Cerebras IPO, Warsh Confirmed Fed Chair, Musk-OpenAI Trial Nears End | Diet TBPN

There's a ton of news. Let's start with Cerebris. The IPO has gone spectacularly well. Cerebris doubled their valuation basically overnight. Brandon Garel had the good fortune of writing up some of the details of the Cerebris news in the newsletter today, tbpn.com. You can go sign up.

Yeah.

Chip company.

And right now, it's sitting at a 64. $4 billion market cap. And a lot of the prediction markets, they didn't even have a category above $50, right? A lot of people were just kind of trading or betting.

And when I wrote the newsletter Friday, Monday, I said a $50 billion IPO and was sort of being optimistic. And it beat those expectations, which is great news. Chip design company Cerebras, if you're not familiar, they make a big, big chip. Big chip company. Instead of—

The biggest chip.

Instead of taking the wafer, putting a bunch of chips on it, cutting it up into smaller chips, they use the whole wafer. It's genius. Genius idea. It's one of those simple ideas taken deadly seriously in some ways. But it's trading at $350 a share on its first day of public trading, which values the company much higher.

$300 now.

$300.

Yeah.

$300. OK, the price in this IPO has been literally up only on Monday. The price range was $150 to $160. Then they raised it. That was up from $115 to $125. And today, we're seeing, you know, much higher prices.

Go back to that picture. Someone should make a set in LA. You know, they have those like fake private jet sets. Imagine if entrepreneurs could have a set where they put their logo in the background, like they're hitting it with a hammer and there's confetti going out.

Yeah, yeah, but it's for your course. Yeah, yeah. And you walk right from there, uh, to, to the Lambo.

1,000 students in your mastermind.

Yeah, no, I had this, I had this idea back in the day when— do you remember the ice cream The Ice Cream Museum, this whole thing?

Oh, yeah.

So there was this trend— I mean, really bad news for the museum industry, but they're getting eaten alive. And so some entrepreneurs— I think they did very well— started something called the Ice Cream Museum, which was not really a museum in the sense of like a presidential library, or the Norton Simon, or the Getty, or the Natural History Museum. It was more of like an experiential place to go and hang out, good for first dates, good for taking kids maybe. And they would maybe give you some ice cream, but most of the museum was just like very Instagrammable things. So there would be like a ball pit or a bunch of raining confetti and stuff and a huge fabricated statue of ice cream that was not a piece of art that would be sold.

A Sprinkle Ball Pit.

There you go. That sounds real. I don't know if that is real, but it sounds very believable. Yeah, they had that.

They had that?

Okay, yeah. And there were a number a lot of other kind of copycats that were trying to jump on and do like, oh, we'll do like the Waffle Museum or something, or the Pancake Museum, you know, because they just wanted to cash in. And my idea was just the Museum of Instagrammable Objects. And so it would have all of those. So there would be a private jet set, and then there would be a Lamborghini set, and this one would fit right in. So it's just, they have a big pink wall so you can go take the pink wall photo, and then there's a beach, and then there was a gym with fake weights so you could go and look like you're maxing out and benching 500 pounds. And so it just says, bring these clothes, or we'll have them for you. And then you move from room to room taking the ideal dating profile photo. Yeah, exactly. Exactly. Oh, you had kids here. You in the hospital. You can live an entire life through this fictional museum of Instagrammable objects. More of a meme than a real business idea. But— No, John.

The Museum of Ice Cream now has 7 locations.

OK, so they're cooking.

They're global.

They're global. They're global. They're doing well. Anyway, let's go back to the serious stuff. Cerebris. It's a complicated— company because they are so deep in the AI supply chain, but we'll break it all down for you. So there's a bunch of interesting takeaways, some really solid positives. Cerebras chips work, which was something people were not expecting for a while. There was a lot of FUD around this company. Just the idea of like, oh, that'll never work. What if the architecture changes? What if we go away from transformers or something? What if we need something completely different? Or maybe the yields will never work because there was this idea that if you're using the entire wafer, Typically, as you're etching the chips onto the wafer, sometimes there's little defects and it's not a problem if you're gonna break up a wafer into like 64 chips 'cause you just throw away one. But if there's one defect on basically every wafer, well then your yield is gonna be super low. We talked to Andrew about how he solved that by creating redundant cores and they don't actually activate all the cores. And so they sort of built in that redundancy and got through that. But that was an early critique of the strategy. Yeah, so they work.

You can use it. You can use Cerebras chips today. Yeah, yeah.

In Codex 5.3 Spark. And so they are very fast. And I think the most important thing that Semi Analysis points out is that token consumers, customers, businesses have shown this revealed preference for and a willingness to pay for speed. And they sort of contextualize it and they quantify it based on their own usage and their experience with Anthropic's Opus models. So Opus 4.6 fast mode Famously, I like that they use famously because it's like famous to like 100,000 people, but famously charges 6 times the price for 2.5 times the interactivity, although it's now under 2x faster. So effectively you're paying 6 times the price for 2 times the speed. That's, that's disproportionately more money for what you're getting. You would think you'd pay 6 times the price for 6 times the speed potentially. But there were a lot of questions about would people really pay for more, that much more for faster models, faster inference. And Andrej Karpathy, Sam Altman was saying like, do you want faster models or smarter models? And he was like, I think— and Sam's point was sort of like these models are very intelligent, but using them faster is sort of more of a magical superpower. And Sam was— I felt like Sam was sort of leading it towards like speed is really important as the next leg up on productivity. And Aadar Karpathy was like, "No, I just want smarter. I'll just let it run overnight. I don't mind that." But that's not what everyone is feeling. Some people, especially the Semianalysis team, leaned more towards interactivity or speed over raw intelligence power.

Well, yeah, and then there's the other aspect, which is just capability. Capability, speed, and intelligence. That's like the question people have had is like, okay, What is— is there a 250 IQ model or is there just a much more capable model?

Yeah, the unhobbled one.

That can use tools more efficiently and is really quick.

Yeah. And that's actually important to Cerebras. Semianalysis was spending 80% of their AI spend on Opus 4.6 Fast. And so they were willing to pay that 6x, like 80% of their spend, disproportionately more, even though when their sort of expectation, as they put it, was that they would always want the smartest model, they would be very cost conscious. They were in reality saying, I'm gonna hammer fast mode, I wanna spend on fast mode. And then I think the price was significant. And so there's probably sort of a renegotiation about when is the right time to use fast versus when do you wanna leave something running overnight. But OpenAI is clearly very pilled on Cerebras. Cerebras has a big 750-megawatt deal with OpenAI and the chips are already serving GPT-5.3 in Codex under the name Spark, as we mentioned. And I've used it, you should use it. It's a very interesting experience because I think a lot people have interacted with LLMs and chatbots and they're sort of used to this token streaming in. It's sort of cute because the phone vibrates and it feels like you're talking to someone who's typing, but it's way better when you just land on a Wikipedia page, the full thing loads and you can just scroll however much you want. And that's the experience that I think people want and will demand across everything, especially if they're firing off a coding task. They just want the code immediately. You can also just go talk to the model like it's ChatGPT. You don't need to use Codex 5.3 Spark. In a coding context, you can ask it whatever you want and it will just act like a normal LLM. I personally think there will be huge demand for faster inference across all parts of the AI economy. There's this old—

Yeah, another, another way to think about it is like if you have two employees with the same skill set, the same capability, but one is just 5 times faster, right? That person can create way more value in the organization. Yeah, right.

And for a lot of things, if they're, if they're 2 times faster, they do command 6 times the price. A sales rep that sells twice as much, or someone who is twice as effective at their job, might actually command a salary that's 5 times, 6 times the actual price. And so there's lots of other context across different business lines that you could draw to. There's also this old adage or saying about e-commerce that might may or may not be real, but it's probably been transposed so many times in think pieces, I don't know the real quote, but it goes something like, "Every 100 milliseconds of latency costs Amazon 1% in sales." I don't know if that's the right way to think about it, but basically as Amazon was scaling, they realized that there were a bunch of things that they could do on the UI side, a bunch of things they could do on the layout side. Where does the buy button go? Where does certain information go? The price, the discount, all of this stuff, the images, they were tweaking the front end, but as they did that, they added bloat and the pages would slow down. And what they noticed was that the slower the page was, the lower the conversion rate, because people were waiting for Amazon.com to load, click on the page, it takes a second, they get distracted, they go somewhere else. And I think that that's happening in LLM use cases all over the place. People fire off a query and they're like, oh, it's taking too long. I'll go scroll Instagram Reels. There's always an Instagram Reel. And they'll be like, oh, I kind of forgot about what I was asking about. I didn't get my answer. And that's certainly true in business contexts as well. This is currently playing out in AI inference. Companies are paying disproportionately more for faster inference, and this is good for Cerebras. But Semi Analysis does point out a number of potential headwinds and problems that the team at Cerebras will have to solve or contend with over the next few years. Mainly, Cerebras chips are not currently as capable of holding larger models in the limited memory that they have or networking multiple chips together to serve larger models. We've heard about the NVL72 racks that wire a whole bunch of Nvidia chips together can serve these really large models. That has potentially been a challenge. So Semi Analysis says, moreover, the industry is trending towards larger context windows ad infinitum. 128K context will certainly not be acceptable for long, especially with the prevalence of agentic workloads. And it doesn't look like there's a simple solution of just scaling the wafer size larger because TSMC is set up with a standard wafer size or adding more memory to the existing architecture because Cerebras' whole design depends on a lot of SRAM, static random access memory directly on the, on the wafer. But SRAM is no longer shrinking as much with each new semiconductor node. So the last version of the Cerebras chip, they've done WSE-1, 2, and 3. They're on 3 now, but WSE-2, had 40 gigs of memory. WSE-3, you would expect, oh, we want a doubling, right? We want a, we want a 10x or something. It got 44. So a 10% increase over one process node, one iteration. Is there an easy way to double this? Is there a question like how will this scale as the models get bigger to add more SRAM? You might have to sacrifice compute area because everything is being done on one wafer if you want computation or memory, there's a direct trade-off because you only have so much space on the actual wafer. But in an agentic workflow, I think it's entirely possible that you want like the biggest, most powerful model, like the vice president delegating things. You want the vice president—

Senior or junior?

Senior vice president, maybe just the president handling the critical work. So future models might not, and that might not be on Cerebras, that might be on an NVL-72 or, TPUs or something. But I imagine that we will quickly jump from the agentic age where you're firing the best, smartest model at the full workload to the orchestration age, and there will be hybrid approaches. So the biggest and best models will delegate certain tasks to smaller, faster models, just like they go and do database queries these days, or they go and search the web these days, and that's CPU bound. There will be certain workloads that the larger, smarter agent model, like the boss model, can sort of delegate to the cerebrus speed workers, the faster workers. A year or two ago when Daniel Gross wrote AGI Bets and was sort of like, is NVIDIA underpriced? I don't know if NVIDIA— he might have said that on Semi on Stratechery. But, you know, we entered the AI age and everyone was like, oh, GPUs are the future. NVIDIA is the company. But then it was like NVIDIA GPUs are good. And then also CPUs are good. ARM is getting into it and Intel's doing very well.

We're going to make big computers.

Big computers. Big computers for sure. Ho Nam says, this IPO illustrates the power of an individual partner over the brand name of the firm. Pierre Lemoine was a partner at both Sequoia and Khosla, but instead of those firms backing Cerebras, it was Eclipse, the firm he joined at the age of 84, that backed this little-known chip company multiple times in the early days. What a way to wrap up a career. He was born in 1930, the same year as Warren Buffett.

Wow.

That is an awesome story. I love that. One-third of the order book, the folks that said, I want shares in the Cerebris IPO, one-third of the book got zero. I guess the top 25 investors took 60%. That's probably the big investment funds, the Fidelities, the State Streets, the BlackRock.

They have done quite well today. This picture looks wildly different than the Klarna IPO last year, in which— only a handful of the team at Klarna popped over, hit the NYSE, IPO'd, and then went back home.

Yeah, it was very much just like another day at the office for the team. Yeah, that's definitely what I was contrasting it to. The Cerebras valuation every round, Series A in 2016, $100 million, Foundation Benchmark and Eclipse. Coatue led the Series B in 2016. VY Capital led the Series C in 2017. Then $1.6 billion valuation in 2018, $2.4 billion in 2019, $4 billion in 2021. That was like maybe a little bit of a slump, but then 2025, Atreides and Fidelity come in at $8 billion, then Tiger comes in at $23 billion. Then in May of 2026, they IPO at $48.8 billion. Let's run through the Kevin Warsh news because he has been confirmed as the Fed chair, Kevin Warsh, who is most famous for interviewing Alex Karp on CNBC while Alex Karp appeared to have popped a nicotine pouch and then spun a notebook on his finger. Did you ever find that clip, Tyler? Is that in the timeline?

Yeah, it should be.

OK. Let's play the clip that really put Kevin Warsh on the map.

I remember I showed up in your office once. I was dressed like this. Screamed at one of the guys. He said, Kevin's here, he looks like the guy from IBM. And I was talking about, well, you know, we need like really finance controls and, you know, how are you going to sell the product and all this stuff.

Okay.

But I would say you certainly built that.

He's really spinning it. I didn't realize he goes back to it like 4 times. He's spinning.

Dirty word anymore.

He's really good at this.

But somehow you grafted that on to the, to the strange company that can produce these products. How's that transition been, if I've got it right?

I have so many questions. First, we have to get him to recreate that for sure. Second, I thought— Tyler, I thought we were talking about that being on CNBC, but that looks like just a podcast. Like, that doesn't have any chyron.

Yeah, no, I don't think it was actually on. I think it was from Palantir. Like, that was a Palantir—

Oh, okay. So it was just like a random podcast. And then, and then when I've seen on CNBC, they were playing the clip. Got it.

I think so. Yeah.

The vote was 54 to 45 in the Senate. The divided vote signals challenges ahead for Warsh, who faces a Fed committee skeptical of rate cuts that Trump has demanded. And of course, we talked about the inflation news. Typically, you don't cut interest rates going into inflation and potentially economic stagnation. You definitely don't cut rates in— that's why stagflation is so difficult, because if you have stagnation and low inflation, you can cut rates very easily. Maybe the economy starts overheating a little bit, you get a little bit of inflation, but then you can pull back. That's what we've done historically. Historically, vice versa. If the economy's running hot, you're seeing high GDP growth and high inflation. Well, if you raise rates, you're going to pull back on both of those. But in stagflation, you're seeing both inflation and sta— and economic stagnation, harder to deal with as a Fed chairman, which is potentially the task he will be faced with. So the Senate confirmed Kevin Warsh as the Federal Reserve's 17th chair Wednesday in a largely party-line vote that required, that reflected how tensions with the White House have dragged the Fed deeper into the political fray. I was looking back at the old Fed chairs. There's some absolutely legends in there because some of them had really long runs. So very quickly you get back to the black and white portrait in the painting as you go back in time.

Who's your favorite Fed chair?

Hmm.

Volcker. Yeah, Volcker is pretty good. Bernanke is great.

Absolute dog. Yeah.

I don't know. Hard to pick. Hard to pick. Chair Jerome Powell, whose leadership tenure— whose leadership tenure ends Friday, captured at least 80 votes in Senate confirmations for each of his two terms atop the Fed. Wow, Jerome Powell, just fan favorite of both teams, 80 votes in the Senate. That's pretty significant. I'm putting him in the conversation, Jordi, but I'm not giving him the GOAT trophy. Yeah, I'm not saying that. Because the challenges faced, he wasn't confronted with a Great Recession, a dot-com bubble bursting, a Black Friday. The economy from 2018 to today—

Global pandemic doesn't— you don't count a shutdown of—

No, because— large parts of the economy. No, no, no, I actually don't, because the economy was pretty strong in 2019. And it went into 2020 with pretty strong consumer balance sheets, low debt. There wasn't a shadow banking economy. Bomb in the US economy waiting to explode. And so although we saw high unemployment briefly, and we did have to stimulate the economy, that's not his job. His job was to set rates. There was a little bit of like, I mean, maybe you put the inflation, the ZIRP era and the end of the ZIRP era and all of those gyrations on him. But the problems that were downstream of both the ZIRP era and the end of the ZIRP era were suffered mostly and benefited mostly on like tech companies and Silicon Valley companies that had really long cash flow horizons. And so there was not a moment where it was a dire situation that the Fed had to intervene in a meaningful way and like save the economy like in 2008. It's a big deal. He did a great job, but he didn't— he wasn't faced with the same challenges of a Bernanke. For example. That's what I'd say. Tyler, what do you think?

Yeah, I think that's reasonable. But also, like, if Powell was worse at his job and you saw some crazy crash because of COVID and then he brought it back, like, then it'd be like, oh yeah, he did face this massive thing. But because he did such a good job, maybe you didn't see any, like, massive crash. Nothing super bad happening is evidence that he was really good as a Fed chairman.

Yeah. Yeah, maybe he's a defensive back. You know, they don't score. There's no great plays. 'cause he's just shut down, shut down cornerback. Anyway, Jensen Huang is over in China. Jason Calacanis has a photo that looks extremely real, zero AI detected, but he's bringing two huge boxes of GeForce RTX 5090s, which are—

This is a picture from when he was in Alaska too.

Jason says, "Never stop selling." I agree. There is some news, which we will cover later in the week around the dynamics around H100 sales. And Blackwell's what's actually happening. It's all in flux as the Trump-China summit plays out on the front page of the Wall Street Journal every day this week because it is headline news. High-stakes US-China summit kicks off. Watch a team of humanoid robots running a full 8-hour shift at human performance levels. And Brett Adcock said this is fully autonomous running Helix 2.

All right, pull up this post from Pete.

Yes, and the stream did fantastically. It was 24 hours, it got 3.4 million views. But at a certain point during the stream, there was some questions about whether or not the humanoid robot was in fact—

All right, back to the beginning. Back to the beginning.

Okay, let's play this.

All right, so it's cooking. I mean, the speed is actually insane.

And we were extremely impressed by this. This was remarkable. Remarkable.

Even if it's teleoperated, it's extremely impressive.

Yeah, yeah, yeah. Like the robot's clearly working. This is very—

But they're saying that it's not teleop.

Okay. So then the robot starts missing things, being a little bit like an inch off and then reaches up and touches the robot's head. The robot, which is something that wouldn't normally be necessary. It doesn't have like a logical explanation or conclusion. So a lot of people are asking—

It does have a semi-logical conclusion, which is that Brett is claiming when it reaches across its body, to go to the right, that it puts its hand up here to get the hand out of the way.

That's what I was thinking was that if the hand is halfway up, it might be blocking the sensor, the camera sensor. And so even though, like, you might— the robot might reach the hand up further to move out of the view so that the robot can look at the next package. So that's one possible explanation. But a lot of people are asking even harder questions saying that potentially Was there a human in the loop? Was this teleoperated? Which is something Brett has said it's fully autonomous. I feel like that means no humans in the loop, but TR Taxis has an artist's representation of Helix 2, figures in-house neural network running entirely on board. And it, of course, is a human in a VR headset. Very, very debatable. We'll see where you stand. But there is— there is a third option which I have shared, which is potentially no humans involved. I don't know if you'd call it autonomous, but you would call it no humans in the loop because you have—

Well, it is an autonomous system, right? It just sort of runs.

Yeah, I would consider this autonomous. It's the, it's the image that I shared in the production chat. It's not of a human and it's not quite robotic, but there's no human in the loop. And so this could explain the system is running with no humans in the loop. If you make that claim and you follow this, I think this qualifies as no humans in the loop. If you have a giant orangutan in a VR headset puppeteering the robot via teleoperation, you could say that this system does not have a human in the loop. And you could make that claim.

And I could make the argument that it's autonomous.

Yes.

The chimpanzee is running its own. It has somewhat of a neural— Neural network.

It's like a neural network. The OpenAI Elon Musk trial is in its final day. The trial is ending. People expected 4 weeks of trial. We only got 3. They're cutting it short. What are the prediction markets saying about who's going to win? I want to know that. And I want to go to Mike Isaac, the Rat King, because he has a breakdown of what's going on. He says, good morning. Closing arguments of Musk versus OpenAI with special guest Microsoft. Are happening today.

The calci— well, Elon, when his case against OpenAI, it peaked at a 58% chance.

Okay, where is it now?

28th, it's now sitting at 30% chance.

30% chance. Okay. So right now the judge is instructing the jury on the criteria by which they should be judging the outcome of the case. Important because if the jury listens and carries this out, it is a very, very specific lens through which they view all the evidence. Ostensibly, it's where theater ends. Listening to this and being read out in court for the last 23, 30 minutes is very helpful because it's clarifying on how high the bar is for the plaintiff's side approving some of these claims. Sort of feel bad for the AV guy during this trial. There's been feedback, been mic drops, but not in the good way. The mics have been dropping out. Funky video feeds. They need to revamp this place, says Mike Isaac. LMAO. The first joke of the tweetstorm, he says. Musk counsel is going after OpenAI execs Altman and Brockman. And has the mugshot-style photo of Altman on the screen. Again, battle of Photoshop of executives in this trial has been entertaining to watch. You want to depict your opponent in the worst possible light. Musk counsel going back and forth, hammering the point they made over and over. The argument essentially painting a picture— Sam Altman, liar. Chipping away at witness credibility has been a core strategy for the plaintiff's side. And we're back to everyone hates Google again. Molo is using Larry Page, who they claim doesn't care about humanity as a foil to the noble Musk, who only— whose only care with respect to AI is the future of humanity. Musk counsel is painting the don't trust Sam picture in a bit more detail for the jury. Also, Musk's side has a picture of Elon and Altman on the screen now. Sam's looks like he's about to be processed by a U.S. Marshal. Musk's looks like he's getting ready for the Met Gala. LOL. Lots of Musk closing side arguments, semi-populist track of pointing open— pointing at OpenAI and saying these billionaires are making gobs of cash while running a charity for the supposed good of the world. I'm curious if jury jury can register this argument, even if it comes from Elon Musk, the world's richest man. Ouch. OpenAI counsel begins closing argument with a broadside against Musk.

Every—

even the people who work for him, even the mother of his children, can't back his story. Oh yeah, back to the war of the Photoshops. Closing remarks now in, in the digital displays on the monitors for exhibits. All the OpenAI executives look like Olan Mills photo shoots. Do you know who Olan is? He says it's complimentary. I need to get up to speed on my photographers.

Olan Mills is a portrait— offers portrait photography.

Ooh, does look very nice. You pull up the Google Images on Olan Mills. Anyway, short summary of the closing. Musk camp: all these OpenAI executives are rich as hell and lying all the time. OpenAI camp: all of that is a sideshow, and literally all the claims Musk is bringing cannot be stood up by actual law. The Microsoft camp disappears into bushes. Dota got mentioned again. They love mentioning Defense of the Ancients. Incredible Photoshop from the OpenAI camp of a calendar of events complete with little characters and a timeline of events. I wonder if they're using ImageGen too or if they're doing it the old-fashioned way. I can't wait until it's entered into evidence this afternoon so he can show us. Sort of want to buy this meme guitar, but I also have two Telecasters. Is that just completely side note? Gamer. Has entered da blog. The Dota moment has been mentioned nearly every single day during this 3-week trial. AI researcher— we gotta have Mike back on the show, it's so good— saw as a true breakthrough in the technology.

What is the timeline for the jury to meet? Okay, is this, uh, something they're doing today?

So they're getting a 30-minute recess, most they've had in a month. I might actually be able to go outside and get real food. There's a Popeyes across the street. Is it a bad idea to get a bucket of red beans and rice? That's what thinking about doing. So not much news on when this will close. It is 1:10 Pacific time. I imagine that they will wrap up by— what did he say, 3 p.m., 4 p.m.? So 30-minute break that happened 40 minutes ago. So I imagine that.

And but they've been taking Fridays off is kind of what I'm getting at.

Oh, yeah.

I guess this could.

So maybe this happens to Monday. This is just closing arguments, not necessarily the end of the trial or the jury get the results.

Or the jury might, might make a quick call.

But well, there was an update unlikely 11 minutes ago. A lawyer for OpenAI on Thursday defended the company's chief executive Sam Altman from withering character attacks by Elon Musk's legal team as both sides deliver their closing arguments in a trial with potentially seismic implications. The stakes are high. Mr. Musk, who was not in the courtroom on Thursday because he was in China with President Trump, is asking for more than $150 billion in damages. He is also asking the court to remove Mr. Altman from the startup's board and to stop a shift the company made last year to operate as a for-profit company. They pushed back. Sarah Eddy, member of OpenAI legal team, tried in her closing argument to dull the attacks on Altman's credibility and to argue that there was never a firm agreement among the founders that could have been breached. Not one in this case other than Elon Musk has testified to any commitments or promises that Sam Altman or Greg Brockman or OpenAI made to Mr. Musk is what she's is saying. After the recess, William Savitt, OpenAI's lead counsel, told the jury that Musk does not have a claim against the startup unless there was a specific agreement between Musk and OpenAI describing how his donations to the nonprofit should be spent. That agreement does not exist, Savitt said. So that's where I guess OpenAI is leaving it for now. We will continue to cover the story as it evolves.

Doug says, is the jury allowed to use Codex? gold be done in 1.5 hours.

There's other tech problems going on. Max Zeff over at Wired has been covering the story as well and says Musk's lawyer brought a big monitor, maybe 36 inches, into the courtroom. OpenAI's lawyers asked to use it. Musk's lawyers said no. The judge told Musk's lawyers that they have to let OpenAI use it. Then OpenAI said it might not be possible to connect their laptops AGI is here, but we'll still need a dongle, I suppose. Dongle has entered the courtroom. Magzef says there's about 50, 15 lawyers standing in the middle of the room right now talking how to use, talking about how to use this big monitor. This is wild.

In other news, Tim Draper says, I think I broke a record. I took 52 pitches in 52 minutes at below 40 degrees. Welcome to my office. #DraperUniversity #SurvivalTraining. What do we think about going in the ice tank?

How cold are ice baths typically? You, you've done ice, ice baths. I feel like I did one and it wasn't as insanely difficult as people said, but then I checked the temperature and I don't think it was 40. I think it was closer to 50.

Yeah, you can totally get closer to I, I, I, I, um, because there's a couple companies that sell it personally. When, when, if you're going surfing and the water is below 45 degrees, it can just be very painful.

Okay.

Like to, yeah. So even in a wetsuit, okay, your fingers go down anywhere that's not covered. A lot of people are putting gloves on, uh, booties.

What do you think, Tyler?

So apparently Joe Rogan's at like 34.

34? Yeah. Wow.

So that's like the cold plunge, you know.

He's the top of the mountain when it comes to ice baths. He's the final boss.

Uh, uh, this, yeah, this, this is just a crazy picture. I did think it was, I did think it was AI, but turns out it's real. It's just funny because it looks like, like, what is this set? What is this setup?

Yeah. What are all the trash bags there? And the wall is like sort of decrepit and there's piping.

It looks like kind of like a prison ice bath.

Yeah. This is not what you'd expect from, I mean, isn't he a billionaire? A billionaire investor. You'd expect some sort of palatial— you see the properties that Mark Zuckerberg is acquiring, that big investors are acquiring, you would expect something that would be much more regal. But he's doing it the old-fashioned way, whipped this up himself, bought some trash bags, and took some pictures. Yeah, that's our show, folks. Leave us 5 stars on Apple Podcasts and Spotify. Sign up for our newsletter at tbpn.com. See you tomorrow at 11:00 AM Pacific time and have a great rest of your day. Goodbye.