Cerebras IPO, WarshTime, General Catalyst Ad Reactions | Andrew Feldman, Amy Reinhard, Ben Hylak, Doug O'Laughlin, Eric Vishria, Steve Vassallo

28:00That's what I would say. Tyler, what do you think? Yeah, I think that's reasonable. But also like, you know, 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 massive crash. So nothing super bad happening is evidence that he was really good as a Fed chairman, right? Yeah, yeah, maybe. He's a defensive back. If they don't score, there's no great players because he's just shut down cornerback for the last couple of years, potentially.

28:36He's definitely in the top 17. I'll give him that. anyway Kevin Warsh Chair Jerome Powell whose leadership tenure ends Friday captured at least 80 votes in the Senate the previous chair Janet Yellen was a little bit more controversial confirmed 56 to 26 seems like not that many people showed up in 2014 to vote for Janet Yellen with many senators absent because of bad weather interesting I wonder what would have happened I mean it feels like she would have cleared it no matter what but a difficult economic backdrop Trump's broadsides against the Fed independence have set up the central bank for a thorny leadership transition.

29:15Senate committee confirmation hearing last month, Warsh faced intense questioning from Democrats over how he would maintain the Fed's independence from a president who places priority on personal loyalty. Warsh said he would preserve the central bank's monetary independence and that he had made Trump no promises about policy decisions. Powell, citing concerns about political attacks on the institution, plans to remain on the Fed's board of governors, defying Trump's insistence that he leave. He says, you're gonna have to drag me out of here. I'm staying at the Fed, says Jerome Powell. Warsh is 56.

29:52He's been immersed in monetary policy debates for decades, frequently as an outspoken critic of the Fed. Former Morgan Stanley investment banker, he became the youngest Fed governor in history at 35, when former President George W. Bush appointed him to the Central Bank's board in 2006. During the financial crisis that struck two years later, he played a key role in tying up rescue deals. He was the bridge between Wall Street and the Fed that sort of Bernanke deployed. And so those are his laurels that he will not be resting on, but he will be drawing on from experience. So Warsh left the Fed in 2011.

30:28He had become a critic of its direction, concerned that as the economy recovered, the Fed's ongoing efforts to support financial markets went too far. So we will have to check in with the progress on Fed Chairman Kevin Warsh soon. But fortunately, we have our first guest of the show, Amy Reinhardt from Netflix in the waiting room. Let's bring her in to the TV show. Amy, how are you doing? Doing well. How are you doing? Doing fantastically. It is an honor to have you here. Yes. Our first ever guest from Netflix. I think so. Thank you so much for taking the time. It only took like 2 ,000 interviews to get you guys on here, but we're excited to meet you.

31:11It's an honor to be the first. Yes. Yes. I mean, obviously big fans of both Netflix and advertising, but would love to start with a little bit of background on yourself, your experience, and just sort of your intro to how you found yourself as the president of ads at Netflix today. Sure. I've been at Netflix for about nine and a half years now in a couple of different roles. Started out first in our content organization, doing both licensing and then overseeing production. And about two and a half years ago, I stepped into this role overseeing our ads here. And it's been a fantastic two and a half years, a lot of excitement.

31:54Feels like we've been able to accomplish a lot and great company. If you take us back to the initial push into ads, what can you tell us about the tradeoffs, the build versus buy debates that were going on at the time, maybe even the cultural changes? I think we are super, you know, we love ads. We think it's a fantastic business model. It's a way to deliver great value to customers at lower prices. And there's so many benefits. But culturally. Yeah, what was the debate like? Yeah, what was it like internally? Yeah, well, I think it's been well publicized, you know, that not being in advertising was a strategic bet for a long time.

32:38Right. And so early in 2021, 2022, when we started to talk about the notion of getting into this business, yeah, it created a lot of, I think, fair to say, you know, angst within the company for a bit of time because it was such a big shift, to your point, culturally and strategically. So I would say, and then we made the announcement that we were getting into it. And in terms of the whole build versus buy, you know, we partnered with Microsoft to enter the business very quickly. And that got us up and running. But it's been, you know, we made the decision about 18 months ago to lean into building our own tech stack.

33:22And we launched that a year ago. So we're just a year. I keep having to remind myself how nascent our tech stack is because we've been able to deliver so many developments and so much progress against that over the course of the last year. But I would say full circle, you know, we were past we put to bed all notions that we should be in this business. I think everybody understands strategically now that it is important for us to be that. And we've been able to grow our user base because we have been able to get to a lot more consumers who are looking for that low cost option and are fine with ads.

33:56Right. So it's been a great thing for the company, I think. And everybody's on board. And, you know, the recent news, as you heard, which we just announced our upfront yesterday, that we're expanding that ad tier into 15 more countries around the world. There you go. Fantastic. Everybody's on board. Full speed ahead. How are you pitching the ad product today? Is this primarily brand marketing? Is there a timeline to get to more of a performance focus? What is your pitch to advertisers? Yeah. As we see in the marketplace, advertisers are oriented around outcomes, right? So we know that we need to be a full funnel solution, and we believe that we have the metrics to support that.

34:40So to your point, we've been very successful with some of the brand partnerships that we've done over the course of the last year and a half. But we've also seen really good conversions in terms of lower funnel and making sure that we're driving purchase intent and consideration. So as we build out more of our solutions, we are going after that full one all solution. What are conversations like around how brands should, how much brands should want to associate with particular pieces of content? Because I think some brands might come in and say, well, I'm advertising, you know, strollers. And I know that parents will be watching k-pop demon hunters with their kids and so like this is the most on the nose directed and i care i want my brand linked to this particular piece of content uh but we've seen time and time again that uh like once the algorithms get good enough once uh dynamic ad placement can actually flourish you every company uh tends to see better performance there.

35:47So where are the ad buyers today in terms of those trade-offs? You know, there's a full spectrum. So absolutely, we get advertisers who want to be associated with K-pop demon hunters like McDonald's or with Stranger Things, right? Like those big, powerful moments, those are oftentimes the easiest to sell. I think K-pop demon hunters is actually an interesting case because when it came out a year ago, we didn't know that we had a hit on our hands until about 60 days into it. And I think that's what the magic is of Netflix is that we have so much variety and depth of content that we're programming and trying to hit all audiences that you never know where your next hit is going to come from.

36:28And so selling those audiences, selling that, you know, audience behavior, moods, targeting moods and relevance is really important to a lot of different advertisers. So, again, we just want to meet advertisers where they're at. And some folks understand that being across a number of different programming choices is important. And some people want to tag along with those big tentpoles. And we want to, you know, provide those opportunities. Yeah. I mean, it's interesting. Netflix has, like, deep, deep experience in machine learning, AI, recommendations, all parts of, like, you know, high throughput data processing.

37:06but I'm interested in any learnings or surprises from building the proprietary ad delivery stack. Has it been as expected? Has it been there's new skills that you need to bring? Because a lot of companies have been successful at scaling content and then struggle to figure out ad delivery. You obviously haven't. But then also there's this AI boom going on, which can help with productivity, but also new algorithms and new ways to actually target content. And so I'm interested in where the build out didn't master expectations or surprised you. You know, as a tech company, we do a lot of testing and we go into things with hypotheses.

37:50So we're constantly testing things around our member experience. And, you know, I think that's been a differentiator for us, like really leaning into reducing member friction, making sure that member experience is a good one with lower ad loads. lower frequency apps, those types of things. But we do know that there are times when we have to pivot. So I would say there's not just one example of a time that we've had a wrong hypothesis. We're constantly testing things out and figuring out where we, you know, where those hypotheses prove out, where we need to pivot and, you know, change swiftly. So it's hard to point to one specific moment where it felt like it's been a learning.

38:35I would say the bigger learning for us just as a company is, you know, this is a relationship business, too. And we've never this, you know, you talked about kind of getting into ad sales. Right. We've never had a sales team in terms of our overall organization. So I would say there's more organizational learnings than necessarily tech learnings because we're so used to that tech cycle of testing and learning and iterating. How are you thinking about the ad product feeding back into the content production? I've noticed that Netflix has been fantastic, in my opinion, of creating more engaging content.

39:19I was watching The Rip with Matt Damon. And you click the play button and you see Matt Damon's face within like two seconds. And it clearly confirms that you're watching the right movie. And then the title card comes in. And that's a departure from 50 years ago. You watch The Shining and, you know, it's a helicopter shot of a car for five minutes. And they show you the full titles. And it is a different style of editing. And some people lament the old style. I particularly like the new style. And I'm wondering about, we went through a period of time when television, there was the famous like fade to black and then the ad break and then fade back in and you resume.

39:55And Netflix has never had to contend with that in media products. But is that going to come back? Is there a next generation pattern for creating content that can both have ads in it and not? Are you seeing glimmers of what the future, like the impact of ads might have on like the editing structure and the timing and the pacing? Yeah, a lot of it, to be honest, depends on our creators. So, you know, working with talent who and some of those and some of that talent may be more tech forward and are thinking through those types of things when they're writing shows. I'll give an example. Shonda Rhimes was used to writing for broadcasts and network for many, many years.

40:36So when she writes a lot of her content, she's already thinking about where those natural breaks are. But not all writers do that. And that's OK. we can still find what are those natural breaks because we want to make sure, again, getting back to the member experience, that it's not intrusive or it doesn't come mid-sentence and is cutting off any of the action. We're able to adapt to any way that our creators want to write the content and fit it into that member experience. For U.S. markets, is there any enterprise spending? I would imagine that a lot of enterprise buyers like have been Netflix subscribers for a really long time and maybe they're not getting served any ads at all.

41:23And so this is more of a consumer opportunity or am I thinking about that the wrong way? Most of our clients right now, the target segment that we're going after are enterprise top 400 clients, right? Because we think those are the ones who have spent. Sorry, I meant B2B versus B2C companies. Oh, we think about this more as a B2C opportunity for the most part. And I think as we expand our learning and expand our offering, may get into the B2B space, but for the most part, B2C. Yeah. Yeah, I feel like all of that, the higher up market, more targeted, that's all unlocked with scale once there's more learnings on responses.

42:06I'm wondering what other signals you think might be valuable because many times, you know, advertisements shown during a TV program are very passive, harder to track. But if someone's watching on their phone, there can actually be a call to action, a trackable link. Like, I imagine that the data's messy, but how important is it to sort of close that loop in an ATT era where it's a little bit trickier, but there's a lot of things that you can do on the signal side anyway. Yeah, you're absolutely right. And this is an area where I talked about the testing and iterating. We're leaning in a lot on the testing.

42:44What does that screen experience look like? You know, again, how do you meet the customers where they're at without being sort of intrusive? A lot of testing going on in this space. But the biggest thing for us is, you know, privacy safe. We want to make sure that we're leaning into, again, that member experience and taking care of our members' data. But a lot more, I think, to come. Have you been surprised by the return of the QR code in maybe podcast advertising? But I see it a lot because people are watching on, you know, they'll watch a YouTube video on a TV. And the creator will, you know, hard code in a QR code to link out.

43:23And that was something I had completely written off QR codes and then they made a major comeback. No, I agree with you from a member experience may not be the most simplistic thing. Understanding kind of the ad tech on the back end. I'm not surprised by it to be pretty complex pretty quickly. Yeah. And there's some we hit some sort of like inflection point where maybe it was in a certain iOS revision where the camera app became so easy to press a button and pull out. and then it detects the QR code so quickly that that flow, because you used to need to like have a QR app separately to scan it.

43:59Now it's all integrated. And so someone can just whip out their phone and run right to it. Jordy, you have something else? Nothing, nothing super top of mind right now. I mean, last question I had is, do you ever expect Netflix to serve more short form, vertical video style ads in something like the clips tab? I know the clips tab right now is focused on basically a content discovery. But I imagine in the future, people will spend more time in a format like that, especially on mobile. Absolutely. And that is one of the announcements we had at our upfront yesterday is that as we roll out this vertical video content, that we are going to be offering that to advertisers along with our to doom.com coverage in 2027.

44:46So, yes, we think that is a big opportunity, too. Last question for me. I would love to know about the intersection between games and ads. That's been a huge, huge growth driver with other categories and other companies. But I'm wondering where that is in the roadmap, how you're thinking about that. We haven't thought about that yet. Look, our roadmap, I could fill our roadmap for the next two to three years based on just some of the foundational things we want to do. and a lot of the innovative areas we want to lean into. But it's an area that we're keeping an eye on. And as we watch that game's engagement increase, I would never say never.

45:27I've learned to never say never at Netflix, but it's not something that's on the near-term or not. Okay, thank you. Well, thank you so much for joining. This was a really great - Great to meet you, Amy. Thanks for breaking it down. Thank you for having us. We'll talk to you soon. Cheers. Have a good one. Thank you. Moving on from Kevin Warsh, who is the newest Fed chair. We have a debate. We have a debate going on on the timeline around General Catalyst's advertisement. Some are calling it an attack ad. Particularly, Andreessen Horowitz is calling it an attack ad. We touched on this yesterday.

45:59But if you did not tune in, General Catalyst, the large-scaled, what do they call it, giga funds now? What do they call it? Platform fund. But there's something else. It's a huge, huge venture capital firm. They launched an advertisement, which we can play again to refresh everyone. Let's scroll back from the beginning. Yeah, let's play it from the beginning. Add some audio. It's only 30 seconds left. Hi, I'm GC. And I'm VC. Who's your friend here, VC? This is Woof AI, an AI native companion platform that combines robotics and machine learning. You'll never want a real dog after this. Well, I think people like dogs as they already are though, VC.

46:35You don't need to walk it. You never need to tell the kids you sent Milo to the farm. We're leading the seed and could probably make room for you. Well, I'd love to hear more, but we actually have a really high bar around responsibility for these things. Is Wolf AI okay? Of course he's fine.

46:55Oh, sorry, buddy. It's easy, easy. Stay. Stay. No. No! Stop. Stop. Stop! Stop! I'm sure he'll be fine. Okay, tons of thoughts, but you kick it off. What's your read on this? Take me through it. So the actual ad, the way it's shot, the timing, cinematography, it's fantastic. I do... Yeah! I think the ending is funny, right? It makes me smile a little bit. The dog's going haywire. The robot dog's going haywire. My first thought is I actually think there's a huge opportunity for a robot dog that is 10 times better than existing robot dogs. There are robot dog toys out there. So I don't. Specifically in the toy market, because this is a Boston.

47:58This is probably I mean, it seems like it's a Boston Dynamics robot dog. And those are not typically used as pets that I know of. I think that they are more deployed. Whenever I see a demo of a Boston Dynamics robot dog, it's like walking through a nuclear power plant that you don't want someone walking into. It's like an industrial product for the most part. And then obviously a fodder for viral videos. But yeah, step through it because it is a crazy back and forth from both firms. First, the stats, General Catalyst. Oh, they're over a thousand likes now, but two million views. so a lot of discussion Anjani Midha says it's a bit cringe guys Olivia Moore at Andreessen says if I was a consumer founder I would run for the hills watching this weird take from a fund that returns so much money from Airbnb and Snap because is the idea that like robot dog is a weird idea but so was Airbed and Breakfast or Snapchat right the biggest B2C businesses always start out looking weird yeah there's a way to do the same pitch for air bed and breakfast, which is, you know, that empty couch, you know, that empty room in your house.

49:10What if you were to monetize it? What if you were to allow strangers to sleep in the empty room in your house? And, and of course that was a lot of the criticism at the time was that, that it never was going to work. And it was strange, but then it created a lot of positive externalities. People build some businesses, people get to travel and integrate with local communities. So the main thing here is I do find it fascinating considering that when you actually look at the portfolio overlap, it is insane. Almost all of their winners. Almost all of their winners, especially in the modern era. They are in both companies.

49:59Yeah, of course. And so they're backing a lot of the same companies. So it's super hard to counter position against them. Now, granted, A16Z has a very different media strategy. They're very loud. They're all saying the R word a lot. And I think GC can kind of counter position against that. But you're not going to counter position against like what companies you're backing, right? Okay, GC, I had to look this up because I thought there's no way that it's true. GC's in both Calci and Polymarket. Yep. Big, great companies, right? But those have been at the center of the debates. But that is the center, those companies are at the center of the moral debate in tech, right?

50:43Certainly for the venture-packed, controversial companies. There are some that are controversial that are not. Yeah, and all the funds have backed various like betting, trading-related companies over the years. I think it was like GV did, what was it? Not DraftKings, but FanDuel, I think, back in the day. So it's not to say - There's companies that start out as controversial, and then they become completely normalized, and everyone sort of comes around to like, oh, that's a good thing. Anduril's a good example. Both Andreessen and GC are in Anduril. When it launched, it was like, wait, you're building defense technology?

51:19That's insane. And now the whole Silicon Valley community has come around to the idea that it's really important to have a functional defense industry. And then on the other side, you have companies that come out as really controversial and people are like, this is the end of the world. And then they just sort of fizzle out. Like, Cluelay would be a good example of a company that has done okay, but it's not like, oh, no one's doing homework. It's completely upended education and it's so successful and it's bad. It's like, no, it's like it was there was a lot of saber rattling around that. Sora went through a similar thing where everyone was like, this is going to wirehead everyone.

51:56And then it was like, yeah, just like some funny memes and ultimately, you know, moved on from it. And and so it's very hard to map like the controversiality to the ultimate outcome and where it lands. Like, yeah, a lot of the yeah, a lot of the prediction markets were not controversial when they were just predicting the election. That that was not what was controversial. Tech started being controversial about it or saying it's controversial once it got into sports betting. Yeah. So the ad is interesting from a couple of ways. One is trying to counter position against Andreessen, GC being like the cool, hip fund that wouldn't back the robot dog company.

52:32Even though when you look at the portfolios, right, there's enough overlap that you can safely say if a company is ripping or has a lot of potential, they're probably both interested in investing in it regardless of what category it's really in. And then the other thing is that like historically, like a 16 Z is the firm that's trying to be like hip and cool and loud and, and do like new media. And GC is the one that I've always viewed as like more buttoned up, more behind the scenes, more traditional, more traditional finance. I think of them as like New York, East coast, Boston. And I love that.

53:05Yeah, we love that. We love that. I think Bain Capital is a good example of another, another firm that's been like pretty straight laced, but still has like aura behind it. And it's like they have a private equity fund attached to the venture fund. And like Bain's done some fun stuff. I mean, Fogo de Chow, and they've leaned into things every once in a while. But they've never been like, oh, we're going to be the craziest brand strategy. It's been like, yeah, we're by the book investors. We find great companies, back them. And, you know, Sequoia's done that too. You know, their whole pitch is very austere.

53:37And that's worked for a long time. It doesn't need to pivot the brand, which is maybe what this is like signaling for towards this is the first time i mean it's very rare for any vc to like take shots directly at another vc just because they're all syndicating deals yeah it's way more direct i mean the the a lot of people clocked it but because the actor could look i guess if you were far away enough like steve something like yeah steve balmer i think it looks like steve balmer or mark injuries but people are saying mark hindrisson but the other I was looking at Mark Andreessen photos, and I could not find a single photo of him in a vest.

54:13So I don't know about this. But clearly, Mark Andreessen did take issue with it because he quote tweeted it something like 45 times, which really amplifies it and creates more of a conversation about it. Strategically, you might have just wanted to mute this if you don't want this to become a thing. But maybe he does. Maybe he's like, yeah, actually, I do want to fight because this is dumb, and I'm going to fight back and I'm going to win. So, you know, that's the strategy. But it does seem like Messi rolling around in the mud when you're wrestling with pigs, you're going to get muddy, right? Isn't that the first thing to say?

54:50Yeah, it's just, again, like creatively it looks great and it's very fresh. And I think Reggie and his team did great work. But it's funny to just, like, take shots at a whole category of investing, basically that is kind of the bread and butter of GC's business. Yeah. Yeah. Drawing the line in the sand. What is the actual line? The really high bar for responsibility around these things. Like, because first off, it's just odd because like robot dog feels very, very low on like the responsibility. Like if some VC was like, okay, we take responsibility really seriously. Yeah. So for example, the last robot.

55:34I would be like, don't fund gambling. Don't fund cannabis. Like, don't upset Sagar and Jetty, basically. It's like the way I would pitch someone if they were trying to be, like, the responsible actor fund. And Robot Dog would be fine. The last Robot Dog pitch deck I saw was a company that wanted to use Robot Dogs as a replacement for actual seeing eye dogs. Oh, interesting. Because seeing eye dogs are, like, incredibly expensive to train. um you know uh kind of out of out of reach for for uh many people and uh and so the opportunity for a robot dog that can maybe you know travel with you like on a plane without you know barking and needing to eat right like that's actually like a very world positive um yeah uh uh kind of uh endeavor yeah i don't know if it'll you know work or what the business will look like but uh but in general like there's a you know anyway so i'm extremely bullish on robot dogs i think it's very complimentary think about i mean especially if it's a it's a toy for kids uh think about how many vehicles kids have gabe says service dogs can reach 60k whoa and that doesn't count lifetime of all the other costs associated with dog ownership with next time i see someone with a service dog like wow it's like whoa buddy no uh the the 60 uh the yeah i mean kids have like you know a bicycle a tricycle a a rc car that drives and then another one and like it's like like you you throw the robot dog in the mix i feel like that's going to be in addition to a dog robot dog rips you said when I said that.

57:22This is going, maybe a thousand robot dog startups will flourish and the most ironic scenario is because the industry will become so deniable that General Catalyst and Andreessen both have to back it and they're like duking it out for allocation at every round and the robot, and the future robot dog founder out there is like, I just do nothing, win, or build a great company and win. Was there anything else going on with the robot dog debate? I, you know, selfishly uh you know i think it's bad for the industry if you have two of our platform funds uh you know just making these somewhat petty videos that are basically ad hominins uh that you know basically um throwing stones from glass castles as one one could put it uh so i think it's generally bad but for entertainment purposes if they want to keep going at it and turn this into you know proper drake versus kendrick situation this might be a good use of a16z new media yeah although much of the talent there is now over at uh i mean i would i would love yeah i would love uh like a like a response video from andreason shot in the same way or something like there is an opportunity for like a rap battle here that's a beef that's like very very entertaining that I would absolutely love.

58:45The flip side, though, is that I agree with you. Like, if you're a VC, you're much better picking a villain that is something around, like, a lack of technological progress. Like, Teal did this very well with, like, stagnation is the boogeyman. Like, if we don't get the robot dog, we don't get the seeing eye dog, we don't cure cancer, we don't do the big thing, we don't visit Mars. Like that is, you can still have like a villain, but the villain needs to be something that the industry and America and all the constituents can align around instead of like picking fights where like these two firms are obviously aligned on like 99 % of like where the future goes and what the goal is of building a business that delivers a value that consumers enjoy.

59:32Yeah, it's just so funny because if you look at cap tables, they're almost always probably touching. They're effectively holding hands on the cap table, right? Because one of them might have more of one company, right? Slightly higher. One of them might have more of the other, right? But in general, they're just hanging out together. I mean, Catherine Boyle did an integral at GC and then went over to Andreessen. And so there's more overlap than differences. Plenty of other things to take shots at. But, I mean, to Andreessen's credit, they've done a good job of that, focusing on geopolitical competition, focusing on China, focusing on stagnation and nimbyism, all sorts of different things that they've been aligned with, like, more of, like, an abundance view as opposed to punching down.

1:00:20Although, you know, there's memetics all over the place. Yeah, it seems like GC has an opportunity to be the buttoned up platform. I think so. You know, they don't need to say the R word. They don't need to be super loud, right? They can just focus on the craft of investing. I wrote about it in the newsletter, but, you know, run some ads. You know, you've been saying this forever. Run some ads in The Economist, Financial Times, Wall Street Journal. Just there's a way to counterposition yourself without attacking your rival. I mean, do you remember the last time General Catalyst went viral? Hamant, CEO, was on Harry Stebbings' show, 20BC, and he said, like, triple, triple, double, double, double is no longer good enough.

1:01:12We want to see 10X-ing every year because that's what's happening in the AI era. And it was a brash statement. It was bold. It sparked a debate. But it actually looks... But look at the results. Like, you know, there are companies that are doing this. Like, we talk to them every day. And sure, and he clarified it on our show. He clarified it on other shows. He was not saying that like you shouldn't build a business that only triples revenue every year or only doubles revenue every year. He was just saying that the reality of the market right now is that there are power law companies that are growing exceptionally fast, unprecedentedly fast.

1:01:47And so you as a venture capitalist have to adjust your benchmarks and think about how you're allocating funds, what companies you're investing in. Make sure you're in the best company in the category that's actually going to win. It might be the company that's growing 10x a year, not 2x a year. And so that was something where it was like thought leadership from Hamant. It sparked a conversation. There was some debate around it, but it was from a position. And so far, that take was controversial but entirely correct when you look at the growth of a lot of the most exciting companies in the industry right now.

1:02:21Yep, totally, totally. And so that sort of more narrow staying in the lane view, it got a lot of attention. It did break through. It caused a conversation. But it still didn't sacrifice. It didn't feel like, oh, he's taking shots at someone specific, right? It was just like a market analysis from someone in a position to give that exact analysis. So anyway, Jensen Wong 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 not. This is a picture from when he was in Alaska, too. Jason says, never stop selling.

1:03:03I agree. There is some news, which we will cover later in the week, around the dynamics around H100 sales and Blackwells, 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 U.S.-China summit kicks off. There was another drama in the tech world yesterday, but we'll come back to it after our next guest, Ben Hilack from Raindrop joins. I believe he's in the waiting room. So we'll let him come in. He's the co-founder and CTO. We've had him on the show before. Welcome back, Ben.

1:03:43How are you doing? Doing well, man. How are you? Fantastic. Great to see you. What's new in your world? Reintroduce the company quickly and then tell us the news. Sure. Raindrop, we make observability for agents. So the main thing we do is self-healing agents. So what that means is that when your raindrop hits a problem in production, we detect it, we fix it. How do you do it? That's a good question. So... At the end of the day, we consider ourselves the intelligence for your intelligence. What that means is that we are the best, fastest way to essentially look at anomalies. What that means is that, let's say you make a change, we're able to very, very quickly find out that users all started complaining about something, or the trajectory, the traces are starting to evolve into a different pattern.

1:04:38And so it's kind of a combination of agents, but also more like classic ML techniques, a lot of like custom trained models for every customer. Walk me through the shape of the agent market right now. Like the way you're talking about it, you know, sort of illustrates the broad diffusion of agents and custom agents. I think that a lot of people think Cloud Code and Codex. And I don't know if you're doing enterprise deals with those firms or that's the goal, but I imagine that every startup, many legacy companies have built some sort of agent, some sort of harness, and I'd love to know the shape of how broadly diffusing custom agents are in companies versus is it the domain purely of startups that create an agent for legal or an agent for sales and then they vend that into a company?

1:05:32Yeah, so I would say that there's two kind of categories of customers. We started with super high growth startups at the time startups. So those are companies like Clay, for example, Framer, Speak.com is one of the fastest growing companies in the world. And those were some of our earliest customers. We're lucky they grew a ton. So, you know, that has helped our growth. It always helps. It always helps. Yeah. And someone once mentioned that, like, you know, this kind of business is a lot like early stage seed investing. Actually, it's kind of interesting. Like, you know, we have, you have to be pretty, pretty picky not to work with companies that are going to die.

1:06:06Um, because if like, especially analytics, like all these sorts of things, like they, you, you succeed as a company when your customers succeed. Like if all of your customers are terrible, it's like, everyone's like, well, why do I, why are you? Yeah. I had a, I had a portfolio company that was working on like agent infrastructure like roughly two years ago and pivoted because he was like, okay, this is clearly going to be a big thing someday. But right now he's looking at all the underlying companies and he's like, I don't believe that any of these like agents in their current iteration are going to work now.

1:06:39Maybe there's an argument. I think it was very counterintuitive at the time, but I think we chose to find companies like Clay.com, right? Which are, clearly on an insane trajectory, but at the time weren't necessarily as large. And so I think a lot of our customers now are pretty large, but at the time weren't necessarily as large. And then in the last few months, we've been moving into Fortune 50s, Fortune 100s, and a lot of amazing things happening there. And again, it's kind of like two shapes of a product. One is, in our bread and butter, companies that are redefining the way people interact in different verticals.

1:07:18But then, yeah, there are Fortune 50s, Fortune 100s that are also deploying agents internally. I think the shape of that looks very interesting. And it's something that being on the forefront of understanding how these companies are deploying things, there's not that much I can talk about right now. But yeah, always very interesting. What do you think is a generally under-hyped agent category right now? I'm sure you're seeing the future a little bit. it's a really good question um i think that i mean uh you know i i so this is a tough question uh i i what i want to do actually is pivot the question a little bit because i want to talk about i want to talk about our launch today if that's okay okay with you guys yeah yeah uh i'll tell you my questions you tell me your answer okay okay sounds good does that mean that you want me to not answer this no no no no i'm just i'm just messing around go for it okay cool the joke is yeah i botched it the joke is what questions do you have for my answers and some ceos show up and they're gonna act like that where it's like you could ask them anything and they're just gonna direct to a point but it's fine i want to hear about the launch today so just tell us about that let's talk about it okay so guys, there's been this crazy thing that has been missing for a very, very long time.

1:08:42That's why I want to talk about it. So like people have been building agents. You're building them locally. Like you're using some sort of SDK. It could be OpenAI. It could be for cells. Whatever SDK it is. And there's no way. It actually is right on a developer's machine? You're just on your laptop. Right. Like before you push to production. Sure. Right. Sure. It's on your laptop. Yeah. There's no way to see what it's doing. Like no standard way. Nothing. Like So people will send those traces out to a server. Raindrop is one of those, and there's a bunch of others. Yeah, but they might also just drop the logs in a non-relational database.

1:09:16Sure. They'll just print it to console.log, like, oh, here's what was happening. It's that bad. Yeah, yeah, yeah. And the other problem there is, so you can't see a nice trace, or you're sending it to some server and it takes seconds to see everything, and whatever, it looks terrible. But then also your coding agent can't see the traces either. So then when you hit a problem and you're like, hey, you know, this response was wrong, plot code will just make shit up. Like, it'll just be like, oh, I think that like maybe this tool was wrong. Or I think maybe like this happened because it doesn't have any of that data.

1:09:48It doesn't actually know what the coding agent did. So I think that like as someone building agents, as like our company building agents, we're like, it's actually kind of embarrassing how long it took us to solve this problem. No one else solved it either. But yeah, that's what we launched today. free local open source tool, brainjob.ai slash workshop. And it's completely free. It's just open source. Why open source? That's a really good question. I mean, I think the genuine answer, and I think part of why competitors haven't done it, I mean, there's probably other reasons for that as well. But I think it's that it can be, right?

1:10:26Like someone else can do it. You know what I mean? I think that it running locally is the best experience for people. And to be clear, there's still things that it enables if you connect it to your production raindrop, which is you can pull in a remote trace and replay it. And then Cloud Code or Codex can just keep doing that loop until it works. So there's still benefits for us. But also the truth is that we want people to hack it. We want people to meld it into whatever works for them. So we use a lot of open source things here, right? So it makes sense to contribute back as well. Yeah, that's great.

1:11:07Yeah, I'm wondering about other just like predictions about the next breakout category of AI agents, what you're seeing. Feels like you're so close to being able to book a flight, but maybe no one wants that. I don't know. I mean, I'm not sure if you guys saw, I had a little bit of a thing with Brian Chesky earlier about Airbnb. Oh, yeah. Oh, yeah. Talk about that. Talk about that. No, I think like, you know, I use Airbnb a lot. I love Airbnb. I think if I had to guess, I would say Brian Chesky knows a lot more about Airbnb than I do and probably a lot more about being a founder than I do as well.

1:11:41And so I think there's probably a lot that I'm not considering. That being said, I think it's fresh. like uh if airbnb had an api i would use it and i would book every piece with it like through cloud code right so it's like i know i would do it um it's i find airbnb very very hard to search um and um i think that there's a lot of i think the tough part and like what i see industry-wide wide right now everyone's trying to figure out is you see companies almost reducing themselves into an API with absolutely no mode. You look at Photoshop, Illustrator, etc. They're like, oh, we have a cloud code integration now, MCP.

1:12:22At the point where people are just using Photoshop, Illustrator, etc. as an MCP, they've sort of lost the game, right? If no one's actually touching the UI anymore. I think that right now companies have to do that increasingly because they have no other choice. I think that there will be a point where the incentives don't make sense anymore. I can give an anecdote from when I was at Apple. Do you guys remember App Clips? Yeah. Where did those go? I only see them with parking meters sometimes. Yeah, right. So one of the hero ideas there was like, oh, you know, imagine you're in line at Starbucks.

1:13:04You don't have the Starbucks app downloaded. Like, well, why not just, you know, scan something, have an app order your drink? And it's like, turns out Starbucks doesn't. That's right. Sure. That's the last thing in the world. Starbucks wants to download the app. They want you to have stars. They have an entire like there's a reason why DoorDash and Uber Eats and like whatever, you know, God knows other apps exist. It's not because they need to, but because each have companies and money and goals. And like, so so why would they reduce themselves into a easily interchangeable API? It doesn't actually make sense.

1:13:36Yeah, but I think it's important to be careful around using a tool like Photoshop interchangeably with a retail store like Starbucks or a marketplace like Airbnb or DoorDash. Because I really think that these marketplaces provide an exceptional amount. All the value is not in the UI, right? I agree. I agree. And the value of Starbucks is not that it's a pretty app. It's because they have specific drinks that they can make pretty much anywhere, you know, someone would be. Yeah, I think of that company by the drink company. They got started during the direct to consumer boom. Obviously, they would have some beautiful Shopify website.

1:14:19They didn't. They just went direct to retail and they had Amazon. You could order it online. And if you went to their website, it would just say go to Amazon. And they did fine. Billion dollar company. And because like the value is not in the e-commerce experience. They didn't play like the the stars game. Of course Starbucks is maybe sacrificing a piece of that business model But it's not giving away the whole cow. I don't know There are going to be ways to monetize this right like they're going to be successful business models built on top of this Sort of layer and to be honest as raindrop goes into the future like that's the future We're building towards that's the future we want I mean we're gonna be announcing a partnership with a really large coding companies as soon as far as integrating with them more.

1:15:01I don't see Raindrop as a company that's going to submit PRs and production to people's codebases. Someone else is going to be doing that. We're going to be the layer that's really good at finding those issues, diagnosing them, and tracking them. I just think it's going to be interesting into the future how much companies are willing to be the API without all those hooks, without knowing everyone's email, having the mailing list, all that sort of stuff. So that's a very interesting trend. I feel like you're generally on the frontier and cutting edge of like adopting all these tools. You mentioned your cloud code use.

1:15:33And I'm wondering about, give me a reality check, a health check on your experience of computer use, because you're lamenting the fact that Airbnb doesn't have an API. And I imagine you could create a scraper or download the HTML and interact with it, like treat the front end as the API, effectively, you know, puppeteer the computer through computer use like where are you on like uh the agi moment in computer use from what you've seen like where does it work where doesn't it work where would you recommend people get started if they want to play around with it yeah that's a really good question um there's definitely places where it works like i think that codex has done a very good job of implementing like browser use actually um both for like debugging applications that you're working on and in general like this something that cloud code just like doesn't do like creates a really again that kind of like i think the next couple months the thing you're going to keep hearing from me but also everyone in the world is like self-healing loops loops loops loops right like how do you create loops where it's how do you close the loop how do you have like cloud code make a ui change see that it sucks and then just keep going right yep um and a lot of like do we have agi or not is how many loops in a row can you do it's all loops right before things just end catastrophically right yeah um because there is sort of this like uh it gets worse right in many cases um so um yeah i think like there's a lot of like ways to answer this like i'm a fairly like security conscious person i think that like the uh you know i'm not like an open claw guy i'm not going to give all my like cookies to some you know agent uh et cetera et cetera um but yeah i think TBD.

1:17:12Yeah, cool. Well, yeah, new challenge. Book an Airbnb with an agent. Can it be done? Is that where the goalposts need to be set? Let's figure it out. Anyway, thank you so much for coming on the show. Great to see you, Ben. Congrats to the team. Congrats on the launch. Of course. Last thing, if you want a hat, we have a new CLI. You can run Raindrop Drip. You can get a hat, an umbrella, a couple other things. Ooh, that's a fun way to give out merch. I like that. That's very creative. Thanks for coming on the show. Great stuff. We'll talk to you soon. Bye. Okay, back to the debate around figure.

1:17:44We've had Brett Adcock on the show before, and he had a live stream. We talked about it a little bit. Watch a team of humanoid robots running a full eight-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. 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.

1:18:27And we were extremely impressed by this. This was remarkable. Even if it's teleoperated, it's extremely impressive. Yeah, yeah, yeah. Like the robot's clearly working. This is very, very cool. 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 robots head the robot which is something that wouldn't normally be necessary doesn't have like a logical Explanation or conclusion and 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.

1:19:12And 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 TOR Taxes 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.

1:19:56We'll see where you stand. But 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 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 it's 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 is that does not have a human in the loop and you could make that and I could make the argument that it's autonomous Yes, the chimpanzee is running its own it has somewhat of a neural network.

1:20:58Yes, yes. No, no, no. No one knows. I think there was a human physically inside. Ooh, physically inside. Yeah, I mean, the thing that I'm so, I want to talk with somebody at a place like Amazon, who I imagine does this kind of thing all day long, and are they asking for a humanoid to do this process. Yeah. Like this seems like something that e-commerce fulfillment and logistics companies have been doing for many, many, many, many years. Yes. Is there not a purpose-built robot that sits right there and makes sure that the packages are in the right orientation? Does it have to, you know? Yeah, if you watch an episode of How It's Made, you will see every variety of custom-made machine for flipping around, sorting packages, that type of activity.

1:21:58There are custom-built machines that run at scale. They might cost like$10 ,000, but they last 50 years. And any time you see a Diet Coke factory or gum manufacturing line, all these things, like the gum that you have there comes off and the gum rattles down and is sorted into the pockets of the packaging and then the sleeve is wrapped around and glued and all of that is done autonomously, but just with a bunch of machinery that was built in probably like 100 years ago, honestly. If it works, don't fix it. But you can clearly see how this type of task package sorting would be like on the curve to a more economically valuable humanoid robot.

1:22:47And like if I was going to buy a humanoid robot to do my dishes, and you showed me this video and it was, in fact, fully autonomous, that would be an encouraging demo to me. That would be something that I would look at and say, oh, well, like if it can do this successfully for hours and hours and hours, I'd probably trust it to put some laundry in the washing machine. That doesn't seem well beyond the scope of capabilities. It's so interesting how quick it is when it's just sorting packages there and then it does the Biden walk on the way off. If you rewind for a second. Yeah, yeah, yeah. The walk is not as...

1:23:27I only use that terminology because that's the terminology that Brett used. That is what Brett used, yeah. Like, look, why does it look like that? If you're able to shuffle like this so fast and so fast, you'd think that you'd be able to hustle a little bit. But maybe that's V2. Maybe that's less relevant for this particular task. You know, there's a lot of different options, but we will dig into it. Brett launched day two. I mean, regardless, putting up views, sorted 32 ,000 packages. Day two is live. And he shared more details on what's going on. The original goal was an eight-hour run. After zero failures yesterday, we decided to keep going.

1:24:06We're now over 24 hours of continuous autonomous operation without failure. This is uncharted territory. The task is small package sorting. F.03 detects the barcode, picks up the package, and reorients it barcode face down onto the conveyor. Humans average around three seconds per package. F03 is now around human parity. The robots are reasoning directly from camera pixels. The robots are fully autonomous using Helix 2, our in-house neural network, running entirely on board F03. There's no teleoperation. Every action comes directly from Helix 02. too. Okay. Well, I feel like that rules out the monkey business.

1:24:50I think teleoperation would fall. If you had a monkey puppeteering this thing, I think it would count as teleoperation. So he is denying that allegation from the timeline. But the timeline seems convinced. YouTuber commenters started naming the robot, Bob, Frank, Gary yesterday. So they added name tags to each robot. And if the robot gets stuck or the AI policy goes out of distribution, Helix triggers an automatic reset you'll occasionally see this happening during the live stream if a robot or soft has a software or hardware issue it autonomously leaves for maintenance and another robot takes over we run our labs and figure this way to maximize uptime if we haven't had a failure yet we haven't had a failure yet but statistically we probably will at some point so um very very fun going back and forth who else is chiming in people are uh i'm the last dar says i'm the last person i expect to rush to figures defense and I'm looking forward to hearing brett's take here and in uh here and in any and all cases I stand with uh pbd king but imo this demo seems authentically autonomous and could see this being learned behavior from teleoperators that collected the data for this model with their vr headsets uh and uh pbd sucks who who uh broke the story or went viral first time said he actually has a pretty reasonable sounding excuse but doesn't give me tons of confidence on the model's brittleness for cross body research for cross body reach the policy lifts its arm lifts its arm to avoid hitting the metal shoot nice try i wasn't i wasn't sure if he was gonna if he was gonna reply to this and sort of engage or just sort of let the let the timeline run wild with it but the metal plate does seem like a piece of what's going on um but people are still hungry for uh teleoperation bombshells it sort of cuts both ways i remember jason carman did did a video maybe with 1x.

1:26:40And everywhere in the video, they said, this is teleoperation. We're doing teleoperation. We're bullish on teleoperation. Put it at the bottom in the text, in the description. So told everyone. And still people were quote tweeting and being like, this is teleoperation. And so people are sort of grappling with what is real, what is fake constantly. Well, is there anything else on the figure story that you'd like to dig through? No. Switch his hands after working more than four hours straight. Huh. Well, there is some new news. A newly released OGE form, Office of Government Ethics, 278T, discloses that President Trump filed 3 ,642 trades involving stocks of public companies between January 1st and March 31st.

1:27:32transactions include hundreds of stocks and etfs such as nvidia microsoft broadcom amazon apple alphabet meta goldman sachs amd airbnb palantir netflix costco walmart jp morgan doordash and others individual purchases of nvidia microsoft broadcom amazon individual so he's averaging around uh roughly 40 trades a day 40 trades check my math there um uh that is in q1 It's a lot of trading activity. We talked about this. Should you just give Jane Street right access to the federal government? Should they just be able to change the laws to optimize for max GDP growth? It feels like we're one step closer to the economic singularity of the hedge fund running the country.

1:28:21Anyway, we have federal government. What else? uh i'm trying to find the history of presidential day trading i don't know if there is one uh jimmy carter famously divested from his peanut farm because he was worried about conflicts of interest but we are in a new era anyway uh we'll have to figure out if trump is long or short the cerebrus ipo he's probably watching right now to hear doug o 'laughlin's take on it to understand what's w bush with cerebrus chat gbd says not a day trader but had a famous controversial stock sale. He sold 200 ,000 Harkin Energy shares in 1990 before bad news came out.

1:29:00Okay. Interesting. And there's no other evidence that we're finding of presidential stock traders. Well, we'll dig into it. But we have Doug O 'Loughlin from Semi Analysis in the waiting room. Doug, how are you doing? Welcome to the show. Good. Good, man. You know, pretty busy day. Another day, dude. Honestly, every day is a busy day. Every day is a busy day. Take us through it. How do you think the market reacted to the Cerebris IPO, to your semi-analysis deep dive on the company? What is the overarching story here? So I think the market was obviously positive. I don't think we're quite as positive as the market, but it's a bull market baby.

1:29:40I think the takeaway is that Cerebris got to IPO, which at one point in time we didn't think that would happen at the semi-analysis world. We've historically been very bearish on SRAM, but I think there's a path forward for them to be a disaggregated pre-filled chip or maybe even an AFD chip, meaning attention feed forward disaggregation. So yeah. Yeah. Unpack sort of the competitive dynamic, like what the fear around Cerebris, as far as I could tell years ago, it was like, will this ever be useful? Will they ever actually be able to make it? Will it have defects? Then it became certain applications, demand side, customer concentration, but where do you think they are now?

1:30:23How has that journey evolved? So first and foremost, Cerebrus is about SRAM. SRAM is like the fastest possible memory, and it's kind of done on a logic process. But the problem is SRAM scaling is dead, meaning that you can't make smaller and smaller SRAM scales. So pretty much they kind of committed to this dead-end process by having the biggest scale-up world as a wafer size, but then the models got much bigger than just a single wafer. And so they have a really, really fast inference, but only a certain size. And I think the real capability problem is, can they inference models larger than a trillion parameters?

1:30:59And I think the answer, as we think right now, it's pretty unlikely in the near term. Yes. So I understand all that. I'm just wondering about the world where should I view it more like a CPU? Because when the AI boom, the chat GPT moment happened, the obvious buy was NVIDIA because we're going to need a lot of GPUs. No one was really expecting a chip shortage in CPUs, but then agents wound up using CPUs for a bunch of stuff. You have to keep the GPUs filled. And so CPUs are now in demand. And I'm wondering if there's this world where there's this, yes, we're going to move past the trillion parameter models, but we're going to keep using them forever, just like we use relational databases forever, even in an agentic AI world.

1:31:48Or you have a scenario where you have a big model that is giving orders, workloads, delegating to a smaller model. Yeah, I think in a perfect world where there's no silicon constraints, that might be true. But obviously there's silicon constraints. And I think Cerebrus is really well optimized for a certain problem. And we think they do a great job at answering that, which is fast inference at a certain size of model. maybe that that that market's going to be large enough and i mean honestly i don't think i was ever bullish cerebus the entire time but now that we're here like not ironically one percent of a very large market works yeah i think they got like one percent of a very large market uh when it first started i was like oh yeah what are you going to do one percent of very large market that's going to be a few hundred million dollars and that's and that's that's like the classic seed seed pitch too.

1:32:41You know, 10 years ago they're... Yeah, is there any for a long time there was a lot of fear around ASICs companies around architecture changes were going to move past the transformer and they're all going to be locked in the past. Is there a is there any optimism around there's an architecture change that actually is to the benefit of Cerebrus and makes them more relevant in the future? do you think that's uh i mean my pay grade that's two gigabrain for me right but where i'm at and the understanding uh there is a narrow path for them i think and i think they're going to be able to inference maybe one trillion framers and very small context window sizes yeah or smaller window uh smaller uh models at very very fast speeds yeah but um i don't know man maybe i mean like you know the true gigabrain take is mythos is so good or whatever that it makes uh compute efficiency super easy and boom, you know, yeah, your, your model is inefficient and AGI understands.

1:33:43Yeah, yeah, yeah. Distill yourself so you can run on a Cerebris chip just as effectively. Okay. Now we're talking gigabrain. That's, that's the gigabrain thesis. But I think, I just think that there is, there's demands, right? Like clearly we're in a shortage and ironically in a shortage, it's not the best company who wins. I mean, you can look at NVIDIA stock chart and that tells you it's the second, third, fourth, best companies where the demand overflows right and so we're seeing all that today yeah and I think I think the reality is the markets big enough for a lot of demand and three versus in that in that space okay so they've done a really good job yeah and I mean it's a cool engineering problem yeah but we think it's kind of a solution looking for a problem because the the world of LLM's blew up at a much faster scale than anyone could have ever thought of yeah the size I think it's really the difference yeah yeah give me a little primer on grok how grok fits into the SRAM machine market, what the view is, because it felt like that that NVIDIA's move there with the license acquire, as you put it, was defensive against Cerebris.

1:34:48Is that the correct framing? Like, how does Grok fit in on this? Okay, so let's talk about exactly where Grok fits into the architecture. So on in the transformer architecture, you like the multi heads of attention and then there's a feed forward network that's a portion of um you know essentially the entire transformer block and what's become really hot in the last few years or not even two years like probably a few months man is you've been disaggregating all the different parts of inferencing into subsequent specialization so we're talking about gpus and asics being a specialization over cpus but now we're actually starting to break the the essentially the constraints of of inferencing into different, I guess, compute and memory bound like pockets.

1:35:32And so for example, we're finding pre-fill ends up being, pre-fill being, you know, essentially loading all the weights, ends up being compute constrained. So you don't really need a lot of memory bandwidth. So why don't you just use a very flops heavy portion and you disaggregate the memory onto the decode portion, which is like extremely memory bandwidth limited. And so this is Grok, where this fits in the strategic thought process here is in the gv200 rack what you can do is you can pass the activations um over to the to the sram in the grok uh lpu rack and that is an extreme speed up and so it's like that's like a perfect example of another like break apart of the transformer architecture yeah i'm pretty technical but that's like the thought process here is that the memory is so fast the memory band or the the speed of the io doesn't really matter and you don't need a huge scale up world size because you're just streaming the activations um that problem wouldn't work with uh the cerebrus trip because you're kind of it's it's an island right if you think of it as an island of compute it's really really good at everything in the middle but moving anything off the island is really hard versus moving something off the island onto a grok chip because there's a plug at the end of it is a lot easier and that's kind of the the calculus.

1:36:50Yeah. So cerebrous lower memory bandwidth, lower interconnect speed. Off the chip. Off the chip. But on the chip, it's as fast as cell. Yeah. Okay. So what does that mean for the Grok NVIDIA ecosystem? Because is this something where the default configuration is going to be a Blackwell and a Grok chip, like in, you know, 50 % of racks, 80 % of racks, or is this like still some sort of niche application where Grok is going to be deployed, you know, sort of sparingly sprinkled into specific use cases? Do you have an idea? Yeah, I think I don't have an idea with high precision. I think you'll find that a lot of these things, there's a lot of different ways to split up and serve your model.

1:37:35So expert parallelism, pipeline parallelism, tensor parallelism, right? And so the correct optimization per hardware rack is going to kind of depend on the shape and architecture of the model. And we don't really know with high precision what is what. And there's been kind of like different roadmaps along the way in terms of what they wanted to do for speeding up inference. A perfect example of this is the CPX rack, which was mostly built for expert parallelism. it's kind of remains to be seen if this is like if the grok gb 200 speed up is going to be like the way forward but it's definitely a technology uh tree that i think jensen is excited about so i mean we'll see what about lisa sue at amd is she excited about this technology tree can you give me an update on uh how amd fits into all of this so amd is mostly just trying to get the last thing to work, which is the Rack scale up.

1:38:30And I think they're going to do a good job of 450. I think what's going to happen is that like, you know, it's a compute shortage, right? So you're talking about overflow demand, I think Lisa's going to figure it out. But on the imprint serving side, I think there's definitely some demand or desire to probably match the NVIDIA roadmap. And I wouldn't be surprised to see if there's some kind of fast SRAM offload FFN chip in the in the next 12 months. But the thing is, the number of candidates there is actually like pretty low. I think Intel is really going for Sampanova, which is a little clever.

1:39:02There's like HPM2. There's a few other players out there too that pursued SRAM scaling. But I think that in this specific case, Lisa's mostly just focused on the last thing, and I think AMD is definitely good enough right now. On Intel, what is the latest there? It feels like the round table has been assembled and sort of everyone has held hands and decided to maybe jump across the transom at the same time, take the leap of faith. But it also feels like, you know, lithography machines are majorly backlogged. Like there's a whole supply chain that they have to answer to that's backlogged. And so really high expectations, but also what is the next milestone for them after they actually get these deals with Apple and Elon Musk?

1:39:52Amazon and Elon Musk. Yeah. And the Giga Fab. Sort of like once they get those signed, like what does the next couple of years look like? I think it's about execution. It's kind of crazy to me that I think the stock price is ahead of the technical turnaround. And I think that I think Liputan clearly has like right of the ship and gotten the right people onto the party, if that makes sense. And I think I really do think the government intel deal was a stroke of genius because Pat Gelsinger spent, you know, three years trying to build a bottom up demand to essentially come to the fab. And Trump's like, yeah, none of this.

1:40:28I'm going to sign the deal from the top. And what's going to happen is you're going to come play because we're in the United States government or else. And so I think I think people are there. I think the customers are there. I think the process is good enough. I think 14.8 will be also good enough given how much of a shortage N3 at TSMC is. And it's all execution risk from here. But the historical Intel has quite a bit of execution problem. So we'll see. Okay. Before we move on to TSMC, which I want to go to next, are there any other interesting ASIC projects on the horizon? We've talked to a few of these companies, but I'm interested in the shape of the differentiation.

1:41:09Like you explained a little bit of the divergence and strategies between Grok and Cerebris, but there's Etched and a bunch of other companies that are working on new chip designs. And I'm wondering if any of them stick out to you as particularly differentiated. I'm not going to go too into the details because I feel like some of them are even like still figuring out their roadmap. roadmap. I think Maddox is kind of interesting, the way that they're kind of trying to pursue the memory problem. I think Etched, I'm excited about the kind of YOLO bet, if it makes sense, is make a big systolic array.

1:41:49But I think there might be niche cases. I think the problem is, at the end of the day, NVIDIA's big bus is still really good for the majority of cases, and you're going to have to start to make really opinionated bets on the ASIC to find what niche market ends up being all like a diverter of demand into their ASIC. And so the ASIC specialization from here, I feel like you have to make some pretty big brain bets in order to make your bets come pay off. And I think most of the bets that I would have guessed when you originally did them, wouldn't have paid off. And the ones I didn't expect did, like it's kind of crazy.

1:42:27Yeah, it is a very weird market dynamic where A couple years ago, we saw ASIC and new chip companies, new silicon companies, raising hundreds of millions of dollars or$500 million. And it was like, well, for that, you're going to need this massive market. Are you really going to flip NVIDIA or something? And then the market grew so much that the 1 % of a huge market sort of potentially masks out for some of these companies now. It's a fascinating development. Jordy, do you have something? China trip. Yes. Oh, yeah. What are you tracking? On the H100? Oh, so honestly, do you guys see the parade?

1:43:00You know Trump loves the parade. Oh, yeah. They're winning them over. Good parade. I was like, dude, I'm not much of a parade guy. But I was like, dude, if they showed up and that parade was for me, I'll be like, these guys could be friends. Yeah. My impression is that the executive branch really wants a deal. And I think, you know, you saw the H200 list, the verified H200 list. I expect probably more lightening up on the executive branch. Something that's really interesting is if you look on the legislative branch, there's actually more expert control bills going through the House than like ever in history time.

1:43:34So there's kind of this tension. But I do think, you know, Trump's a businessman. He loves the deal. I expect I expect to deal. So, yeah, somewhat related TSMC. Ben Thompson was writing that potentially they weren't ramping CapEx fast enough. What do you what are you tracking on TSMC being a potential bottleneck for the AI build out just as more and more Cerebris is now trying to get allocation? It feels like a particularly sharp elbowed place to do business. Yeah, so I think at the end of the day, TSMC is kind of a kingmaker in terms of supply. And there's no reason for them to really let the market go out over its skis.

1:44:19And I think they're happy with the pace of what they're expanding out. Because like, hey, they're growing their CapEx like whatever, 40%. But in absolute dollars, these are big numbers. We're going to run out of TSMC engineers in the island of Taiwan pretty soon here. So I think this is all kind of good on the margin for overflow demand, which is actually it's Intel. Intel's definitely reflecting some of that, but I think the shortages specifically at TSMC is driven by cleanroom. It's a long lead time item. It takes three to five years, or let's just say three years to bring a cleanroom up. And so in order for them to have like figured out and like perfectly matched demand two years ago, they would have to have been like, we have a 10 ,000 square foot house and we need to buy a 50 ,000 square foot house with conviction.

1:45:05Right. It wasn't that clear two years ago. And so I'm going to expect supply to kind of lag over and over and over. But demand signals will continue to essentially command premiums, move up wafer pricing, move up orders. And that's what's going to make TSMC invest more next year and the year after. But they're going to do it in an incremental, not a revolutionary way, but an evolutionary way. They are very methodical and do steps one at a time. Okay. Clean room fungibility. When you say it takes five years to build a clean room, I immediately go to SpaceX. I imagine that Elon can build big things quickly.

1:45:44is there some world where that partnership accelerates Intel, regardless of your timeline for the mass driver fab on the moon, all the crazy long-term stuff, but just having Elon around the table to say, Oh, we need to build something big and it needs to be, you know, capable of, of operating as a fab. Like, is there something where he brings more to the table than just dollars potentially? So I definitely think Elon is the man to do it. Um, I forgot who said this, but like elon makes the impossible late uh i don't expect it to be on time uh you know talking about the cigar in in uh in the tariff lab i'm really i'm really kind of doubtful it's you know i guess from first principles it's easier to just clean the entire room than to make like really hyper concentrated pockets and that's what i would guess the bet is but um i still think by the time elon figures it out the supply response will have reacted already um we're still two three years out And there is some clean room fungibility, and you've already seen this, actually.

1:46:43Micron bought an old power fab. I think this is the PSMC deal. People are buying display fabs. Essentially, every bit of clean room that is not accounted for in the world is being snatched up and retrofitted to kind of meet the supply demands. Interesting. Yeah, I mean, that's happening all over. Didn't Ford just announce some sort of AI play today? The stock's up on something. It's all over the place. I am interested in terms of like 6 % getting powered shells. Ford is worth more than figure now because last year, around a year ago, I remember figure. Your robotics. Was worth more than the Ford Motor Company at one point.

1:47:21But now they're both AI companies, I guess. But what are you tracking on the American data center build out domestically or terrestrially before we move on to space capabilities? Yeah, basically how. Oh, go for it. No, no, no. Just I'm just curious about I mean, we're starting to see glimmers of pushback at the municipal level, different data center bands. And I'm wondering about what are the big levers that are that need to get pulled to actually continue to bring capacity online in America? Yeah, I think that's a good question. And you're already seeing the first level. This is the delays. My favorite clickbait is 50 % of all data centers in America are delayed or canceled, implying 50 % is canceled when it's really just everything is delayed.

1:48:17That's like my favorite clickbait. I got to steal that in the future. but i think that i think it's going to be local municipal and people have to really believe and demand and desire the jobs and i think one of the ways that we're seeing this is like you know capitalism works and effectively the dollar per megawatt has been going up it's like a one-way train in the same way that like you know the power per rack has been going up the cost of making these data centers have gone up and one of the ways that happens is it leaks into labor right So essentially you're super against it, but all of a sudden it offers 3 ,000 new jobs to your home.

1:48:52And you're like, well, maybe I'll take it. And I think that with enough economics, oftentimes money finds a way. And that's kind of how I would guess. But it's going to be like a county by county fight. And some places are just going to say, hell no. Yeah. On that note, we were debating this earlier today. There's been a couple of examples in viral photos and articles about like, I bought a beautiful house in the countryside, and then they built a data center right next to it. And no matter how pro-AI you are, it sounds annoying to have a huge building that's an eyesore and maybe noisy, maybe smoky next to you.

1:49:27But have you been tracking? How feasible is it just to throw the data center truly in the middle of nowhere? It feels like America has a lot of land, but what goes into selecting data center sites these days? Do you have something else? so yeah uh so i i think um pretty much two fiber pairs is the big uh the big desire essentially it's like you're you're you're more than willing to go to where the power is because you have to go to what the biggest actual bottleneck is and power is the biggest bottleneck so you can just uh in the past you're talking about like hey having these imprints or rather like let's say point of presence near uh local cities right but power was never constrained in that world it was just uh you know the biggest constraint was getting this video from tiktok to your phone as soon as possible if the biggest constraint and the largest part of the cost is going to be power why not move the data center to power and then then like you know essentially hook it up with fiber and so i think that we're going to put them in the middle of nowhere that's just how it's going to work um to a certain extent there's going to be more densification in some of the inference near the population but i still think the roi makes the most sense to kick out in the middle of nowhere yeah uh has the political backlash pushback updated your thinking at all around the viability of space data centers i remember you know we talked as this idea is like gained popularity you guys have like consistently said um yeah technically you can do that but like maybe it won't be a long time for there are space data center players now that are kind of loving the pushback against terrestrial data centers because they're like, the more pushback there is, the more it could make sense for us to put this, put these up in space.

1:51:11But what's your view? I still think economics is going to win out. You know, something a pound on Earth is probably 10 times more expensive in space. And it's really hard for us to go to like essentially beat that out with a new completely specialized supply chain for what's going to be a smaller market in the near term it's a real adversary against the adoption in in like let's say the short run in the very long run because i'm sure you saw the anthropic colossus thing where it's like also interested in space right like the biggest maxi vision of this is like agi we have you know 30 ter you know we've a thousand terawatts of gpus on earth and we're like we got to put a terawatt in space right so like in that world, I think space data centers work where a small percentage actually ends up being so big.

1:52:01It's 1 % of the market again. It's just like, oh, and it's a trillion dollar business. VCs vindicated. Yeah. Yeah. VCs are vindicated once again. Tam pitch deck slides vindicated. Yep. Yep. Yep. Yeah. It's literally as big as the galaxy, bro. There's no end to it, actually. Think about how big the tab is yeah um uh so on i think what is more likely is if it continues to be painful to do it from a zoning perspective in america we it will essentially slip into other geographies probably in the western hemisphere there's a lot of power in space in brazil and i think that that's probably good enough right there's definitely ways to make this work um i definitely think the only way you do it is by paying more and finding someone who's like you know what i'll hit the bit.

1:52:46And so that's the important part. But, you know, capitalism plans away. Is that sort of the bull case for sovereign AI initiatives? I was always super skeptical because like Europe didn't get like France's Google, like they just use Google. And for a lot of consumer aggregator type consumer internet companies, it's like Spotify is from Sweden, But it could be from America and it wouldn't matter. YouTube is from America and they use that over there. And you didn't need a national champion in every consumer category. Or there were certainly returns to scale and a lot of the American companies just won.

1:53:28So I never really bought the whole idea that, oh, the French need a locally trained LLM and the Germans also need a locally fine-tuned something or other. But if every country has some sort of excess supply of energy or space or regulatory capacity for data centers, sort of bringing that online and just operating like a neocloud could just be economically valuable for that country regardless of whether or not they're vertically integrated to the point of the consumer or the business that's running an AI agent. I think that's probably the case where at the end of the day, economics is going to like kind of push it through.

1:54:10And there is FOMO and Europe did do a lot of investment in the Internet like really late. And if we're going to use 1999 in this example, I think the thing I keep thinking about is that this AI thing is going to be a big deal. I continuously am shocked and surprised by the magnitude and scale. That's a narrative violation.

1:54:34I don't think it is right now. I feel like we are in a particular moment where the people calling the top and the bubbles, they're awfully quiet right now. And that makes me even more scared. That is on the case. So to be clear, the true top, everyone's bullish. Everyone's like, dude, it's actually going to be bigger next year. It's actually just going to be bigger bubbles. Shut up. I was not concerned about a bubble when everyone was saying. It's a bubble. It's a bubble. Yeah, exactly. I am, I mean, I'm a little concerned it's a bubble, but at this point in time, I think... If you look at the big, I've been reading a lot.

1:55:14Honestly, here's my view. Here's my view. It's not a bubble until you guys are spending 120 % of revenue on tokens. Yeah, our gross margin goes negative. We're raising a major fund. We're not going to be investing in it. We're going to be burning it. It's actually not a bubble until semi-analysis goes public and trades up 600%. Oh, there we go. I like that. That's the real tough. No, I think there's a few things that have to happen. I think open AI or Anthropic, someone has to go public. And it's going to be this year. Like we have to hit that keystone before it's all over. But I also think, I keep thinking about this as like, dude, this is a big technological revolution.

1:55:58I think it's bigger than the internet. And I firmly believe this. I don't think I believed it would be bigger than the internet when I, maybe even two years ago. But I'm pretty convinced this can be bigger than the internet. And if you look at the past, these big technological changes are often sometimes bigger than, I don't know, everything else. It reshapes the entire world. For example, on the sovereign AI thing, maybe you're like, yeah, you don't need to fine tune LLM. But what happens when AI becomes such an important fundamental, almost like society level institution that a government can't control it?

1:56:30That becomes really uncomfortable and weird where it's like, hey, Anthropic can just put 5 % of the compute of Mythos. and run a really effective government whenever you wanted. And you're like, whoa, what does that mean for us? And so this wave is so big that I think people are going to, out of fear and concern that they're going to be left behind and that the institutions that AI will bring is going to be bigger than the original thing that we're doing, I think that that's the problem. The industrial revolution changed everything. The other thing that we were joking about in Q4 of last year is John was like, great, the bubble pops.

1:57:13The bubble inflated and then it pops, but then we got agents and then you have this sort of re-acceleration of every metric across the board. And so the other thing that we're trying to comp the AI boom to the internet, but the problem with the internet boom is that we didn't have the internet. So everything just took, or the internet was coming online and people were getting access to it. And so the entire build out and all the capabilities and all the companies took a lot longer to sort of grow. Right. And now you have that core infrastructure. And so when you're layering on more infrastructure that accelerates all the underlying trends.

1:57:47Yeah. Yeah. I mean, the labs, the lab revenue multiples are like an order of magnitude or two off of dot com peak multiples. and and and in the public markets uh google amazon apple all the hyperscalers uh are at like pretty reasonable uh price to earnings multiple still even with all the capex and stuff and so the pushback would be it's on free cash flow that you can make earnings look good instead of free cash flow but like i think the revenue continues to be real the demand continues to be real and until you just like see demand evaporate like yeah it's hard for me it's hard for me to sit here and be like gp prices are up a ton quad code is really valuable to me i still think i'm an early adopter and you know this is all going to end tomorrow i envision myself using it every single day more for the rest of my life which is kind of crazy and i think i'm a early adopter and so i just think it's hard for me to envision this not being a ginormous deal and it's kind of like we just got the like i really i wrote this whole thing like angles pause or whatever like it's going to change everything like the the amount of net output that's going to increase is going to just blow up our minds um it might be bad for gdp ironically because gdp will be unmeasured like we're gonna like gdp might be broken as a concept gdp got invented in the 1930s to measure how much output you could make um to not screw over the domestic economy for world war ii like it was it was a way to essentially organize the the uh the american economy and it's a statistic it's an estimate.

1:59:20Like, I think all of, I think we're going to like attack in like a lot of institutions and ways that we're doing things and ways we measure are going to be attacked by this because it's like such a big change. We have to rewrite the playbook over again. Um, and people, and it's, and it's funny, I think, uh, wasn't Ben Thompson was talking about this in a recent interview of like, people are comping this, like, okay, Silicon Valley, like, you know, brought crypto online. And then, uh, it wasn't maybe as big as some people had, had pitched it to be, even though it's been yeah self-driving cars were powerful uh and then and then even the way you're talking you're like uh you know we're still early you know which is like a classic uh crypto but the problem if you are early you have nothing or you're saying like you know in crypto is like well like a community could have a dow and that dow yeah could be worth a billion that community could be worth a billion dollars but there's just no way to measure that but now we have tokens and you're saying GDP.

2:00:16But anyways, I'm trying to like unlearn, I think some lessons from that cycle, because there are a number of things that are quite different. It's also good for the reflexivity that people do have a little bit of an immune system to just running away with everything, because you could believe this and then bid, you know, NVIDIA to 10 ,000 times earnings or something and like at certain point you have to start grappling with the reality what about uh robotics has figure had a major breakthrough i mean i one i have not been uh following the feet as close as i should be i just think robotics feels a little further out than the hype would let you believe i feel like robotics is much more akin to the driving car uh paradigm where it's like oh yeah it's definitely going to come and automate everyone's jobs and then it takes a lot longer it's a lot like unsexier i think the the scary or positive thing about ai is since it's information work and it's already been distributed and it has the perfect network to run on which is the internet um it can disperse very quickly and and that's what we're seeing right now and so yeah i i i'm just not anywhere near as bullish robotics as i am yeah the fundamental well i'm bullish on the next semi-analysis uh uh i don't know what are cluster max and uh the inference max what are those called dashboards or analyses or rankings dashboards dashboards now we everything's a dashboard well you need to make a new dashboard uh gtp gross token production this is what we're measuring now uh this will be output of the united states gross token production gtp we need to i mean i think more on this soon actually this is like a place for doing some research on but i think uh you know the real the real bubble metric is if we're like you know how many tokens what's the token uh what's the token um replacement cost that that would be some really good bubble math where it's like yeah yeah software company has a really low token replacement cost per market cap but like a hardware company has an extremely high token replacement cost and then It's like, oh, no, no, it's just enterprise value divided by token replacement cost.

2:02:35Well, the real bubble one will be to go to the full Mary Meeker eyeballs metric, eyeballs multiples. Yes. So you will value companies purely on token consumption. You'll say, oh, well, they're consuming 10 trillion tokens, so they must be worth a billion dollars. And then you'll get really weird gyrations. That would be great for semi-analysis. That would be really good for semi-analysis. We are consuming a lot of tokens. Well, you're also putting a lot of good stuff. I really enjoyed the - Would you guys ever make a sort of political style attack ad against another research firm for having AI psychosis?

2:03:07Hmm. Is that a reference to the GC? Sorry, it's a reference to General Catalyst attacking Mark Andreessen. Andreessen? Yeah. You know, life's pretty long. I actually think it's just peerless. I don't think there's like a neck and neck with someone else. It's just you guys. I was going to say, I don't really know who our competitors are. I don't really think about Mark Andreessen or another research firm like that. Maybe one day. Maybe we will go through AI psychosis. Honestly, you guys need a rival. You guys need an arch nemesis. You need an op. I guess it would be Gartner. I had to say. This is not a good op.

2:03:50You need the 7 analysis hype cycle and it's up only. No trough of disillusionment. straight line no axis it's actually going backwards it's a straight line on a log graph that's what it is semi-analysis hype cycle I love it Gartner doesn't stand a chance but thank you so much for coming on the show this was fantastic full analysis full analysis yeah no more semi-analysis those guys would kick her ass if they had full analysis they'll kick her ass it'd be so over anyways take care guys have a great day we'll talk to you soon cheers goodbye Next, we have Andrew Feldman from Cerebris joining in 20 minutes.

2:04:29We'll go back to the timeline because the OpenAI Elon Musk trial is in its final day. The trial is ending. People expected four weeks of trial. We only got three. 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 open ai with special guest microsoft are happening today thursday may 14th again mike isaac of course he kicks it off with what his lunch is he's got an epic bar he's got the bison snacks he's got a la cologne latte he's got a couple other good things he looks like he's prepared he's got a bunch of snacks i feel like he's in a better position today learned his lesson three weeks of sort of like recursive self-improvement i think that's what's going on here uh so the cal sheet well elon win his case against opening eye it peaked at a 58 chance okay where is it now 28th it's now sitting at 30 chance 30 chance okay uh 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 20, 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.

2:05:57Sort of feel bad for the AV guy during this trial. There's been feedback. The 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 tweet storm. He says, Musk's counsel is going after opening eye execs. altman and brockman and has the mugshot style photo of altman on the screen again battle of photoshops of executives in this trial has been entertaining to watch you want to depict your opponent in and the worst possible light must counsel going back and forth hammering the point they made over and over the argument essentially painting a picture sam allman 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.

2:06:43Molo is using Larry Page, who they claim doesn't care about humanity as a foil to the noble Musk, whose only care with respect to AI is the future of humanity. Musk's 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 must closing side arguments, suddenly populist track of pointing at open AI and saying these billionaires are making gobs of cash while running a charity for the supposed good of the world.

2:07:17I'm curious if jury can register this argument even if it comes from Elon Musk, the world's richest man. Ouch, open AI council begins closing argument with a broadside against Musk. 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 Photoshop. OpenAI Closing Remarks now in the digital displays and 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.

2:07:53Ooh, it does look very nice if you pull up the Google images on Olan Mills. Anyway, short summary of the closing. Must 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.

2:08:27I 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 telecasts. Is that just completely side note? Gamer has entered the blog. The Dota moment has been mentioned nearly every single day during this three-week trial. AI researcher. We got to have Mike back on the show. It's so good. Saw as a true breakthrough in the technology. So Mike Isaac says, I played Dota in the past. What is the timeline for the jury to meet? Okay. Is this something they're doing today? They're getting a 30 minute recess. Most they've had in a month.

2:09:04I might actually be able to go outside and get real food. There's a Popeye's across the street. Is it a bad idea to get a bucket of red beans and rice? That's what he's thinking about doing. So not much news on when this will close. It is 110 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 use 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 for the jury might might make Quick call but well there was an update unlikely 11 minutes ago a lawyer for opening eye on Thursday Defended the company's chief executive Sam Altman from withering character attacks by Elon Musk legal team as both sides delivered their closing arguments in a trial with potentially seismic implications.

2:09:58The 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 push 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 MISC or Musk is what she's saying.

2:10:38And there is a new update that just dropped in. 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, Savit 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 slash goal to be done in one and a half 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.

2:11:22OpenAI's lawyers asked to use it. Musk's lawyer 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 to it. AGI is here, but we'll still need a dongle, I suppose. A dongle has entered the courtroom access, actually. There's about 15 lawyers standing in the middle of the room right now talking about how to use this big monitor. This is wild. They should have talked to OpenAI about sharing their monitor. What I always do, I always tell you when you come in here, talk to the other side. We don't have the technology available right now, so we don't want to use the TV.

2:12:02We think we should just get rid of it, says the OpenAI lawyer. Sam Wallman just walked into the room, by the way. So that happened four hours ago. One of Musk's lawyers carried the big monitor out of the room upside down, wire dragging behind him, defeated. Defeated lion retreats. That is a very, very funny story. 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. Hashtag Draper University. Hashtag survival training. 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 yeah closer to 50 yeah you can totally get closer to i i i put um because there's a couple companies that sell personally when when if you're going surfing and the water is below 45 degrees, it can just be very painful.

2:13:05So even in a wetsuit, anywhere that's not covered, a lot of people are putting gloves on. What do you think, Tyler? So apparently Joe Rogan's at like 34. 34. Yeah. Wow. So that's like the cold plunge. He's the top of the mountain when it comes to ice bars. He's the final boss. Yeah, this is just a crazy picture. I did think it was AI, but it turns out it's real. It's just funny because it looks like, what is this setup? Yeah, what are all the trash bags there? And the wall is sort of decrepit. And there's piping. It looks kind of like a prison ice bath. Yeah, this is not what you'd expect from, I mean, isn't he a billionaire investor?

2:13:50You'd expect some sort of palatial, you know, you see the properties that Mark Zuckerberg's 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. Whip this up himself, bought some trash bags and took some pitches. Yeah. And, you know, who knows? Maybe the next founder of Cursor, Figma, Ramp is sitting there right now. Yeah. Also, 52 pitches in 52 minutes is crazy. A minute is crazy fast for a pitch. I mean, we do 10-minute interviews, 15-minute interviews, barely get to the meat of the interview. And this one, you got four of the founders.

2:14:31Four founders jumping in, one minute. That is remarkable. No stranger to controversy, though. Yeah. Joe Lonsdale says, I am not a humble man, but this is legitimately beyond my capabilities. Absolutely wild. Well, Vercel, Guillermo Rao, friend of the show, is apparently running an ad campaign on Lyft by buying custom license plates and deploying them through Lyft drivers. Is that what's going on here? No, you think it's random? The guy, Peter, the driver, was like, I must love Vercel. Love Vercel or work there or something. If he was the eighth employee at Vercel, I don't think he'd be driving.

2:15:19Hopefully not. Unless he just loves, truly just loves the game, loves driving. Or he's just super illiquid. He's just like, pay me zero, actually. I'll drive Lyft. I want all equity. I'm super bullish on Versailles. That's a possibility. That's a possibility. Well, Alex Conrad says, is your startup even sponsoring Lyft license plates yet? It's an outside-the-box strategy. Someone should pick it up. Someone should do it. Get a bunch of license plates for cars. rent them out to Lyft drivers, get those impressions. Wix is down a bunch. This seems like a very logical company to suffer in the age of vibe coding.

2:15:59People are vibe coding websites all the time. And Wix is a supplier, a service to build websites based on templates. But Wix was buying 30 % of its shares at$92 six weeks ago. but the stock is now down another 45%. And so I was wondering about this. I almost asked Max Levchin about this yesterday. But when you're going through this world, like it seemed like he was very confident about the SaaSpocalypse and did not feel the need to respond or take any dramatic actions, just sort of wait and let the metrics do the talking. But I was wondering about, you know, are you tempted as a CEO when your stock trades down on a narrative that you know does not apply to you, but you're just sort of a collateral damage?

2:16:52Are you tempted to do a quick buyback and just sort of get a good deal on your stock? Even if it's just three months down, then right back up? Can you imagine being a public company CEO and buying back your stock and then getting a return on it? It has to be one of the most euphoric experiences. Yeah, totally. Not actually getting return, but obviously decreasing or increasing everyone's revenue. Well, Wix is a$2.9 billion company now. Yeah, they acquired this company, Base44. Remember, this was like a one-person company. And I think Base44 has been growing revenue quite quickly. It seems like pretty much any of these vibe-coding tools, Yeah.

2:17:40Just the experience is so magical for people that a lot of them have grown revenue. Fascinating stock chart if you zoom all the way out. So during COVID 2021 Zerp era, stock was at$300 a share. It's at 52 today, by the way. It traded down after Zerp era ended all the way to$50 a share,$60 a share. And then post-chat GPT moment 2024, fantastic for the stock, it gets back up all the way to$250,$200 a share. But then since 2025, as AI has gotten better at coding, vibe coding websites, doing front-end design, there has been a significant sell-off that continues today. And so, rough go. I was looking to get a comp.

2:18:25I looked up Squarespace. Squarespace is no longer publicly traded. It was traded on the NYSE, but it was delisted after being taken private by at 7.2 billion. That is tough timing taken private in October 17th, 2024. Oh, interesting. And at the time, there was not a SaaSpocalypse narrative. You couldn't one shot a beautiful website with a single prompt. It's going to be so hard for this firm to make money on this deal. Yeah, it feels like a new customer problem just because it's not the hot new technology that you're hearing about like the podcast ad conversion has to be a lot worse but i would be very interested to know what is retention like because yeah i know some people that have cable businesses basically yeah i know some people that have built these uh web uh website generator companies and then they just keep growing and growing and just sticking around forever because once someone uh has the magical experience of building a little website for their company or their personal brand and then they just let it run forever and they're like 10 bucks a month i'll just let it keep going.

2:19:33Uh, well, yeah. So Squarespace had done around 1 billion of revenue in 2023. Uh, I'm assuming they grew into 2024. We don't have the full year numbers because it was taken private in Q4, but is pretty reasonable revenue multiple. But if they lose out on a lot of those new customers, because there's every single company in the world, every single company in the world, it seems like is trying to make a box that will make you a website. Yeah. Yeah. Anyway, you know what very few companies are making? A nightstand that turns into a bat and a shield for defense. I like this. It looks so unassuming as a nightstand.

2:20:13Very believable. No one would guess. But then something happens. You grab your bat and shield and you're ready to rock. Would you pick one of these up? It has a little bit of a hotel vibe to it. It doesn't. And also, I like a nightstand. All I would say is don't bring a nightstand to a gunfight. Okay. Yeah. Well, people are having fun with the AI generated videos showing that, yes, in fact, if it's not bulletproof, it has some trouble. If you disable, Ben Thompson says, if you disable OpenIt login for the Gemini app launcher that the Gemini app installs in the background without asking, Gemini app launch will immediately re-enable OpenIt login.

2:20:53I will now, needless to say, delete the Gemini app and don't intend to install it ever again. And so this is very, very odd. Gemini login. Oh, so it automatically logs in no matter what. He says, I'm actually struggling to remember a bigger middle finger to a user from an app ever. It's bad enough to install a helper app, but to immediately undo the user's explicit setting change. Incredible. And Josh Woodward from Google chimed in and said, this is a bug. It will be fixed in the next release, aiming for right after Google I.O. more if you're interested. So that's good. They did receive the feedback.

2:21:31Well, we should talk about Nikita Beers. I was reminded of this because he screenshotted and posted it. The greatest growth hack of his career for one of his projects. This happened, was this a year ago? Gas or Explode app? This was about a year and a half ago. Pre-joining X and working with Elon Musk over at X, he launched a company called Explode or an app called Explode. And he had a very interesting growth hack where he incorporated the company as Tap Get Inc. And so in the iPhone app store description under the name of the app, Explode, it would say Tap Get. And then right below it would say Get because it's a free app.

2:22:14And it doubles down on the call to action. He made the entity a call to action. It's genius. These little things really add up. And you've seen them all over X. and he's done a good job of creating re-engaging areas. And I just feel like the UI of X has been improving significantly. I'm really enjoying the latest UI feature where if you're watching a video and you want to speed it up, you can hold on the right side of the screen, which is fairly common in video apps these days. Doesn't work in the iOS native video player. I don't even know if it works on YouTube, maybe. But what's really cool is that if you press and hold it, you will temporarily be in 2x speed mode.

2:22:56But now in X, if you press hold and you're in 2x speed mode and you drag down, it fills a little circle and keeps you locked in that 2x speed mode. And it actually changes the speed of the video permanently until you change it back. And so that little delightful touch is something that I'm seeing more and more of from the X team. And I'm a big fan of. Well, without further ado, we have Andrew Feldman from Cerebrus in the waiting room. Let's bring him in to the TV panel. Andrew, great to see you again. Looking sharp. Feeling sharp. How are you guys doing? Feeling sharp. Congratulations. How has the day been?

2:23:31I would love to get just your reactions from the day. It seemed like there were a lot of people there. Take us through your emotions today. Well, you know, this was better than we'd hoped for. I think a chance to celebrate. We did bring a lot of people from the company, and we brought families. and to share with the team. We brought everybody who'd been at the company for longer than nine years and their families. When you do a startup, the family is a meaningful part. It takes patience from them and a great deal of it. And so they came and we celebrated it. It was really an extraordinary day.

2:24:14We opened up, we priced at 185. We opened up 350 and we settled at about 320. What an extraordinary thing. We're just so proud. Yeah. Take us through some of the history of Cerebris. Has it been a straight shot? Has it been an overnight success? How do you characterize it? What were the darkest moments? What were the highlights? What are the good old days to you? What does that mean? Well, I think in the hardware business, if anybody tells you it's a straight shot, you can call BS. I just don't think that's the way our business works. I think the first time you build a chip with a new architecture, it's a little more than a prototype, a little more than a proof of concept.

2:25:00The second chip, you iron out your challenges and you begin to show it to customers in mass. The third one often that really takes off. And so it's a long, long road in innovative hardware designs. And so, you know, we were founded in 2016. We're more than 10 years old. We sought to solve problems that others, that's right, overnight success. Thank you. Oh, exactly. Like a decade. I was 15 pounds lighter and way faster. As most overnight successes are, you know. Yeah. That's right. I mean, they're just overnight because most people sort of weren't paying attention. But we tried to solve some problems that other people thought were impossible as we showed you last time you know we tried to build a chip that was the size of a dinner plate and everybody told us it was impossible and the truth is for a while it was and you know we didn't solve it until august of 2019 we built this extraordinary chip we were faster than everybody and absolutely nobody cared nobody and ai wasn't ready and it was still sort of a novelty and nobody cares about how fast you are when it's a novelty but but starting with with gpt uh and in 2025 the models got so darn smart they became useful and suddenly everybody wanted to use ai and you use it with inference and and business was rolling yeah uh what were those early rounds like i'm thinking the benchmark round co2 bunch you know eclipse a bunch of others you know we had the advantage of the founding team had been together at a at our last company that had paid pretty well for the venture capitalists and the team and so we we had some wind in our sails when we went out and raised money it's not like today where we're four guys in the word lab and you're raising it a billion free for for your a um that's not us but we went out we we uh we made eight calls we got eight term sheets we chose uh benchmark and foundation and eclipse and we got going you know less than a year later i was expecting uh i was expecting you to say like yeah i mean it was it was a slog you know we were so other rounds were a slog other rounds were a slog yeah at the beginning um not so you know thomas uh lafont at code 2 came in shortly thereafter and um we did a round with them i think the truth is between about uh 2020 and 2023 it was it was much harder yeah um ai was sort of in this situation where uh we everybody was saying oh that's cool look what this model can do look how big it is but it wasn't being used anywhere yeah right nobody was using it they were pointing at it they were saying wouldn't this be nice and they went back to whatever they were doing before and it wasn't until really uh sort of 2025 when the models got good and you just saw this tidal wave of people using ai and demand for ai compute and that that's been exceptional it's just been an amazing thing to ride yeah um you yeah you mentioned like if you have four guys and uh your your company name ends with lab you can raise a billion dollars there's a little bit of that going on in the market with just like chips, semiconductors, AI.

2:28:22There's not that much that needs to be explained, but what were the key ideas or thesis that you needed to explain in the roadshow to investors that wanted to go a layer deeper than just AI chips? Yeah, I think there's the first, the market size and dynamic. And I think Jensen said some time ago on Brad Gershner's podcast that the demand for inference will grow by a million X and nobody believed him. And at the same time, you saw Sam Altman displaying real vision and going out and trying to lock up huge amounts of compute and memory and data center and power because he saw it too. And I think trying to share what that means, what an exponential demand means and that we're still so early and yet the demand for AI compute is overwhelming.

2:29:19I think sharing that was interesting and I think helpful in educating the financial community. The other thing is that there are lots of ways to do this. The GPU isn't the only way. You've got a TPU, you've got Tranium, you've got us. There are lots of different ways to build a solution here. and finally that maybe the the notion that the cuda is sort of this grand lock-in is overplayed and that uh you know the the gemini 3 which is an excellent model was trained on tpus with no cuda that anthropics models were trained on tranium with no cuda i mean that lo and behold some of the best models some of the most interesting things are being done without cuda and that that that lock-in might be overplayed.

2:30:06And I think these three factors were really important in educating the financial community. Going forward, how do you think, how do you and the team think about sort of calling your shot and sort of trying to predict where and how inference demand will look in 2030 and beyond versus like working closely with the labs that now have product lines with billions of dollars of revenue and their own roadmaps that you can work with? yeah you know like the babe i'm going to point out to left field and and just say wait this is where it's going baby um i love it um no i i don't think that's the way it works um look i i i think we're calling our shots every day by making big investments in data center capacity and collaborating with with the the leading visionaries in the field in in working not just with with open AI to serve as sort of the cutting edge and deliver their extraordinary models, but also with AWS to make sure that we can get access to the largest enterprise customers.

2:31:12And instead of having to work with these enterprise customers, procurement sort of organizations who provide master purchase agreements that are the size of a Bible, you can say, look, why don't you buy us through AWS and it'll count against your annual commitment. And so I think those are really important ideas and ways we get access to the market. And then we're taking huge amounts of data center capacity. And so that's the other bet we're making. Yeah. That makes a lot of sense. How do you think the year will play out in terms of just broader consumer awareness of what fast inference feels like?

2:31:54I had a really magical moment using Cerebris in GPT 5.3 Spark and Codex. And even outside of coding tasks, just talking to the model and having it respond instantly was sort of, it felt like a new breakthrough or a new paradigm. And I feel like this hasn't fully diffused, but it also feels like when it does, there will be potentially like entirely new ways of working, entirely new paradigms that might emerge. How are you thinking about actually diffusing the technology? We think that's exactly right. And we think that the experience of engaging with a real-time AI will encourage people to do more things, to stay longer, to work on harder problems, and to invent new things.

2:32:48I they delivered DVDs and envelopes. Right? And when the internet got fast, they became a movie studio. And they didn't get better at DVD delivery, they became something completely different, something that had never been in existence before. A movie studio that delivered directly to your home. I think that's exactly what's gonna happen. And you can just sit back and you can ask yourself, how big is the market for slow search? Zero. How big is the market for dial-up internet? I mean, how much would I have to pay you to swap out broadband at home and bring in dial-up. I'm not doing it. Is it 1 ,000 a month, 1 ,500 a month, 2 ,000 a month?

2:33:22I mean, no way. I mean, it just wouldn't be worth it. And so the community is going to engage with inference in the same way, and that fast inference is going to be all of the market. Yeah. So you make the chips. I believe you also make cooling infrastructure as well, cooling units. Are there other products on the roadmap that you think will be required to roll out and scale cerebris over the next couple of years? No, I don't think so. I think right now we build the chip and the system, and the system includes, it's about the size of a dorm room fridge. You put two of them in a standard data center rack, and the cooling infrastructure is built into the system.

2:34:06And I think that's where we want to focus. We want to be measured on our ability to build AI computers that are faster than anybody else. Yeah. How are you thinking about scaling on-chip memory? It feels like there's some concern about, well, what if the models go to 10 trillion parameters? What if it gets too big? How are you thinking about that challenge? Or maybe it's an opportunity. It is an opportunity. I think a 10 trillion parameter model is hard for everybody. It's actually easier for us. Okay. Right? There's a reason we're not a 10 trillion. It's because it's really hard and expensive to serve for everybody.

2:34:41I think one of the things that we've been able to do for the larger models is to tie together a bunch of these systems in parallel and run them as a pipeline. And that way we can train and do inference on trillion, multi-trillion parameter models in ways that I think are much more intuitive than on GPUs that have much smaller compute. They have off-chip memory, but their problem is the compute. They don't have enough compute per chip. And then how are you talking to customers about potentially bringing Cerebris in, not as a full replacement to their entire semiconductor supply chain or stack, but as a complement to everything else that they're running?

2:35:31Because I have this vision of the next generation of AI agents. You get this genius model, but it needs to use a small model over here, an open source model over there, a super fast model for a certain thing if it's looping through some task. Yeah, the same way you hire, you have a superstar employee. You don't necessarily want them doing every single task themselves. It's like, yeah, you should be able to delegate. Yeah, delegation. How are you thinking about that? Yeah, I think that is sort of a notion of a confederacy of models, right? That there's a collection of different models. And one of the things we thought about early on was how to interoperate in that environment.

2:36:07And we connect in via standard 100 gigabit ethernet nothing fancy nothing proprietary um we we are deployed in in many places where they've got gpus from from nvidia or gpus from amd they've got x86 compute from dell or hp and so that's not a problem at all we're eager for those environments yeah how uh what what do you think the company would look like today if you guys had had access to today's frontier models when you started the company? Like, are you feeling, and how do you think about just like the speed up at the company today due to how good the models have gotten? We use frontier models every day in coding, in running our G &A.

2:36:54I think if you start a company today, you build a very different organization. I think there are whole departments that look different in the next nine to 18 months. I think much of what HR does, much of what training does is solved by some form of AI. I think a lot of the work in finance, right, closing the books, a bunch of what they do is checking. And those are all done by agents. I think what it is to be selling or doing recruiting, those change. I think for a long time what recruiting was was hunting through or writing scripts for LinkedIn. in. I think that changes substantially. And so when we look out, we see sort of fundamental changes.

2:37:41The obvious ones, of course, are, you know, a year ago, engineers were using approximately zero tokens. And now they're using, you know,$10 ,000 worth of tokens a month. And the rate of change and the rate of new PR requests, new pull requests is just extraordinary. And so AI is having fundamental changes. Obviously, it usually starts in Silicon Valley and sort of works in waves to other areas, but that's what we're seeing right now. Since the last time we talked, there's been a ton of movement in the space data center market, a lot of energy just yesterday, SpaceX and Google. I had a launch deal in the Wall Street Journal.

2:38:24Has any of your thinking change? What is your current thesis on space data centers and how it might fit into your business plan over the next decade even? One of the hardest things in a space data center is communicating across chips from one chip to the next, and we solve that. One of the great parts about a big chip is that you have to communicate from one chip to the next less frequently. That's a huge advantage for us in space. I think that this is an idea like self-driving where the last 10 % takes 80 % of the time. Sure. Right. And that we're not three or five years away, we're eight to 12 years away.

2:39:06That doesn't mean we shouldn't be working on it or thinking about it or making progress to it because if you don't do that, it's 25 years away. But I don't see data centers in space in the next three or four years. Yeah. And arguably, uh, you've solved the key problems that you would be asked to solve. And so you'll be ready if demand shows up, but there's not that much for you to do individually to advance that. That's exactly right. Yeah, that's exactly. Well, we're hoping for it. It'd be exciting, but plenty, plenty more to do here on the ground. Congratulations to you and the whole team on this incredible milestone.

2:39:39We're honored that you would spend time with us. We really appreciate it. Work day for the company. Yeah. Uh, and, uh, Let me hit the golf. Incredible to watch your progress. And I look forward to your next appearance. And enjoy the rest of the evening. Enjoy the rest of the evening. We'll talk to you soon. Thank you, guys. It's time for a cocktail. Be well. Fantastic. Enjoy. You deserve it. Goodbye.

2:40:03What a fantastic. I love that. I love that analogy. He's like, I'm Babe Ruth. Yeah. I just point. And he's like, no, I'm not going to do that. It's way more complicated. I've been working on this for a decade. Yeah. Yeah, what a fantastic story. What a fantastic performance. I'm very excited that we're bringing in Eric Vichria from Benchmark, who was in that Series A that Andrew Feldman just mentioned. So we will talk to him about that in just a minute. We're going to bring him into the waiting room. But there are some other posts that we can talk about in the meantime. One, someone is using RunwayML to create, let me see this, a full hurricane inside a TV studio.

2:40:45I want to watch this clip and it's one minute and we will see how convincing is this? Are you going to be turning off the news in order to watch this? But wind is only the beginning. The real danger is when the storm starts moving. This is very cool. As the storm builds, ordinary things stop feeling ordinary. Roof panels, freeland, sign. So you think audio also? Like fully AI generated Because the typical workflow for this is the host would stand on a green screen or LED volume, and then all of these effects would be added in post or live through like a traditional visual effects pipeline. This feels fully synthetic.

2:41:30I think that you'll probably use some sort of hybrid approach, but the ability to prompt something like this on the fly for a small news organization that maybe doesn't have the budget for a huge VFX team, you're just going to see a lot more VFX like this. You're going to see stuff all over the place. There are so many small news channels, local news stations that just don't have the access to digital domain or some huge visual effects house. So it looks pretty good. Before our next guest, Dylan Field has a quick update. They have their Q1 results. He says, quick update, not dead. And putting up some insane numbers, 46 % year-over-year revenue growth Accelerating for the second straight quarter They're raising 2026 revenue guidance for the year It's up 6.8 % today Up 8.6 % after hours Congratulations to Joe Says design matters more than ever The Figma team continuing to execute incredibly well Fantastic news Let's bring in Eric Welcome to the show, Eric Congratulations on the progress Thank you so much for taking the time on such a busy day.

2:42:40Great to meet you. Great to meet you guys. Excited to be here. Long, long overdue. Yeah. Crazy that this hasn't happened already. Excited to have an opportunity. Well, you guys like Ev, you know, so you have Ev on. You don't have to have me. He was a former colleague, but everyone is welcome here. But I would love to just hear the story from your perspective. We just heard it from Andrew's perspective. It seemed obvious, but was it obvious to you? Was it the most obvious deal ever? because we were talking with Andrew. I was asking him for the story of those first couple rounds, expecting him to be like, you know, Chad QBT wouldn't come out for almost a decade.

2:43:17It was a slog. We walked up and down San Hill Road. We got a nose. He was like, yeah, we got eight term sheets. So clearly it was a deal you had to win. Yeah, take us through it. Well, you know what? The hilarious thing about it is in venture, it's very useful to be naive. and certainly I was so naive about how hard hardware actually is. I can't even describe to you guys how naive I was and we were. It was 2016. Deep learning was clearly going to become a thing, which would obviously evolve and empower the AI that we have today. And I was looking at all of these different applications. So I was looking at deep learning for radiology and security and other things.

2:44:03And it was really hard to figure out where it was going to work, like which application was going to take off. And you guys have to remember, this is 2016, right? The TPU hadn't been announced. The transformer paper hadn't come out yet. LLMs hadn't been born yet and obviously not ChatGVT or anything else. And so it's really early, but there was clearly something there. And when I first met Andrew, he came in and I was like, we're not hardware investors typically. I think our last hardware investment before that one was Amborella, which was 10 years earlier. And he came in and he said, it was like the team slide, very impressive.

2:44:46And then the slide three was GPUs actually suck for deep learning. They just happen to be 100 times better than CPUs. and as soon as he said it, it's just like a light bulb went off. Like, of course, of course, like why would a graphics processing unit be the right solution for deep learning? And then, you know, of course, he proceeded to explain like why GPUs were so much better than CPUs for training and also what the like ideal ground up solution could look like. And, you know, and they had their idea of the way for scale and everything else. and you know and as soon as he said it it's kind of like oh yeah that makes sense and like i should you know like we don't know what application is going to work we should invest in infrastructure this is an amazing team and a really provocative idea um you know fast forward like that was 2016 spring of 2016 you fast forward like six seven years and like we're still slogging it out and have raised so much money and have very little revenue and um you know and it's just it just hadn't all come together yet.

2:45:52And then, of course, over the last two years, inference is exploding. It turns out Cerebra switches from training to inference and really focusing on inference and making inference speed where speed matters. Coding explodes where speed really matters. And so all these things kind of came together. And so, you know, a lot of luck, a lot of naivete on my part, but for the team, just relentless grind, never giving up, always taking feedback, but being persistent, being open-minded about where the market was going. So yeah, I'm so, so proud of them. Yeah. What was your role as an investor like over the journey of the company?

2:46:35Because obviously Andrew and his core team, deep engineering bench, were you focused on how you position the company to the private markets, fundraising or management? What were you focused on in terms of value add or just helping build the company alongside? I'm really the algorithm specialist. I go in there and I do that. No, I'm just kidding. I don't know anything. You're in the fab. You were the one that was making the chips. That's right. I was making it up. Clean room. Yeah. It really changes a lot over the course of a company. This is, I think, the fourth company that I've worked with for more than 10 years.

2:47:19And so when you work on them a long time, the companies evolve a lot. You start out, it's just five people. It's just the five founders originally. And so at different points in time, it's a lot of fundraising help. At points in time, it's really helping build out the broader management team. And a lot of it is also just being someone for the founder to talk to. You know, being an entrepreneur is very, the highs are very high and the lows are very low. And so someone you can talk to and be really open with that, like, helps moderate that. And I think that's a part of it. So it's just, it's an evolving, you know, conciliary kind of role.

2:48:00And I really love it. Actually, that's the part of the job that I love the most. And it's very, it's rare and special to have these kinds of relationships. I've had a few of them. I'm very lucky to have a few of them where I just feel really like a lot of chemistry with the founder and just feel like we have a really productive relationship. Where are you excited to invest over the next decade? Because, you know, it feels like we're still in the semis, boom, there's a lot of opportunity there. you could go deeper into that side of the business, but then there's so much software. Yeah, I'm sure you've gotten pitches that look like what maybe would be the next gen.

2:48:42Maybe you're like, I already got my horse. Yeah, well, yeah, that, but then talking to these teams that don't necessarily know what it'll actually take, right? Sure. They didn't learn the hardware is hard lesson yet. Totally, totally. Well, one of the funny things, and I ask myself this question all the time, obviously, is this is a 20, for us as early stage investors and looking for really big outcomes, but willing to take big swings, you really do have to kind of look many years forward and try to see what's going to ripen at the right time, right? So in 2016, you make an AI hardware investment.

2:49:21And Grok was, I think, 2017, for example. So there were several contemporaries of them. And of course, Scroc and Cerebus have ended up doing really well. And so you, you, you, but you're, you're trying to say like, okay, this fruit's going to ripen in like six years. Right. And, and so there's, there's kind of some mention of projection, you know, right now I think, um, I'm, I'm really excited and continue to be really excited about a lot of the AI applications. Um, we're investors in Sierra and Legora and a number of others that, um, where like they're obviously booming. They're selling magic to their customers, and the companies are doing great.

2:49:59We also have these infrastructure investments, like Fireworks, for example, which is also riding this enormous inference demand. And then there are things that are a bit more forward-looking. We invested in StarCloud. My partner, Chafin, led our investment in StarCloud, which is space data centers. And we also led the initial round in Sunday Robotics, which is a home robot. And so I think those things are going to take longer. They're not going to be massively scaling revenue next year. That's not what they are. So you kind of have a combination of these different things, but it's kind of trying to figure out when they ripen.

2:50:42Next time you come on, we've got to have you debate Dellian because he came on and was debating EV and hardware versus software. but you got space, chips, you got everything doing likes. Well, it's nice. It's nice to have a portfolio. And I think, you know, one of the beauties of Benchmark is each of the partners is attracted to different things and different types of founders. And so, you know, you put it together and it works out really well. Yeah, yeah, that makes sense. But walk us through Fund 7 and 8 because there's chatter on the timeline as those funds being some of the best in venture history.

2:51:20And although this is Cerebris' day, this is your first time on the show. Take a victory, lad. We do have a big gong here. Yeah, well, you know, Fund 7 has or had Uber, Snapchat, Elastic.

2:51:39Stitch Fix, WeWork. I mean, there were so many things. It was like, it was such an embarrassment of riches. And I had nothing to do with that fund, just to be clear. Like I joined in 2014, that fund was already deployed and invested in. But the team, you know, that team at the time just did such an outstanding job with winner after winner. Discord is in there. I mean, And it's like really when you have, you know, guys, like in venture, if you catch the trend right and and obviously work hard and get lucky. But you have, you know, the sixth or seventh company in the in the portfolio delivering a multiple of the fund or something like that, like that you're in such rarefied air.

2:52:25And that's there's it's really special. So that's fund seven. You know, Fund 8 is a very enterprise. It's our 2014 vintage, I think. And, you know, it's a very enterprise-y fund. And so, you know, we had Confluent, which returned a bunch, and Amplitude had returned a bunch. And, you know, and then we have Cerebris, obviously, which is big, but Chainalysis is in there and several others. And so it's kind of interesting how these how they switch. I think that's actually more interesting to me, which is Fund 7 was very consumer mobile. And Fund 8 is like very enterprisey. And they're like back to back.

2:53:06But they turn out to, you know, they both work. And so, you know, I think that that tells you a little bit about what what venture is and how we we all have to be really open minded about what's happening and what's the right timing for these various ideas. And then, you know, fast forward and our 2022, I think 2022 vintage has, you know, the first round of Sierra, the first round of fireworks, the first round of Legora, you know, Reduct or Mercore. Yes, absolutely. Langchain. And so, you know, all those are in there. And so obviously, that's a totally different fund and has, you know, a different set of things, but also, you know, looks pretty interesting.

2:53:47So it just, it evolves. And that's what's so hard and tough about this business is staying on your toes when you're in a very, very dynamic world. Yeah, well, it's interesting. Something that has been talked about on plenty of podcasts, but it's worth bringing up. You guys have stayed true to the strategy, and you can count on the market changing and evolving, but a lot of funds are having to deal with markets changing and evolving while having a fund strategy that is changing and evolving. And if you keep one of those things true, it seems, at least from Benchmark's track record, that it gives you some advantage and that, like, you're playing a very specific kind of game and not having to evolve your own game while dealing with changing technology trends and markets.

2:54:39You know, I've been at Benchmark 12 years, and I've thought about this a lot. And, you know, you're watching your peers do all these different things and, you know, and swimming and fees and all these, like, amazing things. And so you're like, wow, that looks pretty cool. So, you kind of like look at this stuff. But I'll tell you what I think it actually comes down to. What it actually comes down to is what do you love doing? And we're obviously in a very fortunate position, and I inherited an amazing platform, and very fortunate to have done that. And so, we're in this amazing position where you get to do what you really like doing.

2:55:17And at the end of the day, we really like partnering with early-stage founders. and working on these companies for a decade plus. And that's kind of what we like doing. And so I think things have definitely evolved. The opportunity set is changing and evolving. And more recently, I mean, just in February, we raised an SPV, which we've never really done before, to invest in Cerebris. And that was unusual. But it was, you know, you can also we've actually a few years ago, we did public market investing when when COVID first hit and the Nasdaq tanked. You know, all the early stage stuff just disappeared.

2:55:58We were like, wait a minute, like these publics, like there's interesting stuff in public. So we started deploying a little bit in the public. So, you know, yes, we're really focused on the early stage and that's what we love doing. And then also occasionally, like we see these special opportunities and we try to jump on them. Wow. Yeah. Well, thank you so much for coming on during a business day. Had to sneak in the SPV round of$23 billion. So congratulations on that investment. Fantastic. Another little cheeky 3X. I think you deserve a drink. Hopefully you can find Andrew. I'll definitely have some drinks tonight.

2:56:36Have a great time celebrating. Well done. Great to finally meet you and congrats to everyone. Yeah, let's do it again soon. Thank you guys. We'd love to do that. Thank you. Goodbye. Up next, we have Steve from Foundation Capital. He's Cerebrus' first term sheet investor, also the first investor in Solana and a bunch of other great companies. So we will bring in Steve from Foundation Capital from the waiting room. Steve, how are you doing? Here he is. Doing great. How are you guys? Sorry to keep you waiting. Congratulations. Thank you so much for taking the time to come chat with us. How are you doing?

2:57:08This is just another day. Are you at the NASDAQ? or you're calling in from home? Yeah, exactly. No, just another day. No, I'm at my hotel on my way to the dinner that Eric's also headed to momentarily. Okay, we won't keep you too long, but I would love to hear the story of you meeting Andrew Feldman in 2007, how things matured from there, how you wound up working together. Yeah, so I showed actually Andrew the email last night over dinner, but yeah, he and I and Gary met in October of 2007. they were raising money for the company that they started prior to Cerebrus, which is called C-Micro. And it was kind of broadly in sort of new server architecture.

2:57:53So these guys have been thinking about these kinds of problems for a long time. But I passed on the investment, but stayed close. We really connected in that meeting. And then when I saw them get acquired by AMD, it was about four or five years later. I was like, guys, Andrew in particular, you guys are not going to stick around this company for too long. So let's start riffing on some new ideas. And that began basically a two-year conversation about a whole bunch of ideas. Actually, it all started really in kind of this concept of warehouse-scale computing. We were looking at companies like Mesosphere, ended up actually doing a small investment there, and CoreOS and a whole bunch of others.

2:58:30And Andrew came in in November of that year of 2014 and shared his ideas with our enterprise team. And then basically we riffed on ideas. in the spring of 2016. So it was like March timeframe. We started telling them, look, we want to be your first term sheet. We've been like courting each other for a while here. And yeah, we got them a term sheet to lead that first financing. And then Eric stepped in and we changed the terms a little bit to make room and co-lead along with Eric and Pierre from Eclipse. Yeah, and then they started it right in our office. That's amazing. Can you talk to me about, there's, you know, crypto and AI feel like two wildly different technologies, but there's a ton of overlap everywhere you see from, you know, crypto miners pivoting to Neo clouds.

2:59:22There's a lot of movement back and forth. And I'm wondering, like, what in your mind the similarities, differences are, like why you've been drawn to both over your career, where the gap is, where there's similarities. So what I would say, the similarities, which are probably in retrospect somewhat obvious, I would say the hardest problems of software and systems live in the area that we're working on in AI. So the AI infrastructure, the frontier labs as well, all the work they're doing there. And the same thing is also true at the bottom of the stack, the layer ones and the very hardest technologies over in crypto.

3:00:00You know, the folks that are attracted to both of those areas tend to be very technology driven. They love distributed systems. They love the hard problems around cryptography and elliptical curve cryptography. They love low latency computing. Like they're quite similar in terms of being systems thinkers. And so those are the ways in which I would say that the problems are quite similar. And in fact, here's a funny anecdote related to this. so Anatoly Akovenko, co-founder of Solana part of the reason why he chose to work with us back in March of 2018 so about two years after we invested in Cerebris was because we were investors in Cerebris he's like, you guys take hard problems seriously he had spent 12 years at Qualcomm that's right, distributed systems and then was at Dropbox and understood those challenges and so he said, wow, you guys care about these kinds of hard problems problems, and that matters to us.

3:01:00So we ended up doing a fair bit more diligence and writing actually a larger check into that very first Solana financing. Yeah. Can you take us back to earlier in your career, pre-investing, obviously fascinating hard problems, but where does all that come from? Does it start in high school, college, early career? Walk me through some of the early days. So I studied robotics and embedded systems, sort of the intersection between mechanical and electrical engineering in undergrad and then came to graduate school and did more of that. And then my very first Friday at Stanford, I met David Kelly, who's the founder of IDO, which is a product development consulting firm that worked with the very best kind of Fortune 1000 companies.

3:01:42When they would hit a snag, a hard problem, or want to invent a new product, and they didn't often know how to wrestle those challenges to the ground, they would call us. And so we did a lot of work for Apple. We did a lot of work for Cisco. We did a lot of work across every industry from healthcare to consumer devices to really hard problems in systems. And so I worked there for five years designing products. In fact, saw one of my other products earlier today on the desk at the trading floor of NASDAQ for Cisco's voice over IP phones, which I worked on now 28 years ago. So just working on cool, cool things, hard problems, mostly where it feels like if you solve that problem, it was worth solving.

3:02:30There's a real prize at the end. OK, so that's how I got started. Yeah, I want to take this full circle then, because robotics is sort of having a moment, but it still feels like it's early in terms of as a consumer, as optimistic as I am. I just don't think I'm going to have a humanoid robot walking around my home this year. Most people we've talked to have said, yeah, it's maybe five, six, eight, ten years away. But that's like the perfect timeline for a venture capitalist to start getting involved. You don't want to be trying to build custom AI chips today. You want to start 10 years ago like Cerebris did.

3:03:04So how are you thinking about pulling your experience from robotics into the modern era? Because if the boom isn't already here, it's probably going to be here in a decade, if not a decade, two decades. It's coming. Robots are going to be real. So how are you thinking about it? so uh we've done a fair bit of work in embodied intelligence in terms of uh research and and as i'm sure you're familiar it's it's always a little tricky to invest in an area that you have some operating experience it tends to bring some scar tissue yeah and so you might be more circumspect than than if you'd had kind of a beginner's mind sure i would say i i am generally um not a big believer in the humanoid uh approach i think there are use cases uh for example in the home companionship.

3:03:49And even in that case, it's a bit of a stretch. I think you need to think about robotics more broadly and think about industrial automation and then look at the problems that are not necessarily the consumer level use cases, but you walk the factory floor and you see people moving around pallets. And the human form factor is not good for moving pallets around. And so you wouldn't actually build a humanoid robot if you were trying to deal with that use case. So I think when I zoom out and I say, what are robotic systems? Robotic systems are basically ways of automating human labor. And in fact, the greatest compliment for most of these systems is when you stop calling them a robot, you actually call them a forklift or you call it a washing machine.

3:04:35And it's when that technology diffuses into the background and you just focus on what is the application. So that's how I look at it through kind of the product lens as opposed to the technology lens. Yeah. Yeah. I was, I was, uh, you know, you see these demos of humanoids loading washing machines and I've been thinking in the back of my head every time I'm interacting with my washing machine, like, is it time just for a ground up first principles rebuild of what a washer and dryer stacked is like if you constrain it to like, you have this dimension, but now you have all the modern technology and your goal is to just take in dirty clothes and put out clean clothes.

3:05:09Like, can you do something better than just a big tumbler and then another tumbler when one with water, one without. And I'm excited by that. Is the implication of that that almost you would be open to talking to entrepreneurs who are maybe thinking a little bit narrower, thinking a little bit smaller, at least in the interim? And then how would you guide someone towards long-term messaging around their company if they are finding a wedge, but then they want to grow at some point? Yeah. So I think it is exactly what you just described, which is, and again, the sort of the applications do matter here, but the notion that you would start with something that is, let's call it sort of big enough to matter, but small enough to win.

3:05:53And in hardware technology, being more focused is actually a huge advantage, a huge point of leverage. And so, and then as you continue to build, you want to be able to access larger opportunities in markets. And so I really do believe that that is the way you get started with hard technologies and hardware in particular. I think there's another thing that we do, and I will just say this kind of brings it to Cerebrus again for a minute, which is we look at workloads. And so one of the reasons why we backed Andrew and Gary and Sean and team back in 2016 was it was quite clear, and we saw this through the lens of our portfolio, that the AI workloads at that time was more ML.

3:06:36They were ramping very, very steeply. And whenever you see computing workloads that are doing something new and different, and you're talking about in the robotics context, and we'll get to that in a second, but when you see a workload that is spiking hard, there's often an opportunity to basically replace the compute layer. In other words, there's often sort of purpose-built silicon that should exist here. And so in the case of personal computers, very clear, serial programming, and you were very well suited to the x86 platform. It was actually something we saw go on and on for decades. As soon as you started to see the need for much better graphics, of course, you would build a graphics processing unit that's really good at rendering graphics, at doing floating point math, at managing lots of multiple cores.

3:07:28and then, of course, take the mobile era. Then you say, okay, wait a minute, what's going on here? I need low power. I need a smaller form factor. When you look at these workloads, oftentimes there is this transformative opportunity, and that's exactly what we saw in 2016 was, wait a minute, there should be purpose-built silicon for this ML and AI workload. At first, of course, we started with training, back to your point around how you start small. Then, seven years in, it was actually a board meeting when Sean, one of our co-founders, said, we got to go after inference. It's just, it's exploding.

3:08:01And so again, to this point, you start small and then rotate towards the much larger opportunity. Yeah. I mean, we talked to Andrew about all the ups and downs, a classic overnight success with tons of moments on, of, you know, intense tumult. But I'm curious about, were you ever worried or hesitant that the company might narrow down too much? And because you've heard like, you know, YouTube has custom silicon for video encoding. And there was probably an opportunity at some point to narrow the focus even more to do chip development for one specific company, be less generalized, and maybe ramp the revenue a little bit faster.

3:08:41But was there a tension there that you were observing? And how did you get through those moments? I'd say that the primary tension that relates to your question was probably around making sure we would not silo ourselves into use cases that were traditionally just high-performance computing use cases. Sure. So those workloads are valuable, and those markets are actually still relatively interesting, but they're not growing anywhere close to the rate of the inference and specifically the reasoning part of inference where you start chaining workloads together. So we worried a little bit about that being a niche that was not interesting enough for us to build a really nodal company.

3:09:23If I zoom back from that and you ask sort of, what are the things we really worried about in those early scary days? I mean, there were, I don't know if Andrew shared this, and there were like five startups worth of hard problems for us to go after. I mean, I mean, it was absolutely, there were moments, I was joking with one of the other founders last night, where you would come back from a board meeting, and you weren't quite sure whether we were going to figure out our way through a very fundamental, you know, thermodynamics challenge. Okay, so when you say five problems, you're not talking about fundraising, a hard negotiation with TSMC, talking to your supplier.

3:09:57You're talking about design. All of that too. All of that's true. I'm talking about the actual hard problems, meaning hard technology problems. Yeah, yeah, yeah. And the ones that are sort of more physical, where you have laws of physics and thermodynamics to obey and you don't get to negotiate. Andrew's a very good negotiator, but he's also learned that he can't negotiate with the second law of thermodynamics. So this was how do you yield a semiconductor? that's the size of a dinner plate? How do you power it? How do you cool it? How do you maintain continuity across thousands of connections?

3:10:27How do you put it in a system and integrate it, and then in a data center, and then put 65 of them or 64 of them in a data center together? It was those kinds of very hard challenges where I say five startups in one. They were, of course, also stacked, which means that the risks are now combinatorial. Even more dangerous. You've been through taking companies public, you know, being involved with public companies several times. A lot of times the founders that you're backing, it's their first time becoming a public company. What are you telling them? What advice can you share with a founder, not Andrew specifically, but any founder who's going public?

3:11:05How will the company change? What are you telling them as they become the CEO of a public company? Yeah. So there's, there's a few things that come to mind. One is buckle up because, uh, it's going to be it particularly in markets like the one we're in right now, where, I mean, you see the headlines change every, every few days. I mean, there'll be another drop of another, uh, model tomorrow that could, you know, whatever upend the public markets. Yep. And so you don't have a lot of control over what the world thinks about your share price. And so you've got to coach your teams and your engineers in particular to know that when the share price is moving, it very often has nothing to do with what you're doing in the day to day.

3:11:50And you just need to steal yourself against that. I think there's also a piece which is you just have to grow up. Like there's a cadence to these businesses, quarterly, unfortunately, I wish they were longer, where, you know, Andrew and Bob are going to hop on an earnings call very soon. And they're going to have to start talking about the business of the business, not necessarily the technology of it. And that requires a level of discipline and planning that oftentimes founders don't have their stuff together well enough in order to be able to sort of manage through that transition. And then the last thing I would say is actually the flip of it, which is don't forget what made you special.

3:12:33Because when you get into this quarterly cadence and you start to think, well, how do I meet the next quarter? You oftentimes lose sight of the long horizon that was the larger opportunity for you to go after, you know, not just, you know, the opportunity right in front of you, but there's much, much larger opportunities. and we're building systems for the next gen and the gen after that and the gen after that. And so you can get tricked into being in a kind of quarterly mindset and it's one of the most toxic ways to kill a company that's built around innovation. So you just want to make sure that there's that horizon that's still calling.

3:13:12That's where we need to go. I love it. Thank you so much for coming on and breaking it down. Sorry for running long. I'll let you get to the celebratory dinner. Say hello to everyone and have a great day. Awesome. Thanks so much. We'll talk to you soon. Have a good one. That's our show, folks. Leave us five stars on Apple Podcasts and Spotify. Another one. Sign up for our newsletter at tbpn.com. See you tomorrow at 11 a.m. Pacific time. And have a great rest of your day. Goodbye.