transcript

Speaker 1:
[00:01] You're watching TBPN.

Speaker 2:
[00:03] Today is Wednesday, April 22nd, 2026. We are live from the TBPN Altar, down the Temple of Technology, the Fortress of Finance, the Capital of Capital. Bunch of major stories today. SpaceX and Cursor are partnering up. More news out of Images 2.0, a bunch of news out of OpenAI. And Mythos, a group of unauthorized users have been using Claude Mythos since the day it was released. A big scoop in Bloomberg. We'll go through. There's a whole bunch of timeline. We can also pull up the lineup and take you through who's coming on. We got Adobe, BuildForever, AngelList, Zanskar, VAST Data, Gradient. We're going through all the news of the day. Well, let's start with SpaceX and Cursor, who are teaming up in a very interesting deal. Is this a gong already?

Speaker 3:
[00:52] This is gong-worthy because it's an option to buy the company, but a $10 billion break up fee. Incredibly, incredibly. Yeah. I think it's a win-win. It's a win-win.

Speaker 2:
[01:04] Yeah.

Speaker 3:
[01:04] Win-win. I think it makes sense for both parties.

Speaker 2:
[01:06] It's a win, no matter what. Well, let's go through the facts first. So, SpaceX partners. Partners fact. Just immediate takes. We assume you already know all the industry.

Speaker 3:
[01:18] Post-fact.

Speaker 2:
[01:19] Do you know all the information? Do we need to give you any information? We'll see. But let's run through it. SpaceX partners with Cursor to, quote, create the world's best coding and knowledge work AI. The deal gets Cursor, who's a Gentic coding model, Composer 2 basically operates at frontier level performance, access to compute from SpaceX's million H100 equivalent Colossus supercomputer. And that is the correct term for Colossus. It is a supercomputer. There were some other terms that Elon was throwing out. Fantastic terminology from the XAI team over there. What was the other one? It was like AI...

Speaker 4:
[01:58] Compute Gigafactory.

Speaker 2:
[01:59] Compute Gigafactory. They're all hilarious and very good. I like all of these. Computer?

Speaker 3:
[02:05] Were they saying computer?

Speaker 2:
[02:07] I don't know. The XAI timeline, I was thinking about it and I was like, when did this actually start? Because it just kind of came out of nowhere and just absolutely blew up. I wanted to actually review and reset on the timeline of events here because it's gotten so crazy to the point where it's like now, the thing that started is Elon sort of being like, I want to buy Twitter, is now a NeoLab with a massive supercomputer data center and a coding agent and code review for the age of AI because don't forget, they own Graphite now, or potentially will, and a social media app.

Speaker 3:
[02:46] The space code review company. Exactly. So I'm really, I'm genuinely so excited for the Graphite team. I'm thrilled for the cursor team. I'm thrilled.

Speaker 2:
[03:00] I'm thrilled for Scott Wu.

Speaker 3:
[03:02] Yeah, Scott Wu is licking his chops. He's like, what are you going to leave out in the wreckage?

Speaker 2:
[03:08] He really is going to have fun with it.

Speaker 3:
[03:10] I also think we need to take one moment.

Speaker 2:
[03:13] Yeah.

Speaker 3:
[03:17] And just send some thoughts and prayers to SBF.

Speaker 2:
[03:21] Oh, yeah.

Speaker 3:
[03:21] Imagine, I don't know how this works in whatever prison he's in, but I imagine hopefully every few days he can go and talk to the outside world.

Speaker 2:
[03:32] Yeah.

Speaker 3:
[03:33] And you can imagine him going, making the call.

Speaker 2:
[03:38] Yeah.

Speaker 3:
[03:38] And he says, for the last few weeks, it's like, sir.

Speaker 2:
[03:42] What would the mark be?

Speaker 3:
[03:44] How is Anthropic doing? How's my baby doing? And it's like, sir, it's traded up north of 800.

Speaker 2:
[03:51] It's almost a trillion.

Speaker 3:
[03:52] And it's quite possibly going north of a trillion. And then he's like, thank you. Comes back the next day. I haven't checked in with Cursor a little bit. How are they doing? Sir, you may not want to hear this, but.

Speaker 2:
[04:09] There's a $50 billion acquisition.

Speaker 3:
[04:11] They've agreed to sell for $60 billion. And if they don't sell, they're going to get $10 billion of non-dilutive capital.

Speaker 2:
[04:20] Absolutely wild. Anyways, what a wild, wild turn of events. Anyway, let's go through the timeline. Because it's interesting to revisit the flurry of news that has come out of Elon in ink over the past just four years when this all started. April 14th, 2022, it's April 22nd now. So we're talking four years to go from just proposing buying Twitter. He made an unsolicited offer to acquire the company. He closed that acquisition after a bunch of back and forth saying, hey, maybe I don't want it. It was very clear that the stock would have traded down significantly from that $44 billion, because this was when the interest rate hike happened and the end of ZERP and basically all software companies sold off significantly. And so we saw declines in SNAP and Pinterest and basically anything that was even meta sold off like 40, 50% post, although that was like an anomaly and they built back up. But the question about like, okay, well, Reality Labs is a 10 billion, 10s of billions dollar bet on revenues that might come in like 10 years. Like it was so far away and the revenue ramp on VR and Metaverse projects was so slow that the market just had to discount those future revenues even if they were still bullish on the idea of Meta winning the VR race, winning the Metaverse at some point. It just wasn't going to happen anytime soon. So you got to discount that back at 6% instead of 3% or whatever your risk free rate is in your DCF. And so everything sold off and Elon had locked in that pre end of Zerp price. And there was a big question about, could he get out of it? Were they going to twist his arm? There was a little bit of arm twisting. The arm was a little bit twisted, but Morgan Stanley came on board and a bunch of other.

Speaker 3:
[06:11] It was almost broken.

Speaker 2:
[06:13] But the people whose arms were twisted, Morgan Stanley and all the VC backers who came in, they wound up with SpaceX stock. And so they wound up doing very well because they wound up with XAI stock and then SpaceX stock. And so it's all looking like, you know, it was never bet against Elon. Like that was the thing. It was like, surely this is the time to bet against Elon. He's buying Twitter for $44 billion. It's a crazy idea based on the market, where things are, but everything's sort of penciled out. So he closed the Twitter acquisition on October 27th, 2022. And he took control of the platform at the end of that month. That was sync day. Of course, he comes in with a sync, something about the, what was the joke about the kitchen sink?

Speaker 4:
[06:52] It was like, let that sink in.

Speaker 2:
[06:54] Oh, let that sink in. Okay. It wasn't, it wasn't like I'm doing the whole, the whole, isn't the whole kitchen sink another phrase as well?

Speaker 4:
[07:00] Yeah. Like throw the whole kitchen sink at it.

Speaker 2:
[07:01] Okay. Yeah. Well, he did that too, because he threw everything together. Yes. Good job. Yeah. So XAI came later. He publicly announced XAI on July 12th, 2023. And that's only nine months after Chet GPT, maybe eight months after Chet GPT. Google quick followed with Gemini. And it was a very fast-following, I think, to get XAI off the ground.

Speaker 3:
[07:27] And that was like, just for context, that was right around the time you first publicly talked about the potential for a tech livestream, right?

Speaker 2:
[07:35] Oh, yes. Yes, I do.

Speaker 3:
[07:36] 2023.

Speaker 2:
[07:38] I think that was actually very close to the date. Yeah, I was making YouTube videos. I made a whole YouTube video about the Elon Twitter acquisition, and I was sort of trying to justify it as a, you know, it was more about his desire for free speech than anything else, like, you shouldn't look at it in financial terms, I think that still probably holds. But there wound up being a whole bunch of other knock-on effects for Elon's strategy. Anyway, so he was, you know, coming out on July 12, 2023, saying, I'm back in the AI horse race, I'm competing directly with the big labs, I'm going to go up against DeepMind still. Remember, that's why he founded OpenAI. He wanted to push back against DeepMind. I'm going to go up against Anthropic, going to go up against OpenAI. And so, the first major product milestone came just a couple months later, November 3rd. That's when they introduced Grok, November 3rd, 2023. So it's been almost three years. The first real integration with Twitter happened on December 7th, 2023, when Grok started rolling out inside of X for premium plus subscribers, which was a new tier. It's actually crazy how many features...

Speaker 3:
[08:42] Everyone got verified, remember?

Speaker 2:
[08:44] I mean, that year on Twitter was insane. Like just product feature, product feature, and they were shipping stuff that had been clearly developed beforehand. Like I think the Community Notes idea had been workshopped and even like engineered in the pre-Elon era, but he just got there and was like, ship that tomorrow. And like there were a lot of things like that that happened. And there were other things that got pulled back and review. And like there were other pieces of the puzzle that were like not doing so well and he was just like, cut, cut, cut. And so he sort of like put it back in startup mode and it felt a lot more agile and it still does. And so that was the moment Grok finally became a part of the X product experience. In early 2024, XAI started shipping updates quickly. March 17, 2024, open source Grok 1. March 26, 2024, Grok access expanded to X premium subscribers. Two days later, they announced 1.5. Then on April 12, 2024, they announced 15V, which added multimodal capabilities. Then Grok 2, Grok 2 mini. By the end of 2024, Grok was available to all X users. And so 2025, XAI moved from being connected to X to absorbing it at the product level. On February 19, 2025, XAI announced Grok 3 beta. Then March 28, 2025, so over a year ago, for some reason this feels more recent than that, XAI acquired X in an all-stock deal. So March 28, 2025, effectively merging the AI company with a social platform. After that, X kept releasing faster model updates. They did Grok 4 fast, Grok 4.1. Then came the SpaceX deal. That was February 2, 2026. So the clean sequences that Musk first proposed, the Twitter acquisition, then founded XAI, then brought Grok into X, then merged XAI with X, and then SpaceX bought XAI. And so now Cursor is joining the team.

Speaker 3:
[10:37] Yeah, and this just makes so much sense, right? Cursor needs compute. They need the resources. They need the capital to train a frontier coding model.

Speaker 2:
[10:47] They've also never done a pre-training, I believe, whereas the XAI team has, right? Correct.

Speaker 3:
[10:52] And the big, big thing is that the Grok brand has been through so much. There was an idea being thrown around last year that it had been banned in more workplaces than it had been adopted.

Speaker 2:
[11:07] Yeah, yeah, yeah.

Speaker 3:
[11:07] So more people had said, like, you cannot use this product in the workplace than we're actually using it in the workplace. Cursor's a great brand, right? It's a brand that I think can probably expand outside of coding, right? Say in the announcement. Best to create the world's best coding and knowledge work AI. So we're at a point right now where everyone is building the exact same thing. We got everyone on earth building a box that you can tell to do things and it does things.

Speaker 2:
[11:38] Oh, so you just want one company to do it all? Communist?

Speaker 3:
[11:41] No, no, I don't. I think the competition is great.

Speaker 2:
[11:44] You want the government to have one.

Speaker 3:
[11:45] It's bringing out the best in, it's bringing out the best. It is, it is. But I think Cursor's like.

Speaker 2:
[11:49] Knockout, dragout, fight.

Speaker 3:
[11:50] Cursor's always had a great brand.

Speaker 4:
[11:51] I saw someone else.

Speaker 2:
[11:53] SBF replied to SpaceX's Tweet saying, that's me. Pull up the first post here and then scroll down. The SpaceX and Cursor are now working closely. It should be like the first one in the timeline. SpaceX and Cursor, SpaceX AI is what they're calling it now. Is it not up there? And Cursor, I can find it and send it in. Let me find this post and send it into the production chat.

Speaker 3:
[12:23] Tuxedo Sam says, do you think they'll make Elon take his shoes off at the Cursor office?

Speaker 2:
[12:30] Okay, so Richard Wu has some context. There you go. Look, SBF is somehow on Twitter. How can you be on Twitter from jail?

Speaker 4:
[12:38] All these people in jail on X, I don't understand.

Speaker 3:
[12:41] No, it says it in his bio. It says it in his bio. It's managed by somebody else. We can use BOP approved phone calls, emails to tell others what to post on our socials. I think it would be a free speech violation to say, if you are in jail, you cannot distribute information in the outside world in any capacity, but it feels like this was maybe some legislation that was created pre-internet, because it seems like having a ghostwriter on your account is a really good way to start kind of influencing public perception. I think this is, Elizabeth Holmes has had enough kind of moments where it was like she, her proxy posted something that was mildly kind of entertaining and over time that just wears on people and eventually people are like, maybe she isn't so bad after all, right?

Speaker 2:
[13:34] Well, Richard Wu broke down the structure of the deal. He says, the structure of the deal is pretty interesting here. I think what's happening is, one, XAI is having trouble training a state-of-the-art coding model, hence co-founder departures. They might have a bunch of idle GPUs. Cursor doesn't have capital to blow on a $5 billion training run to compete with Codex and Claude. XAI, three, XAI says to Cursor, use all the GPUs you want at cost and get to a state-of-the-art coding model as long as we have the option to buy you. Four, Cursor also gets a free option. Train a model better than Opus and get bought out for 60 billion, or get 10 billion that pays for all the GPUs you rented. Win-win. I was reflecting on Michael Truell's fantastic entrepreneur, remarkably young, but his aesthetic is very much in the Stripe world, I imagine, because I feel like the one really cinematic podcast he's done is that one with, was it Patrick Hollison? Is that the one I'm thinking of? And it's like them at the coffee shop and it's so welcoming and warming. It's like that is that is welcome in every corporate entity in America, right? Like, and to your point about like, you know, oh, like if your corporation is like, oh, what's going on with Elon and politics, blah, blah, blah. Do we really want Grok running around with Mecca and Aony and all this crazy stuff? But if it's just like Michael Truell from Cursor, he's so reassuring. Like I, if I'm like Coke or GE or Ford, I'm like, yeah, of course, like we love Cursor. That's great. I mean, very, very, aesthetics do matter. Vibes do matter. And I think it makes a lot of sense.

Speaker 3:
[15:12] Matt Slotnick says he loves math.

Speaker 2:
[15:16] Okay. What is the math here?

Speaker 3:
[15:18] What he's talking about Julian. He's so Julian says at a 30 X revenue multiple at first glance, it appears that SpaceX is overpaying for Cursor. However, the deal is wildly accretive for SpaceX, given it is expected to go public at more than a hundred X revenue, a 70 term multiple expansion on 2 billion of revenue adds up. Wow.

Speaker 2:
[15:38] This is a notorious thing in corporate M&A, and occasionally it's gone poorly. But there is an old adage that if you can acquire earnings at a lower earnings multiple and maintain your current multiple, that is accretive to the stock. And so there's a whole philosophy around that. But the smart investors should price each earning stream differently, and having a monopoly on launch capacity should be a higher multiple than a super competitive oligopolistic coding market, if that's what this winds up being. It's a tricky, tricky situation.

Speaker 3:
[16:13] Will Brown. Wow. Cursor just hit a $10 billion run rate.

Speaker 2:
[16:16] They did. It's guaranteed, right? There's no way that they won't make $10 billion this year. That's not even a run rate. That's just like, it's locked in. It's more than contracted.

Speaker 3:
[16:24] I don't know. And it's very meaningful because it is effectively an exit, and then it's by itself. They'll be in a position to actually reinvest that. That's like a nice little NeoLab Series A, basically.

Speaker 2:
[16:43] But Ken says, no. You've got to multiply that $10 billion by 12. Because in that month, where they get the $10 billion check from SpaceX, it will be $120 billion run rate. They will be the largest AI company in the world that month. And then they just have to figure out. They don't collect until end of year if they're still independent. Otherwise, it's more like $25 billion. OK. Well, so Fleeting Vids has some other thoughts.

Speaker 3:
[17:10] What is this post from Patrick?

Speaker 2:
[17:13] Wait, which one? Which one?

Speaker 3:
[17:14] This is, Patrick is quoting Scott Wu.

Speaker 2:
[17:18] Oh, yeah, yeah. Last of the Mohicans. Scott Wu. I love it because despite this does not look.

Speaker 3:
[17:24] See, without images too, without images too, we just this this kind of. I actually think this might be done the old fashioned way.

Speaker 2:
[17:31] No, no, no. This is Nano Banana.

Speaker 3:
[17:33] There we go.

Speaker 2:
[17:34] It's good at cutting out faces.

Speaker 3:
[17:35] Thank you, Watermark.

Speaker 2:
[17:36] Yes. He says, here we go again. Last of the Mohicans. Yeah, Scott Wu is the last one standing in this particular category. And yeah, he's licking his chops thinking about who might want to hop over to Cognition, Cursor, Cognition, Windsurf, Devon, Cursor, Zombie Corp as the ghost ships continue to line up on the shores of Scott Wu's territory. What else should we go through with the Cursor? Cursor's long-term viability was contingent on- I think that's it.

Speaker 3:
[18:09] I'm very happy for everyone involved. Yeah, I'm very happy. Some news from Space News Inc.

Speaker 2:
[18:15] This is very interesting.

Speaker 3:
[18:16] China backs Orbital Data Center's start-up with $8.4 billion in credit lines.

Speaker 2:
[18:19] They're piled. They're piled.

Speaker 3:
[18:21] Yvonne is interested.

Speaker 2:
[18:23] $8.4 billion in credit lines. That is a lot of money. A Beijing-based space start-up has secured early-stage funding. Early-stage funding to the tune of $8.4 billion? What are we doing here? And extensive credit backing is part of a broader Chinese push towards space-based computing infrastructure, Beijing Orbital Twilight Technology Company Limited. We don't know how to name companies like that in this country. Seriously.

Speaker 3:
[18:46] This is the new meta.

Speaker 2:
[18:48] Yeah. What is Cursor's real name? Any Sphere? This is a pretty good name. I like Any Sphere and I like Cursor, but it doesn't hold a candle. So Beijing Orbital Twilight Technology Company Limited, also known as Orbital Chengguang, announced the completion of a pre-A1 funding round April 20th. The round saw participation from venture and industrial investors, including Hisong Capital, CITIC, Construction Investment Capital, Cathay Capital. They got everybody. It's a murderer's row over there. At the same time, Orbital State said that it has obtained strategic credit lines totaling 8.4 billion from 12 major financial institutions, including the Bank of China. Are they going to build rockets with this? I mean, I don't understand why this would be so capital intensive if they're not going to fab the chips and they're not going to launch the rockets.

Speaker 3:
[19:45] Well, they're going to put a lot of GPUs in space.

Speaker 2:
[19:48] I guess they're just going to buy a lot of Huawei chips or something. Are they going to go to Huawei and get some special stuff?

Speaker 4:
[19:52] Yeah. I mean, this is pretty interesting because I feel like, you know, generally the main bull case for space data centers is that the regulatory environment in the US is going to be so hard to build data centers on normal land. Supercomputers. So you got to send supercomputers to space because there's less...

Speaker 2:
[20:10] No, we can do data centers in space. If it's on the ground, it's a supercomputer.

Speaker 4:
[20:14] Okay. Yeah. That makes sense.

Speaker 2:
[20:16] Because we don't want any more data centers on Earth. It's Earth Day, by the way. Congratulations, Earth. You've done fantastically.

Speaker 4:
[20:22] Yeah. But the whole thing in China is you can just build things there, right? There's very little regulatory overhead.

Speaker 2:
[20:28] Yeah.

Speaker 4:
[20:29] So I feel like the space data centers make a lot more sense for the US. Yeah. If you're worried about... If the bull case is regulatory, which it seems to be, that's generally consensus, I think.

Speaker 2:
[20:40] Yeah. I was laughing about how there's all this fear about data centers using water in America. But over in China, they have the Three Gorges Dam, which generates electricity from water. And it technically uses a lot of water. The water is not destroyed or anything. It just passes through the dam, generates electricity.

Speaker 3:
[20:56] But they're using the entire ocean of water.

Speaker 2:
[20:59] Exactly. The Hoover Dam, that's a nightmare. If you just... Like, there's one frame where you don't want the water to be destroyed or made unpotable, so you can't drink it anymore. But there's another one where you think like water has individual rights and should not be used at all. Like it should not be used. It should not flow through a water wheel. It should not flow through a dam and generate electricity at all. It should be left to its own devices still and just chill. Maybe. Anyway, Orbital has incubated, was incubated by the Beijing Astrofuture Institute of Space Technology, which itself is backed by Beijing's Municipal Science and Technology Commission and the Science Park Administration. The Institute leads a consortium of 24 organizations. The rationale for the constellation in November briefing. So, large scale data centers have expanded rapidly worldwide, but further growth faces major obstacles, including heavy land use, weird, soaring energy consumption, weird, limits on atmospheric cooling. These things usually don't apply in China, but maybe they are skating where the puck is going, and maybe they're thinking that they will need to change their direction. So, they're planning a Dawn Dusk orbit about 700, 800 kilometers above the Earth, aiming to achieve a large scale space data center to support space based computing by 2035. Wow, thinking in decades over there. So, they're going slow. They're getting there. An initial phase spanning 2025 and 2027. Wait, why are they talking about last year? We'll focus on core technological changes and the first computing.

Speaker 3:
[22:31] They're manipulating time, John.

Speaker 2:
[22:34] The experimental satellite was slated for launch in late 2025 or early 26, but it does not appear to have launched. They have decent launch capacity with the Long March rocket. I think that they just are not amazing at landing it, but you got more money. You can just YOLO more rockets up there, I guess. Problem solved, although I would be surprised if there's as much pressure to not build super computers next to the Three Gorges Dam. Anyway, moving on. More images out of ChatGPT. Images 2, ImageGen 2.

Speaker 3:
[23:09] Pull these up.

Speaker 2:
[23:09] Images V2. These are crazy. Has anyone done that rune test of the guy driving the car into the whole thing, where he was like, it's AGI if it can understand this meme? I guess you can't because that particular meme has been saturated on the Internet, and so it no longer is a challenge.

Speaker 3:
[23:29] I'm going to have it make an image. This is a crazy image. I am a tiny man.

Speaker 2:
[23:34] What is this? MySpace.

Speaker 3:
[23:36] My son was born.

Speaker 2:
[23:38] This is truly...

Speaker 3:
[23:39] They handed me to him.

Speaker 2:
[23:41] Never forget where you came from. Blink 182. It really packed so much stuff in here. It's almost too much. I have been noticing the Gabriel over there is pushing the model into chaos and seeing what happens. Cows are flying, horses are flying, trampolines are flying.

Speaker 4:
[23:57] The next one by Ethan Mollack has every image benchmark in one.

Speaker 2:
[24:01] You were asking about this. You said, and explain the history of this.

Speaker 4:
[24:06] Originally, when Dolly first came out, the image that everyone was like, oh, this is crazy, it was an astronaut riding a horse on the moon.

Speaker 2:
[24:13] Yeah.

Speaker 4:
[24:13] So then it's like, okay, that's very easy. Then it became-

Speaker 2:
[24:17] Well, it's very hard to Photoshop that. It's very hard to go get an actual picture. Because if someone's just make a picture of a dog and it's photo real, everyone's like, oh, who cares? We have a picture of a dog. We don't have any pictures of astronauts riding horses on the moon.

Speaker 4:
[24:30] There's people riding horses, right? Yes.

Speaker 2:
[24:32] It should be able to process.

Speaker 4:
[24:33] There's a sense where maybe it doesn't need to fully understand everything that's going on because there's a lot of references it can pull from.

Speaker 2:
[24:40] Totally.

Speaker 4:
[24:41] So then it became, can a horse ride an astronaut? Yes. It's like the reverse.

Speaker 2:
[24:46] Yes.

Speaker 4:
[24:46] Early image models would always just do the flip. They would just put the astronaut on the horse.

Speaker 2:
[24:50] Because that's more logical.

Speaker 4:
[24:52] So there's a number of these things where if you ask a person to draw it out, it's like, okay, you just think logically, this is how it would look. But there's just no reference images online. So another one was a full wine glass. So you think of a full wine glass as it's still only technically halfway, three-fourths full.

Speaker 2:
[25:07] I never understood why that one didn't work. I saw the whole video for you.

Speaker 4:
[25:10] There's just very few images online of a full wine glass being like-

Speaker 2:
[25:13] Oh, full to the brim because people typically fill them halfway. So in the training day, okay, got it.

Speaker 4:
[25:18] Yeah, and then there was the-

Speaker 2:
[25:21] What is this image? This is not the one.

Speaker 3:
[25:24] This is not the one.

Speaker 2:
[25:25] This is not the one from the timeline. That one's way more aggressive than the- This is the one. This one looks aesthetic and it still looks weird.

Speaker 3:
[25:33] The only thing is, would a horse's belly really look like that?

Speaker 2:
[25:37] It is sort of like a humanoid horse.

Speaker 3:
[25:39] It kind of looks like a human that-

Speaker 2:
[25:42] But it does have the wine glass completely filled. And then explain the clock.

Speaker 4:
[25:46] The last one you pulled up was Grok, I think.

Speaker 2:
[25:49] Okay, explain the clock. What's going on with the clock?

Speaker 4:
[25:52] Yeah, that one's just another understanding thing. Where, if you give it a time, can it do the clock?

Speaker 2:
[25:57] Yeah.

Speaker 4:
[25:57] Like the correct time? There's also one where you do a bunch of clocks all in different time zones.

Speaker 2:
[26:02] Yeah.

Speaker 4:
[26:03] And it couldn't do the clock.

Speaker 2:
[26:05] It couldn't do the clock. It has two hour hands.

Speaker 4:
[26:08] Yeah, this one.

Speaker 2:
[26:08] So you know what that means? We're moving the goalpost.

Speaker 3:
[26:10] Do it.

Speaker 2:
[26:11] Moving the goalpost.

Speaker 3:
[26:12] The goalpost, we also do it. It's time. It's time.

Speaker 2:
[26:18] It's time to move the goalpost. We gotta, we gotta one job. It's 99% complete. That is not. It's not complete yet. It's not complete yet.

Speaker 3:
[26:29] You guys have more work to do.

Speaker 2:
[26:30] No, no. Sam was talking about this with Ashley Dance. He was saying that like, you know, he thought he thought job was finished with like ChatGPT images because it was really good. And then they worked a lot harder and they realized that there was more to do. And this is like the car path thing about like, yeah, you get the self-driving cars to 99% and then takes another year to get at another nine and then it takes another year to add another nine and then another nine. And it just takes forever to improve these things because we demand perfection. We do not accept two hands on a clock. Keep grinding, folks. Keep grinding. Anyway, there are a lot of other fun posts. Semi-analysis, I thought this was just a real image of Dorkesh taking a selfie and then it was recontextualized via a meme. It is, in fact, an AI image.

Speaker 3:
[27:17] And it doesn't even look like the new model, though.

Speaker 2:
[27:19] Hi, I'm Dorkesh. I grew up all over the US and now SF based and always down to nerd out about AI science and history. A little about me. I host the Dorkesh podcast, Study at UT Austin. I just published a book on the history of AI scaling. Let's grab coffee or do a fun activity this summer. Because, of course, this is a meme template that is very popular and has gone viral with a lot of new people that have been hired and moved to San Francisco.

Speaker 3:
[27:44] So the other thing I've noticed with images, too, is that I think it has fully... The new model has actually has taste.

Speaker 2:
[27:53] I agree.

Speaker 3:
[27:53] And it has fully democratized high quality lifestyle and product imagery. And I'm shedding a tear just a little bit because you used to be able to tell the kind of... Somebody who's working on a CPG company, you could kind of clock their ability as a founder based on the quality of their images, right? Because maybe they're not super creative themselves. Maybe they haven't raised a bunch of money, but if they're scrappy, they can meet the right photographer, they can put stuff together. And now it's like everyone just has a great product photography. And I saw this morning with, there's that Andreessenbach company that does electric scooters.

Speaker 2:
[28:39] Oh yeah.

Speaker 3:
[28:39] They were just ripping out a bunch of images that look like they spent tens of thousands of dollars doing them, but they're clearly like images too, which is cool. It's just like funny that we've entered a world where anyone can have a great image. Yeah.

Speaker 2:
[28:52] I've seen some people. I think that the end result will be like, you will see more opinionated and creative and more people. Like there will be a collapsing around, like everyone will copy Apple or Linear, but then on the flip side, you will see people that are doing things that are really unexpected. And those things will be copied. But if the brand can run through and actually establish itself as like, oh, it has this unique aesthetic, it won't matter that somebody can re-create it. Because plenty of people did that with the Red Antler stuff. It was like there were brands that really owned that and carved that out as like their aesthetic, and then there were a bunch of copycats, and no one really liked those. I was reflecting on the fact that like for a long time, Mid Journey felt like it had a very unique aesthetic, like ArtStation and like painterly and sci-fi really well. And then CHPT images V1 and some of the other image models just felt like stock photography. And now I feel like I'm starting to see more stuff out of images with CHPT that feels more opinionated and has a stronger aesthetic, and it can do more of like the sci-fi stuff. Although sometimes it leans in a little bit too much to the photorealism. I think you got to get kind of crazy with the prompts to actually get something that's abstract, because I was taking some Mid Journey prompts and I was putting them into CHPT images, and I was noticing that like it was just putting out stuff that was like, it was like, like what the prompt was like make a video game of like a car racing, and it just looked exactly like a video game, because it just looks like a screenshot instead of like the idea of a video game.

Speaker 3:
[30:24] Okay, last one we're going to pull up and then we have our first guest.

Speaker 2:
[30:27] Yes.

Speaker 3:
[30:27] Post from Ben Hylak, the legend. It says, Nightmare Blunt Rotation.

Speaker 2:
[30:33] Oh, yeah, it can do 360 images. It can do 360 images, which is really cool. You got Sam, so it generates a full equirectangular image, which is something you could view in VR. And then you can load that into a panoramic stereoscopic image generator. I wonder when 3D images will come. And also, I mean, the big question is like, people are going to want to animate these. What's the downstream tool chain for actually turning this into video? Are we going back into video at some point? We will see. Anyway, people are having a lot of fun with it. And it should help with front end and a lot of other stuff. It seems like it's done very well on design and layouts and all this stuff. Well, we have a perfect person to talk about AI imagery, AI generative AI, creative tooling and more because we are joined by Anil from Adobe, where he is the president. So let's bring in Anil. How are you doing? Welcome to the show.

Speaker 1:
[31:38] Thank you for having me on. Great to be back on TBPN and congrats on your acquisition.

Speaker 2:
[31:43] Thank you.

Speaker 3:
[31:44] Thank you. It's great to see you.

Speaker 2:
[31:45] Great to see you again. I would love to just get a general update on what has changed with Adobe. What have you been working on since the last time we spoke?

Speaker 1:
[31:56] Look, I'm coming to you from Adobe Summit. We are here in Las Vegas, in a big show, 14,000 people. You were just talking about Jensen. Jensen was here on Monday. Really talking about how Nvidia and Adobe are working together. You were just talking about 3D. I caught the tail end of your comment there. That's actually one of the big things we announced is, how do you have digital twins so that you can take the digital twin and carry it all the way from product design into marketing and customer experience. With HP, for example, they have 15,000 new SKUs every year with all the products they have. They're working with us and with Nvidia to bring it together into marketing. So, we are super excited about what we call customer experience orchestration, which is, how do you use AI, how do you use all the software you have to deliver personalized experiences? How do you bring the right content, the right data about the customer, and then put that into the channel that they care about and really get the most out of the customer lifecycle and build loyalty? That's the big topic of the conference here.

Speaker 2:
[33:03] Yeah, walk me through that HP example, because if they have a SKU, I imagine that there's a CAD file at some point, and then they might want to instantiate that in text, or imagery, or video, or the 3D rendering, and they might want to go over to one of your 3D products or bridge to another. How important is Adobe at the center of asset management actually creating some sort of abstraction on top of what the actual core item is, versus just translating from one sort of output to the next in the way that someone might take a PNG from Photoshop and drop it into Premiere Pro?

Speaker 1:
[33:44] No, that's exactly right. So they start with the 3D image that they have, or the 3D rendering, as you said, a CAD file. From that, what we do is we create the digital twin, and then we apply the brand intelligence on their behalf. So in HP's case, for example, if it's a new PC that they're releasing, they have all kinds of things on what they want when they say it's a laptop and the laptop is open, what's the kind of image they want on the laptop? What's the kind of lighting they want on the laptop? And then they release it all over the world, so there's pictures of people, they always want to show a business professional in the laptop, along with the laptop. They want them, showing them using the laptop to do something. So they have all kinds of brand guidelines, of course, but then there's a lot of tribal knowledge on what makes an ad successful. And it's not only for them, then they have to get all of that traveling through the entire marketing campaign because one of the big problems has been, you know, in the current world, they use the 3D CAD files for everything from manufacturing and so on. But the marketing, the content, starts with a photo shoot. They're not actually using the 3D CAD file that they have, the source of truth. And that's what we're enabling them to do. Use the source of truth so that the images are completely high fidelity, they're brand preserving. But then you can generate everything around that. You can generate the background, you can generate the foreground, you can generate the users, and then of course you can do what we call transcreation, which is the translation into different languages. All of that can be generated based on their brand guidelines and what works for their brand.

Speaker 2:
[35:26] So is your relationship with Nvidia that you want to marshal enough compute that you can be delivering inference to a customer? Because I remember using ContentAware Fill back in the day, it ran locally on my device. As the models get more compute intensive, they eventually won't run on device, they'll run in the cloud. I know you have API partnerships, but is there a vision to deliver inference to the customer all in one go?

Speaker 1:
[35:56] Exactly, it depends on the campaign. Let's say HP is running a back to school campaign, then they want a set of imagery, they want a set of things that they can transfer over to their channel partners, along with accurate product data. Or if they're running, for example, a holiday campaign, a different set of imagery, and so on and so forth. So depending on the campaign, depending on the geography, depending on the customer segment, making sure that they have the right campaign, that is obviously the content, but it's also the product data, making sure that that's super accurate, because it's got to match what exactly the customer's buying. And then anything that's relevant for the particular channel partner, it could be through their own direct channels, but it could equally be through CDW or through other channels, and they want to make sure that the entire thing carries over. So that's what we're doing for them, is getting the workflow right, getting the Adobe brand intelligence, which is one of the big things that we announced this week at Summit, getting all of that together so that they can have a single, seamless marketing workflow and get the benefit of both AI and the 3D technology together.

Speaker 3:
[36:59] Jordi? You guys announced a big buyback this week, and that's been exciting, but what do you think you need to do from a result standpoint to show that you guys are an AI beneficiary versus a victim, right? Because the narrative is obviously against you, the market has spoken, but at the same time, AI is a powerful, creative tool. You guys have massive distribution into millions of individuals and businesses, and so I think people are waiting to actually see the story in the numbers, and there's only so much you can say to give people confidence, but how are you thinking about it?

Speaker 1:
[37:42] Yeah, exactly. As you said, we announced a $25 billion buyback. That is a signal of our confidence, of this is going to continue to be a very profitable business for years to come, and we wanted to make sure that everybody in the market knew that. Look, I think to your point, first step for us is AI adoption, and making sure that AI is delivering real value, whether it's to individuals and real value to users, or to enterprise customers like we were just talking about. And for us, what that means is, how do you really embed it into the tooling so seamlessly? Whether you are a marketer, whether you are a creative, or whether you are a business professional using Acrobat, that AI works for you flawlessly, and it does what you want. I love the example from the last show that you had, which is sometimes you do want the horse riding the astronaut. That was an interesting concept. But you know, that may be, but we have a lot of customers like Home Depot that just want sawdust and nails, and that's what makes their campaigns authentic. So depending on what the customer wants, depending on what the user wants, making sure that AI is helping them get value, not AI is getting in the way. That's our focus right now, is just making sure that customers, whether they're enterprises, individuals, small businesses, students, understand that AI is critical to the next generation of creative platforms and marketing platforms and tools. But it's in the context of what they're using, it brings the UI, the agents and the reasoning, the models and the data all together to work for them. So that's, I think we've made a lot of strides on that front here at Summit in over the last couple of years. I think as the results show, one thing for us is I think, from where we are in the market, for the market even to see us continuing the performance that we've had. We're a double-digit grower, we have very healthy margins, even continuing to see that for the next couple of years, I think will change a lot of minds. And then I think we also see the opportunity through customer experience orchestration to reach a real inflection point. So that's what we're looking to do.

Speaker 3:
[39:50] Jordi, you can- Yeah, I was going to ask, how are you, what's your M&A outlook? It seems like there's a ton of really talented teams building creative tools that could fit in to Adobe. Hopefully, you're spending a lot on the buyback, but hopefully there's still some dry powder for some talented teams.

Speaker 1:
[40:10] We do, we have plenty of dry powder. We haven't overextended ourselves. In fact, we are really pleased. We just announced that we have received all the regulatory approvals for SEMrush. And we are in the waiting period to close it. So in the next few weeks, we'll be closing SEMrush. We're super excited about that, because SEMrush, along with our portfolio, solves a real problem for marketers. Marketers, I mean, we heard a lot from customers at Summit. Every brand is like, how do I show up in the right way through OpenAI, through chat, through chat GPD, obviously, but through Cloud and Gemini and Perplexity and Grock? I don't even know how consumer, they know consumers are going there in droves. What they don't know is, what are they even prompting for that I should know about? So if I'm a brand in the cosmetics world, how are they actually prompting? I don't even know what they're prompting for that I should be aware of. Then, how should I make sure, what do I need to do to make sure that I am included in the response? And then what do I need to do to make sure that I'm included in the response in an accurate manner? And then how do I get that traffic coming to me? Or how do I close the sale right there if it's something that I can close right there? This is a new world for marketers. They have, marketers have no idea how this whole thing works. I mean, they don't know, for example, what happens when you put in a prompt into ChatGPD? What is the queries that get kicked off? Where does it get kicked off to? How is that information assembled? How does it impact their brand? They don't know the first thing about it is what they're telling us. And they're saying, Adobe, help us.

Speaker 3:
[41:57] I'm interested to see how this category plays out because there's obviously a bunch of companies doing, they call it answer engine optimization, AEO or GEO, whatever they're calling it. But the big question was always, this feels like a very natural thing for someone like a SEMrush to enter in a big way. They already have the distribution, so it'll be an interesting battle between SEMrush and some of the upstarts like Profound and some other players.

Speaker 1:
[42:23] So I think the battle will be over pretty soon according to me.

Speaker 2:
[42:25] Yeah, there we go.

Speaker 3:
[42:29] I think James and Profound, we should have you guys both on and go at it.

Speaker 2:
[42:34] That's great. I want to talk about video. So, I mean, we saw OpenAI pulled back from Sora. There are some really amazing models that are happening. Some of them are in China. There's a whole bunch of IP stuff. But what I'm interested in is that Photoshop continues to be an important tool, even in a GENAI world, because there's so many fine details. Having GENAI as just one possible tool is valuable. The models are getting better. We're three years into this boom, but video is moving slower. It's more inference demand. And I'm wondering about how you're taking lessons learned and strategies that you applied to the evolution of Photoshop, how that integrates with different model providers, different tools, different in-house solutions, and how you're planning to bring that to After Effects and Premiere, because this feels like a place where you would need even more opinionated editing, like we're nowhere near text box editing, like, you know, to like 40 hours of video into a movie. Like that's just not, like we're so far from that.

Speaker 1:
[43:39] Exactly, so look, this is where we believe Adobe brand intelligence will be a huge differentiator, because that's what then gives us the right information to pass on to the creatives, to say, this is how you use the Adobe Creative Agent, and this is how, where you want to let the AIB take over and this is where you want to be opinionated. I mean, what we have done is provided that flexibility. You know, we announced over 30 integrations now, whether it's Runway or Flux, obviously Google with both Vio and NanoBanana, et cetera. So we've been very open, and we're very open to integrating any other models that come up as well. The key, though, is the creative themselves, if you're working for a brand, I mean, if you're working for, I mentioned Home Depot earlier, or if you mentioned working for Coca-Cola and so on, they don't have enough information by themselves, unless they really get a really super detailed creative brief on what exactly to where they need to take control, where they can let the AI run. We believe we can automate that and provide the right information at the right time to the creative. They can bring the brand idea, they can bring the hero asset, they can bring the creative idea, and then you can apply the intelligence and exactly to your point, you can be a lot more opinionated in what you produce.

Speaker 2:
[44:56] Yeah. It is very fascinating that we got a fully generated video before we got a tool that puppeteers Premiere Pro in a way that can sync up music and edit to be, make cuts just on normal non-AI generated footage. But that's just the nature of computer use and whatnot. So I'm sure it's an exciting time. Lots to build, lots to work on. Congratulations on all the progress.

Speaker 4:
[45:24] Yeah, great to get the update.

Speaker 2:
[45:25] Yeah. Thanks so much for taking the time.

Speaker 4:
[45:27] Good to see you.

Speaker 1:
[45:27] Thank you for having me on.

Speaker 2:
[45:28] We'll talk to you soon. Have a good one. Goodbye. Up next.

Speaker 3:
[45:34] One quick thought. I think right now, already the great image models, the Nano Bananas, the Images 2, it is like you're just talking to somebody who is a digital guy or girl who is very good at Photoshop. That is the experience today. And it was not that way 12 months ago. It is that way now. I no longer need Photoshop. I don't need to go to Fiverr to say like, hey, I need somebody that's good at Photoshop. I don't need to text like Ben and be like, hey, can you help me Photoshop this? And you can just actually just prompt your way. You do not need any UI anymore.

Speaker 2:
[46:16] That's true. That's true.

Speaker 3:
[46:17] For the average. For the average, kind of.

Speaker 2:
[46:20] For, yeah, I mean, we're crossing into the frontier.

Speaker 3:
[46:23] And I'm just saying, that's gonna get there with video, where you just have a timeline, and you can click on a scene or a segment.

Speaker 2:
[46:30] But speed is really, really important here. Like, if there's one word that's wrong on image and you need to regenerate it, you're gonna wait 45 seconds, and it will be faster to have done that in just a traditional workflow. Now, it's getting faster.

Speaker 3:
[46:45] It's so fast now.

Speaker 2:
[46:47] It's very fast.

Speaker 3:
[46:48] It's so fast.

Speaker 2:
[46:48] But if you're editing a two-hour podcast and you say, oh, I want you to cut to Jordi in minute 45 and it has to go regenerate the entire thing, like, that is slow, you're going to need to puppeteer the tools. You're gonna need tool use in here, I think. I don't know.

Speaker 3:
[47:04] Just because the input is possible. I was just shocked because I was playing around with generating product photography, and you're able to say, put the text here, turn it around, put it at a different angle, more shadow, less shadow, all this stuff. And it's wild what you can do without any UI. But without further ado.

Speaker 2:
[47:25] We have Naveen from BuildForever. He's the former Pinterest CPO. Welcome to the show. How are you doing?

Speaker 5:
[47:32] Hey guys. Thanks for having me.

Speaker 2:
[47:34] Thanks for having me.

Speaker 5:
[47:35] I like the bomber, Jordi. Nice piece.

Speaker 3:
[47:37] Thank you. Thank you. It's a one of one.

Speaker 2:
[47:41] New York Stock Exchange.

Speaker 6:
[47:41] New York Stock Exchange.

Speaker 5:
[47:43] Oh, NYSD.

Speaker 2:
[47:45] What date was the New York Stock Exchange founded?

Speaker 3:
[47:47] You tell me.

Speaker 2:
[47:48] 1792. 11 Wall Street. Wow. That is a very old-

Speaker 3:
[47:52] Great address. Great year to get into business.

Speaker 2:
[47:55] Great year to get into business. Best day to get into business.

Speaker 3:
[47:58] But it's great to have you on the show.

Speaker 2:
[47:59] Yeah. First time on the show. Please introduce yourself and the company a little bit.

Speaker 5:
[48:04] Yeah, totally. So my name is Naveen Gavini. I'm the co-founder and CEO of BuildForever. And honestly, we're just a group of engineers and designers and people that love building products that people love to use. And we've worked, as you said, I was early at Pinterest and we worked on a number of consumer products that people use around the world today. But our focus has been on a product that we launched yesterday called Extra. And it's really a reimagination of email as your life's inbox. And so for many of us, we spend all day kind of working, sending email. And when we have time to get to our personal email, it often feels overrun, overwhelming, and just like, I don't know, I personally gave up on my personal email. I had over 250,000 unread emails. And so we were just kind of looking for a solution of just making email more manageable, more fun and delightful. And so with Extra, it keeps track of what's important for you. So you never have to miss something. It helps you clean up your email, organize it around your life. And it does things proactively for you in the background, and helps you get stuff done. And so this endless to do list feels not so overwhelming, and it just feels delightful and joyful to open up your email every day.

Speaker 2:
[49:11] Is it a for you page for email?

Speaker 5:
[49:15] Yeah, essentially. That's how you could think of it. That's a good analogy. Yeah, so everything that's important in your life.

Speaker 3:
[49:20] We turn every email that you have into a short vertical looping video.

Speaker 2:
[49:25] It's not quite that, but Joe wasn't always talking about this.

Speaker 3:
[49:27] I know what you're saying. It's basically like, yeah, just actually picking and choose. It's always been so silly that inboxes were primarily based around who messaged you last, not based around what was actually important or actionable or anything like that. Yeah, this is what I was talking about. I feel like we need to move the idea, the whole idea of inbox hero is just such a pre-AI idea, where you are just getting flooded with more and more and more and more and more spam, and I think products that can help here are great. Also, it feels like you can kind of just, yeah, I'm curious, so you're built on top of Gmail, I don't know if you're supporting other email providers. Google is like aware that AI can be powerful in email, they're working on a lot of features, but I feel like this is one of those things that is gonna require really, really rapid iteration. And so I feel like you probably have this beautiful window of maybe three to four years where they're kind of just slow to figure out some of this stuff and you can probably build a cool business in the meantime. But where does this go? How are you thinking about this as a venture scale opportunity?

Speaker 5:
[50:50] Yeah, totally. Well, I mean, maybe starting where you kind of left off, I think one of the challenges in email is historically for the past 20 years, all of the innovation in email, if you think about it, has gone into the enterprise and it's gone into really sending emails faster. So that's kind of all the email clients that you've seen have been like, let's help you get to inbox zero and send faster. And when in reality, our different take on emails, that when you think about your personal email, not your work email, the amount of emails you send is actually very little relative to the amount you receive. And so the entire experience actually needs to be rethought of from information consumption, not as a communication tool. And I think that's the big pivot with email to think about on the personal side is that it's more around information consumption delivering to you the right information at the right time. And then from there, there's an entire business to be built on how do you actually get things done for people in their lives? How do you help them along that next point in time of the journey without them having to do work? And so you're seeing a whole ecosystem of amazing companies being built on the agentic side around fulfilling different actions, but all of them need a distribution entry point of how do we start that journey and what is the personal data that we actually help achieve some of those actions upon? And so I think email is a really great place for that. And if we can build an experience that starts to make that seamless for a user they don't have to go and set up an API key or connect to a service and they could just seamlessly launch that from an experience that feels native to them like email. It could be a really compelling experience. And I think we previously built a very big business with ads at Pinterest and other companies. And so this idea of being able to show people products and services at the right time could lead to a really incredible consumer product that's also accessible to the masses.

Speaker 3:
[52:43] Ads. I was not expecting that.

Speaker 2:
[52:45] Well, that was at Pinterest.

Speaker 3:
[52:47] No, I know. But you're saying, aren't you saying like in theory, if you build a really beautiful...

Speaker 2:
[52:51] Yeah, you pay at the top of the inbox. I mean, everyone's sending you a thousand emails. And if I advertise and pay, I can get more surface area maybe.

Speaker 3:
[52:59] Also, I think people, I mean, our stance and many people's stance, I'm sure your stance is like if you get a really nicely targeted ad, it is like additive to a product experience. And so I think in the world in the future where somebody is using extra for their email and you decide to turn on ads, you could probably serve really high quality ads.

Speaker 5:
[53:24] Yeah, some of our beta users really love actually finding deals and products from brands that they actually love that often get buried and missed in their inbox today. And when we show CMOs and marketers the product, they absolutely love the idea of their products being displayed natively, not buried in a promotions tab. Their CTRs are through the floor with the existing treatment in many people's mailboxes. So if you're actually interested in a brand and you've bought something from them before, the idea of being able to see other complementary products or things from that brand in the future could be very compelling. And I think we're thinking about multiple tiers. I think there's obviously a lot of folks that may just want to not have ads and pay. And so I think there's lots of different ways to go about it. We're still early in the journey, but right now we're focusing on getting as many people to have a joyful inbox experience as possible before we start to monetize.

Speaker 2:
[54:13] What's the beachhead agentic experience? Is it just unsubscribe?

Speaker 5:
[54:19] People love coming in to clean up their inbox. It's crazy. I recommend everyone that's listening in. If you're tired of your inbox being overwhelmed, five minutes with our onboarding flow will give you a inbox designed around your life and you'll feel a lot lighter and cleaner after using Extra. But I think a lot of people-

Speaker 2:
[54:35] Is that specifically for the person that's sitting on 200,000 emails? I probably have 10 emails in my personal, and they range a lot from need to write a thoughtful response, to need to do some flow in some web app, or need to send a payment, or need to do- And I'm like, I don't know that I would hand over the keys to an agent for most of those, but I would definitely love a For You page on my promotions and updates tabs in Gmail, which are basically newsletters and sponsored stuff. And then I would love, because Gmail's done an okay job with the unsubscribe button, but it misses it a lot. But then there's some services that are just like, we're breaking the law, and you have to call us to unsubscribe from our emails. And I'm like, I'm not gonna chase this down, so I'm just gonna keep getting random, are privacy policy updated for some telecom service, usually?

Speaker 5:
[55:36] Yeah. So I think with Extra, you would get an amazing free page with the information that you want. And I think honestly, a lot of people just feel the sense of control and clarity of being able to see it in a different view of like, here's what's important, here's what I need to do today. And it's distilled down to just a few items versus this long list of things that you have to do in your inbox.

Speaker 2:
[55:57] That's cool. Is the app live on the App Store?

Speaker 5:
[56:00] It is, yeah. We went live yesterday.

Speaker 3:
[56:04] Amazing.

Speaker 2:
[56:05] Your Life's Inbox, here we go. Happening now, I'm getting it. Thank you.

Speaker 3:
[56:10] There we go.

Speaker 2:
[56:10] Very excited to try this.

Speaker 3:
[56:11] It's great to meet you.

Speaker 2:
[56:13] Well, thank you so much for coming on the show, breaking it down for us. Congratulations on launching. Thanks for having me. Excited to give it a try. Talk to you soon. Cheers. Goodbye. Up next, we have Avlok from AngelList. And I believe we might have someone and Ankur. Ankur is joining as well? Fantastic. They've both been on the show before. You know them, you love them, and they have a big announcement today. AngelList is launching USVC, a public venture fund alongside Naval Ravikant. How are you doing?

Speaker 3:
[56:42] Yo, yo. Hello.

Speaker 2:
[56:44] Feeling great. To the show.

Speaker 3:
[56:46] Big day.

Speaker 2:
[56:47] Big day. Break it down for us. What is USVC?

Speaker 7:
[56:52] All right, perfect. I'm gonna let Ankur break down what is USVC.

Speaker 3:
[56:56] We're working on getting a four up. Just give us one second.

Speaker 2:
[57:00] Okay.

Speaker 3:
[57:00] We can just hang out. Great, great, great hair. Did you just get a haircut?

Speaker 2:
[57:04] Here we go. We got everybody.

Speaker 7:
[57:06] There we go.

Speaker 3:
[57:07] Yeah, there we go.

Speaker 7:
[57:08] Yep, got a haircut just for TBPN.

Speaker 3:
[57:10] There we go. I thought so. Great to see you guys. Welcome to the show. Massive day. Ankur, it's been too long since last week. The whole weekend.

Speaker 5:
[57:21] Since I've been here. Every Wednesday afternoon, blocked out. But no, today's launch is really fun. I mean, we couldn't reveal that much last week, but really, the last month has been gearing up towards this. And I think, I think Naval mentioned it when he first started AngelList. This was such a big part of his vision of what this company could become. And it's really fun to like finally get this out there.

Speaker 3:
[57:47] Let's get right into it.

Speaker 2:
[57:48] How are you describing the product?

Speaker 3:
[57:49] Yeah, let's talk specifically about the product. This, everyone is aware of the companies that are a key part of it. But yeah, talk about kind of the decision making that went into the product, how it's different than other products in the market, all that stuff.

Speaker 2:
[58:08] Cool.

Speaker 5:
[58:09] Yeah, so the idea with USVC is we wanted to open up access to the asset class of venture. Right now, I believe it's very siloed, you need to know a lot of people. It's very, very hard for most of America to have access to the place where most of the wealth is created. So that's the goal with USVC. Can we build sort of a high quality way to index into venture as an asset class? What's unique about this structure is, there are a lot of private market ETFs. People may have seen the Destiny ETF, the Robinhood ETF, all of that. The difference with this is this is set up differently, where it's a closed and tender offer fund, which sounds like a lot of heavy words, but what it really means is, when you're investing in this, you're actually holding something very close to the underlying business. So the price of what you pay and what you redeem at is roughly equal to the price of the underlying companies. It's not driven by FOMO or markets being super excited or down. I think that is structurally very different.

Speaker 3:
[59:13] I don't know if Avlok can add anything to that. Part of the challenge with some of these other products is they can have great assets that make up the fund, but it's hard to justify if they're trading at five, six, seven times NAV. It doesn't matter how good the underlying assets are. No good investor can confidently say, I'm going to invest in this fund unless you truly think that the assets are mispriced fundamentally by five or six X.

Speaker 7:
[59:44] Yeah, that's exactly right. I think the way to think about USVC is it's meant to be a vehicle that you can think about over the long term. So rather than trying to think about, am I getting it at the right NAV? Am I getting it higher or lower than it's valued? You can just trust that when you invest in USVC, you're getting it at the right NAV and you can hold it for the very, very long term. That's why we made the decision, or that's why USVC made the decisions that it made.

Speaker 2:
[60:13] So how do investors actually onboard?

Speaker 3:
[60:18] It's very easy.

Speaker 5:
[60:19] So right now it's, yeah, it's very easy. We'll get you all to invest soon. But it's fully self-serve, usvc.com. It's been, yeah, then that's sort of been the innovation here. Like, historically these types of funds required people to be accredited investors. But now access is truly open to anyone with as little as $500.

Speaker 3:
[60:40] How are you thinking about number of bets? It's open-ended, so it sounds like uncapped, but is this the kind of thing where you want to, I feel like you want to concentrate on like 20, 30 core positions similar to a venture fund. I imagine this isn't like you want to spray and pray at Seed, but maybe you would if it's the right founder. How are you thinking about it?

Speaker 5:
[61:07] Yeah, so I can talk about portfolio construction. You'll see a lot of the names we've gone out with today are the names everyone has heard of, you know, XAI, OpenAI, Anthropic. However, long-term, I think a lot of the long-term alpha is not even necessarily in these names, so we absolutely will also start investing in a lot of seed stage companies. The idea is these are bets, it's not just about the next one year, but bets that will pay off in the next three, five, seven, 10 years. So about a third of the portfolio, the goal would be to have it skew early stage as well, just because we want to be finding these companies before they're actually discovered.

Speaker 3:
[61:49] Yeah, so similar to a platform, VC, where they're going to concentrate a lot of their capital into later stage, establish winners that are more stable, and then you can still get exposure to the early stage of super promising companies. That's very cool.

Speaker 2:
[62:06] Can you talk about the concept of direct ownership? How many layers of abstraction? I think that there's just like FUD generally among retail investors that I've talked to, that they will see a name that they're excited about, and then they will find a product that sort of proxies that name, but it's seven layers deep. It's very confusing, and they don't really know how to process it. And mostly, they're not even necessarily worried about fees or anything like that. They're more worried about like, I thought I owned SpaceX, and then it just turned out I didn't. And we've talked to Matt Grimm at Anderil about this. There's been all sorts of stuff.

Speaker 3:
[62:47] Yeah, people promoting Anderil SPVs that don't have access.

Speaker 2:
[62:50] Don't have anything. And it's just like, yeah, and I think that that messaging is important. So can you talk this through, like, how you think about ownership, what rights you actually do need, what rights you don't, how you think about delivering exposure to the end user, to the end investor?

Speaker 5:
[63:10] I'm going to let Avlok take this because AngelList as a platform has drawn the line on what they will expect as an SPV. So Avlok, why don't you take this one?

Speaker 2:
[63:18] Sure.

Speaker 7:
[63:19] Yeah. One of the unique things about USVC is that it runs on AngelList. So we're able to have it take advantage of all of the infrastructure of AngelList. And one of the things I tweeted out a few months ago was, AngelList, as an example, had banned all layered SPVs by default. For the reasons that you mentioned, in fact, when we did it, we lost revenue because of it. But that's because we didn't know who the underlying owners were, and we had no way to actually even trace it. And so we banned it. So in general, when it comes to the infrastructure that we're running at AngelList, we are always thinking first and foremost about ownership of the underlying assets, because we're running infrastructure for funds, SPVs at scale. So from that vantage point, you can think of it as USVC, and the way it thinks about it, acquiring assets, has the exact same ethos, which is you want to only look at assets where you actually know where the underlying assets are coming from, rather than these layered SPVs that have fees that are not disclosed and carry that's not disclosed. That's something that we effectively banned from AngelList a while ago.

Speaker 3:
[64:37] Makes sense. What is the pitch for founders? Why should they take USVC money? I can give reasons, but how are you positioning it?

Speaker 5:
[64:48] I think that this is the most fun part, and you're going to see this soon where you'd argue that Anthropic doesn't really need more promoters right now, but we're going to be taking some bets on companies and start-ups that have very loyal, very passionate communities, but they may be a $50 million business, a $100 million business, something in that range, and to them it allows them a very scalable way to actually let their community share in the upside. And that's going to be one of the magical things here where it's not obviously an IPO or anything, but now we can have a vehicle for people to get their communities involved in their upside. And for most founders, it's generally pretty cool to be able to say, hey, by the way, if you are a customer and you want to participate in this, you can invest in USVC.

Speaker 2:
[65:33] There's a $500 minimum. Is there a maximum?

Speaker 5:
[65:38] There's no maximum. So load up the truck.

Speaker 2:
[65:42] What happens if Elon, Sam, Dario, these guys are like, you know what, I want to just team up with the other guys. Let's throw $50 billion collectively into each other's companies.

Speaker 4:
[65:53] Through USVC.

Speaker 2:
[65:54] Through USVC. Yeah, let's just all create a karetsu. This is the Japanese way, correct?

Speaker 7:
[66:01] Yeah, yeah.

Speaker 5:
[66:03] You did strike something interesting. The nature of this fund is different, right? Effectively, it's an evergreen fund, which means we can accept kind of unlimited amount of capital, but from a deployment perspective, every time that happens, effectively, we have to kind of come up with a strategy for that. So it's a very different structure.

Speaker 2:
[66:23] Yeah. How should investors think about the time horizon? If you're going, I've talked to people that have LP'ed into VC funds and they're like, I don't even know if I'll see it before retirement. I mean, there's people who got into early rounds of SpaceX and they're like 20 years into, it looks great on paper, but I still don't have liquidity and that's a benefit, but it's also a drawback. And I think going in with eyes open is important, but how should the investor, should they think about this as 10 years journey or something that they're throwing in retirement bucket mentally or should they think about it, obviously it's not something that they're gonna be trading in and out of on a day to day basis, but what's the right mindset to go into this with?

Speaker 5:
[67:07] So I'll caveat that this is not a liquid instrument, right? Like we've been told to repeat, this is not a liquid instrument. However, the goal with this type of structure is, at our discretion, things are looking good, and this is our goal. We will have up to 5% of the fund available for redemption every single quarter. So the idea is that people, theoretically, once we get into a good rhythm, can kind of pick and choose for how long they want to be a part of this journey.

Speaker 2:
[67:36] Sure.

Speaker 5:
[67:37] Again, it's not the most liquid instrument, but from a timing perspective, people can kind of come in and come out, however, only through quarterly redemptions.

Speaker 2:
[67:48] Yeah, that makes a lot of sense.

Speaker 3:
[67:49] Very cool.

Speaker 2:
[67:49] Jordi, anything else?

Speaker 3:
[67:50] No, this is great. I'm very, very excited. This is the most AngelList product ever, I think, even though you guys are more than a decade in now, right? And yeah, I'm excited to see where this goes. I feel like, I imagine you guys are going to be spending a little more time on the East Coast with this. I guess you're already over there, Ankur.

Speaker 5:
[68:11] We're already in New York, and that works well. And we're in the West Coast, so we have good coverage.

Speaker 2:
[68:15] The website is usvc.com. There's a beautiful video of Nival Rahman.

Speaker 3:
[68:20] And I have no doubt we'll have many of your new PortCo founders on the show.

Speaker 2:
[68:25] We can't wait.

Speaker 3:
[68:26] So keep us in the loop.

Speaker 7:
[68:27] Excited for it.

Speaker 3:
[68:28] It's great to see you guys.

Speaker 2:
[68:28] Have a great rest of your day.

Speaker 7:
[68:29] Yep, God bless.

Speaker 2:
[68:30] We'll talk to you soon. This launch video is very funny because there are clips of Nival and then there are clips of founders. And the first clip sort of makes it look like Nival is talking to Steve Jobs if you just have the sound off. But what a fantastic portfolio. Go check it out at USVC. There are seven companies in the portfolio currently. XAI, Crusoe, who's been on the show, Anthropic, Sierra Technologies, Brett Taylor, Lagora, OpenAI, and Versel. You have seven different companies here represented. Go check it out at usvc.com.

Speaker 3:
[69:10] Well, before we go into the next guest segment, I'm trying to... This hasn't been posted by any super reputable sources yet, but there's a number of sources saying that Toma Bravo, actually according to Reuters, is nearing agreement to turn software firm Medallia over to creditors, which would be a $5 billion loss.

Speaker 2:
[69:38] That is rough.

Speaker 3:
[69:39] Absolutely brutal. We'll dig in here more next.

Speaker 2:
[69:42] Anyway, we have Joel Edwards from Zanskar in the waiting room. Let's bring Joel in to the TBPN UltraDome. Joel, how are you doing?

Speaker 3:
[69:51] What's going on?

Speaker 8:
[69:52] Good. Hey, guys.

Speaker 2:
[69:53] Welcome to the show.

Speaker 8:
[69:54] Thanks for having me on.

Speaker 2:
[69:55] Thanks for hopping on. And thanks for cleaning the camera. I appreciate that. I always want to look sharp on TBPN. First time on the show, please introduce yourself and the company.

Speaker 8:
[70:04] Hey, guys. Joel Edwards. I'm a geologist by training. I'm from Zanskar Geothermal. We're a group that we wildcat for new geothermal resources out west to make power.

Speaker 2:
[70:15] Okay. What's the best?

Speaker 3:
[70:17] Incredible.

Speaker 2:
[70:17] What's the best geothermal?

Speaker 3:
[70:18] Actually music to my ears.

Speaker 2:
[70:19] What's the best geothermal?

Speaker 3:
[70:20] If I got one more AI agent, I would... No, I'm kidding.

Speaker 2:
[70:26] Name every geothermal resource. Like what are we actually, we just concretize it for me. Like what are we talking about here? What is you striking gold look like?

Speaker 8:
[70:36] Striking gold. And in your head, have you guys ever been to Yellowstone National Park, first national park?

Speaker 2:
[70:40] Yeah, I think so.

Speaker 8:
[70:41] Seeing the old faithful geyser, any of those thermal features.

Speaker 2:
[70:45] Okay.

Speaker 8:
[70:45] These are the types of systems we're looking for, except for the systems we're looking for are hidden or blind. Okay. So there's nothing at the surface. There's no geyser, there's no hot springs.

Speaker 2:
[70:54] Okay.

Speaker 8:
[70:54] Nothing. But there are massive geothermal resources at depth that you can tap with a well field. You can pull that heat out of the ground and you can put it in a turbine and make electricity.

Speaker 2:
[71:05] Interesting. Yeah, take me through the geology 101. Where's the heat coming from? Why is this underground? How do we get it out? Is it just, there are just like pockets of hot air, hot water? I really dumb it down for me.

Speaker 8:
[71:24] There are pockets of hot water underground.

Speaker 2:
[71:27] Okay.

Speaker 8:
[71:28] Not hot air.

Speaker 2:
[71:28] Yeah.

Speaker 8:
[71:30] And they're fairly discreet, fairly local. But when you find them, they're incredibly energy dense. So think in your mind like volcanoes, right? That's a manifestation of a geothermal system.

Speaker 2:
[71:41] Okay.

Speaker 8:
[71:42] Think hot springs and so forth. There are parts of the world of the crust where there's just a lot of heat.

Speaker 2:
[71:48] Yeah.

Speaker 8:
[71:49] And that gets manifest in these different thermal features. And you can drill into these things and you can pull steam or hot brines out of the ground. And then you put it into a power plant, just like all thermal power plants, nuclear, coal, combined cycle gas. They all put heat into turbines, turbines spins the generator and you make electricity and so forth. Yeah.

Speaker 2:
[72:12] It's that classic meme. We discover a new way to generate power and we are going to use it to boil water and generate steam and spin a turbine so we get more electricity. And this is like, every time we discover something new, what is the business actually going to look like?

Speaker 3:
[72:26] Is this whale hunting where you're really trying to find a single site in the next 24 months and then you'll spend years building that?

Speaker 2:
[72:34] Do you want to commercialize it or do you want to sell it off to another company at that point? How far back do you wind up going here?

Speaker 8:
[72:43] Yeah, we already own an operated power plant, geothermal power plant in New Mexico. So we sell electricity to an investor on utility and then they service Albuquerque and Santa Fe and so forth. So the business is to find geothermal resources, build a power plant and then sell the electricity to a customer. So this is part of that.

Speaker 2:
[73:02] Yeah, sorry. Is there, this feels like eco-friendly? Is there pushback to geothermal energy production generally? Like people are worried about earthquakes or something? I don't know. It feels like this is a step forward.

Speaker 3:
[73:17] People are going to find a way to hate anything. So what are they going to hate about this?

Speaker 2:
[73:23] Are you in, like, are you renewable? Are you clean energy? What category are you in, do you think?

Speaker 8:
[73:30] Yeah, right now we are beloved by both sides of the political aisle.

Speaker 6:
[73:34] So you show up in DC.

Speaker 2:
[73:36] Enjoy while it lasts, buddy.

Speaker 8:
[73:38] Yeah, exactly.

Speaker 2:
[73:39] Somebody will find a way.

Speaker 8:
[73:40] Triple glaze. We're one of the few, like, bipartisan things where you show up in DC and everybody loves you, shakes your hand. It's a really exciting moment. There's attributes about geothermal that people love. It's baseload. There's no emission profile. It's domestic, so all these resources are in the US. You know, it uses US supply chains. It uses drillers. Everybody loves drillers. Not everybody, but a lot of people love drillers. And so forth. So it has a lot of those attributes that speak to both the left and the right. And then probably, you know, another attribute is the underdog attribute. Everybody loves a good underdog. Geothermal is an underdog. We're a niche, small industry. We have a lot of the same setup that oil and gas had like a hundred plus years ago, where it looks like there's a lot of resource out there. Looks like a ton of potential. It's still niche. Is it going to scale?

Speaker 3:
[74:28] Yeah. Is this one of those things like rare earths are not actually that rare? It's just hard to find, hard to get to, we don't like doing the refining nearby.

Speaker 2:
[74:40] How rare is like the kind of energy is there? Are we talking like tens of gigawatts potentially, if we were to put in like AI data center parlayence?

Speaker 8:
[74:50] Yeah. I think tens of gigawatts is near term super duper realistic, based on the tools and the tech that we have today.

Speaker 2:
[74:58] Yeah.

Speaker 8:
[74:58] So, exciting. Yeah. Obviously, there's people talking hundreds of gigawatts, terawatts. We'll see what happens. As things as industry scale, non-linear, unpredictable things happen. Costs and technology and all these things change. It's hard to predict what's going to happen 10 years from now. But basically, there's two things that drive scale for resources. It's the number of resources out there in existence, and then it's your ability to extract the resource, and that's really technology dependent. So, geothermal, where Zanskar really focuses on finding more geothermal hotspots. We have a thesis that there's a lot more out there. We've already found a bunch of sites. We've announced a few of them. There's more to come. And then there's other groups that have focused on how do you get more out of these systems? And those are in the unconventional bucket. It's like the oil and gas play in the Permian in West Texas. They came in with unconventional well fields. They drill horizontal wells. They stimulate. They get more hydrocarbons out of the rock. That process is happening in geothermal right now as well. So you have the exploration piece, finding more and then getting more out of it.

Speaker 2:
[76:01] Yeah, double clicking on the exploration piece. It sounds like AI can be used to do more computational discovery, actually interpret data. But what's the gold standard for actually obtaining the data? Like what sensor are you using to detect the potential of a geothermal discovery?

Speaker 8:
[76:28] System, what's the secret? The trick in geothermal is that there's not a single type of geologic data that tells you if a system is in existence other than just drilling a well into the thing and measuring its growth.

Speaker 2:
[76:40] So there's nothing you can do just like radar or like pull something through the ground and find it that way?

Speaker 8:
[76:47] Unfortunately, no. I wish it was that easy. In oil and gas exploration, they use seismic reflection imaging and that was kind of their silver bullet tool set to find a lot of these reservoirs. In geothermal, we use a mix of data sets to try to find these hidden systems. And that's where AI tools really flex because they can handle the hyperdementiality problem really well, better than humans. So we basically build a sandbox in which the models learn how to find systems. And building the sandbox piece is the really hard piece. You have to put the right data in there, you have to put the right learning, objective rates and so forth. That's the piece that we live in. We build the sandboxes for the models.

Speaker 2:
[77:26] Interesting. Last question for me.

Speaker 3:
[77:28] I feel like you guys are building towards the meme template, like the world, if it ran on geothermal energy, and it's like, yeah, this is like, like, you know, there's a flying car, I like it. Everything's green.

Speaker 2:
[77:43] Hypothetically, a friend of the show, Mark Benioff, he's out in Hawaii, he's big on AI. Could we put a cap on a volcano and capture all the energy out of a volcano and use that to power Salesforce AI?

Speaker 8:
[77:58] Sure, why not? A cap? What does the cap look like?

Speaker 2:
[78:01] I don't know, I'm just imagining, I'm imagining a physical, something to trap the heat that comes off of the volcano. Maybe you want to drill into the volcano and extract the lava that way, but has anyone actually, at least, theorized about capturing energy from volcanoes? They seem very powerful.

Speaker 8:
[78:19] They're pretty powerful. We have a lot of active, operational, geothermal well fields on volcanoes today.

Speaker 2:
[78:25] Really?

Speaker 8:
[78:25] So, the main island of Hawaii has a geothermal well field. They've drilled into the side of that volcano and they make electricity out of it.

Speaker 2:
[78:33] That's crazy.

Speaker 8:
[78:34] I guess if that's the cap.

Speaker 2:
[78:35] Yeah, yeah, yeah, I guess, yeah, the cap is the wrong little mini-cap.

Speaker 8:
[78:39] Yeah.

Speaker 2:
[78:39] But they are extracting energy from the volcano. That's a remarkable.

Speaker 8:
[78:43] That's right.

Speaker 2:
[78:43] Wow.

Speaker 8:
[78:44] Yeah. So, there's a lot of geothermal operations, power plants in Indonesia, Japan, Philippines, where a lot of these big volcanic systems live. In the US, we have some volcanic systems generating power in California.

Speaker 2:
[78:57] Yeah.

Speaker 8:
[78:57] And then most of the rest of the systems are generating from cracks or fracture zones in the crust. Sure. Yeah.

Speaker 2:
[79:04] That's very exciting. Did you raise money?

Speaker 8:
[79:09] We raised some money. Yeah.

Speaker 2:
[79:10] How much did you raise?

Speaker 8:
[79:10] We got some cash.

Speaker 2:
[79:11] I want to ring the gong for you. It's exciting.

Speaker 8:
[79:13] The gong is coming. I knew the gong was coming.

Speaker 2:
[79:15] Yes.

Speaker 8:
[79:16] We raised $115 million a few months ago. So good.

Speaker 2:
[79:21] Congratulations.

Speaker 8:
[79:23] Thank you.

Speaker 3:
[79:24] $40 million what? Credit facility?

Speaker 8:
[79:27] It's a credit facility, yeah.

Speaker 3:
[79:29] Massive.

Speaker 8:
[79:29] Yeah.

Speaker 2:
[79:30] It's all good.

Speaker 3:
[79:30] I'm really glad you're doing this.

Speaker 2:
[79:32] Yeah, this is amazing.

Speaker 3:
[79:32] I'm really glad you're doing this. Appreciate it. People talk about bottlenecks in AI, right? Talent, chips, energy. There's this cycle in technology live streaming right now. Right now, there's a talent bottleneck and an equipment bottleneck. But if we keep doubling from here, there will be an energy bottleneck in technology live streaming. So I'm glad you're doing this work.

Speaker 8:
[80:02] Thank you guys. Appreciate it. Have you ever been on a drill rig?

Speaker 3:
[80:05] No, I haven't.

Speaker 8:
[80:08] You guys have not lived yet. I mean, this is the American experience is to be on a drill rig.

Speaker 3:
[80:12] I know. Tell us when you're in Southern California. We would love to go live from the rig.

Speaker 2:
[80:20] Yeah.

Speaker 3:
[80:20] So anyways.

Speaker 2:
[80:21] Thanks for having me. We'll talk to you later.

Speaker 8:
[80:23] Thanks guys. Appreciate it.

Speaker 3:
[80:24] Cheers.

Speaker 2:
[80:24] Goodbye. Up next, we have the founder and CEO VAST Data. Just hit a $30 billion valuation. With a $1 billion Series F. Massive news. How are you doing? Welcome to the show.

Speaker 9:
[80:42] Good. How are you? Thanks for having me.

Speaker 2:
[80:44] We're good. Would you mind just giving us a little bit of the journey, a little bit of the background? I'd love to know all the things that went into building the company to this point, since it's such a massive milestone.

Speaker 9:
[80:59] Of course. It's been 10 years in the making. We started in 2016. We wanted to redo infrastructure. We thought AI required a new infrastructure stack. Way back then, if you remember 2016, it was the very, very early days of AI. But it was already clear that you needed fast access to a lot of data to train these massive systems. And now we needed to infer and to fine tune and for reinforced learning. And so we've been on this journey with AI throughout its various evolutions. We started from storage, building a massive...

Speaker 3:
[81:39] Was there any points on that journey where you were like, maybe we were too early. Did we pick kind of the wrong category? Or was it kind of like steady, you felt like there was steady progress being made and you had line of sight to getting to where you are now the entire time?

Speaker 9:
[81:57] We definitely did not have line of sight. When we started, if you looked at my presentation that I built for myself, the last slide had a picture of a brain on it and it asked, can we build a thinking machine? I'm not sure we still have today line of sight to doing that, but it's been our north star. And over the years, we always partnered with the organizations that were on the bleeding edge of AI. Before Generative AI, it was hedge funds and life science institutes that were doing massive analytics using GPUs. And then of course, once Generative AI hit, it became the labs and the AI clouds that became our biggest customers.

Speaker 2:
[82:40] Do you have insight into how hedge funds are scaling compute resources? I just saw, didn't Jane Street invest a billion dollars in CoreWeave? It seems like I saw another company that they funded that was doing custom silicon, and it feels like they have an incredibly advanced compute stacks that are a little bit more opaque because they maybe just have a different recruiting flow or a different public messaging flow.

Speaker 9:
[83:07] That is exactly right. In fact, Jane Street is a customer of ours both directly and through CoreWeave, and so we know them well. We play in that space now for seven or eight years. I found that before the big AI labs, the hedge funds were the ones that had the biggest GPU clusters. Yeah, they're ahead of their time and they're very secretive, so we don't know much about what's going on there.

Speaker 2:
[83:34] What about the social networks and the social platforms? I feel like ad delivery is also potentially underrated as a source of large-scale machine learning, large-scale compute clusters. We've seen Meta trained the Llama model on the Reels sized cluster that they built as sort of a bonus, but how big is that of a business for you and how do you think it comps to the hedge fund world?

Speaker 9:
[84:02] I think the hedge fund world is a lot more secretive, but I would dare to say that it's bigger in terms of size. There are very few of these Metas out there and there are a lot more hedge funds.

Speaker 2:
[84:15] Oh, interesting, okay. Well, talk about what the next phase for your company is on the back of this financing round.

Speaker 9:
[84:25] So we're trying to fill in that software infrastructure layer. Jensen gave a really good analogy of a five layer cake, power, chips, infrastructure, models and applications. We're that middle layer. We want to abstract this new hardware away from these new models and applications. We want to make it easy, make it secure for everybody to generate AI agents and use AI in production. And especially as we move from the labs into enterprises, I think it needs to be simplified. And it's always been that software infrastructure layer, what I call the operating system that took a new technology from new hardware and a killer app to making it widespread where everybody can use it. And I think we're at that moment with AI and we're trying to do our part in accelerating the adoption of AI.

Speaker 2:
[85:24] How have you been processing the CPU shortage? This idea that as agents get more and more robust, they need more CPU, they need to be fed. You got to feed the GPUs. Is that something that you're working on particularly or do you have a view on the overall just CPU shortage, which is sort of blindsided, I think, a lot of people in tech who had been following the GPU ramps, but then they're saying, oh, well, what's going on with the CPU crunch?

Speaker 9:
[85:54] I think these AI factories are bigger pieces of technology than we've ever built before. It includes CPUs, it includes DPUs, it includes GPUs. In some cases, it includes TPUs. Sorry, what are you reading?

Speaker 2:
[86:08] DPUs? Can you break that down?

Speaker 9:
[86:10] D, data processing units.

Speaker 2:
[86:11] Oh, data. Okay, yeah.

Speaker 9:
[86:12] Yes. And so, all of these chips are in high demand. We're seeing a NAND shortage that's extremely severe right now. We're seeing a memory shortage. And so, I don't think there's anything that is of abundant supply right now. The fabs need to be built out. Nobody was expecting this type of curve in the growth of AI. And I think it's going to continue for definitely a few years to come, if not many years to come. And so, the hardware vendors need to build out a lot faster than they have been.

Speaker 2:
[86:47] Yeah. Can you walk me through at a deeper level your relationship with CoreWeave and how that fits together? I think a lot of people think of CoreWeave as servicing the companies that are training and inferencing models specifically. What are you getting out of that partnership?

Speaker 9:
[87:06] So, CoreWeave has been an amazing partner for us. We're the biggest of these new AI clouds like NScale and Crusoe and Lambda. You see them around the world also as sovereign clouds. And basically, they're building this new stack and they're making it easy for end users to consume this new stack in a cloud environment. We're just the software builders. And so, we try to provide them with as much software as we can, such that they can turn that around into cloud services, whether it's a storage service or a database service or a streaming service. As we add more and more layers of this stack, those are the things that are required from those end users.

Speaker 2:
[87:56] Okay, so we were just talking to the president of Adobe. It sounds like Adobe is doing inference and they're training some models and they're doing a lot of different things. They might go to CoreWeave and then VAST Data might be powering the software underneath and they might not even necessarily have a direct relationship with you because they're getting just access to the best possible product from CoreWeave directly effectively. Is that right?

Speaker 9:
[88:17] It is right. Adobe specifically does have a direct relationship with us. Most of these larger enterprises tend to have both cloud environment that they're leveraging and on-prem and hyperscale. And what we've built, what we call a data space, basically allows them to do all three of those and have one abstraction layer that enables seamless experience.

Speaker 2:
[88:44] Interesting.

Speaker 3:
[88:47] Given your exposure to the world of hedge funds, are there a bunch more situational awareness-esque funds that have absolutely printed over the last year or so, but just done it a lot more quietly and the West Coast kind of hasn't picked up on it?

Speaker 9:
[89:05] That's a really good question. I actually met those guys from situational awareness a couple of weeks ago. They have a really interesting view into the future, and I think they're capitalizing on that view for every phase as it unrolls. I am not the right person to ask because those funds tend to not have as much infrastructure. The ones that we work with tend to be more quant-driven, situational awareness I think is just a few very smart people. They don't need that much compute power.

Speaker 2:
[89:38] Yeah, it's more macro research.

Speaker 3:
[89:40] Doing it the old-fashioned way with guts.

Speaker 2:
[89:43] Yeah, I love it.

Speaker 3:
[89:44] Conviction.

Speaker 2:
[89:45] Yeah, conversations and research and having a contrarian view. Well, congratulations on the round. Thank you so much for taking the time to come chat with us.

Speaker 3:
[89:54] Yeah, great to meet you. Appreciate you breaking it down.

Speaker 2:
[89:56] We'll talk to you soon.

Speaker 3:
[89:57] Thank you.

Speaker 2:
[89:58] Have a good one. Yeah, can you imagine situational awareness with a couple gigawatts of compute under the hood? Anything's possible at that level. What was that copy trading profile? You know the one I'm talking about where you can create the Nancy Pelosi style?

Speaker 4:
[90:17] Autopilot.

Speaker 2:
[90:18] Autopilot. Autopilot has a tracker for situational awareness.

Speaker 4:
[90:23] Every time they post about it, they use this AI image of them. It doesn't look anything like.

Speaker 2:
[90:27] No, no, no, no, but there's so few images of Leopold on the Internet that that AI image has just become like what mainstream media will pull for him because they just assume that that's actually him and it's not, but it's just very funny that it's a man who has only appeared on Dwarke Cash. Yes.

Speaker 3:
[90:44] There's no other, there's only video of him.

Speaker 2:
[90:46] SBF just posted his full holdings. If Lawyers Hadn't Fire Sold, he's up 165X on Anthropic, 22X on Solana, 8X on Robinhood, Genesis Digital. Anyway, he's taking a victory lap. We have our next guest, Darian from Gradient Ventures in the waiting room. Welcome to the show. How are you doing?

Speaker 3:
[91:08] What's going on?

Speaker 6:
[91:09] Hey, how's it going? Good to see you, Jordi.

Speaker 3:
[91:11] Good to see you. It's been a long time.

Speaker 2:
[91:12] Good to see you too.

Speaker 3:
[91:14] Where are you calling in from?

Speaker 2:
[91:15] Yeah.

Speaker 6:
[91:16] I'm in our office in Jackson Square. We just moved in here about eight months ago and we're right next to Thrive and Obvious and IVP. It's like a VC community now. We can almost live here even. There's apartments upstairs, you know?

Speaker 3:
[91:31] That's amazing.

Speaker 2:
[91:34] Since this is the first time on the show, I'd love to get some of your back story, some of your journey to venture, just a little bit of how you wound up in this particular seat in Jackson Square.

Speaker 6:
[91:45] I mean, I grew up in Silicon Valley. My father came here in the 70s, he worked in tech as well.

Speaker 2:
[91:52] What was he doing in the 70s? Like, what was tech like in the 70s?

Speaker 6:
[91:54] Semiconductors. Semiconductors.

Speaker 2:
[91:56] The true Silicon Valley.

Speaker 6:
[91:58] Yeah, true Silicon Valley, where we actually made stuff. Yeah, we actually made stuff.

Speaker 2:
[92:02] He was industrializing, now we're re-industrializing. So, he was more in the 70s, okay.

Speaker 6:
[92:08] Yeah, and then he sort of fast-tracked and coached me through everything on what startups were, venture financing, all those kinds of things. He was actually fortunate, because in business school, his closest friends were Vinod Khosla and Bob Kegel. Probably everybody knows Vinod, but Bob was one of the founders of Benchmark, and so he had been steeped in all these different kinds of communities that were very, very venture-focused and startup-focused, and the industry has evolved a lot. Then I was fortunate because I actually got an introduction to Sean Parker when I was 17, through my cousin Hadi Partovi, who I think you've had his brother on the show. He introduced me, and I visited the Facebook office and met Mark, and Mark was like, oh, you should come work here. I think they were struggling to hire people at the time because I wasn't exactly the best engineer, but it was a fun time. We built a lot of stuff, we launched news feed photos, et cetera. And then I left to go to college.

Speaker 2:
[93:02] Really quickly, is the story, is the potentially apocryphal story of everything was a single file, and you would yell, hey, I'm changing the code. Do you think that story is real at all?

Speaker 6:
[93:15] Oh, I mean, when we wanted to push to the web tier, we would just rsync the latest folder on Dustin's laptop. It was like, that was the push process. And then we introduced subversion. Actually, there was a guy that I worked with, Aaron Sigg, who was brilliant, who we put together, like, subversion, checked in files in and out. We created templating. I worked on that project, too. But when we got there, there was like tons of SQL interspersed with HTML. It was hilarious. But that is what startups are about, is it's super messy. And that's what I learned there. Although I also learned that only one in a billion are as anomalistic as Facebook. Not every startup can go that way. But also hilariously.

Speaker 3:
[93:55] Did that warp your kind of like, where I don't even know the full story.

Speaker 2:
[94:00] Did you come out and you were like, everything I touch turns to gold. And then it's like, okay, normal VC world, there's going to be failures.

Speaker 3:
[94:07] I don't know. I feel like I'll talk with founders sometime and it's their first company and it's going so well. They don't even know how anomalous it is. And sometimes they'll just be like, you have something really, really special here. And stay locked in because the odds of this happening another time in this way are very low.

Speaker 6:
[94:28] Oh, totally. I mean, I ended up starting an enterprise software company which was much more difficult. I remember meeting Aaron Levy when he was starting Box. He was in a bunk bed with Dylan in a house in Berkeley. And they asked me if I'd invest and I thought they were crazy and I didn't and that was a huge mistake. So, you know, but then there are positive stories. Like I met most of the founders of Palantir and invested personally early in Palantir. And that was ended up being an incredible company. Or, you know, when Luke Nosek was talking about SpaceX, like almost a decade ago, and I was like, you're crazy. We're going to launch rockets to the moon. Like we're not going to do that. And ultimately, you really just have to surround yourself with really smart people. Fortunately, I've always been surrounded by people much smarter than myself. And so I think that's why I'm in this chair. I ended up being a founder, invested in a lot of great companies, like First Investor and Case Text, which got bought by LexisNexis, one of the first investors in Legora, which is now on a tear. And then at Gradient, we've seeded Lambda Labs. My partner did that deal. I joined here about eight years ago with the goal of investing in AI, mainly because I didn't get crypto. And I was like, I don't understand why crypto is interesting. And so I joined the nerds at the AI fund.

Speaker 3:
[95:38] Yeah, during the 2021 era, you were Google's early stage AI fund, but you were still, as a fund overall, some of the partners were branching out and would do different stuff, obviously. But you guys now get the benefit of, we were doing all these companies almost a decade ago, or a decade ago, and now they're in core infrastructure.

Speaker 2:
[96:03] What was the enterprise software company that you built? And coming out of consumer social, why enterprise?

Speaker 6:
[96:12] Yeah, I mean, I was always obsessed with data. I actually thought that the edge that Facebook had was how clean the data was in everyone's profiles. People would just give us their birthday, what classes they were in, all this information, and it was very well organized. And this is before LLMs where you couldn't organize and massage that data very easily. Now you can. Things can be amorphous and it's easy to process.

Speaker 7:
[96:38] But before you couldn't.

Speaker 6:
[96:39] And so, I was very interested in small business data. I thought that we could compete with Dun & Bradstreet. It was a company called Radius that we scaled to pretty significant ARR. And we sold it. It was a huge, it was a long journey. It was full of crisis, full of learning. And actually, that kind of helped me with becoming a VC, mainly because I really empathize with how founders are going through a terrible time. I mean, running a company is not fun, regardless of whether it's going well or not. Like the best companies in the world, it may look like everything's going well, but the mess is just masked by growth. It's like, that's the difference between a good company and like not a good company. And in general, like founders, I really have a lot of respect for because I decided not to sign up to found another company after my own. I decided to go to the dark side and be a VC, which sometimes I say is a cop out, but you know, being a founder is really what it's, is really the most difficult job. If you can sign up for it multiple times, I mean, that's incredible. That's a sign of like just incredible resilience.

Speaker 3:
[97:38] Or a masochist. I'm so curious what you're excited about investing today. And I know it's probably like comes down to like just backing great teams because that typically works well. But we're in such an interesting time right now where it feels like all software, all enterprise software is like converging on the same kinds of simple use cases, this cat style interface to get agents to do things. Like everything is converging.

Speaker 2:
[98:14] Just the text files.

Speaker 3:
[98:14] And you guys, you did Lambda, you did a NeoCloud eight years ago. That was like the best time to be investing in a NeoCloud. And then now that it just feels like that you have SaaSpocalypse in the public market, and then a lot of early stage companies that are getting investment are still SaaS. So I'm curious, do you still believe in SaaS? What kinds of opportunities are you most excited in?

Speaker 6:
[98:44] I believe in shorting SaaS if I can. That's probably what I believe in right now. I generally think that software is...

Speaker 2:
[98:52] Bullish on puts.

Speaker 6:
[98:53] That's a good laugh.

Speaker 2:
[98:54] Bullish on puts, yeah.

Speaker 6:
[98:56] Yeah, I'm bullish on Salesforce puts is what I'm saying. But I think that the reality is that we are doing a lot of soul-searching, like a lot of seed funds. There are a lot of things that are still very interesting and investable. We just invested in a robotics company that I'm super excited about, that has a hardware component. I wouldn't touch hardware with a 10-foot pole five years ago. Now I'm very interested in it. We've invested in tools that help you manage multiple coding agents. We've invested in video editing solutions. We're investing in an AI hedge fund. We are investing in a lot of really interesting things that are outside of the software-as-a-service scope. And the real reason is just that if you want to build anything, you can in a few hours. It's just so easy, too, and I think that that is a major change, not just for software companies, but generally for the bottom 40% of work that you sit behind a desk for. Maybe the bottom 60%. And so we're spending a lot of time thinking about ways in which we can think about new areas. Now, we have the benefit of having done this before, because when we launched in 2017, right after the Transformer paper came out, there were no AI companies. There were none. And OpenAI was a non-profit, and the nonprofit didn't exist. DeepMind was still a small division within Google. So we had to go and hunt and find companies like Lambda, like RadAI, like Streamlit, like Rider, like a lot of these businesses. And so we're getting back on to what we had done before, which is scouring and doing a lot of outbound, going and meeting founders, getting to know founders, and really slowing our deployment pace until it's very clear where the value is going to accrue at the seed stage. And that, I think, is the smart thing to do right now. I think that software in general is really in jeopardy. And we've made some software investments, but we believe they have strong moats because they have network effects or they have data network effects. But in general, like 80% of software companies are really in trouble.

Speaker 2:
[100:56] Yeah. Talk about the pipeline for founders and how it might be changing. I'm sure you've been tracking, there's this crazy fall off in the number of computer science grads, and that used to be just fertile ground for it. It used to be general casting, right? Central casting for VC back founder was like Stanford CS. I don't know about Stanford specifically, but it seems like we're getting a lot less or fewer computer science grads. I'm wondering if you envision a future where you'll be pulling more physicists and mathematicians or theologians or philosophers into entrepreneurial stuff. I mean, Mark Zuckerberg did not study computer science as his primary major, right? Wasn't he a philosophy major, I think, or something?

Speaker 6:
[101:41] Psych major in psychology.

Speaker 2:
[101:43] Psych major. There's plenty of examples that say it works.

Speaker 3:
[101:46] It honestly makes a lot of sense for social media.

Speaker 2:
[101:49] Brilliant.

Speaker 6:
[101:49] Founder.

Speaker 2:
[101:51] But do you see there being a pipeline crisis? Is the contrarian move now to study computer science at a time when coding jobs are going away? Walk me through how you're processing this idea that our best and brightest aren't going to just learn to code and become computer scientists at the same rate.

Speaker 6:
[102:11] Oh, I mean, absolutely. You talk to any scale up or tech company today, the mid-level engineers are managing coding agents in English. They're not even coding. They're managing hundreds or many dozens of coding agents at once. I think at the senior level, the engineers are probably okay because we do need more code reviews and evaluations because a lot of these coding agents are spitting out bad code at volume. And that will get improved over time, but I think it is a challenge. But I do think for entry-level positions, we've told a whole generation, including my generation, that you should go to college when, like, I don't think that that's necessary, right? Like college was originally formed, especially liberal arts, was formed for the process of being creative or thinking or philosophy or things like that or writing. You know, we've told people that they can go to college and get a good job at a tech company, all those kinds of things. I think that that's kind of in jeopardy currently. My hope is that we focus more on, like, real trades, right? Like welding and plumbing and a lot of the or, you know, ceramics and pottery. Like, these are going to be, like, more respected work lines of work in the future as knowledge work just because completely replaced by AI. I don't have a great answer for you, but I generally do worry about this because I don't know if colleges should be teaching computer science to everybody. That being said, I think everyone should take a course to understand how AI works, how these LMS actually work. I think that everyone should do their best to read the Transformer paper, you know, everyone in the world because it is kind of the Magna Carta of this generation. But, you know, I do worry about this. I worry about, you know, workforce displacement and how that transition works. And if our government is even capable of helping people transition from one phase to another, or one era to another.

Speaker 2:
[104:00] Yeah, I'm just wondering, like, is the next great, like, pottery entrepreneur going to go through pottery trade school or, like, be a business major and be able to, like, marshal a billion dollars of capital to, like, build the pottery empire of the future? Like, do you go deals guy route and then tack on the trade or do you pull from the trade school? Maybe it's a moot point because you'll know it when you see it and you meet the person. But it's a fascinating world to imagine because for the longest time it was like, oh, you want to do something in pottery? Well, it's going to be a SaaS company and you're going to have to know computer science. And now it's a little bit different, right? I'm like somewhat right here.

Speaker 3:
[104:36] Do you think?

Speaker 6:
[104:37] I think actually, go ahead, Jordi.

Speaker 3:
[104:39] No, I was going to take the conversation another way. So finish the finish.

Speaker 6:
[104:43] Oh, I was just going to say that, like, imagine being someone that's incredibly good at, like, some form of ceramics. You would create your product and then AI would market it, take photos of it, would design it, buy ads for it, do the back office and do the finance for it. That's actually the future that I think we're going to end up in. Now, ceramics is kind of a weird example, but you know what I mean? Like a car mechanic, like an antique car mechanic or a welder. Those are examples of, like, how AI would help those people. So I think we'll have many, many more entrepreneurs that are not building unicorns. They're going to be building, you know, smaller lifestyle businesses.

Speaker 2:
[105:14] Yeah, I completely agree. It feels a lot like what happened when everyone got an iPhone and a YouTube account. There were a lot more creators. There was this flurry, or Shopify, same thing. You're democratizing these long-tail businesses that previously it would be like, oh, you want to, during the dot-com boom, there was like, oh, you want to sell T-shirts online? Here's a $10 million check so you can buy some servers and rack them and just have a website. Yeah, well, remember Teespring?

Speaker 6:
[105:41] Teespring was like $45 million.

Speaker 2:
[105:42] Yeah, Teespring was sort of a meta platform a little bit. But yeah, I mean, it's a good example of a lot of expensive infrastructure for doing something pretty basic. All right, Jordi, what's that?

Speaker 3:
[105:51] I was curious, do you think you'll write more checks this year than last year or vice versa? Like, have you gotten to or have you reached a point of frustration around valuations? You're like, you've been through cycles enough to kind of know when things are getting probably overheated.

Speaker 6:
[106:13] Yeah, I mean, we don't feel as though valuations are out of control at the preceding seed stage, where they are out of control are probably in the later stage. You know, like Series A, Series B, even really late stage are trading at incredible multiples. I mean, you know, I think that we did this robotics company at like sub-50, we've done, you know, this other multi-coding agent company at sub-50 as well. Like, we're pretty focused on keeping valuations below 50. And I think that capital-constrained companies are the ones that end up being very successful because they sort of figure out how to build better products and become more efficient. It's when you over-fund companies, like some of these new Neo labs that are raising billions of dollars, people like start making bad decisions when they have, when they're over-funded. And so, I think that where we play, which is not funding the next contender to Anthropic or OpenAI, the valuations are pretty favorable.

Speaker 2:
[107:05] Yeah. Jordi, anything else?

Speaker 3:
[107:09] Thoughts on solo GPs today. Is it overrated to be a solo GP?

Speaker 2:
[107:14] Yeah. And should there be a trade school for becoming a GP?

Speaker 3:
[107:18] Should we take millions of plumbers and teach them how to write checks? We need to create millions of venture capitalists.

Speaker 2:
[107:25] Everyone who's doing pottery.

Speaker 3:
[107:26] Pottery billions.

Speaker 2:
[107:27] You know, we keep going back to the pottery example. If you are a top-level ceramicist, which is the actual term, it is incredibly lucrative, incredibly prestigious.

Speaker 3:
[107:36] I didn't know you had this pottery.

Speaker 2:
[107:37] Oh, yeah. Ceramicists are real. It is an art form, and it is incredibly high-skill ceiling. Similar to venture capital.

Speaker 3:
[107:44] But not as high of a skill ceiling as venture capital. Not as high of an art form.

Speaker 2:
[107:49] Yes, yes. It is an art form. But yes, thoughts on SoloGPs.

Speaker 6:
[107:53] Yeah, I mean, I met one this morning. I've invested in a bunch of them. I think that the sub $50 million SoloGP is a great business. If you can raise the money, you can get allocation in rounds. You don't have to compete. So when you get above $50 million that it's really challenging because you're going to be ownership constrained, you're competing against someone like us. And we have we read a larger check. I think also another thing is that the SoloGPs are really effective at feeding companies to the multi-stages and to pure place seed funds like us. And so I think it's actually a fantastic place to be. But it's just going to be really rare for the SoloGPs to break out fund size well beyond that. So you have to be comfortable with being a fund of one. With no help, because your fee structure is not going to be able to support much more than that. But I am bullish on it. And especially with these AI tools, you can really diligence companies without needing more people. You can run your back office entirely without needing other people. And so I'm in general pretty excited about them. They have struggled to raise more recently. LPs are not deploying capital at the pace that they were when SoloGPs were breaking out in 2021, 2022. And so I think that you're going to see a lot of them probably go join funds. And a lot of the really good ones with good returns be able to raise their next fund.

Speaker 3:
[109:15] Do you think more of them should be thinking like, okay, I'm going to do a $30 million fund, a $30 million fund, and then a $30 million fund, because it feels like a lot tend to be like, okay, I'm going to do the $25 million fund. And then I instantly want to ramp up as much as possible. And then suddenly I have a different strategy. Suddenly you're actually competing head to head, where it feels like if you do want to break out and become a brand and a platform over time, if you have like three really high quality funds back to back and deploying them on a shorter time horizon, maybe it could be a better route.

Speaker 6:
[109:47] Yes, faster deployment cycles, smaller fund, because they're just sort of liquidity constraints across LPs. But a lot of the fund to funds I've noticed are now focused on sub $75 million funds. And so there is a market for that, excuse me. And so I would generally focus on keeping your fund size consistently small at $30 million, maybe deploy over a shorter time horizon. And then you can also get LPs to pre-commit to multiple funds, which is something I've seen people do, is that, hey, I'm going to do this every 18 months. Do you want to commit some amount every 18 months? And that actually ends up being a better story for people than raising one bigger fund. And so, I generally do think that the smaller fund on a faster cycle will yield better results, because you also have to put a lot of companies in the portfolio. Like, if you run portfolio modeling, which we do quite often here, at our fund size, it's usually 40 to 50 companies per fund in our Monte Carlo simulation that yields a 4 to 5X fund. In the smaller funds, it's really like 80 to 120. And so, you have to be writing a lot of checks and get to conviction quickly and be willing to own less. And then you can run SPVs into the follow-on rounds, which I think has been really successful for a lot of people. But the smaller the fund, the more work in my mind. Because you have to constantly be looking at deals every week. You have to be putting capital out every week into different companies in order to make the math work out.

Speaker 2:
[111:17] Yeah. Well, tell us about the latest fund at Gradient. What's the structure? How much did you raise? I want to hit the gong.

Speaker 3:
[111:24] Yeah.

Speaker 6:
[111:25] We raised 220 million.

Speaker 2:
[111:32] I think we already talked about deployment and how many.

Speaker 3:
[111:35] It's also possible we already hit the gong for you. Well, just whenever it got announced. But great to see you. Thanks for coming on. Appreciate all the insights. Let's get your new robotics bet on the show as soon as they're ready.

Speaker 2:
[111:49] Absolutely. That'd be amazing. Yeah. Have a great rest of your week. Have a great rest of your day. And we will talk to you soon.

Speaker 3:
[111:54] Great to see you.

Speaker 2:
[111:55] Goodbye.

Speaker 6:
[111:56] Thank you so much. Great to see you all.

Speaker 4:
[111:57] Later. Yay!

Speaker 2:
[112:00] Anything else going on in the timeline? There's a bunch of stuff. Tons of images. Where else do we want to go today?

Speaker 3:
[112:09] What other news?

Speaker 2:
[112:11] Oh, I wanted to get your take on this. Imagine if Codex existed in 2005. And it's this very retro. People are doing, imagine if Codex existed in 2012. And it's the Apple design cues from the early Mac OS X. And then the Windows XP aesthetic. Do you think the Windows XP aesthetic is overdue for a comeback? This is in the middle of the GPT Image 2 feed right there. This aesthetic.

Speaker 3:
[112:45] It's gotta come back.

Speaker 2:
[112:46] This in a Mountain Dew.

Speaker 3:
[112:48] It would fix you.

Speaker 2:
[112:49] This would fix me. No, I have somewhat fond memories of XP.

Speaker 3:
[112:58] Imagine playing Halo while you just look over, and this is just running there.

Speaker 2:
[113:04] I don't know.

Speaker 3:
[113:05] You're just drinking a Mountain Dew.

Speaker 2:
[113:06] For some reason, I don't know. A lot of the Windows features that were launching during this time were a little bit rough. This was when Mac was starting to take off, and these releases, Windows Vista, Windows Post XP, Post, what was it? I don't even remember the other versions, but Windows 8, I think, was one of them. They were starting to be less loved. They were starting to be a little bit more like, is it worth the upgrade? Is it a good vibe? I mean, it's not nostalgic for me yet, I guess, is what I'm saying. But there are a couple other important warnings in here. One of them, let me find it. I know you had thought about potentially putting on a bear costume and trying to defraud your car insurer. And if you in the audience were thinking about dressing up like a bear and attacking your car in order to collect an insurance payout that's up to $141,000, think again. Think again, because humans, this is in the New York Times, humans who used a bear suit to defraud car insurers are sentenced to jail. You might be thinking, I'll just throw on this bear suit and I'll attack my car and then I'll call my insurer.

Speaker 3:
[114:31] Collect a check.

Speaker 2:
[114:31] And I'll collect a check and it'll be easy, easy money. Easy money, get rich quick scheme. No.

Speaker 3:
[114:36] Three Southern California residents were sentenced to jail after masterminding a scheme in which they staged fake bear attacks on their luxury cars, then collecting more than 141,000 in insurance payouts. To carry out the attacks, the residents had a person in a bear suit, climb into the cars and use claw-like kitchen essentials to leave scratch marks. The Los Angeles residents then filed claims to defraud three different insurance companies. So I don't understand why they had to be in a bear suit. Like, were they filming? Were they filming?

Speaker 4:
[115:06] There is security footage, it's okay.

Speaker 2:
[115:08] Okay, we're gonna pull up the security footage. It's absolutely wild.

Speaker 4:
[115:14] Rolls Royce Ghost.

Speaker 2:
[115:15] Yeah, 2010 Rolls Royce Ghost. I know someone who has one of those. I don't think he's responsible for this, but they are dressing up like a bear to get into the car and rip everything and destroy it so that you can file an insurance claim.

Speaker 3:
[115:36] Hey, I'm just a bear. I'm gonna just get in this car.

Speaker 2:
[115:39] The schemes are really out of control these days. That is a wild, wild one. The California Department of Insurance began its investigation called Operation Bear Claw after an insurance company flagged a suspicious claim about a bear rifling through a 2010 Rolls Royce Ghost in Lake Arrowhead, California, where there are in fact bears. So it's not that unreasonable. The defendants claimed that the bear had damaged the interior of their Rolls Royce with photos they submitted to the insurance company showing scratched seats and doors. Video footage submitted with the claim and released by the department shows what appears to be a bear crawling around in the backseat of the Rolls Royce and swatting at the dashboard. Investigators later discovered fraudulent claims submitted to two other insurance companies that claimed a bear had damaged the same interior of two Mercedes-Benz's.

Speaker 3:
[116:28] Just scratching everything.

Speaker 2:
[116:30] That is like the most perfect scratch line. Like it's so suspicious. Like it's so clearly like I feel like a bear's claws would be way more organic and like also hopefully doing more damage.

Speaker 3:
[116:41] That looks like the weakest bear ever.

Speaker 2:
[116:43] Yeah, because it's not a bear. It's a human. After its investigation, the department concluded that the culprit was not in fact a particularly nimble bear. The defendants were arrested in November of 2020.

Speaker 3:
[116:56] My first thought is not super believable that the bear walks up to the Rolls Royce goes, opens the door and just goes around. But few weekends ago, I was hanging out at former guests of the show's house. He has goats, friend drives up in his car, parks and leaves the door open. A few minutes later, what's in the car?

Speaker 2:
[117:21] A bear.

Speaker 3:
[117:22] A goat.

Speaker 2:
[117:22] A goat.

Speaker 3:
[117:23] A goat went in the car. A goat just went and got in the car and was just like, and this was a Land Rover Defender. It was like quite a jump up.

Speaker 2:
[117:31] Goats jump.

Speaker 3:
[117:32] Goat jumps up and is just hanging around, like actually just.

Speaker 2:
[117:35] Was there damage to the Land Rover Defender?

Speaker 3:
[117:37] I don't think that, if there was, he didn't bring it up. But there were maybe some hoof marks.

Speaker 2:
[117:41] Hoof marks.

Speaker 3:
[117:42] Some hoof scratches.

Speaker 2:
[117:44] And this is all complicated insurance schemes.

Speaker 3:
[117:46] This just seems like such a wild scheme.

Speaker 2:
[117:49] Oh, here's a real bear going in a car. From Tyler. Okay. It really can open the door.

Speaker 3:
[117:56] I feel like they had to have seen this video and thought, finally.

Speaker 2:
[118:00] I thought, I feel like most cars will automatically lock the doors. You know, this wouldn't happen with those, everyone loves to hate on the flat door handles that all the electric cars have. But bears going to struggle to open a Tesla door for sure. This is, is the bear still in there or is he, he's, wow. There's, there is, there's a history of bear visitation.

Speaker 3:
[118:25] What do they know?

Speaker 2:
[118:25] Pasadena. What do they know? Where there was a woman who was on the local news and said that a bear came and, and swam in her pool and she seemed like oddly happy about it or like excited, like she sort of liked having the bear come and visit. And it felt like she wasn't exactly like building the strongest fence and maybe was sort of excited about the idea of a bear coming for a dip in the swimming pool. But people do odd things with animals. People dress up as bears. Scientists also apparently have been giving salmon cocaine. I have no idea why, but The New York Times has a post. The salmon got high on cocaine. That wasn't the craziest part. Scientists in Sweden made an unexpected discovery. I think Tyler read this piece and can spoil the ending What are they doing over there, Tyler?

Speaker 4:
[119:18] I think they tested what happens when you give the fish cocaine. I think the answer was that they swim much faster and they can swim for longer.

Speaker 2:
[119:25] Okay. That was unexpected?

Speaker 3:
[119:29] Imagine being the scientists that didn't get a grant for their research. They were working on something.

Speaker 2:
[119:35] I'm really close to breaking Alzheimer's.

Speaker 3:
[119:37] They're reading this article and they're like, wait, I was going to do Alzheimer's research and then these scientists just wanted to give hard drugs to fish.

Speaker 4:
[119:46] Nearly twice as fast.

Speaker 2:
[119:48] Nearly twice as fast. I guess that's somewhat interesting, but this does feel like something that could be one-shotted by LLM.

Speaker 3:
[119:55] There's just no way you could have just...

Speaker 2:
[119:56] You had to prove it.

Speaker 3:
[119:57] You had to prove it for science.

Speaker 1:
[119:59] I mean, I guess it's... This is relevant in the field of environmental toxicology, as much as we're joking around.

Speaker 2:
[120:03] This is a good quote. While it's unclear if swimming faster and further while under the influences harm these fish, experts say it's probably not great.

Speaker 1:
[120:12] But yeah, I mean, I guess if you're an environmental toxicologist, it is useful to have various data points on what happens with contaminants in the environment to the fish populations in specifically. And so I am willing to believe that there is good that will come out of this other than just a viral post. He wasn't trying to bring a Halloween hoax to life. He wanted to see how salmon in the wild reacted to pollution from the illegal drug. And there might in fact be pollution if the, you know, if importation goes poorly and narcotics are delivered to the water supply. That would certainly not be good. In recent years, there has been an alarming rise in the number of waterways polluted with the drug cocaine, prompting scientists to wonder how fish might be handling their highs. As it turns out, fish indeed get wired. In a study published Monday in the journal Current Biology, Dr. Brandon, his colleagues showed that coked up salmon, this is in The New York Times, coked up salmon swim. Isn't there, isn't there some account that just says like, like, like first time it's ever been printed in The New York Times and they just screenshot like words and phrases don't feel funny in that particular, when they're shown in the gray lady in print. It makes them swim faster, travel farther than their sober counterparts. The study prompts additional questions about the effects that human drug habits may be having on salmon and other freshwater fish. Well, we certainly want clean waterways.

Speaker 3:
[121:35] Speaking of things under the sea, Red Lobster brings back endless shrimp for a limited time starting April 20th. Luke Metro says, this is an EA Cause area, hostile takeover of Red Lobster, make it vegan. Make it vegan. Make it vegan.

Speaker 1:
[121:54] No, they gotta make a play to make it come back and this seems like something that customers were clamoring for, so. Have you ever been to Red Lobster?

Speaker 3:
[122:02] Nope.

Speaker 1:
[122:03] I don't think I've ever been to Red Lobster. I've done the Outback Steakhouse.

Speaker 3:
[122:06] There are things in life that I don't think I will ever do. No. And Red Lobster, I believe, is one of them. Ben, have you been to Red Lobster?

Speaker 2:
[122:14] I've been there.

Speaker 1:
[122:15] Yeah?

Speaker 3:
[122:15] You, what's your?

Speaker 2:
[122:16] They're big in Minnesota.

Speaker 3:
[122:17] Out of five times. I want to rate it. It's fine. I think they're all gone now.

Speaker 1:
[122:22] One to ten. What are you rating it?

Speaker 3:
[122:24] Like a five.

Speaker 1:
[122:24] Like a five.

Speaker 3:
[122:25] I think before it was perfect. No fives. No fives. You've got to pick a side.

Speaker 2:
[122:29] Four.

Speaker 1:
[122:30] Four.

Speaker 3:
[122:30] Four.

Speaker 2:
[122:31] Okay.

Speaker 1:
[122:31] Subpar. It's sub five, in fact. Anyway, thank you for watching. Anything else Jordi you want to run through?

Speaker 3:
[122:39] No, it has been an honor and privilege to...

Speaker 1:
[122:42] Well, this is kind of cool. ESPN launching the sports only trivia show called ESPN Jeopardy. I like this. I thought this is a really, really good idea. I can't believe it took them 50 years to come up with this concept, but apparently Joe Buck is closing on a deal to host the show. ESPN Jeopardy is expected to air on Hulu, Disney Plus and may make a run on linear TV on ABC or ESPN streaming platforms. This seems like so obvious in hindsight. I think it will be very effective. A lot of sports fans love trivia, and now you can watch it.

Speaker 3:
[123:15] We love you.

Speaker 1:
[123:16] Goodbye.

Speaker 3:
[123:17] See you tomorrow.