's like, no, you're asking about a video game. We know how to interpret that appropriately. But there needs to be a human in the loop to decide where that frontier is and where that particular trigger is.
Martin Shkreli, what does he say? He's coming on Monday for the great debate, the great peptide debate. Good music is the last mile of AI. And Lil Wayne has some thoughts on AI music. Let's play this clip.
Let's play this 2-minute clip. How do you handle AI in this business now?
Challenge.
The challenge.
Bro, that's wild. I love it. AI is a better thing. I love that AI is what it is.
Yeah.
Because man, I love to be able to stand right next to whoever AI is, he, she, they, whatever, or whatever AI is, stand right next to them and I'm still better. I'm gonna keep telling you what you do again. Yeah, you're gonna run your list. I do this, I do that. I love it. I love the challenge of it. The first time I seen it, somebody was— there was my friends was a little worried. It was like, man, bro, they got this AI stuff where you can just ask it to give you a verse like Lil Wayne. And so I did it. I said, look at me, let me hear a verse. It gave me Her Best Shot. Yeah, I've done it on a couple of devices. Asked her to give me one and they all, oh, you suck.
So that's all right.
We're going to be okay.
I fuck with that. AI is another— Beanie Sigel, I think he had to start using it because he was losing his voice a little bit.
Yeah, another rapper to mog.
Basically, that's his take. That's so funny. That's great.
There is some breaking news that we do got to talk about. Jeff Bezos in talks to raise $100 billion for AI manufacturing fund. The Amazon founder traveled to the Middle East, Singapore, in fundraising effort linked to Project Prometheus.
That is incredible.
Very, very exciting.
Breaking news. Advanced talks. I don't care if it's just advanced talks.
I'm hitting the—
Congratulations to Jeff Bezos.
It's meeting with some of the world's largest asset managers to raise funds for the project. A few months ago, he traveled to the Middle East to discuss the new fund with sovereign wealth representatives. It's being described as a manufacturing transformation vehicle. I am absolutely—
They're going up against TK, right?
Maybe.
I mean, TK is not as directly focused on manufacturing. Like, this is something I asked.
Yeah, but transportation vehicle, right?
No, no, he's saying manufacturing transportation, like it's a vehicle, a fund for transforming manufacturing.
Oh, yeah, yeah, yeah.
It's like an investing vehicle. It's aiming to buy companies in major industrial sectors, such as chipmaking, defense, aerospace. It would dwarf the size of some of the world's largest buyout funds and rival SoftBank's $100 billion fund. I got to wonder, how much do you think Jeff is pitching in himself? He's like, I'm good for $30, something in that range. But this is such a white pill. Basically, we need to reindustrialize America. We're not going to do it by just copying everything from the past. There's some element of transformation that needs to happen as well as new efforts. This is tremendous news.
Yeah. And I mean, there has been like a venture capital boom in reindustrialization, but Most of the funds that we talk to that are in that category are $50 million, a couple hundred million, certainly nothing at this scale. And this has got to be incredible news for the founders that we talk to that are part of the reindustrialization effort. Thank you for watching. Leave us 5 stars on Apple Podcasts and Spotify.
It's been an honor to be with you today.
We will see you tomorrow. Going Flashbang. Goodbye.
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