Meta AI Deep Dive, Jeff Huber, Sheel Mohnot, Leif Abraham, Samuel Hammond, Víctor Perez, Jai Malik, Pratap Ranade

TBPN.com is made possible by: Ramp - https://ramp.com Eight Sleep - https://eightsleep.com/tbpn Wander - https://wander.com/tbpn Public - https://public.com AdQuick - https://adquick.com Bezel - https://getbezel.com Numeral - https://www.numeralhq.com Polymarket - https://polymarket.com Follow TBPN: https://TBPN.com https://x.com/tbpn https://open.spotify.com/show/2L6WMqY3GUPCGBD0dX6p00?si=674252d53acf4231 https://podcasts.apple.com/us/podcast/technology-brothers/id1772360235 https://youtube.com/@technologybrotherspod?si=lpk53xTE9WBEcIjV (01:09) - Meta AI Deep Dive (35:09) - Jeff Huber (55:21) - Jai Malik (01:06:18) - Samuel Hammond (01:34:58) - Sheel Mohnot (02:06:42) - Víctor Perez (02:20:16) - Leif Abraham (02:36:55) - Pratap Ranade

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00John Coogan?

  You're watching TVPN. It is Tuesday, April 8th, 2025. We are live from the Temple of Technology,

• 0:07Jordi Hays?

  the Fortress of Finance, the Capital of Capital.

• 0:11John Coogan?

  And today, we are particularly in the Temple of Technology because we're doing a deep dive on Meta's open source AI strategy, talking you through the history of Llama and how they built out that LLM and what their strategy is with it. Also, all the teams behind it. There's some interesting

• 0:28Jordi Hays?

  And some of their latest moves.

• 0:29John Coogan?

  internal dynamics.

• 0:30Jordi Hays?

  Benchmarks hate this one simple trick.

• 0:34John Coogan?

  Saturate your models, apparently. That's the trick. We will be as fair and balanced as we can about it.

• 0:40Jordi Hays?

  No, we're excited about.

• 0:41John Coogan?

  There's a lot of, yeah, I mean, there's a lot to like. There's a lot to be skeptical of. And there's a lot of uncertainty. But we are going to bring on a guest, a surprise guest, Jeff Huber, who was not in the announcement post, but will be joining at 11:30 to break it all down. But let's start with AI at Meta on X. They post today is the start of a new era of natively multimodal AI innovation. Today, we're announcing the first Llama 4 models. This dropped on the weekend. Shout out to Zuck for grinding constantly. You love it. Llama 4 Scout and Llama 4 Maverick are most advanced models yet, and they're the best in the class for multimodality. Always funny when you say our most advanced model, our most,

• 1:22John Coogan?

  it's our most powerful iPhone ever, because if it was less powerful, you wouldn't release it. Like, everything you do should be superlative in the context of your own business. Anyway, it clearly did mark a step forward, and they nailed some other superlative news because they had the industry-leading context window of 10 million tokens. Of course, that means, how much, how much information can you stuff in the, into a prompt and still get reliable results out? Google took it up to 1 million tokens and that was amazing. You could upload a two hour podcast, you could upload an entire TBN episode, start asking it questions and it would be able to find things. It was pretty good, at least Gemini, I saw some demos of them picking needles out of the haystack. Hey, I changed one word in this entire book, can you go find it?

• 2:07John Coogan?

  And it would do it. Very, very cool. Bit of a debate online about what that means for RAG, Retrieval Augmented Generation, which is where you load up a bunch of documents into something that the LLM can kind of process through. And there's debate now about is, does, does large context windows, do they kill RAG? Well, we're having Jeffrey Huber on from Chroma. He's a RAG expert and has built vector databases and he will defend his position. And I think he'll have some interesting takes. They also launched Lama4 Maverick. That's a 17 billion active parameter model with 128 experts. So these are mixture of experts models. So there's a little bit of internal routing to find, you know, what, what, what neurons in the LLM

• 2:51John Coogan?

  need to be activated to go after math or writing or poetry or whatever. And then they also have image class, best in class image grounding with the ability to align user prompts with relevant visual concepts and anchor model responses to regions in the image. And so a lot of these models are going multimodal so they can deal with images and text. And that's very important because obviously we as humans can process both images and text. So if you want to make something that's human level or AGI or even close to it, you gotta be able to do everything that a human can do. And so this is where it gets controversial. They, they said we have unparalleled performance to cost ratio with a chat version scoring Elo, 1417 on LM, LM Arena.

• 3:34John Coogan?

  That's where all the chatbots battle and humans score which ones they like. Very controversial. People are saying that the results don't tell the full story. So we're going to dig into that. But first I want to go to-

• 3:45Jordi Hays?

  Who was it was saying that the vibes were way off?

• 3:49John Coogan?

  I mean, Rune was talking trash about Llama when it dropped initially. Of course, he's pretty aligned with OpenAI. I think everyone knows that at this point. But Rune was saying, you know, everyone was like, oh, OpenAI is cooked because Llama is now open source. And he tweeted just like, have you talked to that thing? Like, and it was this idea of like, who cares about like, whether or not they have the same number of parameters or it's open source. It's like, do you have a good experience actually chatting with it? And that's where the vibes are off. But there has been more commentary about the vibes. We will get into that. But first, I want to hear from Zuck himself. We have a clip from Zuckerberg explaining Meta's open source AI strategy. So we're going to play that. And then we'll use

• 4:32John Coogan?

  that as the backbone of this analysis to really kick off how he's thinking about open source AI at Meta, because it did kind of come out of left field with VR, the very closed source, clearly going towards, let's build a platform, let's lock everyone in. But took a very different tact. And to be fair, some of the open, some of the VR work is open source. But and they do want to build an ecosystem, but they're being much more aggressive about open sourcing in AI. And there's a lot of good reasons for that. Ben Thompson has broken that down. And when we've seen, Ben Thompson's made a very convincing argument for their strategy.

• 5:11Jordi Hays?

  Yeah, basically, why open sourcing this and just making it widely available for free will benefit their ad business long term, which is the real, you know, cash.

• 5:20John Coogan?

  It's a bad day to not be commoditizing your compliments.

• 5:24Jordi Hays?

  That's right.

• 5:24John Coogan?

  You always want to be commoditizing your compliments. But let's hear it from Zuck himself.

• 5:29Jordi Hays?

  Let's do it.

• 5:30Speaker 02

  Do we have a chance to play that clip? My view is that open source is a really important ingredient to having a positive AI future. And that there are all these awesome things that AI is going to bring in terms of productivity gains and creativity enhancements for people. And hopefully it'll help us with research and things like that. But I think open source is an important part of how we make sure that this benefits everyone and is accessible to everyone and isn't something that's just locked into a handful of big companies. At the same time, I actually think that open source is going to end up being the safer and more secure way to develop AI. I know that there's sort of a debate today about is open source safe?

• 6:14Speaker 02

  And I actually take the different position on it. It's not only do I think it's safe, I think it's safer than the alternative of closed development. And a realistic aim that we should hope for is that we use open source to basically develop the leading and most robust ecosystem in the world in that we have an expectation that our companies work closely with our government and allied governments on national security. So that way, our governments can persistently just be integrating the latest technology and have a, you know, whatever it is, a six-month advantage, eight-month advantage on our adversaries. And I think that that's, you know, I don't know that in this world you get a 10-year permanent advantage, but I think a kind of perpetual lead actually will make us more

• 6:57Speaker 02

  safe in one where we're leading than the model that others are advocating, which is, okay, you have a small number of closed labs, they lock down development, we probably risk being in the lead at all, like probably the other governments are getting access to it. It's, that's my view. I actually think on both these things, spreading prosperity for more evenly around the world, making it so that there can be more progress, and on safety, I think we're basically just going to find over time that open source leads. Look, there are going to be issues, right? It's like we'll have to mitigate the issues, we're going to test everything rigorously. We do, we work with governments on all this stuff, we'll continue doing that. But that's my view of kind of where the equilibrium, I think, will settle out, given what I know today.

• 7:38John Coogan?

  I think it's fascinating, looking back at that historical clip and seeing how

• 7:45John Coogan?

  Incredibly front and center AI safety was.

• 7:47Jordi Hays?

  Yeah.

• 7:48John Coogan?

  And then you look at the Llama4 announcement today and no one's saying, oh, well, like Llama4 is like not safe or we should be having a safety debate. It's all about the benchmarks. It's like, it's not superhuman enough. It's not aggressive enough. And, and so we've kind of blown past that. But again, I do think there is a good AI safety argument to be had about open source. And I think it's played out kind of like he said, like it's kind of good that, you know, at the very least, it's like when you open source something like Llama, it, it very easily can get in the hands of us. Let's, let's not go to paper clipping, but let's just go to, uh, you know, fraud on your grandma. Right. Sending spam texts that are LLM generated, so they're a little bit more convincing. We haven't really seen an epidemic of that yet.

• 8:33John Coogan?

  And there's been just as much economic force towards preventing that type of spam and scams that the open source, like the net impact, I think has still been positive. You get, you get plenty of, plenty of small companies who, or kids who, yeah, I have a GPU rig that I used to game on. That was my Christmas present and now I can fine tune Llama and make some app or deploy it really cheaply. And that's a net benefit and the scammers aren't really getting away. Like I keep going back to the election and it's very hard to make the argument that AI swung the election.

• 9:10Jordi Hays?

  Yeah.

• 9:11John Coogan?

  Right? Even though, I don't know, both parties would probably have used AI.

• 9:14Jordi Hays?

  Zuck has been accused, Zuck has been accused of doing that, you know, or being

• 9:18John Coogan?

  With the 2016 election, right?

• 9:19Jordi Hays?

  In that.

• 9:20John Coogan?

  Yeah. But, but it's much harder to make, which is weird.

• 9:23Jordi Hays?

  I just think it's funny. I, I, I, I love that he takes the position generally that he's like, you know, it would just be, I really think we should avoid having like a few big companies control this like very important technology.

• 9:34John Coogan?

  Except in social networking.

• 9:35Jordi Hays?

  Meanwhile, Meta controlling, you know, 20% of the US digital ad spend, you know, not even including, you know, social networking, which I'm sure is significantly higher.

• 9:46John Coogan?

  And also just this idea of like, if you want to put something on the internet increasingly. Like this idea of like the open internet where everyone has a website and they all have their own style guides and it's all like this chaotic, you know, like what do they call it? Web 1.0, web 2.0 or something? I don't know. The that independent web has really like disappeared because of Meta's like power over it. But but you know, I don't know, it still makes sense and I think it makes more sense from a strategy thing. He's kind of making some arguments that sound good in theory, but maybe aren't fully motivated. They're more motivated by just his business needs.

• 10:21Jordi Hays?

  He's an absolute dog. He wants to win.

• 10:23John Coogan?

  And I think their values are real.

• 10:24Jordi Hays?

  Yeah.

• 10:24John Coogan?

  And I think they're valid.

• 10:25Jordi Hays?

  No, there's, there's two things that can happen simultaneously. One, open sourcing Llama and allowing anybody to build on top of it and do what they want with it is, is a net benefit for the world.

• 10:38John Coogan?

  Yep.

• 10:39Jordi Hays?

  It also very clearly is highly strategic and he's doing it because he wants Meta to be a much bigger company in 10 years from today than it is, you know.

• 10:46John Coogan?

  Yeah, yeah, no, 100%. But if you are trying to look like Mark Zuckerberg, you gotta get on bezel. Go to getbezel.com. Shop over 24,500 luxury watches, fully authenticated in-house by bezel's team of experts. You know he's got a Cubitus, he's got a Patek, he's got a Pijorn.

• 11:02Jordi Hays?

  Pretty much.

• 11:03John Coogan?

  He's got everything. He's got it all. And now's your chance to catch up to Zuck by going big on bezel. So download the app too. The bezel app is fantastic. Highly recommend it. You can scroll, filter, find what you like, create a little wish list and then pretty soon start knocking those down as you send wires off to get holy trinity watches.

• 11:24Jordi Hays?

  Yeah, I want to, I'm gonna have, we're gonna have Quaid on again this week to talk about the watch industry's reaction to the tariffs.

• 11:32John Coogan?

  Yep.

• 11:32Jordi Hays?

  Which has not been, you know, Switzerland specifically has been targeted.

• 11:37John Coogan?

  But moving on to the reaction to Llama 4, the headlines were generally glowing. Two mediums, two new medium sized mixture of expert open models that score well and a third, 2 trillion parameter behemoth is promised. So they didn't launch that yet. They're still training it. That should be the largest open model ever released. And again, openness is spectrum here. There's open weights where you can fine tune it. There's fully open source where you can actually see the code and all the changes. There's open data. You can have the data, open source that they trained it on. And also, this is open source, but they, all the big tech companies are doing this funny thing where they're like.

• 12:17John Coogan?

  Hey, anyone can use this, really anyone, except for if you have over a billion, over like $500 billion in revenue or something like that. And it's basically just to exclude the other big tech companies.

• 12:27Jordi Hays?

  Yeah.

• 12:27John Coogan?

  And they don't care. They said it like, right, whatever Snapchat's revenue is or user base is. They're like, if they have 10% less, you can use it.

• 12:36Jordi Hays?

  Yeah.

• 12:36John Coogan?

  Which is like, honestly amazing for a lot of entrepreneurs. So it's cool, but it's very funny that they're like, you know, I would not actually gonna help my competitors.

• 12:43Jordi Hays?

  Evan might kick the bots off and be like, oh, fair game now.

• 12:47John Coogan?

  But it's funny because like, the, the history of open source has been like MIT license. You can even just take this code and just go and sell it immediately. And if you can get someone to buy it, you can make money off of it. Now, they are in, there, there's a whole variety of open source licenses. But anyway, Meta just got a huge jump. This is from LM Arena, from 1268 to 1417. And that puts them allegedly higher than OpenAI, higher than XAI. But it was hotly debated, as we'll get into. And so there were a couple of takeaways here. Llama4 released on Saturday. The, the blog post, so they, so they didn't launch like the paper.

• 13:31John Coogan?

  And there's nowhere near the level of detail from the Lama 3 paper in terms of transparency. And so that's another aspect of open source is sometimes people want to know, hey, what other algorithmic tricks did you come up with? What are you, what are you coming up with? It was interesting, one of the, one of the most fascinating leaks, I guess you could call it, from the Lama open sourcing process was that they had a bit of code in there that was just called, "Do not blow up the power station," or "Do not blow up the data center." And basically what they realized was that when they're training Lama, they're running, they're pulling so much energy from the grid that if, if they finish a training run and then the power consumption drops, it will, it will do something with the power substation and the transformers.

• 14:15John Coogan?

  And the, the data center literally might explode or something like that. So, so basically what they did was they just said, hey, when we stop training and we're not doing all the matrix multiplication and all the math that you need to do to crunch all these numbers down to create the weights, just do random math. Just, just, just keep doing random math because that will, at least the energy will be the same. Obviously, it's not efficient, but we need to like wind down the energy consumption slowly. So, very funny.

• 14:38Jordi Hays?

  Yeah, it's like sprinting, right?

• 14:39John Coogan?

  Yeah, yeah, yeah.

• 14:39Jordi Hays?

  If you're sprinting and then you try to just halt completely.

• 14:43John Coogan?

  You're gonna break your knees.

• 14:43Jordi Hays?

  You wanna slow down, you know, slower.

• 14:46John Coogan?

  And so the smallest scout model is 109 billion parameters. And this cannot run on consumer grade GPUs. And there was this funny interaction between, oh, what's his name over at Google? He's an absolute legend. I forget. Anyway, one of the top, Jeff Dean, Jeff Dean, he's like the greatest programmer in history. And someone was like, oh, this is such a bummer. I can't run the new llama on my consumer grade GPUs. And he was like, what are you talking about? Like, of course you can't. And somebody was like, oh, like, like, Google, like GPU expert, AI expert, like discovers what it means to actually have a consumer GPU.

• 15:21Jordi Hays?

  Yeah.

• 15:21John Coogan?

  Because whoever this was clearly was talking about like an Nvidia gaming PC. But I'm sure Jeff Dean's like consumer rig is probably like $50,000. Because they're just like, here, Jeff, like, why don't you just take the best thing of everything? Even when you're training at home, you know, you want to be able to run.

• 15:36Jordi Hays?

  Costs as much as a house.

• 15:37John Coogan?

  Yeah, exactly, exactly. And so there's also this, this question about the claimed context token window. They're claiming 10 million and it's certainly far above what the real context is. But it might not actually be 10 million. We're going to get into this with Jeff. But there's this question of when you zoom out the context window and you get so big, just like a human. If you're walking around a library, you're not, you might have access to every book in the library, but you can't actually recall all of that. So LLM seem to be, there's this debate right now in this take that the really, really high context windows. Maybe you get fuzzier as you get lighter, just like a human. And so that's where something like RAG and search and deep research from OpenAI.

• 16:22John Coogan?

  Like it is a big context model, but really what it's doing is it's like going searching a webpage that's maybe 10,000 tokens. Compressing that down, finding the key insight, quoting that in. And so when you get a deep research report, it's not really that it's stuffing all of it into one context window. It's that it's doing this thing iteratively like an agent.

• 16:39Jordi Hays?

  Yep.

• 16:40John Coogan?

  And then there was.

• 16:41Jordi Hays?

  Agentic search.

• 16:42John Coogan?

  And then this is where it gets controversial. So LM Arena, we talked about how they're scoring very high. But they used a special experimental version for LM Arena, which caused the good score. That's not the version that was released. This discrepancy forced LM Arena to respond by releasing the full data set for evals. And it does very poorly on independent benchmarks like AI dur. And so now there's so many different benchmarks out there that you can, you can kind of game one or a few or the top ones. But if someone comes up and says like, oh, well, you're actually doing worse on Arc AGI. It's like, well, you didn't get a chance to fine tune on that. So, so if you underperform like a truly breakthrough genius LLM should just be better at every benchmark, even my benchmark of tell me a joke.

• 17:25John Coogan?

  And so, you know, it's tricky. There's this game of like, we gotta, we gotta rank on the important benchmarks. But now they're such a long tail that you can't really, can't really optimize for all of them. And then there's an unsubstantiated post on Chinese, Chinese social media that we covered on Monday that claims the company leadership pushed for training, for, for training more aggressively to meet Zuck's goals. But this was categorically denied by Meta leadership and we should go into what Ahmad over at Meta is saying.

• 17:55Jordi Hays?

  He says, "We're glad to start seeing Llama 4 in all your hands. We're already hearing lots of great results people are getting with these models. That said, we're also hearing some reports of mixed quality across different services since we dropped the models as soon as they were ready. We expect it'll take several days for all the public implementations to get dialed in. We'll keep working through our bug fixes and onboarding partners. We've also heard claims that we trained on test sets. That's simply not true and we would never do that. Our best understanding is that the variable quality people are seeing is due to needing to stabilize implementations. We believe the Llama 4 models are a significant advancement and we're looking forward to working with the community to unlock their value."

• 18:34John Coogan?

  Yeah. I think what's happening here is that we are hitting the pre-training plateau as we've heard before. We talked to Dwar Kesh about this and, and, and that's like underwhelming. And then at the same time, Everyone has such strong opinions about all the foundation labs. Like you, you meet someone, it's like, oh, you're a, you're an anthropic guy. Oh, you're an XAI guy. Oh, you're, you're, you're a meta bull or whatever. And, uh, and so there's a lot of emotions that go into these things. At the bottom, I, I think the correct frame of mind to evaluate Lama four in is, is what will people do with this that they couldn't do with a closed source model? And so when, when, uh, when Google open sourced their dream studio, uh, there were, there were people that were able to fine tune that and create those magic avatars, which are

• 19:18John Coogan?

  now kind of the Studio Gibli's, um, where you could upload a couple of photos, get a, get a custom avatar of you looking like Superman or something. And so what's cool about Lama four is that because it's open weights, it's easy to fine tune. And also it's not from deep seek, so it's a little bit less politically controversial, but there's still a lot that you can do with it. It doesn't run on consumer GPUs now. I'm sure that won't be a problem. I'm sure that people are going to figure out how to distill this and do a bunch of different things. And, and when we go through the history of Lama, we will talk about, uh, some of the ecosystem that has actually cropped up and is exactly what Zuckerberg was describing in that.

• 19:55Jordi Hays?

  You want to hear a joke from Meta AI?

• 19:58John Coogan?

  Please.

• 19:58Jordi Hays?

  Tell me a joke like Theo Von about Sam Altman. Sam Altman is the ultimate tech bro. He's out here trying to make AI do all the work so we can just sit around and think about how great we are. I mean, I'm pretty sure his five year plan is to invent a robot that makes avocado toast and brings it to him while he's meditating on a beach somewhere. Cause that's the real dream, right?

• 20:21John Coogan?

  Wow. AGI has been achieved internally, externally, everywhere. Hang it up, folks. Uh, quit your job.

• 20:34Jordi Hays?

  That's brutal. And to be clear, I'm not actually, it's not clear that Lama, I don't think Lama four is actually running on meta.ai yet.

• 20:42John Coogan?

  I think you're probably using Lama three.

• 20:44Jordi Hays?

  But.

• 20:45John Coogan?

  These rollouts are always really staged and, uh, and, and in fact, uh,

• 20:49Jordi Hays?

  Was that the style of? Theo Von?

• 20:51John Coogan?

  I thought I was listening to Theo Von.

• 20:54Jordi Hays?

  Yeah.

• 20:54John Coogan?

  Could have fooled me. That is remarkable. Was that a Theo Von quote? It's remarkable how spot on that is.

• 21:01Jordi Hays?

  Just the avocado making, making an avocado joke is like very 2020.

• 21:06John Coogan?

  2012 coded.

• 21:07Jordi Hays?

  Yeah, like 20, 2018.

• 21:09John Coogan?

  Hipsters are quirky. Yeah, okay, we're past that. Anyway, so there are mixed quality reports across different services using Llama 4 and implementations should stabilize in a few days. This is kind of common when they roll out these big new models. They gotta figure out how to run them on, on, on all the hardware, get them into the data center, swap things over. Like, people say, oh yeah, switching an LLM, it is just one line of code. But there are more things to it, especially on the performance side. We've seen this with Studio Ghibli, like the GPUs melting, which I think we all believe is real. Because how many times, I mean, this happened to be a bunch where I've said, hey, make this, make this image Studio Ghibli. And it's just like, hey, I stopped. And it's like, what? No, like Instagram filters don't just stop halfway.

• 21:53Jordi Hays?

  No, we talked, we talked about this with Aiden.

• 21:55John Coogan?

  Yeah.

• 21:55Jordi Hays?

  Or was it Aiden or no, Swix?

• 21:57John Coogan?

  Yeah.

• 21:57Jordi Hays?

  Swix was saying that the, the models are already showing signs of needing rest, right?

• 22:04John Coogan?

  Yep, yep, yep.

• 22:05Jordi Hays?

  Anyways.

• 22:06John Coogan?

  It's crazy. And so there's, there's a bunch more going on. Let's move through this. So, so there's, there's a couple of themes that are sticking out in the discussion about Meta's Llama 4 performance. The big one is, is just a general disappointment from the AI community, I think, based around the, how much horsepower was going into this. So the claim was that they trained on 100,000 H100 GPUs. Of course, Zuck and Jensen have done the famous Jersey swap. He's one of the biggest Nvidia customers. He can get the best, he's not under any import restrictions. There's really nothing stopping him. And most importantly, potentially is the fact that

• 22:51John Coogan?

  Meta can really, really go full send on the CapEx here because

• 22:54Jordi Hays?

  Yep.

• 22:54John Coogan?

  Zuck knows that, hey, if, if Lama doesn't go anywhere, we never, we like, LLMs cap out, it's not important. Yeah, we're going to use those 100K H100s to train the Reels algorithm better.

• 23:06Jordi Hays?

  Yeah.

• 23:06John Coogan?

  Or, or the new thing. That was the whole thesis behind.

• 23:09Jordi Hays?

  Yeah, or at the very least, do our own Ghibli style.

• 23:12John Coogan?

  Yeah, yeah, yeah. I was thinking about this. Like, if I wanted to, if I was like the PM, if I was like the PM at Instagram, I would immediately implement the Studio Ghibli filter and just send every Instagram user a Ghibli of their most popular post or of their profile picture. Just pre-render it all, just batch them all and then send them and just say, hey, do you want to try the new filter? And everyone would be like, this is amazing. It would be this amazing viral moment. They could definitely do that. But it would be extremely expensive from a, from a inference perspective, but they could probably afford it and it would be cool and delightful. And I, I think they should do it. Anyway, so despite having fewer resources, DeepSeek claims to have achieved better performance with models like DeepSeek V3, and there are some benchmarks where DeepSeek is still outperforming Lama 4,

• 23:56John Coogan?

  which you hate to see if you're duking it out in the open source world. Yan Lequn stated that FAIR is working on the next generation of AI architectures beyond autoregressive LLMs. And so this is a debate that we've been hearing for a while. Like, we probably, scale is important and we need to continue to scale. And we want to do big data center build outs, but we also need new algorithms on top of those. The poster suggests that Meta's leading edge is diminishing and that smaller open source models have been surpassed by Quen with Quen 3 is coming. And then there's another debate about Meta's Lama 4 fell short. Scout and Maverick have been released but are disappointing. Meta's AI research lead has allegedly been fired.

• 24:37John Coogan?

  The models use a mixture of experts set up with a small expert size of 17 billion parameters, which is considered small nowadays. Despite having extensive GPU resources and data, Meta's efforts are not yielding successful models. And so I think that there's a debate about, George Hots was talking about this when GPT-4 launched. It was a mixture of experts model and a lot of that is defined by

• 24:56Jordi Hays?

  Yep.

• 24:57John Coogan?

  the actual structure of the chips and the interconnect and what we talked about with Light. Light wave?

• 25:01Jordi Hays?

  Light matter?

• 25:02John Coogan?

  Light matter?

• 25:03Jordi Hays?

  Yeah.

• 25:03John Coogan?

  Just this idea that, yes, you can have 100,000 GPUs, but if they're not networked together really, really well, you're maybe their memory constrained. There's all these different parameters that can constrain you. And so you wind up having to fractionalize your, your, your, your LLM. And that can be fine if, if 17 billion is enough and, and, and, and you can route and there aren't any problems that require multiple experts or bigger experts. But clearly in this scenario, a lot of people are disappointed. And so someone said, they left me really disappointed. You hate to be disappointed.

• 25:36Jordi Hays?

  Yeah, I mean, what's obvious is-

• 25:37John Coogan?

  Free magical intelligence that's here to achieve to meter. Show some, show some-

• 25:41Jordi Hays?

  Respect.

• 25:41John Coogan?

  Show some respect for Zuck giving you something that cost a billion dollars for free.

• 25:45Jordi Hays?

  Something that, that-

• 25:46John Coogan?

  You like it?

• 25:47Jordi Hays?

  Three years ago would have been groundbreaking.

• 25:49John Coogan?

  Yeah.

• 25:49Jordi Hays?

  No, but, but the expectations are extreme.

• 25:51John Coogan?

  Yep.

• 25:52Jordi Hays?

  Uh, they're, they're spending, you know, almost as much as anybody on this.

• 25:56John Coogan?

  Yep.

• 25:57Jordi Hays?

  And ultimately it's becoming clear that ability to spend is not all that, you know, it takes finesse too.

• 26:04John Coogan?

  Yep.

• 26:05Jordi Hays?

  And so it's like, okay, Meta can-

• 26:07John Coogan?

  Yeah. And so people are, people are joking. I'd like to see Zuckerberg try to replace mid-level engineers with Llama 4. And one commenter joked that perhaps Zuckerberg replaced engineers with Llama 3, leading to Llama 4 not turning out well. Brutal.

• 26:22Jordi Hays?

  Ouch.

• 26:22John Coogan?

  Another commenter suggests he might use, he might need to use Gemini 2.5 Pro instead. I love that people are just like absolutely trash talking with the most like industry jargon here. Like, oh man, like, this is more of like, like you're, you're Llama 4 coded, not Gemini 2.5 Pro coded. It's like, guys, having too much fun. Anyway.

• 26:43Jordi Hays?

  Yeah, this one was even more brutal.

• 26:46Jordi Hays?

  Somebody's saying that, calling it a complete joke and expressing doubt that it can replace even a well-trained high school student.

• 26:53John Coogan?

  Oh, yeah, yeah. I mean, in general, I think my takeaway is like, you know, Lama 4 might be underperforming, but you can't sleep on AI even for a minute. There's a new model every day. You can't sleep on AI innovation, but you can sleep on an 8-sleep. So go to 8sleep.com, nights that fuel your best days. Turn any bed into the ultimate sleeping experience. That's right. Use code TBPN. So this was the debate that was popping up from Sean, who came on the show last week. He says unpopular opinion right now, but Lama's 4 10 million token window will finally actually end the long context versus RAG debate. That's Retrieval Augmented Generation, but not the way that other guy is thinking. And so this was a

• 27:35John Coogan?

  very like, I'm gonna, we're gonna talk to Jeff about this because I was like, hey, you gotta come on the show just to explain this. But I think what he's saying is that is that huge context window is not a perfect substitute for RAG and RAG still might have a place in the future of AI agent development, AI implementation. But I'm excited to dig into this because I didn't fully understand this post and I want to know more here. Anyway, let's move on to another LLM eval that happened with Stagehand. The results are fascinating. What LLMs can actually do consists, can actually parse deeply nested structured data like a DOM, Document Object Model, an A11 Y Tree, which is like parsing a website, basically. And

• 28:17John Coogan?

  so this founder benchmarked Lama 4 against other models and found that Lama 4 came in maybe eighth, below GPT-4O Mini, below Claude 3.5 Sonnet and below DeepSeek V3 and then Gemini 1.5 Pro, 2.0 Flash are all higher. And so at least from his benchmarking, he thinks that, you know, given that this is the latest and greatest and newest product from Meta, it's underperforming stuff that's been on the market for a couple of months. So not the best information. Then there's actually an example here that from Vic that I thought was pretty good. This is the clearest evidence that no one should take these rankings seriously. In this example, it's super yappy.

• 29:03John Coogan?

  And factually inaccurate, and yet the user voted for Lama four, the rest aren't any better. So this is what, this is what a LLM arena actually, or LM arena, like, interface actually looks like. So there's a prompt, and then you see both of these. You don't see the names of the models, I believe. But you have to pick which one you like more. And so the question was, what is the latest season of Fortnite? And Claude 3.5 Sonnet said Fortnite, Chapter 5, Season 2, titled Myths and Mortals, is the current season. It begins on March 8th, 2024, and features Greek mythology theme with characters and locations inspired by Greek gods and legends. Then Lama 4 Maverick Experimental says, "A super timely question. Fortnite seasons are very short-lived, and they last about 12, and it's like yapping, yapping, yapping." And then it gets it wrong.

• 29:48John Coogan?

  It says, "The current season is Fortnite, Season OG, also known as Chapter 4, Season 6", which I believe is like before Chapter 5, obviously. I don't know enough about Fortnite to fact check this, but it seems like it's wrong. And then, and then there's a bunch of emojis. And so there's a debate from LM Arena, and they go on to write, "We've seen questions from the community about the latest release of Lama 4 on Arena. To ensure full transparency, we're releasing 2,000 head-to-head battle results for public review, so anyone can go see these and decide for themselves, hey, did, did the folks at LM Arena get this wrong? Or are they, are they happy? Early analysis shows style and model response tone was an important factor demonstrated in style control ranking,

• 30:30John Coogan?

  and we are conducting a deeper analysis to enjoy, to understand more emoji control, because some people might just be voting, "Oh, I like the emojis", even though that's kind of taking you away from the facts. Or they might just be like, "Hey, I like a more verbose answer."

• 30:44Jordi Hays?

  Super short answer.

• 30:45John Coogan?

  Yeah, exactly, exactly. So there's all these like human biases that are coming in. And at this point, we are in this like qualitative, you know, like the OpenAI guys say, just talk to the model. Figure out the vibe of the model. People seem to like Claude Sonnet and just the vibe of that, of that model. And so there's still more debate over company leadership potentially blending test sets from various benchmarks during the post-training process. Meta has denied that allegation, but there is a lot of debate raging. And Ethan Malik says, "The Lama 4 model that won LM Arena is different than the released version. I have been comparing the answers from Arena to the released model. They aren't close." And so what he did was he, was he looked at

• 31:29John Coogan?

  The the actual results that were posted on L M Arena and then same query on the Lama four model that was released and this is evidence that they that they went to L M Arena with a separate model.

• 31:40Jordi Hays?

  Yeah.

• 31:40John Coogan?

  Which is controversial.

• 31:42Jordi Hays?

  It's not what you want to be doing. I mean, it doesn't inspire trust.

• 31:45John Coogan?

  Approach cotton.

• 31:47Jordi Hays?

  Yeah.

• 31:47John Coogan?

  But you got to do what you can when you're marketing these things.

• 31:50Jordi Hays?

  Jeff thinks about all this.

• 31:52John Coogan?

  And so Ahmad says, seems like there was a lot of truth in this leak from two months ago. Lama four is beyond disappointing. It's a model that shouldn't have been released. And this is from probably blind or something. Meta Meta Gen AI Oregon panic mode. It started with deep C B three, which rendered Lama four already behind in benchmarks. Adding insult to injury was unknown Chinese company.

• 32:13Jordi Hays?

  Yeah, I remember this post.

• 32:14John Coogan?

  Training budget. And and there was that meme of of Iron Man being like, they built this with screws in a cave.

• 32:23John Coogan?

  Like, you have a trillion dollar budget. But if you want to control your budget, you got to go over to ramp.com. Time is money. Save both.

• 32:29Jordi Hays?

  Save both.

• 32:30John Coogan?

  Corporate cards, bill payments, accounting and a whole lot more all in one place. And so Jeff is going to be joining in just a minute. We will run through some of the timeline and break down what happened with Lama and the development here. The the most interesting thing that I found when I was digging through the history of Lama was the company's notable foray into large language models was an academic tool called Galactica, which most people hadn't heard about. That actually backfired months earlier. The demo was pulled after only three days amid criticisms that it confidently generated false information. And if you remember G P T three, like it was, you get some wild hallucinations out of that thing. And so Meta's leadership was cautious at that point as generative AI fever swept tech.

• 33:14John Coogan?

  And once chat G P T came out and it became like customers want this, then they started to push forward. And so there was a team at Meta's fair research lab in Paris. I believe this is the one the on lacoon is involved in. They were they were hard at work on large language model they believe could compete. Lama one was the fruit of that effort, a set of models ranging from seven billion to sixty five billion parameters, trained on a rich diet of text, which of course they have because they have every piece of text. Not only do they have everything in the Facebook ecosystem, but they also scrape every link that's shared to Facebook, which is every link ever. And so they have the entire internet scraped.

• 33:54John Coogan?

  Unlike OpenAI's headline grabbing GPT-3, Llama wasn't offered as a public chatbot or API. Instead, its initial release Meta, in its initial release, Meta made the model's weights available on a case-by-case basis to academic researchers. So you would just email them and say like, "Hey, I'm at Stanford. Can I have the weights?" And they'd say, "Sure." And then, of course, that leaked immediately, which is awesome. So it was a non-commercial license. So they would send you the weights, and then you could mess around with it and test. But then, of course, someone, it was quote-unquote "open research," not open source, so you couldn't build a company on top of it. It was more like a research paper with some downloadable code. But this leaked onto the internet, and then developers everywhere had their hands on a

• 34:34John Coogan?

  GPT-class model in raw form. And so that spawned these fine-tuned models, Alpaca and Vicuna, which are derivatives of Llama. I think they're related mammals. And so then, people started fine-tuning with instructions and getting it more into a chat mode. And then, Llama became a product that had close to a chat GPT-like experience. And so I'm excited to talk to Jeff about this. I'm not sure if he's in the temple yet, but let's bring him in.

• 35:05John Coogan?

  Jeff, how you doing?

• 35:06Speaker 03

  I'm good.

• 35:07John Coogan?

  It's great. How have you been following? Well, first, welcome to the stream. Can you do a little introduction? But then I want to hear your reaction to the Llama 4 news, how you're processing, and what it means for your business.

• 35:19Speaker 03

  For sure, yeah. I'm Jeff Huber, the co-founder of Chroma. I'm working on retrieval for AI and broadly working with developers kind of across the ecosystem to build production systems with AI. A lot of it is focused on business applications, good old-fashioned business process automation. And so always super excited to see new open-source model drops.

• 35:39John Coogan?

  Can we go to this post from Sean? He says, "Unpopular opinion right now, but Llama's 4 10-million-token window will finally actually end the long context versus rag debate, but not in the way that other guy is thinking." What does he mean by that?

• 35:57Speaker 03

  Yeah, yeah, for sure. I think, you know... Silicon Valley has a tendency to be sort of extremely intellectually shallow. This is both a strength and a weakness of the Valley, to be clear. And in our view, like AI is not this like Deus Ex Machina, this like tech machine god, you know, where all of the information of all time is always going to be in the weights of this model. You know, this is really just a new form of computing. And so in the same way that we have a memory hierarchy in classic computers, right? We have the CPU, RAM, disk and network. We are also going to have a similar memory hierarchy in language models. And again, it already exists today. We have the actual sort of transformer attention heads. We have the context window. We have the retrieval system and tool use.

• 36:41Speaker 03

  And these things have different trade offs, right? You think about kind of access, speed, capacity and cost. There are trade offs to all of these things.

• 36:50Speaker 03

  You know, I think like, you know, saying something is dead, like plays pretty well on Twitter. I've actually gotten myself into some trouble where I, some people were allegedly shitposting and not actually sort of sincere posting about this. And I didn't know, right? Because they're hard to tell, like what's a shitpost and what isn't.

• 37:07John Coogan?

  Of course.

• 37:07Speaker 03

  But you know, the bait, the bait is strong on Twitter. And so what Sean is saying is actually that like, we've all been, there's a certain class of people who are like, long context is all you need. Again, these people are probably like 21 years old. That's fine, we love them. But they just haven't seen how like, uh, real systems depend on trade offs between speed, cost and accuracy. And like 10 million tokens is not a panacea. You need to keep information outside of the context window. You need to give developers and programmers control over what information's inside the context window. You know, even these like needle in the haystack tests, like are not actually that representative of like real world utility and reliability of long context windows. You know, they mentioned in the training for Lama 4, they didn't even have passages that are longer than, I think 250,000 tokens.

• 37:52Speaker 03

  And so anything past 250,000 is just synthetic data, it's just made up. And so what Sean is saying is that like, well, what 10 million tokens is finally, context window for Lama 4 is finally going to put to rest, is that long context windows are all you need. He's going, you know, the 10 million, the 10 million context window length is going to finally, hopefully, you know, make people understand that like, no, there are different things here that are good at different things and we can put them together to create a good system.

• 38:16John Coogan?

  Should we amanitize the eschaton?

• 38:20Speaker 03

  I don't know how you knew that I was writing about this this morning. No, we absolutely should not. Yeah, we absolutely should not. It's always been a trail of tears. Let's not do that.

• 38:27John Coogan?

  Yeah, you explained that to me a while back. I had fun with that. So, so let's talk about Llama4. How should, how should startups be thinking about Llama4 as a tool in the toolkit against the other options that they have?

• 38:45Speaker 03

  Yeah, I mean, I think like, you know, Twitter is equipped to, and research in general, right, is equipped to sort of view state of the art as the only thing that matters. And I think that actually, in many cases, being first is overrated. You know, we've seen, you know, going all the way back to sort of the Slack and Teams charts, where you've seen the famous chart, Slack versus Teams, right? Distribution is incredibly important, as long as, you know, sort of the incumbents can wake up and can catch up. You know, I would not bet against Zuck and $100 billion of profit per year. You know, I think that, you know, Zuck also is in some sense playing a different game. Like, he's not trying to build like the, the sort of very best open source, like chat experience for consumers.

• 39:26Speaker 03

  What Zuck sees, I think rightly so, is that, you know, having an open source model, which is really good, is good for the ecosystem and is good for meta. And, you know, most businesses don't love using closed source models. They want to use open source models for all kinds of reasons, you know, privacy, security, continuity, cost, you know. You can build your startup on TPT4, and it's amazing. And then, you know, there's a new version out, and opening it deprecates, you know, the old version, right? And all of a sudden, all of your prompts don't work the same. And so, you know, open source models are going to continue to play an extremely important part in the ecosystem. Now, obviously, like, you know, the DeepSeek R1 launch a few months back, like, totally took everybody from surprise.

• 40:09Speaker 03

  You know, I think we're still in the early innings of this stuff, where like, good ideas can come from anywhere. And oftentimes, good ideas do come out of the sort of group think, you know, context of Silicon Valley, right? So, you know, but yeah, I wouldn't, I wouldn't bet against that.

• 40:24John Coogan?

  Do you think there's an opportunity to build a company like Red Hat in Linux, but for LLM implementation on top of something like Llama? Or is that like a crazy idea that doesn't really match to the modern foundation model landscape?

• 40:40Speaker 03

  I mean, the bull case for Llama for Meta is that it's actually more equivalent to how Meta open sourced its data center, kind of layout and text, right? And that's the bull case for Meta is actually industry sort of forms around that and becomes a standard, right? That's sort of why, you know, what argument for why they did it. In terms of like the Red Hat four, you know, I think that like Red Hat four works well for operating systems, but I don't think of an LLM as an operating system. I think an LLM is much more like a CPU, right? It's an information processing unit. And so obviously it's a new thing. It's not exactly like a CPU. But yeah, I'd have to reason about that some more, I'm not sure.

• 41:19John Coogan?

  Yeah.

• 41:19Jordi Hays?

  If you're running Meta AI, what would you do from here?

• 41:25Speaker 03

  Hmm.

• 41:26Jordi Hays?

  Not to put you on the spot or anything.

• 41:28Speaker 03

  Yeah, I'm not, to be clear, I'm not running that AI. I've not received that job offer at all. I mean, I think that like, you know, you have to keep going. You can't stop. I think focusing on like the business use cases is pretty important. I think focusing actually also what developers actually need and want out of models is also very important. You know, you see a lot of like model drops that come out, but they don't actually provide the real hooks and they do very well on the benchmarks, right? They do very well on like kind of the public leaderboards, but they don't actually provide the hooks that developers need to do like good tool use or reliable structured data output or the practical stuff, right? The developers actually want out of models. And so like, if you want to create a ground style of developers that like love your tools, like do the developer experience part, like meet them where they are and like give them

• 42:12Speaker 03

  all the hooks that they need and don't just stop at like, hey, look, you know, we hit standard of our benchmarking, aren't we special?

• 42:18John Coogan?

  Yeah. Is there, is there a narrative here where maybe they're trying to do everything all at once and instead should focus on like Llama is amazing at code or Llama is the next version of Llama five is like all about tool use or super great at reasoning or just like the best at deep research or just the best at image generation, for example. Like it feels like there's kind of a bifurcation of the market and maybe the opportunity is actually to, to laser in on something that's high value, but then let the other stuff kind of, you know, simmer out there amongst other teams.

• 42:52Speaker 03

  I mean, focus is probably always a good lesson for all of us, right? Do less and do it better. And so presumably, it's also true for Meta. I think also, obviously, unlimited capital can both be a blessing and a curse in that way.

• 43:07Speaker 03

  Yeah, again, like focus on developers. What some developers want, I think that's the beachhead. That's how you win the B2B market. If you win the B2B market with your open source models, like you get all of the sort of downstream effects that you want. You know, you don't need to beat, you know, GPT-5 on some.

• 43:23John Coogan?

  Yeah. Do you think that part of the narrative that we're seeing around Llama 4 is just pre-training, scaling, hitting a wall? A need for new algorithms, a need for a deeper focus on reasoning? And maybe even whatever comes after that?

• 43:36Speaker 03

  I mean, you know, I, you know, so you mentioned a moment ago, sort of the, you know, imitating the eschaton, right? You know, grand history, you know, every exponential that we've observed eventually results in a sigmoid curve.

• 43:45John Coogan?

  Sigmoid, yeah.

• 43:46Speaker 03

  You remember early COVID, right? The fur of like, oh, my gosh, you know, the Twitter guys doing their thing where they're like, well, if doubled the amount of people get it every day, then everybody on Earth will have had it seven times.

• 43:57John Coogan?

  100 billion people will have it.

• 44:00Speaker 03

  Yeah, exactly, exactly. And so, you know, I think that there are laws of physics here. I think that there are, you know, diminishing, they're clearly diminishing marginal returns, right? Or sort of spending 10x on compute, we're not getting 10x or better models. At least evidently not yet. And so, you know, the transformer is incredible, is amazing. It's a, you know, technology is probably as important as the invention of electricity. It will probably, you know, bring about a increase in GDP that is on the order of the industrial revolution or greater. And so I think we should not like minimize this technology and sort of boil it down to, oh, this is sort of just dumb pattern matching, right? By the same token, you know, we also should not believe that all technology, we're going to be able to rent seek on sort of forever.

• 44:42John Coogan?

  Yep.

• 44:42Speaker 03

  So, yeah, new things are definitely needed. And, you know, I think the thing that like an infinite time compute, internal change of thought is really promising. And, you know, I look at the stack today and I think about how sophisticated computers are, right? And how good architectures are and operating systems and kernels, like compilers and all of this stuff. And, you know, we're just like in the baby phase today of AI. Like, it's just in its infancy and there's a lot to build.

• 45:05Jordi Hays?

  From a recruiting standpoint, have you run into some of these super aggressive non-competes that we're seeing? There was a headline today about, you know, Google basically paying engineers to not.

• 45:15John Coogan?

  Not work at Chroma.

• 45:16Jordi Hays?

  Not work for a year when, you know, they could be working at Chroma or any of these other labs.

• 45:22Speaker 03

  I mean, yeah, you know, airplane red dots, dot PNG, right? I guess like if I was affected by that, I wouldn't know it.

• 45:28John Coogan?

  Yeah. Yeah. Uh, what, what, can you take us through some of what Chrome is building today and where customers are getting the most value? I've talked to you a little bit about some of the use cases and I think they're underrated potentially in like how simple and obvious they are when you explain them, but I want you to take me through some of the modern context.

• 45:47Speaker 03

  Yeah, I mean, you've heard left and right on the internet now for like three years, all about this acronym RAG. Well, I don't know why anybody would ever name something rag. That seems like a dumb idea. We just call it retrieval. And of course, the idea with retrieval is that if you want to build an AI system and you want to be good at something, well, you need to teach it how to do that. You gotta teach it about your data. You gotta give it your instruction set, right? And updating the weights of the model is not a very good idea because you cannot really deterministically control that, right? You can fine tune, but what you're gonna get at the other end, you know, again, you don't really control. And so giving the system access to a repository of instructions or knowledge about your organization, your business problems, that is something that you can control. And that's what, that's the problem that retrieval solves.

• 46:30Speaker 03

  And so, you know, I mean, we talked to like enterprises and businesses building like useful applications. I think like today, 90 plus percent of it in enterprises is retrieval advantage generation, or it's, you know, using retrieval, it's sort of chat on top of unstructured data. You know, I think if you zoom out though and view like what is really AI, right? AI gives us the primitives and the ability to process unstructured data in a common sense fashion. And you think about the scale of data, right? Even today, like inside of enterprises, like unstructured data is like 10 times the size of unstructured data. We have 10 times more unstructured data. And then you consider like the real world, right? If we're actually like putting robots out in the real world, like how much unstructured data they're going to be ingesting and needing to process and reason about and action on.

• 47:12Speaker 03

  And like, it's just sort of like, you know, gonna be a thousand X, 10,000 X, 100,000 X the data that we have today. And so like, That's kind of the direction I think is like not so much like sort of this, you know, sort of a simple like one human, one AI talking in a chat stream back and forth. But it's like real embodied intelligence, which you know, you could call it agent, you can call it robot, you know, I don't love any of these terms. But like really the goal here ultimately, I think for anybody who's built something practical is building something that's reliable. You know, you think about like, we've been seeing self-driving touted as like this technology for like 10 years. And of course, if you live in San Francisco, you can use Waymo and it is actually incredible, but it's taken 10 years. The gap between demo and production has always been so great in AI.

• 47:54Speaker 03

  And so if you're building something practical in AI, your big question as a developer is like, okay, the demo is super sexy and cool, but how do I actually make it work really, really, really well reliably? And the ability for these systems to sort of like self-improve or improve under human guidance, I would say is like the biggest thing that's underrated today. And of course, you know, we think that like retrieval plays a key part in kind of how that happens.

• 48:16John Coogan?

  Can you concretize that a little bit by walking me through like a potential use case for us? I mean, we stream three hours a day. We're probably emitting, you know, I don't know, tens of thousands of tokens every day. If I used Whisper, I transcribe every minute of our show. I could search that through, you know, fuzzy search or deterministic if I want to just search like every time I mention artificial intelligence directly, find that. Or I could try and fine tune Llama4 on it and maybe it just hallucinates like, oh yeah, John was talking about this randomly. How would I, how would I use Chroma to create a more definitive index of every time John

• 49:00John Coogan?

  or guest has talked about artificial intelligence or llama in, you know, hundreds of hours of video? Is that something you could do?

• 49:09Speaker 03

  Yeah, yeah. We were seeing some like kind of fun things today where like, you know, people are taking the corpus of all of their writing or all of their speaking and they're kind of like quote, teaching the model it, they're loading it into a tool like Chroma, so hooking up to a language model and they're giving end users the ability to like chat with John and like, you know, see what John thinks about artificial intelligence, right? And that's exactly right. So we've got all those transcripts get processed, they get broken into pieces, they get indexed and searchable in various ways. And then when the user asks the query, you know, hey, John, what do you think about the latest, you know, llama release? Remember they didn't say llama, they say like the latest release, latest AI from Facebook thing right there?

• 49:44John Coogan?

  Yeah, exactly.

• 49:45Speaker 03

  Llama? Like, the search is good enough that it can like find all the relevant things that you've said and then the L can like respond as you, because it kind of ground itself into the things that you've said before. So that's a-

• 49:55John Coogan?

  And so it's basically taking like different blocks of text, different ideas, and then kind of vectorizing them into some way that's not necessarily human readable, but it can still, it's basically like better fuzzy search in many ways. Not to degrade what you're doing, but it's amazing. It's magical and super powerful.

• 50:11Speaker 03

  Fuzzy, yeah. Fuzzy search is really useful when people like are not, you know, experts in their own data, right? Instead of your Google Drive, you know how to search for stuff pretty well, right? But like, your users don't know how to search for the stuff that you've said before. And so that's the kind of the power of like embeddings and vector search. That's a cool toolbox. It's not a panacea. Again, we're not monetizing the escatine here. We're not too fanatic, right? But it's like a very powerful tool and people are getting a lot of value out of it. Yeah.

• 50:36Jordi Hays?

  I'm curious your reaction to AI 2027. Our point of view generally, just from all the conversations we've had, is that like sort of model progress and advancements could sort of slow and that would be fine just because there's so much value to unlock out of the underlying models. I'm clear, I'm curious to think how you processed just the forecast generally, maybe, maybe take it from there.

• 51:05Speaker 03

  We think the capability overhang we have in the model that we already have today and we will have absolutely in six months is immense. You think about, for example, the possibility of democratizing access to state of the art services to everybody on earth. Like, it is very possible the poorest people on earth today, or, you know, in 10 years, will have access to better healthcare, better legal representation, you know, better financial services than like billionaires have today. I think that's like entirely possible, and that's impossible with the model that we have again today. And so the capability overhang is immense. You know, every time an extremely long essay from a sort of effective altruist drops, right? You know, they clearly tend to make waves. I think if you tell people that the world is going to end, they're going to pay attention.

• 51:51Speaker 03

  And, you know, I'm just like not that frankly, that interested in like secular eschatologies about, you know, apocalypse and the end of the world, right? Like, like, there's a natural tendency for all humans to believe that, like, we are the chosen ones living in the special time and the last days, right? You know, even Fukuyama, right, you know, wanted to, you know, sort of like end history, right? And so, yeah, natural human tendency, you know, this is again, the hypnotizing the eschaton, we'll mention it three times now. It's like, it's really dangerous, right? Like, you think about like what's happened throughout the last hundred years in like really, you know, you know, the hundreds of million people that have died, you know, across like different world wars and different, you know, dictatorships. Like, it is oftentimes, it's like messianic complex that leads to a lot of that.

• 52:36Speaker 03

  And so, I don't know, I'm just like, I think it's, I see it as entertainment more than anything else.

• 52:40John Coogan?

  Yeah, on a more practical note, like, I go to the Wall Street Journal's website. I just try and search for an article and they say, oh, a search is powered by AI. It's not clear, it's clearly not powered by AI because I cannot fuzzy search at all. I can't say, oh, I know that it mentioned this person and I think it was about this and it was in the last week. It's not there. What does it take to actually roll this stuff out? Are these even potential customers of Chroma or is there another company to be built here? What do you think about that?

• 53:08Speaker 03

  Yeah, Wall Street Journal, if you're watching, you know, send me an email. Yeah, all that's very doable today. I think that, you know, the reality is that, you know, your classic, you know, the future is already here. It's just not evenly distributed yet, right? Like, you know, any technology of consequence, even if generationally important, you know, still takes decades to roll out. And, you know, that's just the same is true here. So.

• 53:30John Coogan?

  That's great. Well, thanks so much for stopping by. We got to move on, but this was a fantastic conversation. We'll have to have you on again to talk more. Really appreciate it. Talk to you soon. Bye. And we got a big funding announcement. We're shifting gears. We're out of AI and into manufacturing. Going to talk tariffs, going to talk industrialization, another theme we love on this show. We have some big news.

• 53:54Jordi Hays?

  And I just want to know, was this fundraiser's announcement intended, always intended to go out today? Or did they bring it, they bring it up?

• 54:04John Coogan?

  Oh, because of the tariffs.

• 54:05Jordi Hays?

  Tariffs and everything, because the timing is just.

• 54:07John Coogan?

  It's entirely possible.

• 54:08Jordi Hays?

  Just too good.

• 54:09John Coogan?

  So Jay says, today I'm excited to launch the advanced manufacturing company of America. We've raised $76 million. Let's hear it. A massive round coming out of stealth from caffeinated capital. That's Raymond Tonceng, Founders Fund, Lux Capital, Andreessen Horowitz, and others. The best time to build this business is right now. Yeah, no joke. But the real work began decades ago and they launched a beautiful.

• 54:38Jordi Hays?

  And he just decided, I'm gonna get every big fund. I'm just gonna get them all.

• 54:42John Coogan?

  Yeah, it's great.

• 54:42Jordi Hays?

  Ran a process, says, I'll take a bit from everybody.

• 54:46John Coogan?

  And it's great. They put out a four minute video produced by Jason Carmen, Story Company. It's beautifully lit, beautifully shot, and they brought in, you know, we've been hearing for a long time that the legacy manufacturing companies are run by folks who are aging out and maybe they don't have the next generation lined up to take over the business. Well, they sat down, they interviewed one of those folks and it's a fantastic video. You should go check it out. Anyway, is he ready to come on in the studio? Let's bring him in and hear the news from him directly. Welcome to the studio. How you doing? Congratulations.

• 55:20Speaker 03

  Hey, how are you guys?

• 55:21John Coogan?

  We're fantastic. Thanks so much for taking the quick moment to chat with us. Can you introduce yourself, the company, and what's the news today?

• 55:29Speaker 04

  Absolutely. So my name is Jay Malik. I'm the CEO of the Advanced Manufacturing Company of America. We call it affectionately AMPCA. And so, you know, what we do is we design, manufacture, and certify the next generation of critical products that go into all aerospace and defense systems. So that's both existing and new systems, you know, the stuff that Boeing makes and the stuff that Anduril is going to make.

• 55:56John Coogan?

  Okay. Can you break down a little bit more of like what the first products that you'll make will look like? We've heard about what Hadrian's doing. We've heard about, you know, injection molding plastics, like there's a lot of different buzzwords. Obviously, everyone kind of wants to do everything in the long term, but what are you focused on first?

• 56:15Speaker 04

  Yeah. So first, let me just start at a high level, right? Like when we talk about the aerospace and defense primes like Lockheed or Boeing, they don't make anything today, right? They've outsourced a lot of their manufacturing and engineering to thousands of suppliers. Some suppliers are focused on high-volume manufacturing, things like wire harnesses, machine parts, which is what Hadrian's doing, injection molding. There's a lot of great suppliers that are focused on that. But there are also hundreds of suppliers that are focused on critical engineered products. Those are the products that, you know, basically determine system success or failure and are often, you know, very, very highly specialized. So stuff like avionics products, power units, you know, specific engine products. And so

• 56:57Speaker 04

  we're focused in those areas, in the most critical areas where you need to both engineer and manufacture at relatively low volumes for the end customer for their system to succeed. So we're focused on a pretty different, I would say, part of the market compared to most of the sort of software-defined manufacturing startups that you often see today. In terms of where we're starting, we're starting, you know, almost entirely on avionics, you know, the part of the plane or the ground control system that involves, you know, controlling it, right? So the stuff we've seen in a cockpit, for example. So we're focused on things like switches, panels, displays, power units, you know, things that are critical to the pilot if it's a manned system. And, you know, if it's an unmanned

• 57:42Speaker 04

  system, critical to communication and executing on the mission. So those are the areas that we're mostly focused on right now.

• 57:50Jordi Hays?

  Can you talk about the timing of the announcement? Was it just a happy accident? You were always planning to go out this week? Or did you pull it forward due to the everything in the news?

• 58:01Speaker 04

  A little minor news this week. We were supposed to launch this week anyway, but we actually had a few reporters that I think got scared of the tariffs. You know, didn't want to cover anything. And so we basically said, I'm not sure if I'm allowed to curse in this podcast, but after that, and said that this is actually the best effing time to like, you know, take our company public. So we just did it. And so, yeah, it was planned, but, but obviously timing is definitely in our favor.

• 58:28Jordi Hays?

  Can you talk about, this is obviously a big raise to come out the gates with. Can you talk about, you know, kind of the use of proceeds? And kind of like, I'm curious about kind of like how you're thinking of the the structure of the business generally?

• 58:43Speaker 04

  Yep, so we're going to be, we've already acquired one business that is a critical avionics supplier, which you saw video, or some people may have seen a video about. We're going to be acquiring probably another two to three of them over the next, you know, 12 to 18 months. We're also going to be doing our own clean sheet, you know, design and development of adjacent products in this space with our own manufacturing and engineering talent. So it's a hybrid approach. You know, I'm a firm believer that especially in this, you know, area of the supply chain, you can't, you can't just hack your way into it. You also can't just be a private equity firm and buy and price it up. You know, that's not going to achieve what like, you know, companies like Andro

• 59:28Speaker 04

  want to achieve, you know, for their customers. And so we're taking a hybrid approach where we're buying, you know, companies with products that we think are going to be hard, you know, to just redesign from scratch. And also developing ones that we think we can do a great job of ourselves.

• 59:43Jordi Hays?

  And is part of your advantage over traditional private equity is just the time horizon? You're thinking about of saying like, we don't need to come in and just like immediately cut costs by 50% and increase, you know, pricing to, and then hopefully flip the business in three years. Like I imagine you're buying to hold and that's part of why somebody would want to sell to you in the first place, I imagine.

• 1:00:03Speaker 04

  Yeah, it actually goes deeper than that. So I would say the one thing that I have learned building this business so far, at least, you know, it's still early. Is that owners don't really necessarily care just about the time horizon, your ability, obviously, to underwrite. You know, the deal, they also care about, one, not selling to MBAs, not selling, you know, to traditional finance people, you'd be surprised, it's a big, it's a big thing for them. And that second, that you know what you're doing, meaning like, you know, you're not a bunch of like search funders. You're not, you know, a bunch of people, you know, this is stuff from the MBA argument, but like, you're not a bunch of people that haven't spent time in manufacturing, you know, shop floor, etc.

• 1:00:43Speaker 04

  And so our entire team are engineering and manufacturing folks. We spent our entire careers, you know, designing things for SpaceX, manufacturing things. You know, we're also young, which I think people like to see when they're selling their business. They know that just looking, you know, looking at the person across the table, that they're going to be there for that, for the next 20, 30 years. So I'd say all of those things combined make it a pretty strong pitch for wanting to sell to us.

• 1:01:10Jordi Hays?

  Did you have this idea in mind or a rough idea of it when you decided to go back, you know, enter your next chapter? I remember it felt like a year ago when you decided to move on from, from active investing. It felt like, I just remember that like instantly you shared it and it just was like everywhere. And because people at that time, it was like every non-deep tech, hard tech investor was like starting to pile into the category. And then everybody's like, wait. Wait, if he can't do it, I'm screwed. What are we doing? It didn't slow anything down, obviously, but I'm curious, like, you know, kind of the origin.

• 1:01:49Jordi Hays?

  Yeah, I'm curious like how, how the idea and the opportunity came together.

• 1:01:53Speaker 04

  Yeah, so I, you know, I spent three or four years, obviously, my career. At Countdown, when I was 24 years old, you know, I started the firm. I spent a lot of time, you know, with manufacturing startups and also with mom and pop suppliers. Like, as part of my diligence for whether I should invest in companies, I would, you know, talk to mom and pops. And so I'd spend, you know, three or four years in the space. And it didn't really click, I think, until after I shut down Countdown, that one, the mom and pops, you know, have both the expertise and, you know, in some cases, the qualifications that you need in order to develop, you know, and manufacture and, you know, bring the

• 1:02:33Speaker 04

  product to market. And then it also didn't occur to me, obviously, when I was venture investing, that, you know, maybe there is a path where you can combine, you know, the mom and pop, you know, advantages with the spirit, the culture, the talent of a startup, right? Like, when you're venture investing, you know, three or four years, you know, every single day, your mind is just like, you know, startup, startup, startup, new things, new things, new things. You're not even able to think about what does the future look like using something that already exists, right? And so it wasn't until I had actually shut down Countdown, had like a month and a half to reflect, think about what I had learned, wrote down some, wrote down some key, you know, themes, and then, you know,

• 1:03:16Speaker 04

  sort of iterate from there. You know, talk to people, talk to customers in the industry, talk to people at companies that are already, you know, building very successful ones, both in startup world and in mom and pop world. And that's when the vision started to come together. Like, hey, I'm uniquely in the center of these two movements, right? Like, I helped, I think, start and invest in a lot of startups in this space. And at the same time, I know a lot of people who are in the traditional, in the traditional world, and I should use that to the maximum advantage that I can.

• 1:03:45John Coogan?

  I have one last question, and then I'll let you go, because I know you're busy today. Charlie Munger criticized TransDigm for buying aerospace parts manufacturers and then locking primes and aerospace companies into long contracts, raising prices. It was a little bit of a controversial strategy, but it's performed very well for that company. What is your takeaway from the TransDigm model?

• 1:04:10Speaker 04

  Trans- Transzyme is actually a phenomenal business and it's actually not the cause of any of those issues. The cause of those issues, certification, lock-in, et cetera, et cetera, has to do with decisions that were made 30 years ago at, you know, the top of Boeing, which is a paper right here, you know, basically pillorying that decision. But the decision at the top of Boeing to outsource every single thing that they do from engineering and manufacturing at the component and at part level up to the product level. And so Transzyme is just a recipient of the system that was instituted 30 years ago. If you really want to change things, we believe that you have to start from the bottoms up with the critical products, build your way back up in

• 1:04:54Speaker 04

  partnership with the customer to reverse that type of decision-making and culture. And so, yeah, my answer to that is I think Transzyme is actually a great business. They have run businesses very, very well. They're in an environment that was not created by them. They have taken advantage of it, but it was not created by them. And to fix that, it's going to take partnership with a company like Appz.

• 1:05:15John Coogan?

  Well, that's a fantastic answer. Thanks so much for hopping on on short notice. Congratulations on the round and we'll have to have you back.

• 1:05:22Jordi Hays?

  Yeah, I have so many other questions I want to ask.

• 1:05:24John Coogan?

  We can talk for an hour, I'm sure.

• 1:05:25Jordi Hays?

  Yeah, very excited for you and the team and excited to have you back on the show soon.

• 1:05:29Speaker 04

  Thank you. Let's do it. Take care, guys.

• 1:05:31John Coogan?

  Talk to you soon. Bye. Well, we are moving on to someone from FAI, the Foundation of American Innovation, I believe is how they call it. FAI.org, theFAI.org. I've been to a couple of their events, very fun.

• 1:05:47John Coogan?

  Gary Tan spoke at one, Trey Stevens spoke at one.

• 1:05:49Jordi Hays?

  Yep.

• 1:05:50John Coogan?

  Trey Stevens has been involved. I went to one in San Francisco and there were actually protesters outside, which is kind of fun. But they were like in very good spirits and kind of like taking pictures with everyone. It was a lot of fun. Anyway, welcome to the stream.

• 1:06:04Jordi Hays?

  Boom.

• 1:06:04John Coogan?

  How you doing?

• 1:06:06Speaker 05

  Hey, man. How's it going?

• 1:06:07John Coogan?

  It's good.

• 1:06:07Jordi Hays?

  What's going on?

• 1:06:08John Coogan?

  Thanks for hopping on.

• 1:06:10Speaker 05

  Your hair game is on point as usual.

• 1:06:12Jordi Hays?

  Chill week, chill week for you?

• 1:06:15Speaker 05

  Sleepless nights, probably on maybe eight hours over three days.

• 1:06:20John Coogan?

  Ooh, not good. You should get an Aids sleep. Go to Aidsleep.com/tbnn.

• 1:06:25Speaker 05

  I have a helix.

• 1:06:26John Coogan?

  No.

• 1:06:27Jordi Hays?

  No.

• 1:06:29John Coogan?

  We'll get you a switch. Anyway.

• 1:06:30Jordi Hays?

  No, it's great to have you on. What, what's running through your brain? There's a bunch of things we can talk about, but where should we start?

• 1:06:38Speaker 05

  Oh, just the contagion effects and potential collapse of the world economy. Simple stuff like that, you know?

• 1:06:46John Coogan?

  How bad is it?

• 1:06:47Speaker 05

  US primacy.

• 1:06:48John Coogan?

  Are you a, is there any element of cautiously optimistic about this for you? Or are you just totally blackpilled on it?

• 1:06:58Speaker 05

  I mean, my white pills are Lucy's, so I do, I do have some of those.

• 1:07:05Speaker 05

  But, you know, you're gonna need a higher milligram for.

• 1:07:08John Coogan?

  For this week? Well, walk me through why, why is it so disruptive to you and what you do? And maybe just for the viewers, give a little background on yourself and the organization.

• 1:07:19Speaker 05

  Sure. So I'm chief economist for the Foundation for American Innovation. I'm ripping the swag here.

• 1:07:26Speaker 05

  We are a tech policy think tank in Washington DC, originally founded to bridge Silicon Valley and the DC culture. Today, we work on the intersection of national security, tech and governance. I focus on AI, but cover sort of all economic issues as well. And, you know, I think we kind of, or at least associated with the sort of tech right with, with you guys like yourselves. Like I'm rooting for y'all and hopefully Martin Scarelli's Bloomberg Terminal Killer takes off. So then we can combine, combine you guys and completely disrupt Bloomberg.

• 1:08:02Speaker 05

  So, you know, I, I think you see this in the administration too. The Trump administration is, is a series of factions or coalitions and we are definitely, you know, in the mix. But, you know. Elon Musk today called Peter Navarro, Peter Retardo. And I kind of, you know, definitely hard to argue with.

• 1:08:26John Coogan?

  Can you talk about the, the bridge between Silicon Valley and DC? It feels like that bridge is massive at this point. There was a moment where maybe tech was drifting away from DC. But now it feels like tech has taken over DC. At the same time, you go back to the Obama administration. I always think about this statistic that I believe the number one organization that was non-governmental that Obama visited during his eight years in office was Google. And so there, there was, there was a moment when big tech and DC were tightly intertwined. Just happened to be with the Democratic Party. Now it happens to be with the Republican Party. But what is, what is the state of the bridge and how did we get here?

• 1:09:10Speaker 05

  Yeah, I think it's almost like a qualitative difference. So if you think like the last 80 years, the power structure in the US is being sort of either Wall Street or like West Texas oil. So we either get like Rex Tillerson or Jamie Dimon.

• 1:09:23John Coogan?

  Sure.

• 1:09:23Speaker 05

  And, you know, since the internet took off, you know, there's this new, new wealth on the West Coast. And as that sort of germinated and matured, it originally was just sort of like one interest group among many, you know, they still, still had those two main power elites. And I think with the, with this last election, it was, it was sort of an example of Silicon Valley, at least a part of Silicon Valley asserting itself as its own distinct power center.

• 1:09:48John Coogan?

  Sure.

• 1:09:49Speaker 05

  And that, that is, that is very, very different. Of course, you know, all the other power centers still exist to some degrees. And so it is, it is sort of a constant struggle. I think there's a lot that this administration is doing great. You know, the stuff on energy, I think Doge at some point is going to turn to regulation. And that's what I'm most excited about, you know, once we start cutting whole parts of the CFR. You know, I, back in the day, I used to do like supersonic policy and early, worked early with booming aerospace and, and it's good that they're getting a hearing now and maybe I'll be able to fly to their coast in a couple of hours rather than.

• 1:10:22John Coogan?

  I'd love that.

• 1:10:23Speaker 05

  So, so there's a lot, a lot to like. It's just. And I think there's also like a steel man case for like these trade actions, you know, we participate with like the re-industrialized conference. We have our own techno industrial playbook that will be coming out in a couple of weeks. So we're all on board for the like, you know, America needs to build again. And, you know, that especially as AI like deflates all the knowledge sectors, like we're going to need more aluminum smelting and stuff like that.

• 1:10:54John Coogan?

  Is there any glimmer of hope that there's this Mar-a-Lago summit? I forget exactly what Chamath is referring to, but the accords and you do see reciprocal tariffs, but they they actually have the effect of driving it down to zero tariffs anywhere in the world, either direction. Are you hopeful for that? And would that be a good outcome in your economic framework?

• 1:11:18Speaker 05

  That would be sort of the best possible world. There's also risks associated with that, right? Because, you know, I wrote a piece recently discussing the sort of way the market reacted. And, you know, on the one hand, you could say, oh, Trump just likes tariffs. And that's definitely true. He's a 40 year track record of just liking tariffs.

• 1:11:38John Coogan?

  Yeah.

• 1:11:38Speaker 05

  But then you have other people like Stephen Moran and Scott Benson, and you sort of JD Vance himself as well, who at various points talked about the curse of the US dollar being international reserve currency. And there's a lot of truth to that, like the fact that, you know, China wants to hold our treasury debt. And, you know, we, you know, they build cheap cars, we build treasury bills is, you know, it does raise our living standards, but means that we are not ready to fight a war.

• 1:12:10John Coogan?

  Yeah.

• 1:12:10Speaker 05

  And so that is a core, a core problem. But then the question is like, how do you deal with that? And if you do go all the way to a Mar-a-Lago accord, what you're saying is this isn't just about tariffs. This is about resetting global financial imbalances.

• 1:12:24John Coogan?

  Yep.

• 1:12:24Speaker 05

  And you, we need to do that, but we need to do that sort of gradually. Because if you do this all at once, what that means is the entire floor will fall out of the stock market and the real estate market. And, you know, with huge cascading effects through merging calls. And, you know, I think, I think mortgage debt is now back to its 2007 levels. So it's less to me about like, the mood or the

• 1:12:47Speaker 05

  The ideas behind the policy, but the execution.

• 1:12:49John Coogan?

  Yeah.

• 1:12:50Speaker 05

  That they're, they're, this is a rug pull of, you know.

• 1:12:53John Coogan?

  Rugged.

• 1:12:55Jordi Hays?

  Can you talk about, you know, the value of the yuan has been dropping? I guess it's at a record low. Can you talk about trade wars turning into currency wars? And, and, um, you know, if that's what people should really be focused on?

• 1:13:14Speaker 05

  Yeah. So, you know, China was a currency manipulator through, throughout a lot of the 2000s and early 2010s. But really, that really hasn't been the main way that they, they cheat. They cheat by basically suppressing household consumption and, you know, having these 60% saving, savings rates. And so they end up building these ghost cities and, you know, whatever technology they enter, whether it's cars or telecom equipment or pick, pick your poison, they just overproduce it to the maximum, drive down the, the, the costs worldwide and then have to find these export markets to dump it. And, and the way they resolve, the way that we're ever going to resolve this is especially now that like the US is like, is going to have a hundred percent plus tariffs on China and Europe doesn't want their shit either.

• 1:13:57Speaker 05

  They need to like build up their domestic economy, you know, they need to like reduce their own savings rate, raise the standard of living of their households, like introduce like some basic, you know, social welfare programs or something so that they, uh, you know, actually have a domestic consumer base. And if they do that, like, that's actually the best way that they can retaliate in a sense, because they're sort of shielding themselves from the tariffs, but it also is, it helps correct the big imbalance. And so that, that is like, it's sort of aligned in that sense where like if, if China does the right thing, then it's a win-win situation. If instead they double down on tariffs and trade war, um, you know, I, I don't see, I don't see, we just exacerbate the, the, uh, the contradictions in the economy and, and don't get to a resolution.

• 1:14:42John Coogan?

  Ben Thompson has been advocating for a rethinking of the CHIPS Act, mainly shifting from export controls, removing those and instead, uh, taking a more operation warp speed approach where, uh, the US government is potentially a, uh, a massive buyer of domestic made 3 nanometer, 5 nanometer chips, uh, with the demand signal there, the American market should solve it. How are you processing the, the current CHIPS Act and what are you hopeful for going forward?

• 1:15:16Speaker 05

  I'm not opposed to the idea. The thing about Nvidia's chips is their, the demand is kind of saturated, right? They can kind of pick who their buyers are because there's just so much demand for them. And at the same time, they've not been the most sort of like loyal actor in this space. And you know, if there's any sort of big meta narrative or theme to a lot of the right, the tech rights move into DC, it's been, you know, since from Project Maven on that, you know, these companies have had corporate social responsibility policies, but not corporate patriotic responsibility policies. And technology is becoming geopolitical and you sort of have to pick your side. And so, you know, every time we introduce an export control, Nvidia's two weeks later has a new chip

• 1:15:59Speaker 05

  that just gets under the line of what's being controlled. And the latest one is the H20. The H20 is an inference chip. It's, you know, it will power these reasoning models. If you're, if we're worried at all about search staying competitive, I don't think we can give up on those. And in fact, we should, we should be doubling down and that would be like a smarter kind of trade war than just across the board tariffs.

• 1:16:20Speaker 05

  But that doesn't have to be mutually exclusive with doing a kind of industrial push. And that's what I'd like to see because if we're going to do this big rebalancing, you can't just pull the rug. You have to, you know, to mix my metaphors, you have to be the Indiana Jones that like swoops in the bag of sand or something as you take the holy grail. And what is that, what is that like new thing that we're going to be swooping in? What is the industrial bank that we're going to be using to bootstrap the industries that we need? Because they won't just materialize on their own.

• 1:16:45Jordi Hays?

  Can you talk about putting the, the trade wars in the context of like this race for superintelligence, right? In many ways, people are arguing like, hey, if we're making like transformers like harder to get and more expensive, like, does that hold us back from winning the AI race? And is that the only race that, that really matters? You know, we've joked on the show about this idea of like picking up pennies like in front of a steamroller, right? Like AIs, you know, has potential to transform the economy in so many ways. And like, it's very possible that like that, just winning AI matters more than like winning, you know, the trade war in the year 2025.

• 1:17:27Speaker 05

  No, I I hundred percent agree with that take like I can forgive a lot of stupid policy because in four years we're going to have such powerful AI systems that like really it swamps everything else and the you know we know what the bottlenecks are going to be right like the building these models only has a few basic ingredients you have like the the data and algorithms which the US you know the algorithms are basically public domain the the data China maybe even has an advantage because they don't have privacy laws and they can just scoop up everyone's like genome or whatever and you know then it comes to like energy and chips the expert controls exist because right now our only structural advantage is at the chip

• 1:18:08Speaker 05

  and hardware stack where you know our install base of Nvidia data centers is you know a huge portion of the world's China's been basically cut off since two thousand twenty two and twenty three then when it comes to energy you know China added four hundred and forty six gigawatts of energy last year it was twenty percent year over year increase they're going to do that again this year we added zero net new energy we had a lot of renewables but it came directly out of coal and other sources and so you know the the chips are the chips is the short run bottleneck so that's why we need to lean into that and then the long run is like how are we going to supply the energy and then as the stuff diffuses you know to the the people who worry about deindustrialization it's like it's true the last forty years we've

• 1:18:51Speaker 05

  specialized in you know higher education knowledge work legal management services Hollywood you know the creative class all the stuff that is going to like be deflated and China will have the factories that will become fully automated and due course because they'll also have the workforce that they can extract all the like the tacit knowledge out of and put into their robots and so we it's like a really urgent thing that we don't just like try to win on AI but like win on AI plus heavy industry and robotics because otherwise our our innovation in bits will be their innovation in atoms.

• 1:19:25Jordi Hays?

  Yeah, the the one point of view on on the Trade war and trying to bring manufacturing back to America is like, yeah, yeah, we can bring the production capacity back, but will the jobs come back in the same way, right? Just due to, if we, if we actually want to scale production, we need to lean into automation and robotics. How do you think about job creation as part of reshoring and increasing domestic production in the context of long-term, a lot of production just becoming automated and, and just, just because that's going to be the most efficient way to produce the most amount of goods?

• 1:20:09Speaker 05

  Yeah, we need to bring back manufacturing, but it's not, it's not a jobs program. That's for, that's for sure. In fact, the only way we're going to bring it back is if we automate significant amounts of this. And maybe the guy who presses the on button every morning gets paid, you know, multiple six figures, but it's not going to be this nostalgic vision of like 1950s where we're all going into the factory. And that's just like a structural thing. We're not, but you know, AI is going to do that for a lot of stuff, probably, you know, most stuff at some point and we're going to have to figure out what the new jobs are. Like I saw on, you know, I saw a video of like professional backscratcher. You know, and in the VC world, those exist already, but like, but this was like a woman with long acrylic nails and some, you know, maybe we can start growing her nails up.

• 1:20:53Jordi Hays?

  Crazy.

• 1:20:54John Coogan?

  My case is that there's like, there's, there's so much knowledge work to do around an advanced factory. I mean, we just talked to Jay from the Advanced Manufacturing Company of America. There's clearly a lot of high skill labor that is not getting displaced anytime soon that could.

• 1:21:11Speaker 05

  It's not millions of people.

• 1:21:13Jordi Hays?

  Yeah.

• 1:21:13John Coogan?

  Well, it might be if we're manufacturing a Dyson sphere with a million robots or something. I don't know. I, I, I could see a world where yes, there are a million jobs in the manufacturing sector, but it's all at the higher level.

• 1:21:26Jordi Hays?

  But if two million, you know, traditional like white collar jobs get evaporated, you know?

• 1:21:33John Coogan?

  In the interim, maybe.

• 1:21:34Jordi Hays?

  There's clearly some big, big questions we're going to have to be thinking about.

• 1:21:36John Coogan?

  Yeah.

• 1:21:37Jordi Hays?

  Do you have strong opinions on unit? Or any of these other Chinese robotics companies that are trying to. He's just like, I love them. Yeah, I'm curious if you've written about it, if you've had, you know, policy recommendations that you or FAI have have made around,

• 1:21:54Jordi Hays?

  you know, some of these more hybrid sort of dual use. Well, everything's dual use in China.

• 1:22:01Jordi Hays?

  Dual use back scratching.

• 1:22:03Speaker 05

  No, the unitry is really impressive. And you know, I've seen it do like Kung Fu and it it does breakdancing better than that Australian lady.

• 1:22:11Jordi Hays?

  Oh, yeah. Not the highest.

• 1:22:14Speaker 05

  Like, you know, if you, you know, Shenzhen is like, you know, it's like going to a flea market wherever you trip over like baskets full of microelectronics. And we need to be building some of those like ecosystems in the US. That's number one. And number two is like, yes, we have the the data centers and the better models, but China, you know, has the batteries, right? They they they have like that. That's one area where they they have leapfrogged us. And whether it's electric vehicles or robotics or drones, like we need to have our own battery stack. And maybe, you know, we do need like a chip sack too, but we also probably need like a batteries act to compete with that because other like that that will be the thing.

• 1:22:56Speaker 05

  It's fine if, you know, Anduril builds a drone factory, but where are these batteries going to be coming from?

• 1:23:00Jordi Hays?

  Yeah. Not asking for financial advice, but where where are where specifically in America are you long? You know, areas that could be that sort of American Shenzhen, or maybe it's multiple places. I'm curious what what what areas that, you know, you know, different regions in the United States are are, do you think, benefit from reshoring most intensely?

• 1:23:27Speaker 05

  In recent history, it's been sort of the the South and South Atlantic. You know, the North Carolinas, the Tennessees, Nashville. You know, partly because those all have the best housing markets, right? It's so much easier to build when you have greenfield.

• 1:23:47Speaker 05

  Longer term, this is also not something that the US can do alone. Like, we're going to need almost like a North American plus, like, production, you know, frontier where, you know, you know, let's figure out the thing with Canada, like, do we need their lumber? Don't we, you know, whether, you know, do we want their bags of milk or not? But like, we do need their aluminum, right? And we will need to have some kind of integrated production ecosystem to be kind of competitive and stand up to China, because China, you know, already in purchasing power parity is larger than the US. And, you know, they want to gobble up their neighbors too and get even bigger. So, but I do think there is an opportunity here, because when you

• 1:24:32Speaker 05

  do have, like, I'm not a technological unemployment guy, you know, I think new jobs get created, they'll just be very weird, not necessarily in the sectors that matter the most. Like, the purpose of industry, heavy industry and robotics is like more military and like, do we control the supply of core goods and services?

• 1:24:50John Coogan?

  On energy, what do you think the lowest hanging fruit is in terms of energy deregulation? Should we be focusing on the NRC, nuclear? What's the biggest opportunity to help us jump from, I guess, 0% to 20%, where I want to be? Maybe 40% would be nice, maybe 200%?

• 1:25:11Speaker 05

  Yeah, you guys should definitely have my colleague Thomas Hockman on to talk about this for a full half hour, because he's been putting up the winds lately. We've helped pass a bill in Utah. There's activity in like Arizona, Montana, and other places. There's a huge appetite to unlock America's energy. In the short run, especially for these data centers, it's going to be natural gas. It's going to be a bridge to more permanent based load energy. And then the next bottleneck is like the grid itself, because if you want to Do a, even if it's just like natural gas energy is rolling in, like it, that investment makes way more sense.

• 1:25:51Speaker 05

  If you know that after that, you know, G P T seven is trained, that you get to put your energy back into a grid and have, have, have customers for it.

• 1:26:00Speaker 05

  So that needs to be fixed. Other energy sources, you know, I think enhanced and advanced geothermal are, they were underrated. I think there are people are starting to finally wake up to the potential, you know, with, with like, really advanced geothermal. We could make like everywhere in America, kind of like Iceland, where like, you know, you have energy under your feet. And then with nuclear, you know, there is this case before the courts that I think it's Texas, Utah versus the US government that, uh, N R C. That argues that the N R C doesn't have jurisdiction over small modular reactors.

• 1:26:34Speaker 05

  And there's, I think there's a good chance of this, that Pam Bondi and the Attorney General settle that case. And in which case states could then stand up their own licensing boards. And I think there's actually already movement in Utah to have their own like nuclear regulator. And so that could, that could happen sooner than people realize.

• 1:26:51Jordi Hays?

  Do a bunch of young founders building, you know, small nuclear reactors, does that scare you? Does that keep you up at night? Or do you think the technology is, you know, it's solved?

• 1:27:02John Coogan?

  Doug Burnout, Ed Radian isn't that young. He's got kids. I trust him with my life.

• 1:27:08Jordi Hays?

  Yeah, basically, I think it's a requirement. You should, you should have to have kids to be a nuclear founder.

• 1:27:12John Coogan?

  He worked at SpaceX. He's got a pedigree. I love that company based in El Segundo.

• 1:27:18Speaker 05

  Yeah, the big problem with nuclear is it, it's, it doesn't really pencil out without like large government support.

• 1:27:23John Coogan?

  Yeah.

• 1:27:23Speaker 05

  And, um, and so I would love to see like the 600 billion in tariff revenue, you know, be given to Doug Burgum to like, build a reactor template and build 200 of them all around the country and like make this a. You know, use every national security, national emergency trick in the book to get it done as quickly as possible. But it does need, it will need like some kind of, you know, fixed capital backstop to make those investments, at least with the current technology.

• 1:27:51John Coogan?

  I mean, given what you're, like, you're kind of optimistic about Doge, it seems like you're pretty bearish about the tariffs. Like, are we in a regime where you trust the government to do mega projects yet? Because I think everyone was excited about the moon landing. And then, since then, a little bit less excitement about the big projects. High-speed rail in California has been a little bit of a rough go. And I don't really want to see a California high-speed rail of 600 billion get burned on a nuclear strategy that doesn't produce a single watt of electricity for, you know, 70 years or something, which would be like the bad case.

• 1:28:28Speaker 05

  Yeah, 100%. You know, the state capacity incompetence is really, you know, it's the jagged frontier.

• 1:28:35John Coogan?

  Yeah.

• 1:28:36Speaker 05

  Places that have a lot of it, places that have a little of it. You know, I would have more, you know, I would have more trust in a Burgum or like a Chris Wright of actually, you know, executing on something like that. It wouldn't be the Pete Buttigieg slush fund where it's just filling potholes in Indiana. They, they would know how to cut through the red tape. They wouldn't make it like this, you know, everything bagel, you know, we're going to build TSMC chips, but then also like, you know, rehabilitate justice-involved individuals. You know, we need to keep our potatoes and our gravy separate, so.

• 1:29:13John Coogan?

  Got it. How are you thinking about the DeepSeek versus Meta's Llama strategy? We were talking about that earlier on the show, and it's kind of hard to, to, I think a lot of people on the vibes of DeepSeek, they're like, I don't like this. But then it's difficult to formulate an argument, because are you anti-open source? In which case, are you anti-Zuck and Meta? How are you thinking about kind of the intellectual property that's being developed in America around large language models and then makes its way across the Pacific Ocean?

• 1:29:49Speaker 05

  I think what I find most impressive about DeepSeek is less the model they put up, but just that they sort of have imported a kind of Silicon Valley model of like, and that that came from their CEO being like a hedge fund manager doing this as a side project. It's very, you know, Sam Altman wasn't a hedge fund manager, he was a VC, but sort of analogous, right?

• 1:30:10Speaker 05

  And that's striking because it's just a different model of corporate governance than you're used to seeing. And I think there's a question of like, how long, does DeepSeek become a victim of its own success? And like, you know, they are the tall poppy. And it's not that China tries to hurt them because of that, but actually tries to help them and makes them a national champion and thereby sort of perverts it.

• 1:30:38Speaker 05

  But, you know.

• 1:30:39John Coogan?

  It's a fun take.

• 1:30:40Speaker 05

  They've been great to, you know, publishing what they're doing and everything sort of has checked out.

• 1:30:46Speaker 05

  But they don't have the chips and they've said, they've said that, like their CEO said their biggest bottleneck is hardware. And so we shouldn't help them on that front. Like, there's $16 billion of orders for H20s, just sort of sitting in limbo about to go at the door. The Commerce Department has, Howard Lutnick has said that he's going to export control the H20, but they're so distracted by tariffs, they haven't prioritized it and the time is kind of running out.

• 1:31:13Jordi Hays?

  What's going on with TikTok? We've been following the poly market around a new band before May. There's markets around, you know, potential buyers, things like that. Do you have any insight that you can share around the latest there? It feels like, again, one of those things that's just like not getting the attention and the focus because obviously, you know, if we are, enter into the greatest global trade war of all time, like, yeah, it's rightfully, people should maybe be sort of focused on that. But at the same time, it feels like something that we were supposed to have answers around by now and we definitely don't.

• 1:31:54Speaker 05

  Yeah, totally. I mean, FAI, we led the charge to ban TikTok over a couple of years.

• 1:32:01Speaker 05

  And I fully support it. I also enjoy TikTok, but I do notice that like between my barbecueing steak videos and like funny memes, I'll get like a Pyongyang tourism board video now and then. It's like, well, that I don't plan on visiting North Korea anytime soon. But yeah, I don't have any super deep intel. You know, there has been talks about or rumors about Oracle maybe being part of this. And I think Trump still wants it to be part of the new sovereign wealth fund.

• 1:32:36Speaker 05

  And actually, as sort of Zanyan idea that is, like, he kind of has a point. Like, if TikTok became American and, you know, quadrupled in value, that would actually help pay down the debt.

• 1:32:50Speaker 05

  The interesting thing here is like, you know, people have pointed out that, you know, Trump has sort of placed fast and loose with the Constitution, with the law and stuff like that, you know. And as a matter of fact, all the people he's fired, totally constitutional. The biggest, the most unconstitutional thing he's done today is not enforce the TikTok ban.

• 1:33:09Speaker 05

  Because that was a direct, you know, statute that Congress passed that said, thou shalt ban TikTok. So I'm hopeful that they can get a deal. The reason I would just doubt it is China has very strong expert controls. Like, the reason TikTok can't sell is because algorithms in general are expert controlled. And so they would be able to buy the brand name and like the offices, but they have to completely revamp the algorithm, which is like the secret sauce of the thing. Now TikTok is in our building in DC, so I can try to plant a bug for you if you want.

• 1:33:42John Coogan?

  Well, Polly Market has the chance of TikTok being on the App Store on May 1st at 97%.

• 1:33:50John Coogan?

  And who will acquire TikTok? Oracles at 27% number two. Larry Ellison directly at 24%. You'll love to see it. Amazon's still up there, but I just want to say, thanks so much for joining. This was a really interesting conversation. We'll have to have you back soon.

• 1:34:04Jordi Hays?

  Yeah, no, get some sleep.

• 1:34:06John Coogan?

  Yeah, get some sleep.

• 1:34:07Jordi Hays?

  We'll work on getting you an eight sleep.

• 1:34:09John Coogan?

  Yeah, yeah, yeah.

• 1:34:09Jordi Hays?

  Start putting in some proper sleep.

• 1:34:11John Coogan?

  Yeah, I want to see a hundred for a week straight. I think.

• 1:34:14Jordi Hays?

  Yeah, less red light from the stock market, more.

• 1:34:18John Coogan?

  Yeah, more sleep.

• 1:34:20Jordi Hays?

  Anyway, go get some sleep. Thank you for, for coming on and yeah, looking forward to the next one.

• 1:34:25John Coogan?

  Yeah, talk soon. Bye. Later, Matt.

• 1:34:28Jordi Hays?

  Cheers.

• 1:34:28John Coogan?

  Next up, we have Sheel coming back on for his second TBPN appearance. We're going to talk about fintech, the markets, the tariffs, his dust up with another capital allocator on X the other day. Had a lot of fun with that, and I'm sure we'll have plenty to talk about. So as soon as Sheel gets here, we'll bring him into the studio, but those are some interesting questions. There really are so many debates right now about China. It's like DJI, Unitree, TikTok, Deepsea. There's like seven different, really important questions. Maybe we'll talk about it with Sheel, maybe we won't, but let's bring him in to the studio and welcome him to the show. Welcome.

• 1:35:07Jordi Hays?

  Boom, back with a suit.

• 1:35:10John Coogan?

  Looking great. How are you doing?

• 1:35:11Jordi Hays?

  Looking good. Looking good.

• 1:35:13Sheel Mohnot?

  No, no Apple Watch.

• 1:35:15John Coogan?

  No Apple Watch. There we go. We'll get you on Bezel now. That's the next step. We've, we've de-radicalized you from the Apple Watch. Next is radicalizing you to Bezel.

• 1:35:24Jordi Hays?

  Yeah, the tariffs haven't hit the secondary market yet.

• 1:35:26John Coogan?

  No, it's a great buying opportunity. This is financial advice. Go to getbezel.com, download the app.

• 1:35:32Jordi Hays?

  Just for Sheel.

• 1:35:33John Coogan?

  Just for you, not for the listener. For you specifically, you specifically. I want to see an Adam Arpegay or a Royal Oak on you, something like that.

• 1:35:44Jordi Hays?

  Well, you've had a bit, you, I feel like you've been, the timeline's been in turmoil and you've been at the center of it.

• 1:35:51Sheel Mohnot?

  Been turmoil, yeah.

• 1:35:52Jordi Hays?

  I guess, I guess Tremoth knows who you are now, now that, that people reminded him that he would use your content in his newsletter.

• 1:36:00John Coogan?

  Yeah.

• 1:36:01Jordi Hays?

  But.

• 1:36:01Sheel Mohnot?

  That's so funny. Whole thing.

• 1:36:04Jordi Hays?

  The whole, the whole thing was, the whole thing was funny. I'm, I'm sorry. I'm, I mean, I honestly, probably good. Metrics, I'm sure, we're up and to the right, so.

• 1:36:13John Coogan?

  Elon bucks are flowing.

• 1:36:14Jordi Hays?

  The creator payout this month.

• 1:36:15John Coogan?

  Elon bucks are flowing.

• 1:36:16Jordi Hays?

  It's gonna go from 200 bucks to 100.

• 1:36:19John Coogan?

  Except he, Shield is gonna pay for screenshots of his content with just, this is why, I can't believe this Twitter, this, this app is free. And this is why I'm never deleting this. I'm never leaving this app because of the interaction.

• 1:36:30Sheel Mohnot?

  Yeah, exactly.

• 1:36:32John Coogan?

  Anyway, uh, yeah, can you give us just your, your high level reaction and how you've been processing the tariff news? Kind of set the table for us and then we'll dig in.

• 1:36:39Sheel Mohnot?

  Yeah, wow, right into it. Okay, um, I'm kind of like, I've always been more of a free market kind of guy.

• 1:36:47Jordi Hays?

  An American?

• 1:36:47Sheel Mohnot?

  And I think, free market, American, yeah, American. I've been an American guy. And I, I tend to think competition makes us better. And I also, like, spent time, like, living in protectionist India.

• 1:36:59John Coogan?

  Sure.

• 1:36:59Sheel Mohnot?

  And so, for those who don't know, like, until the 90s, India was a closed economy. Like, they had super high tariffs on all foreign goods, and it sucked. There were, there were two local car manufacturers, and, and the cars were, like, built in the 50s, and they, like, didn't get any better from the 50s until the 90s.

• 1:37:20John Coogan?

  Yep.

• 1:37:21Sheel Mohnot?

  Because India had so much protections on their local car industry.

• 1:37:24John Coogan?

  Yep.

• 1:37:25Sheel Mohnot?

  And that was terrible. So, like, they didn't innovate, they never improved the quality. They were super high, so people couldn't afford, the prices were super high, so people couldn't afford them. And so, that's what really scares me. And then you might say, that would never happen in America. But you'd be totally wrong, because that's exactly what has happened in the US shipbuilding industry. So, like, the Jones Act basically says that if you, if you're shipping goods between two US ports, you need to use a US-built ship crewed by US citizens and owned by US citizens. So, like, it's a super protectionist to the US shipbuilding industry, and US ships suck.

• 1:38:06Sheel Mohnot?

  They're like five times as expensive as other ships, and they've never had to innovate because they have these protections. And then it totally distorts the markets in general, like, on the East Coast, I'm in New York right now, on the East Coast, a lot of, like, the East Coast gets some fuel from. Internationally, because it's easier to ship here than it is to get it from Texas. And that's just like a perversion of markets that exist because of the Jones Act. So anyway, so I think like all these things, like I'm totally anti-protectionist. There's a question of like, what is Trump doing? Is like with, it's not really a reciprocal tariff.

• 1:38:46Sheel Mohnot?

  Now everybody realizes it was a funny situation last Wednesday when people were like, what the fuck are these numbers? And then, you know, the guy who did the math was like, oh, this is about our trade deficit, not reciprocal tariffs.

• 1:39:01Sheel Mohnot?

  I think like if you, if like now people are coming around and saying, oh, this is all about lowering trade barriers. I think that's bullshit because like you have Lutnik saying like, we need millions of Americans screwing in tiny iPhones or whatever. And, and you, and they also say that the tariffs are going to replace income taxes. So if those things are true, then it's not about leveling the playing field to zero. It's about like putting these tariffs in place to reshore. And I, I personally don't like that.

• 1:39:32Jordi Hays?

  Isn't it fascinating too? There's this focus on trade deficits, but we're completely ignoring like services and specifically like digital services. Right? So it's like, like, uh, like Switzerland, for example, you know, we have a trade deficit because they have eight ish million people. And we have hundreds of millions. And then they like make all the world's fine watches, which we just talked about. But then like, they also probably love Netflix. I guess, I guess that like a lot of people in Switzerland are, are subscribed to Netflix. And we're just like completely ignoring all of that.

• 1:40:06Sheel Mohnot?

  Yeah.

• 1:40:06Jordi Hays?

  And, and, uh, you know.

• 1:40:08Sheel Mohnot?

  Yeah, I have a follow. We're the richest, most prosperous country in the history of the world. It's fucking awesome. We can afford to buy all their shit. Like they don't need to buy stuff from us. They can't afford it.

• 1:40:18John Coogan?

  So, so, yeah. So the steel man here is like, uh, first off, do you think DJI and the consumer drone market is a problem? And then if so, what is your solution if not just ban DJI tariff DJI? Like we did a deep dive on GoPro versus versus DJI. And it really just felt like China was like, we are going to kill GoPro in the drone market. And they put so much firepower behind it. And I'm like, I still get that there's some weirdness going on here and it's important industry and it's dual use. And there's a million different factors. So how do you walk through that specific example narrowly? Let's, let's, let's take away the blanket tariffs. Walk through that for me and how would you solve this in a more free market, uh, more progressive fashion?

• 1:41:03Sheel Mohnot?

  Yes, that's a great question. So, so first, like we have tariffs on every country, not just our enemies.

• 1:41:09John Coogan?

  Yeah.

• 1:41:09Sheel Mohnot?

  Um, with Trump, but China specifically, I, I do think China's playing unfairly.

• 1:41:16John Coogan?

  Yep.

• 1:41:16Sheel Mohnot?

  And, and they're our enemy. And we, we shouldn't let our enemy get data in the United States. Like that could be really bad.

• 1:41:25John Coogan?

  Yeah.

• 1:41:25Sheel Mohnot?

  There definitely are national security issues with drones.

• 1:41:28John Coogan?

  Yep.

• 1:41:28Sheel Mohnot?

  Um, I also think we should ban TikTok.

• 1:41:31John Coogan?

  Sure.

• 1:41:32Sheel Mohnot?

  And, and so I think those things can be dealt with, but they have nothing to do with tariffs.

• 1:41:36John Coogan?

  Yeah. I guess one of my, one of my scenarios would have been if I could, if I could replay everything with everything I know now. Maybe you, you see what's happening with DJI and, and GoPro. And you say, hey, we are the richest country in the world. Uh, we do have, China buys a bunch of our debt. Let's lever up essentially and create a drone buying program from the government to stimulate demand for American made drones.

• 1:42:02Sheel Mohnot?

  Totally.

• 1:42:02John Coogan?

  Essentially backstop, uh, GoPro. Let them get down the learning curve. Hey, if they make these drones in America, we're going to buy them even more. Uh, and, and, and let us develop that. And then we are competitive and we say, hey, it is a little bit, we're, we're still shifting the invisible hand, putting our hand on top of the invisible hand. But, uh, it's still somewhat of a free market in the sense that like, just like what we did with EVs with Elon. Like anyone could have gone for those electric vehicle, uh, incentives. Elon did a great job taking advantage of it. Like, and we got a great product, you know, and sold really well eventually.

• 1:42:36Sheel Mohnot?

  Yeah, I think that's absolutely right. I think, and like, look, we moved in this direction already. Like, the CHIPS Act and IRA both did make good moves. Like, they, they enabled, they subsidized US chip manufacturing that are critical for military systems and other stuff. I think they, they have made some moves away from foreign chips. And so that all, that all stuff is good. I think like leading with a carrot is way better than leading with a stick, personally. And I think, like, the, the ideas you, you mentioned, John, are spot on. And by the way, like, we helped Tesla along the way. Like, we loaned, the US taxpayers loaned $500 million to Tesla. Like, that kind of

• 1:43:16Sheel Mohnot?

  thing, I'm totally in support of. Enable US manufacturing to be better, to compete on an even playing field by being more innovative, not by blocking, like, other countries from, from competing.

• 1:43:29John Coogan?

  Yeah, yeah. Jordy?

• 1:43:32Jordi Hays?

  Bummer to see the IPO window close. We had Klarna, StubHub, we'll see if Circle gets out. Klarna would have been especially nice for fintech broadly to get some marks.

• 1:43:45John Coogan?

  Circle's still at 86% on poly market for this year.

• 1:43:49Jordi Hays?

  Yeah, they might just be like, you know, crypto, we, we were born in the darkness. We're going out. Did you, did you have a take on the Circle IPO in general? I saw a lot of people just were not kind of loving the S1, particularly just based on how much they were paying Coinbase to distribute the token. I'm curious if you had a, had a, had a take on the IPO or dug into it at all. And you don't need to have any knowledge to have it. You don't need to have any knowledge to have a take, by the way.

• 1:44:20Sheel Mohnot?

  Yeah, no, I, I would say like on, on Circle in particular, like, I saw all the same stuff you saw. Coinbase gets half of the revenue from Circle's token and all this other stuff. But I don't, I don't have a strong take on how the IPO will perform. I, I tend to think that these things are somewhat, like, initially somewhat disconnected from the reality of what's going on. So like, I think, you know, We talked about Bridge last time I was on, and I think there became this stablecoin hype. And I bet if Circle was public at that point, they would have gotten a huge bump for no particular reason.

• 1:44:58John Coogan?

  Totally.

• 1:44:58Sheel Mohnot?

  Um, but I think overall stock market, yeah, like, what does, what does poly market say about Klarna? Is there a market for that?

• 1:45:06John Coogan?

  Oh, I don't know. Jordy, can you?

• 1:45:07Jordi Hays?

  Well, Klarna, I think officially pulled their.

• 1:45:10Sheel Mohnot?

  It pulled. Well, like, the thing is, these tariffs are especially, especially bad for Klarna, right? Like, it's consumer discretionary spend that you use BNPL on. And consumer discretionary spend in a recession or with high tariffs, like, goes, goes to the toilet.

• 1:45:30John Coogan?

  Yeah.

• 1:45:31Sheel Mohnot?

  So like, you're not buying that extra $2,000 item that you didn't exactly need.

• 1:45:35John Coogan?

  Yeah.

• 1:45:35Sheel Mohnot?

  And that's what you were BNPLing anyway.

• 1:45:38John Coogan?

  Yeah.

• 1:45:38Sheel Mohnot?

  So I think we've seen a firm stock.

• 1:45:41John Coogan?

  Oh, yeah.

• 1:45:41Sheel Mohnot?

  I think our firm stock got cut in half.

• 1:45:43John Coogan?

  Yeah, I want to go deeper on Circle because I feel like it's one of those companies that if they're about to IPO, I can't even name the founders. I don't know all the big investors. Like, it's this, it's this fascinating. This is a case with a lot of, a lot of crypto companies, but even Bridge, like, we heard the story of like, who made the money on this? Okay, they got acquired by Stripe. Like, they're very much in the Silicon Valley world. And Circle obviously is, but has been, hasn't really told their story in the way. And so it's interesting. They could have a meme stock moment where it's like, the, it's the primary way that you get exposure as a public markets investor to stablecoins broadly, I guess. And that could be a good narrative. It could just be a meme stock because, hey, crypto, it's, you know, whatever.

• 1:46:25John Coogan?

  But, but they haven't really told their story in a way that's broken through, at least with me. I don't know if you, if you've processed it any differently, but.

• 1:46:33Sheel Mohnot?

  Yeah, I think it's certainly less, less hyped than all the others. The CEO, Jeremy Allaire, I, I went to a stablecoin conference a couple of months ago and he spoke. And so he's very sharp. And he's, he's been at it for a very long time. He's like of a different, slightly different generation than us. Like, he, he started a company that IPO'd in, in like the 90s, like dot com boom. And then he was actually a venture capitalist. Like, he worked at General Catalyst for a little while.

• 1:47:01John Coogan?

  Oh, cool.

• 1:47:01Sheel Mohnot?

  Um, and then, and then launched Circle, whatever, 10 or 15 years, not, obviously not 15 years ago.

• 1:47:06John Coogan?

  Yeah.

• 1:47:07Sheel Mohnot?

  Bitcoin didn't exist, but, but, yeah.

• 1:47:09John Coogan?

  That was the best time to launch a stablecoin before Bitcoin. Getting really early. I mean,

• 1:47:15Jordi Hays?

  Well, so here's the bull case for USDC and like, and here's my bull case.

• 1:47:22John Coogan?

  Sure.

• 1:47:23Jordi Hays?

  So Tether is like the most profitable financial institution ever, right? Like it's literally, what are they, is it eight million dollars?

• 1:47:30John Coogan?

  It's like 50 million per employee or something.

• 1:47:33Jordi Hays?

  I forget the actual, you probably shared it at some point, Sheel, but it's like some absurd number. They're more profitable than like any of these other major financial institutions. The risk with Tether is like, it's opaque. You don't fully know what's going on. Like there could be, people for a long time said there could be systemic risk. You know, associated with Tether, they've been accused of a lot of stuff over the years. Constantly. Yeah, yeah, but, but they're dominant from a market cap standpoint. The second, the second biggest stablecoin is, is USDC at a $60 billion market cap. And a market cap is obviously just one to one with the supply, right?

• 1:48:11Jordi Hays?

  And then you go down the list, the next one is DAI, which is also, you know, run in a very like crypto native way from what I know. And then you are, to get to the next stablecoin made from a sort of true traditional Western institution, you have to go to First Digital USD, which is under a $2 billion market cap. And below that is PayPal USD, USD, which is an $800 million market cap. And so to me, I'm looking at Circle and it's like, here's like the,

• 1:48:42John Coogan?

  Power law winner.

• 1:48:43Jordi Hays?

  The dominant, you know, they're 80, they have 80 times the circulating supply as their next like regulated, you know, Western institution, and they have USDC. Like it's a pretty good ticker.

• 1:48:56John Coogan?

  I mean, the crazy part is we talked to,

• 1:48:58Jordi Hays?

  Not super sophisticated, but it, you know, brand matters.

• 1:49:00John Coogan?

  I mean, we talked to Zach Parre at Plaid and we were like, if you had, you know, full authority, you were like the president, could you speed up wire transfers in ACH? And he was like, absolutely, but it's not going to happen. And so it's like, yeah, maybe stable coins are here to stay and all the pitch about just, hey, it's just gonna, you're just gonna be able to transfer money two days faster. Like, that's enough, even though it seems like you should just be able to speed up the government transfers.

• 1:49:26Jordi Hays?

  What's your, what's your read on any sort of predictions on venture right now? I think that the lesson, the lesson in venture since 2020 has just been, take advantage of chaos, invest through market cycles, never stop deploying. I remember in 2022, we were talking about the, what is it? Denominator effect?

• 1:49:47Sheel Mohnot?

  Denominator effect, yeah.

• 1:49:48Jordi Hays?

  Denominator effect, but then it didn't fully play out. We saw this, I mean, we saw like a, again, a bifurcation of like the big funds, raising all the money on paper, but you know, if you're a specialist fund with like a strong story, you can, you know, still get, get funds done. But I, but I'm curious first about the venture market, and then I want to kind of ask more about portfolio stuff.

• 1:50:11Sheel Mohnot?

  Yeah, first, like maybe a fun tidbit for you guys is like, just the last few days, obviously markets have been in various states of turmoil and venture capitalists are, some of them are like trying to seize the day where like, for example, there have been a couple of companies in our portfolio that some investors have been really trying to invest in. But the companies are well capitalized and don't need the capital. And now the investors are like, hey, markets in turmoil, might this be a time that you would consider taking my money?

• 1:50:43Jordi Hays?

  Yeah.

• 1:50:46Jordi Hays?

  Yeah, yeah.

• 1:50:48John Coogan?

  Really living up to the vulture capitalist name. I like it. Making money.

• 1:50:53Jordi Hays?

  Yeah. How do you, how do you even think about, uh, there's going to be some enterprising founders that are like, look, I'm building a startup around that's, that's, you know, built to help solve, you know, global supply chains or something like, you know, the chaos is a ladder. I'm going to take advantage of this. To me, it's like, okay, if we're entering this sort of protectionist phase of de-globalization, maybe it's too early to make bets, but yeah. How do you, you see companies like actually being able to make something out of the chaos? Or are you just telling your, your portfolio, you know, just stay focused on the customer, ignore the noise, that kind of thing?

• 1:51:33Sheel Mohnot?

  It's really like stay focused on the customer, ignore the noise. I think we don't have any companies that are like super exposed for some reason or any other. I saw you guys have Jamie Lee coming on later today, which sounds like you timed that perfectly.

• 1:51:47John Coogan?

  Yeah, it is crazy. Yeah.

• 1:51:50Sheel Mohnot?

  Literally.

• 1:51:51John Coogan?

  I mean, there's a few of those companies that have been, I mean, that's been the thesis for a while, just general reindustrialization, but they really hit a royal flush this week.

• 1:52:01Sheel Mohnot?

  Yeah. So, you know, it's mostly stay the course. I think there like people are saying, okay, venture capital dollars are going to decline. But as you know, like the way it works is we raise a fund every few years and we have plenty of capital. So like, it's not like, you know, an LP, there's some impact on the markets today and that means we don't have money tomorrow. It's like, if there's any impact, it's a few years out, though it doesn't change how we invest. Now, the later stage investors, it is a different equation because for them, they have a certain timeline. They're hoping these companies go public and if the public markets are kind of frozen,

• 1:52:43Sheel Mohnot?

  that makes things difficult and, and like their thinking on an IRR basis, like has, their opportunities have declined if they can't, if the companies don't get out at a reasonable time.

• 1:52:55John Coogan?

  Yeah. So mostly just texting founders in the portfolio. Have you seen this with a, with a screenshot of the market?

• 1:53:00Sheel Mohnot?

  That's just what I always do.

• 1:53:02John Coogan?

  Yeah, exactly. I want to get your reaction to this post from Semel over at Haystack. He says, "Seed is again going to be the hot zone where nearly every VC fund will want to invest, just like when COVID struck and in the early, in early 2022, VCs shifted early to balance large checks by firing $3 million seed bullets. LPs should expect median seed entry prices to be up 50% in the next vintage." Does that seem like a good take or what do you think?

• 1:53:30Sheel Mohnot?

  No, I like, I love Semel, but I don't know if I buy that.

• 1:53:39John Coogan?

  Sea price is already pretty high, right?

• 1:53:41Sheel Mohnot?

  That's the thing.

• 1:53:42John Coogan?

  Yeah.

• 1:53:42Jordi Hays?

  Please, please.

• 1:53:44John Coogan?

  Please, please make them lower.

• 1:53:45Jordi Hays?

  Don't tell the founders this.

• 1:53:47John Coogan?

  There's like, wait a minute, I can raise my safe by 50% with one stroke of a pen? Let's do it.

• 1:53:54Sheel Mohnot?

  Yeah, it doesn't, it doesn't make sense to me because so we started this fund in 2019. And actually, like, the seed valuation is 2021 was an insane time, especially in fintech. Like, everything we were investing in seemed like it was like turning to gold and then, you know, and then maybe turning shit afterwards. But, but, but, but actually, like, seed valuations have actually increased from that time. And it's basically kind of in like a straight line upwards. And what he's talking about actually started happening in 2022. And a lot of the funds invested at seed in companies, you know, and, and the problem is, if you're a multi-billion dollar fund and you write a $2 million check into a company

• 1:54:37Sheel Mohnot?

  and you invested in the wrong company in the category, like, you don't get a chance to write a $250 million check into the right company. So I think it's pretty foolish when those funds invest at seed. And we have a bunch of examples now of like, of friends of ours who took money from a multi-stage, but like the multi-stage doesn't care about them that much because it's a small amount of money. So I don't know, I'm skeptical that this is going to happen again, or that it's going to re-accelerate and prices are going to go up. I don't know, we'll see. Well, we should make a bet and have Peter Walker from Karta give us the data in a year. I love his stuff.

• 1:55:19John Coogan?

  Can you talk about, there's this meme of like, oh, for a while, if you're building a consumer or something, like you're going to get steamrolled by what if Google builds it, right? And there's this story that Google is allegedly paying some AI staff to do nothing for a year rather than join rivals. Hilarious. I want your reaction to that. But then I also want to know, like, is there, does that meme exist in fintech? Is there, is there an idea that, oh, Amex or Visa or JP Morgan are going to build this? And has that ever actually happened in practice?

• 1:55:51Jordi Hays?

  Well, yeah, and even potentially on that, I'm curious, like, OpenAI wants to run your entire life. Have you heard any sort of like rumors or is any concern around people saying, oh, I'm building a consumer agent, you know, for financial, consumer financial services.

• 1:56:09John Coogan?

  Yeah.

• 1:56:09Jordi Hays?

  But then OpenAI might be like, oh, by the way, we launched a partnership with Chase and or we launched a partnership with Cash App.

• 1:56:16John Coogan?

  Yeah, we can analyze your credit score now with an agent and that that model, that rapper company got steamrolled. Yeah. What's your take on all that?

• 1:56:24Sheel Mohnot?

  Okay. So first thing I think you said was the rest invest situation.

• 1:56:27John Coogan?

  Yeah.

• 1:56:27Sheel Mohnot?

  Where, and so I thought it was really funny because you guys watch Silicon Valley, the TV show?

• 1:56:32John Coogan?

  Oh, yeah.

• 1:56:33Sheel Mohnot?

  So good. And there's that, obviously, there's the phrase rest invest. I learned it from that show. And it's certainly playing out of Google.

• 1:56:41Jordi Hays?

  I had no idea that that that phrase was like popularized in some way by the show.

• 1:56:46John Coogan?

  Oh, yeah.

• 1:56:47Sheel Mohnot?

  Yeah.

• 1:56:47Jordi Hays?

  I thought it was, I thought it was a 2021, like big tech thing.

• 1:56:51John Coogan?

  No, no, no, no. This was a thing going back like a decade.

• 1:56:55Sheel Mohnot?

  If you haven't seen it, you got to go back and watch. It's so.

• 1:56:58Jordi Hays?

  So I never could, I never could get into it because I, it was just too close to reality.

• 1:57:05John Coogan?

  Yeah, same thing.

• 1:57:06Jordi Hays?

  Like the most like, it was not like, I watch TV because like, I want to like, you know, not think, but then watching Silicon Valley is like, oh, that's an email I need to reply to. Like, I should follow up with that founder. You know, it's just like.

• 1:57:18John Coogan?

  My first company, Soylent, was in the intro to Silicon Valley, like in the intro sequence. And they're just like, making fun of me every single day. Also, one of the creators went to my high school and so like I knew him and he's like actively poking fun at me every single episode.

• 1:57:33Sheel Mohnot?

  Amazing. That's amazing.

• 1:57:35John Coogan?

  It was great. But yeah, it's very silly that Google would let this even leak out. I don't know how that happened, but.

• 1:57:40Sheel Mohnot?

  Totally. It's crazy. I mean, the things you hear out of Google are so crazy.

• 1:57:45John Coogan?

  It's wild.

• 1:57:46Sheel Mohnot?

  I think more, more so than any other big co, like my wife works at Meta and they've like really got their shit together, like the year of efficiency, stuff like that. I think probably before then it was had stuff like this, but not now.

• 1:58:00Sheel Mohnot?

  Okay, so that was that was topic one. I think topic two was like, what if X company builds this? And is that the case in in fintech?

• 1:58:06John Coogan?

  Yep.

• 1:58:06Sheel Mohnot?

  I I don't think so. Like, in fact, you actually had, look, one of the sponsors, Ramp. So Stripe had built Ramp. Stripe had a corporate card. And it didn't work. Like, they ended up investing in Ramp and deprecating that card. So I think people have tried to do stuff. There is the, what if Stripe does this? What if Plaid does this? And there are, in some cases, I think that's totally valid, but for the most part, I think there's plenty of green space out there. And, you know, Stripe has been acquisitive. Obviously, we talked about that before.

• 1:58:43John Coogan?

  Bridge.

• 1:58:44Sheel Mohnot?

  There's nothing I'm super afraid of. I will say in some categories, like, for example, in wealth management, there was the wealth fronts and betterments of the world, the robo-advisors, and people said, okay, like, we're not charging 2%, we're going to charge you 25 bips. But the reality is that the service offered by somebody who's charging 2% is different than what they offer at 25 bips. And the 25 bips solution was fairly easy for Vanguard to build. And Vanguard became by far the largest robo-advisor in the world.

• 1:59:12John Coogan?

  Got it.

• 1:59:14Sheel Mohnot?

  But I'm not I'm not afraid of that in general. In fintech too much.

• 1:59:18Jordi Hays?

  Do you think that, do you think humanoid robots present an opportunity for loan sharking as a service?

• 1:59:25John Coogan?

  Come break your legs autonomously.

• 1:59:27Jordi Hays?

  Break your kneecaps autonomously. It's like, hey, we're going to offer you this great rate, or whatever. It's secured against your kneecaps.

• 1:59:36Sheel Mohnot?

  It's funny, like, we, our tagline for our fund when we started, it was, everything is fintech. It would be funny if we invested in a humanoid robot company and then just, we were like, deadpan, like, what do you mean? Like, obviously, the use case is for loan sharks.

• 1:59:52John Coogan?

  Yeah.

• 1:59:55John Coogan?

  I mean, I was talking to a sales guy.

• 1:59:56Jordi Hays?

  I'm curious, like, my thought goes with, the, do you think that AI can, can get, is already or could get materially better at underwriting than? Then a human just spending, you know, months on an opportunity and is that something that, do you think that fintech broadly has fatigue around investing in like AI lending? Just because it's been sort of this like ongoing narrative, isn't there like, what's the, what's the public company that was sort of promising this for a while? Something.

• 2:00:32John Coogan?

  I mean, there was Metro Mile, which was better underwriting.

• 2:00:35Jordi Hays?

  Upstart, yeah.

• 2:00:35John Coogan?

  But even Metro Mile is better underwriting for your car insurance based on how you drive. They put a GPS tracker and like a gyroscope in there, basically. See if you're stomping on the brakes every two seconds, give you a higher insurance premium. A lot of promise there, but not a lot of, you know, massive adoption over time.

• 2:00:54Sheel Mohnot?

  I think they didn't execute that well. And I think with Metro Mile, the, there's actually Root has done a better job of it. But Metro Mile, it was primarily just mileage based, the number of miles you drive. And then Root gives you a phone, you put your, your phone in it like checks if you're breaking hard and where you're driving and stuff like that. So I, I think that there are opportunities to be used in insurance. In underwriting for loans in particular, it can be tricky because you're, the regulatory framework in the United States, Equal Credit Opportunity Act, Broker Reporting Act, et cetera, that you're not allowed to discriminate on the basis of race and gender. And some of these other things are tied to that.

• 2:01:33Sheel Mohnot?

  So that, that can become tricky and you're actually, you have to respond, you have to give people the reason why they were denied. Like it's adverse action notice. So you can't have a black box model that's like, here's all the data.

• 2:01:50John Coogan?

  They just give you a massive matrix of weights and they're like, this is why you're denied. Figure it out.

• 2:01:57Sheel Mohnot?

  Totally. So that.

• 2:01:59John Coogan?

  Tensor number 76 was activating for you, so get out of here.

• 2:02:05Sheel Mohnot?

  Yeah. Um, so actually, you know, if we didn't have that lending would be probably more efficient and like you'd better be able to target the right customer, but we do have those things for a reason. And so we can't have a black box model. Um, and so, so there are actually companies, we invested in a company that's like in part detecting bias in, in AI underwriting for this purpose to make sure that you're compliant.

• 2:02:32John Coogan?

  Yep.

• 2:02:34Sheel Mohnot?

  And yeah, so anyway, I, I, I think it can be used and can be super useful, but because of those regulatory bound like guidelines, I'm not sure it's going to like be a step change in underwriting.

• 2:02:45John Coogan?

  Yeah, makes a lot of sense. Uh, Jordy, last question, you want to let Sheel get out of here?

• 2:02:49Jordi Hays?

  No, this is great. Always a pleasure.

• 2:02:50John Coogan?

  Always fun.

• 2:02:51Sheel Mohnot?

  Super fun, guys.

• 2:02:52Jordi Hays?

  Looking forward to the next one.

• 2:02:53John Coogan?

  Yeah, this is great.

• 2:02:54Sheel Mohnot?

  Likewise.

• 2:02:55John Coogan?

  Have a great rest of your day.

• 2:02:56Jordi Hays?

  Godspeed.

• 2:02:56John Coogan?

  We'll talk to you soon. Uh, well, we got some breaking news, another massive funding announcement coming in to the studio. Victor from Krea, is that how you pronounce it? Krea, uh, is coming in, uh, AI video company that just announced a massive, uh, fundraise. Uh, let me, let me look up if I can find the, the details, um, of this fundraiser so I can get everyone up to speed. Before we bring Victor in here, the website is krea.ai, K-R-E-A, uh, and they just announced a huge funding round, eighty-three million dollars, just a couple million over, uh, over, uh, Jay, uh, not that it's a competition. They

• 2:03:41John Coogan?

  got Andreessen Horowitz, Bain Capital in the, in the round. Um, the past 14 months at Krea have been hectic. We rolled out over 50 major product updates, grew to over 20 million users organically, and they 20x their revenue, all with a team of eight, working out of a living room in San Francisco. That is fantastic. You love to see growth like that. It doesn't happen every day, but it's happening more and more in AI. So excited to bring Victor into the studio and talk about that. They write, "The numbers are exciting, but they can miss something crucial. The team behind it all. Crea is the work of a small, talented group of imaginative, incredibly

• 2:04:21John Coogan?

  dedicated people. And yes, most of us still live together." That's fun. "Until now, we've never shared metrics or announced our funding. Heck, we didn't even have a blog until a few hours ago. Those details always felt secondary compared to what truly matters to us, making AI intuitive and controllable for creatives. Now, after the release of our redesign, the growth of our team and recent funding, it feels like the perfect time to open up about what inspires us and what we're building towards." So they write, "We're living through a moment where everyone talks about automation, APIs, and how AI and software are eating the world, perhaps too much. Don't get us wrong. While AI is powerful, transformative, and is going to radically change creative work, creatives

• 2:05:02John Coogan?

  aren't going anywhere. Forty thousand years ago, we painted red ochre onto cave walls. Later, we drew with graphite on paper. Today, it's complicated. We use cameras to digitize light through glass lenses and silicon sensors, transferring data through metal wires to illuminate the LEDs lighting up the screen you're reading on now." How do you know I didn't print this out? I could have printed this. The printer still works at TBPN. We might have shifted to laptops, but you never know. Too much pushback. Don't assume anything. No, I am reading this on the screen. Paper usage. And, uh... Do we have Victor in the waiting room yet, by the way? Not yet. "Old tools and workflows will disappear, but our creative itch won't, and I agree with that. Excited to dig into that with him. We will build new and more

• 2:05:46John Coogan?

  powerful tools to keep doing what we've always done, master new mediums for self-expression and storytelling. AI will render some tools obsolete, but not the people behind them. We see AI as a new medium that lets us express ourselves through any format: text, video, sound, and even 3D. Such a medium needs better, smarter, and more controllable tools. That's where Crea comes into play." They say, "It won't replace... AI will not replace creativity. Creativity is not disappearing, but the walls between creative mediums are. Traditionally, excelling in one creative medium rarely translated smoothly into another. AI changes that, and we're bringing..."

• 2:06:24John Coogan?

  Victor into the studio to tell us more about Creia and the fundraising. So, welcome to the stream Victor. You here?

• 2:06:31Jordi Hays?

  Yo.

• 2:06:31John Coogan?

  How you doing?

• 2:06:32Jordi Hays?

  What's going on?

• 2:06:34Speaker 07

  Yeah, I'm here.

• 2:06:36John Coogan?

  Great. Can you give us a brief-

• 2:06:38Speaker 07

  Doing great. Great to meet you guys.

• 2:06:39John Coogan?

  Fantastic.

• 2:06:39Jordi Hays?

  Uh, is, uh, is the, is the office gonna change with this new fundraiser? I gotta ask. Are you, uh, are you guys gonna stay posted in the living room?

• 2:06:51John Coogan?

  Do we have you Victor? I think we might have lost you.

• 2:06:53Speaker 07

  Seems like we're, seems like we're having some technical issues.

• 2:06:56John Coogan?

  Okay, well, we, we can hear, see and hear you now.

• 2:06:59Speaker 07

  Yeah, okay, let me go downstairs.

• 2:07:00John Coogan?

  Far away from the wifi router. I mean, that is the issue with working at home. Complicated wifi. You need the enterprise solution soon. Now that you have the big series B done.

• 2:07:08Speaker 07

  I know, I know. It's gonna be so very soon.

• 2:07:12John Coogan?

  Yeah.

• 2:07:13Speaker 07

  Oh shit, they are doing another meeting, so I'm gonna steal Diego's room.

• 2:07:17John Coogan?

  This is great.

• 2:07:18Jordi Hays?

  I love, I love getting the, I love getting the tour.

• 2:07:21Speaker 07

  You guys wanna see the office?

• 2:07:22Jordi Hays?

  Yeah, yeah, yeah. Let's just do a tour.

• 2:07:24John Coogan?

  Anything that you can show us. You can turn around. Oh, okay. There you go.

• 2:07:27Jordi Hays?

  No API keys hopefully.

• 2:07:28Speaker 07

  Mexican music going on, that's cool.

• 2:07:30John Coogan?

  That's fantastic.

• 2:07:31Speaker 07

  I'm real life.

• 2:07:33Jordi Hays?

  Yeah, what's up guys?

• 2:07:34John Coogan?

  Wow, hey guys. How you doing?

• 2:07:35Jordi Hays?

  Congratulations on the milestone.

• 2:07:38John Coogan?

  Looking great.

• 2:07:38Jordi Hays?

  Wow, you guys said, you guys were not kidding about the living room, but you've really built it out. I love it.

• 2:07:44John Coogan?

  That's amazing.

• 2:07:44Speaker 07

  It's looking, it's looking good.

• 2:07:46John Coogan?

  That's good.

• 2:07:47Jordi Hays?

  Uh, nice. Uh, why don't you introduce yourself? Uh, John, John was gonna ask you that and then I cut him off.

• 2:07:52John Coogan?

  No, you're all good.

• 2:07:55Speaker 07

  Yeah, sorry, sorry about that.

• 2:07:56John Coogan?

  No worries.

• 2:08:00Speaker 07

  Oh, so, my, my background, my background, my, yeah, like, I guess on my background, like, the T L D artist, I, growing up, I was very interested into creative things of all kinds. I mainly had a, a music band and I was doing from playing multiple instruments in the little studio that I created in my house, to producing music, mixing, mastering, like, learning about all of these, uh, processes around music production. But through my music band, I also got super interested on doing photography and like, doing different kinds of content for that music band.

• 2:08:39Speaker 07

  So that way I, I explore like many different things from graphic design, 3D graffiti art. I, I also had like a big passion for that. And and at some point, I was, that was in twenty fifteen. I was in, I was just like finishing, I just finished high school. And I didn't, I was not sure about what to do after that. And I had like two options in in front of me. One of it was go and do classical guitar studies at the Conservatory of Barcelona, at the Conservatory of Guitar of Barcelona. And the other one was doing something around computer science or physics. I really liked math.

• 2:09:19Speaker 07

  And I guess that what I like about math is is kind of like the challenges that it poses and like the interesting. Yeah, like I I guess I like, I I love challenges in math. Put like a a lot of challenges in front of me. But in the end, I found like this middle ground on this degree that it was called audio visual systems engineering. It was kind of like this degree where they showed you how a microphone works, how MP3 encodes audio, how MP4 encodes uh video, et cetera. And that's where I met Diego, my co-founder. That was like ten, ten, ten years ago. He ended up in that same degree, following kind of a similar story. In his case, he came from having a lot of interest in film and a lot of interest in in three D as well.

• 2:10:03Speaker 07

  But also, he also loved programming and he also loved engineering. So we both ended up like in in that degree. And on the second or third year, I got introduced. I mean, first of all, I loved coding, like right, right after getting into the degree. I loved coding, um, found it like extremely creative. Later on, I found about AI. Um, I was mind blown by deep learning, like just like the fact that you can have these new networks, learning by themselves from data and being able to do such complex, complex tasks was very interesting to me. And when I discovered about GANs, that they were like very early models for image generation, that's when I fell super deep into the rabbit hole.

• 2:10:46Speaker 07

  And I ended up like reading a lot of papers, doing a ton of implementations by my own from all these papers that they were out there back when everything was open source. Uh, and and and ended up.

• 2:10:59John Coogan?

  The good old days, the good old days. Uh, do you have a first question or?

• 2:11:04Jordi Hays?

  No, go for it.

• 2:11:05John Coogan?

  I, I, I, 20 million users, absolutely massive, congratulations. Where are you seeing those folks come from? Is it consumers just having fun? Prosumers who are maybe doing little contracting work monetizing their creativity on social networks? Or are you already in the enterprise or all three?

• 2:11:23Speaker 07

  All three. I think that up until recently, there were like two very well-defined blogs of users. One of them, it was a consumer type. It was people who, this technology gave them a zero to one when it comes to creative freedom or to like, uh, enabling them to create. It's people that didn't necessarily come from a creative background, but they had a lot of joy out of expressing their creative ideas using this technology. And they were, they were paying for the subscription almost in the same way that you could pay for a video game or that you could pay for a camera. Then we had the professional and, and the professional was that

• 2:12:06Speaker 07

  user that did have a creative background and that he was using our technology. I went on, I'm in our platform to speed up some of their processes. These are speed ups like Varai depending on the, on the industry. Like you, you would see architecture studios coming to Korea with very low resolution renders and using our enhancer to get these renders up to 4K resolutions with very crisp textures. Or you would see game designers coming to our real time tool, putting a bunch of ideas around characters and being able to create prototypes for some characters that they were designing.

• 2:12:47Jordi Hays?

  Can you talk about just general adoption? So during the, during this sort of like Studio Ghibli moment, it's still, you know, top of mind. We saw a lot of people that still weren't aware, they had no idea how these images were being created. John and I think that some people thought it was like Snapchat filters or something like that. Can you talk about just like consumer sort of awareness and adoption broadly? You know, are, are, are you guys still finding people every single day that are just sort of like completely new to this sort of new image generation models? Or, or, you know, how, what, what do you think the broad consumer awareness is today?

• 2:13:27Speaker 07

  I mean, I was, I just came two days ago from a short trip to New York. And I feel like that, that trip to New York made me realize how deep in the bubble we are here in SF. Like, I, I, I think that I take for granted that people know that nowadays you can generate images with artificial intelligence. And that's not the case. Like, I think that we haven't, we haven't reached. I, I wouldn't even, I wouldn't even know what's like the percentage of, of like reach that we have had right now, but it's definitely very, very small. Like, this technology is still nascent. People like us are trying to make it intuitive and usable for really anybody to just like grab a phone, type a URL and be able to create an image very easy.

• 2:14:10Speaker 07

  But I think that people still need to know that this is even a possibility. Like, I think that, that they, they just don't even think that some of the problems that they have when it comes to marketing or when it comes to doing product design can be solved today by artificial intelligence. So I don't know if I'm the best one, like if, if I'm the best person to have like a good sense of what is the core adoption because of how deep we are in the SF bubble.

• 2:14:37Jordi Hays?

  Yeah.

• 2:14:38Speaker 07

  From my experience that we, that I've had in New York, I don't know, like, I have this fun story that I was on an Uber. And the Uber, like, uh, she, she just like saw that I was like talking on the phone in Spanish and she was from Puerto Rico. So she started like talking with me and asking, asking me what, what I was from and what I was doing. And this woman, she had like, um, like she was like selling a sort of like beauty products on Instagram.

• 2:15:01Jordi Hays?

  Mm-hmm.

• 2:15:02Speaker 07

  And, and I saw it and she started asking me, oh, so can I use your tool for doing like this photography? Or can I use like all these things? And then she was talking, I was like, yes, you can do it, but you need to go through a process. It's not like some magic thing that you like go there and, and like D I I does everything for you. You need to go and train a model with your product. After the model is trained, you go to the image generator. There you create like all the assets that you want. And after you have this workflow in mind, uh, uh, after you have like this workflow in place, you can generate as many assets as you want and like your workflow is going to be extremely optimized. Yeah.

• 2:15:37Jordi Hays?

  How do you, how do you think about prompt engineering long term? Is it, is it, you know, I, I remember.

• 2:15:45John Coogan?

  Like a year and a half ago, maybe a year ago, everybody said every company like prompt engineer is going to be this new role. And now it feels like it's getting easy enough to prompt a lot of these tools. I'm sure like Korea, that maybe it's just not necessarily, maybe it's a skill set, but not necessarily a job. But I'm curious how you think, um, do you think that prompt, prompt engineering will still matter in five or 10 years? Or it'll just be super intuitive?

• 2:16:14Speaker 07

  Um, I mean, prompt engineering at the end of the day, it's, it's, it's, it's just like being able to communicate your ideas in a clear way with like this technology, you know? Like we have like this AI model that can understand language and that can do things. And from engineering is just like the way that you tell this knowledge that we have encapsulated, how to do things or what exactly to do. So at the end of the day, it's just managing and I do think that this feels like a new way of doing software. And I do feel like this is gonna, like in the future, most, most software that we see out there has been created by a very big percentage

• 2:16:56Speaker 07

  through prompt engineering, through steering AI models towards whatever you want to accomplish. And I see this on the, on the visual space, like I see, I see us building Korea in the future more and more through instructions. I see our users working with our platform more and more through instructions rather than through just like,

• 2:17:21John Coogan?

  Yeah.

• 2:17:22Speaker 07

  Like type, type, typing, typing a prompt and just like getting an image. I think that the Disney model from OpenAI kind of shows that.

• 2:17:29John Coogan?

  Yes. Speaking of the new OpenAI model, uh, it seems like they've evolved the actual underlying algorithm. It's not purely diffusion based. Are there new buzzwords or keywords that, uh, have you reverse engineered any of how they're doing that? Uh, because it seems like there's a number of steps, like they're actually transforming the prompt. There's some reasoning in there. The image loads top to bottom, which we haven't seen before. Mid journey kind of diffuses everything from blurry to crisp, just the whole image at a time. It seems like they're doing some sort of blocks or line by line rendering. What can you tell us about how that system actually works?

• 2:18:07Speaker 07

  I don't have a, I mean, I have some intuitions, but I don't like super, I don't have high confidence on how it works. It seems like there's some auto-aggressiveness going on.

• 2:18:17John Coogan?

  Yeah.

• 2:18:17Speaker 07

  And we have already seen similar things with Croc image generation.

• 2:18:21John Coogan?

  Mm-hmm.

• 2:18:21Speaker 07

  But I feel like to me, what is really game-changing about this new image model is the, it's like very similar to what we were like, uh, talking about before. Like this, if this is an image model that is able to reason and it's able to understand instructions.

• 2:18:38John Coogan?

  Mm-hmm.

• 2:18:39Speaker 07

  Like it's able to understand, here's like the picture of my dog, turn it into Studio Ghibli.

• 2:18:45John Coogan?

  Yeah.

• 2:18:46Speaker 07

  And, and like this, this is like something new. This is like something that previous diffusion models, we're not good at.

• 2:18:51John Coogan?

  Yeah.

• 2:18:52Speaker 07

  Like the models are good at, you have like a text and you can generate an image that kind of represents that text. But it's very hard to have them reason and to have, think about like what you want to do and what is the instruction uh, that the user wants and how to accomplish that goal.

• 2:19:06John Coogan?

  Yeah, yeah. It seemed like there was like, how, it was like everything that style transfer should have been, plus the, the latest and greatest in diffusion models. Like they really like packaged that up very well. And so I think that's why it broke through. Uh, but anyway, congratulations on the round. Thanks for, uh, thanks so much for stopping by.

• 2:19:23Jordi Hays?

  Yeah.

• 2:19:23John Coogan?

  And thanks for the office tour unexpectedly. That was, that was really fun. Uh, but we'll let you get back to work.

• 2:19:28Jordi Hays?

  Yeah, give our best to the whole team.

• 2:19:30John Coogan?

  And, uh, and we'll talk to you soon.

• 2:19:32Speaker 07

  Sounds great. Thank you so much for having me.

• 2:19:34John Coogan?

  Thanks a lot. Talk to you soon. Bye. Very interesting.

• 2:19:37Jordi Hays?

  Nice. Uh, we got Leaf coming on from public.com. I'm curious if he's been sleeping at all.

• 2:19:45John Coogan?

  It's a wild time in the market. He has some interesting data on what's happening on public because that's where people go to trade. Uh, multi-asset investing, industry-leading yields, they're trusted by millions, folks. You've heard us do the ad reads before, but now we have Leaf in the studio, breaking it down for us. And we will bring him in right now. How you doing, Leaf? Welcome to the stream.

• 2:20:07Jordi Hays?

  Boom. What's going on? Great to finally have you.

• 2:20:11Leif Abraham?

  Nice. Took some. What's going on? Let's go.

• 2:20:15Jordi Hays?

  I was just saying.

• 2:20:16Leif Abraham?

  I had my caffeine already, so that's why I'm like.

• 2:20:19Jordi Hays?

  Good.

• 2:20:19John Coogan?

  Fantastic.

• 2:20:20Jordi Hays?

  Good. Somebody was commenting yesterday about our caffeine consumption.

• 2:20:24John Coogan?

  Oh, yeah.

• 2:20:24Jordi Hays?

  Like, yeah, it's easily, easily 500 milligrams plus.

• 2:20:28John Coogan?

  Oh, yeah.

• 2:20:29Jordi Hays?

  At this point. John, that's 500 milligrams during the show.

• 2:20:31John Coogan?

  Yep.

• 2:20:32Jordi Hays?

  But he's like built like a horse, so he can, he can take it. Uh, how, how are you doing? Uh, we were just joking about, uh, whether or not you had slept at all the last week. Um, I know it's been, uh, busy, you know, I'm sure it's been a busy time for you and the, and the whole team.

• 2:20:48Leif Abraham?

  It's been busy, but ours doesn't have, our systems have been, have been up at least compared to other folks, so.

• 2:20:54John Coogan?

  That's great.

• 2:20:56Jordi Hays?

  Yeah, that's good. Um, walk us through, uh, some, I mean, I'm mostly curious to hear, uh, you had shared on X yesterday about how there had been more buyers than sellers over, at least in certain moments over the last week. Um, uh, maybe break down that data point and, and then we can talk about some other stuff, uh, that's top of mind.

• 2:21:19Leif Abraham?

  Yeah. I mean, generally speaking, just like a mini step back is like,

• 2:21:25Leif Abraham?

  this generation of investors, like call it especially millennials, like, man, they have been through market cycles like crazy in the past five years, right? And.

• 2:21:34Jordi Hays?

  Oh, yeah.

• 2:21:34Leif Abraham?

  Or even just like through their lifetime. And I'm, I like, I even saw some of, some like some meme on, on X the other day of like millennials experiencing their fourth once in a lifetime opportunity of a drop in market, you know?

• 2:21:44Jordi Hays?

  Yeah.

• 2:21:45Leif Abraham?

  And so on. And I think especially like the March 2020 drop where like surface breakers hit and so on.

• 2:21:55Jordi Hays?

  It's crazy.

• 2:21:55Leif Abraham?

  Is still in people's minds. And I think that specifically because you saw a lot of, um, like individual investors actually also making money on that. Um, and I think that has stuck with a lot of people. And so generally speaking, this behavior of buying the dip is a little bit retail investing culture now. And so whenever you see these like massive drops, this is really when we see some of our best days.

• 2:22:18John Coogan?

  Yeah.

• 2:22:19Leif Abraham?

  Um, and so yesterday was like, you know.

• 2:22:21John Coogan?

  Yeah.

• 2:22:21Leif Abraham?

  One of our record days in just deposits, for example, and yeah, but yeah.

• 2:22:25John Coogan?

  Yeah. Well, my reaction, uh, you know, the stock market was down 5% back to back days. And I was just like. What is everyone complaining about? We're not even hitting circuit breakers. Like, this is not that crazy to me because I remember 2020 and it was way crazier. But of course, like, it's very serious.

• 2:22:41Jordi Hays?

  Can you actually break down the mechanics of what exactly is happening? And what truly triggers the circuit break?

• 2:22:51John Coogan?

  Yeah.

• 2:22:53Leif Abraham?

  I don't have the exact numbers in front of me, but it's essentially just if it drops too quickly to, you know, specific thresholds, I believe it's 7% and then 10 and 15 or so. Essentially, they pause the markets and that didn't used to exist in the past, right? And so it's essentially like a little bit of like a safety trigger, like a speed bump to, you know, make sure that investors can take a breather when these markets start to drop too quickly.

• 2:23:25John Coogan?

  Yeah. In Japan, don't they have lunch break in the middle of the?

• 2:23:28Leif Abraham?

  They do. Not just in Japan, other countries too.

• 2:23:30John Coogan?

  Other countries too. I love that. But yeah, it makes sense. I mean, a couple of years ago, when the algorithmic trading got really popular, there was like the flash crash.

• 2:23:39John Coogan?

  I think the market traded down like 20% in like two seconds and then went back up. And yeah, obviously you want to avoid that. What about overnight trading? You always hear, oh, you're watching the futures market and it seems like somebody has an edge here that they can trade before the market opens. Is 24/7 trading coming to America? We've heard some rumors. Is there a way to get in on that action?

• 2:24:05Leif Abraham?

  Journalist being, I think, is definitely coming. Like, it will also come to public at some point. Right now, we essentially have, you know, 4:00 AM to 8:00 PM. But the thing that you have to think of is that each trading window has its own participants and its own liquidity and execution venues. And so think of it as like this, the regular opening between your 9:30 and 4:00 PM. That's the most liquidity. It's when like most people participate. You could call that the healthiest time in the market in theory. Then you have essentially pre-market and post-market, which is, you know, 4:00 AM to 9:30 and, you know, 4:30 to 8:00 PM. And then you have overnight, which is like the new thing.

• 2:24:46Leif Abraham?

  Overnight, right now, there's essentially only like one major player who drives the liquidity for that. And what happens there is that because you have only one player, you have a lot of. Um, like, or like, yeah, if you have not asked many platforms participating yet. And so you can have these moments where there's a lot of kind of unilateral flow happening. And that's why in the, in the, in the overnight markets, you often see certain stocks just suddenly rally. Also on, and that is a little bit, I don't want to call it fake, but it's a little bit like, it has these wild swings because the, the types of people that trade in those times of the markets.

• 2:25:29Leif Abraham?

  And it's a concentrated liquidity pool. And so, you know, these swings just happen, you know, way more dramatically. And so you often have these moments where like, in overnight, a stock goes up and you see on Twitter, everyone's like, I'm sorry, on X, everyone like, posting the screenshots of like, oh my God, you know, Palantir is going nuts right now. Or whatever the company might be. And then suddenly like nine thirty market opens and it goes, goes down and everything kind of normalizes again, right? And that is really just because each market window has their own participants and their own pools of liquidity. And so you kind of have to take a little bit with a grain of salt, like, can you play that? Maybe, but there's always some risk there as well.

• 2:26:08John Coogan?

  Can you talk a little bit about information diets? Uh, and really I want to know what events that are predictable, not like Trump imposing massive tariffs all of a sudden on liberation day. But what can we count on like clockwork every single day to be the highest volume day of the year? Is there a Super Bowl of, of stock trading that happens, whether it's earnings day or jobs day? Uh, what, what are the big reliable sources of high liquidity in the market?

• 2:26:43Leif Abraham?

  Um, I don't know if I have a good answer there. My, my gut reaction would be just from internal measures like Monday mornings. Because you have all, you have a lot of queued orders from the weekend and stuff like that.

• 2:26:54John Coogan?

  Yeah, makes sense.

• 2:26:55Leif Abraham?

  You could execute it at the open.

• 2:26:56John Coogan?

  Okay.

• 2:26:56Leif Abraham?

  Um, because not everyone will trade pre-market and stuff, because spreads are wider and so all this, all these things.

• 2:27:03Leif Abraham?

  But specific days, not really sure to be honest.

• 2:27:06John Coogan?

  Maybe like big tech earnings too is kind of like a season for that.

• 2:27:09Leif Abraham?

  Generally speaking, it's always like, it's often just driven by market events, right? And at the end of the day, people will trade when they see opportunity.

• 2:27:18John Coogan?

  Yep.

• 2:27:18Leif Abraham?

  And if you can predict that, let's start a hedge fund together tomorrow. But other than that, but other than that, you know, it's, it's like, it is driven by these, by these moments, right? And whenever, like, we have good days when the markets are in the news, no matter which direction. But as long as the markets are in the news, we have good days because people get inspired one way or the other.

• 2:27:38John Coogan?

  Yep.

• 2:27:38Leif Abraham?

  And, you know, so, so in a way, trading volumes for companies like ours are a little bit like competing with any other thing that competes with attention. Because, you know, if markets are in the news, you get inspired by something and that might drive action and that's what we see.

• 2:27:54John Coogan?

  Yeah.

• 2:27:55Jordi Hays?

  What do you see from a demographic standpoint? I'm curious, so public obviously offers access to bonds, which, you know, it was probably good to be in bonds, you know? If you sold last week before liberation day, but, but do you see a lot of demographic differences? You know, sort of like Gen Z's basically like, uh, bonds for me are just like, you know, GameStop, right? Like, I, you know, I always know it's gonna be worth something.

• 2:28:21John Coogan?

  Yeah, it's a store of value.

• 2:28:22Jordi Hays?

  It's a store of value, right? Uh, but I'm curious if you see sort of, um, pretty specific, uh, activity across different demographics in terms of interest in these different types of assets.

• 2:28:34Leif Abraham?

  Yeah, I mean, straight up bonds always skew older, just from the perspective of the older you get, the more you're like thinking of preservation versus growth.

• 2:28:43Leif Abraham?

  But then I think what's interesting now is that, so we've launched multiple yield accounts essentially. So you have your high yield cash, which is, you know, similar to a savings account, you just get your yield and it's variable based on interest rates and such. Then you have like your bond account, which is essentially like a basket of corporate bonds underlying. And then you have like your treasury account, which is like US government treasuries. And those kind of simplify. The investments into bonds because you just deposit money, earn yield. It's like very simplified and just like you don't have to like pick certain bonds and stuff like that. So what we've seen is with that is that um a lot of people are using those to just put money into the markets, waiting for these moments of of uh um like of opportunity, right?

• 2:29:24Leif Abraham?

  So what we've seen in the last few trading days essentially is that people cycle out of the the yield accounts and into stocks and ETFs because they essentially had this cash lying around and we're like, okay. You know, I totally what we've been hearing a lot is that like, hey, after Trump was elected and the market started ripping and there were, you know, all time highs and a bunch of things going on all the time, that there was also a bunch of you know, individual investors who were essentially feeling like, oh, I'm just buying the top right now. And so they put it into these yield accounts. But then also, the minute you saw things drop the way they've done now, they've basically cycled it out of the yield accounts into stocks and ETFs specifically. So so you're so you're seeing younger generations using it less as a hey, I'm gonna now actually hold the bond to maturity for ten years from now

• 2:30:09Leif Abraham?

  and more use like these account ties that we've created for, you know, just like earn some yield on your stuff, you know, uh until you um you know, actually see other opportunities.

• 2:30:18John Coogan?

  Yeah.

• 2:30:19Jordi Hays?

  Do you think AI is already helping retail investors better understand the companies that they're investing in, right? Every public company is putting out a huge amount of information unless you're becoming just overly uh obsessed with this specific stock. It's hard to figure out what's what's important. What should I be looking at? Um, uh, what have you guys seen? I know I know you've like, you know, released products to help people leverage all of that data with AI, but I'm curious what you're seeing.

• 2:30:49Leif Abraham?

  That's a great layout, Jody, by the way. Thank you.

• 2:30:53John Coogan?

  Real softball.

• 2:30:54Leif Abraham?

  Trading to my pitch, you know? Thank you for sponsoring.

• 2:30:57Jordi Hays?

  Yeah.

• 2:30:59Leif Abraham?

  But uh uh yeah, a hundred percent. And like we obviously launched Alpha, which started off by just you can swipe down on any stock, ask any question about the stock. And um, you know, and that just created this like bite sized researching for for things. And we've kind of fed the model with a bunch of data that we already had from years ago, like, for example, we acquired a company like three, four years ago that was essentially a tool that turned all the SEC filings that had, you know, Custom company KPIs of like subscriber numbers and you know how many cars has Tesla shipped and things like that. Into more structured data and then we use that structured data to kind of train our models and such. To make that very easily accessible. Now, what now has happened is that it's much more proactive than you know than just you kind of have to pull information.

• 2:31:43Leif Abraham?

  And so the obvious one is what we call why is it moving, which essentially. If a stock is going in either direction very heavily, we kind of pop this card on that page. And tell people. You know, the like why this thing is likely moving right now and then you can tap on that. That brings you into a conversation with Alpha. Gives you more, you know, granular breakdown on that. And so it's much more the the pulling versus the. Uh, like much more like the the pushing versus the pulling. And I think that's also just generally where where it's where where it's going. But it's but like what's awesome to see is that these like. These like bite sized contextual moments where AI can be super fast. Where it's just really great at summarization.

• 2:32:24Jordi Hays?

  Yeah.

• 2:32:24Leif Abraham?

  And can also go against biases, right? So like if we go for news stories, for example. We sort of say that QA multiple sources. So we're not just coming from one source and pop it to you, but we QA multiple sources. And then the summarization comes from the multiple sources. And so there is a little bit of like QA built in. And a little bit of like taking the bias out that maybe one writer will have or something.

• 2:32:45Jordi Hays?

  Yeah, speaking of. Speaking of data quality, what what do you think? Uh, do you know, yesterday Walter Bloomberg. Shared shared some news that that wasn't quite uh accurate and moved the market, you know, trillions of dollars. Um, maybe helped us avoid uh whatever it was, Black Black Monday Kramer was calling it. Uh, what what do you think is uh, do you think that? Do you think that there's any like solution to that? Or it's just the nature of the internet where now you have these accounts that basically act? They publish, they're basically like mainstream media, except they just publish headlines. They're not doing any journalism. They're not even looking at data. They're just sort of like. Trying to be the first or second or third big account that's like sharing a headline. Is there any is?

• 2:33:31Jordi Hays?

  What's the fix there, right? Is there one? Or is that just the nature of the internet where this sort of information breaks? And then markets are going to react really quickly. And now retail investors are so ready to act on information. You know, a good example is like if you just happened to be on X when Trump posted Trump coin and bought 20 grand of it, you became, you know, a millionaire within a few hours. But I'm curious, like if you've thought at all about like how?

• 2:34:01Jordi Hays?

  Yeah, just, just, I don't know if there's, I don't know if there is a solution, right?

• 2:34:06Leif Abraham?

  Yeah, but I think it's, I always come back to,

• 2:34:11Leif Abraham?

  who are you building for? And therefore, what behavior is, is your product inspiring? And, you know, generally speaking, what like the way you design your product will always have an impact on how people use it and their behavior. And in our case, you know, yeah, you cannot, you can buy a Bitcoin, you can do options trades. But generally speaking, the way we've designed the product and the offerings that we have are more focused around building long-term portfolios for people that want to, you know, compound their wealth over time, you know, the, all the fixed yield, the fixed income offerings that we now have, et cetera. And I think there are just certain design decisions that, that impact in the end the

• 2:34:54Leif Abraham?

  behavior of like, like of these users, right? And therefore, in the end, I think that is much more important for, for people to make healthy investment decisions than necessarily, you know, like, like how they consume and so on. But like, like that behavior you're, you're, you're talking about is obviously not necessarily coming from the potential wrong information from some X account. That behavior is more cultural or how they were trained when they started being in the markets, you know? And so I think that is, that is much more the sense of like, if the platform you're using is closer to gambling, you will enter being more of a gambler automatically, just based on the design of how you were introduced to the markets. And therefore, you'll be more prone to, you know, potentially react on these types of

• 2:35:39Leif Abraham?

  things because your investing style will be closer to a gambler than maybe someone who tries to compound their wealth over time and, you know, cycling money out of a hacker account into, you know? Amazon stock or whatever because they see an opportunity that

• 2:35:53Jordi Hays?

  Yeah.

• 2:35:54Leif Abraham?

  Both to to then also hold it for long term and so on. So I think that's much more the the issue, so to say, than than than those accounts.

• 2:36:02Jordi Hays?

  Um, I have a bunch of other questions, but I think we're, I think we're over. We'll have to have you back on very soon. Um, I know you got some big, uh, stuff in the works. Thanks for coming on.

• 2:36:12John Coogan?

  Yeah, I'm excited for the announcements. This will be great. We'll talk to you soon.

• 2:36:15Jordi Hays?

  See ya.

• 2:36:18John Coogan?

  And we have our last guest of the show announcing a $30 million Series B, the smallest round of the day. It's rough out there.

• 2:36:27Jordi Hays?

  What is this, a round for ants?

• 2:36:29John Coogan?

  I don't want to talk to his trash.

• 2:36:33John Coogan?

  It still gets a size gong hit. Um, but it is funny. We've seen a bunch of huge rounds today. Uh, it's a good day in the markets. Uh, the markets, the public markets are down, but the private markets are ripping. Let's bring in the founder and CEO of Arena AI. Uh, today he's announcing a $30 million Series B and introducing Atlas, an AI hardware engineer that is used by many of the world's most respected and ambitious hardware companies. I'm excited to talk to him. Now, if you're there, welcome to the studio. How you doing?

• 2:37:03Jordi Hays?

  What's going on?

• 2:37:04Pratap Ranade?

  What's going on? Nice to see you guys.

• 2:37:05John Coogan?

  It's great. Uh, would you mind with just starting with a little introduction on who you are, the company, and maybe a little bit of your background? Cause I, I thought the, the, the previous company was really interesting too. So I want to hear about that.

• 2:37:15Pratap Ranade?

  Thanks. No, that's awesome. Yeah. So, um, I'll tell you like a bit of that company. It's Atlas AI hardware engineer. Company's called Arena. We're based in New York. Um, yeah, background. I started out as an applied physicist. So I spent like a decade when I thought I was doing physics, dealing with hardware problems. Again, this was like a while back. Um, you know, switch gears, went, did a brief stint through consulting. Um, so wore suit for a short flash of time over there. Uh, and then

• 2:37:39Jordi Hays?

  Bring it back.

• 2:37:40Pratap Ranade?

  Yeah. So it started, it started right during that financial crisis too, which was a wild time to be starting a job. Uh, but then, uh, then sort of missed tech, moved out of San Francisco. The first company to your point was in 2014. It's called Kimono. So the idea was to make it really easy. I mean, to write a web scraper, right? And it was, uh, pretty popular. We had a, uh, we grew to 150,000 users. We got bought by Palantir, which is where I met my co-founder. We were there for a while and then started Arena 2019.

• 2:38:05John Coogan?

  Very cool. Uh, can you take me through the founding of Arena? Uh, how did you settle on this to build? It seems very on trend now, but you've been working on it for a couple of years. What what what inspired you? What was kind of like the early go to market, the first customer that you were talking to? What does customer development look like? All that stuff?

• 2:38:24Pratap Ranade?

  Yeah, totally. So just, you know, we had a bit of an interesting path here. I would say it's like a little bit non traditional. We started, we decided to bootstrap the company.

• 2:38:32John Coogan?

  Oh, wow.

• 2:38:33Pratap Ranade?

  So we said, well, you know, if you think about like our view on enterprise problems, if you think about the B two B problem spaces, there's almost like a Maslow's hierarchy, right? Which is if you, let's say you've had a job for two to four years and you're like, you've encountered a certain group of problems, like you've encountered payroll, onboarding, communications. But then if you've been there for a while, you're deep in that industry, you're almost, you're seeing another set of problems, right? And I think one of the things Palantir did so well is they were able to go so deep into a customer for so long that they encountered problems that for which there was very little competition for. And like previously, you had consulting companies kind of doing that. So there's, there's, I think, a whole host of sort of untapped problems. And so our view is if we want to tackle problems that are really deep in an industry that are really valuable,

• 2:39:16Pratap Ranade?

  we need to go really deep with our customers. So that's been the philosophy since the founding days. Instead of saying, we're going to sell to other startups and sell bottom up. The view is to start with a very difficult to enter customer, start top down. And the the origin of the company was actually more, let's say, less vertically opinionated. We, you know, had added depth and reinforcement learning and transformers were like, let's go and apply that for enterprise problems. So we were not as sort of like, you know, our thesis hadn't formed as sharply as it had today. And then we saw traction in a few different markets and like post chat G P T. We were like, look, I don't think for a small company playing in horizontal A I is really a winner's game. But we found that like, there was this beautiful intersection that went back to sort of my days as a physicist, where like,

• 2:40:00Pratap Ranade?

  two different technical fields together with like, you know, applied physics, electrical engineering and A I. Now you have an interesting customer set where you look at like a hardware test lab. It actually hasn't changed in a long time. The incumbent competitor set are three companies from the eighties, you know? It's it's weirdly the the in underpinning layer of technology on which all of our software runs. Weirdly hasn't changed that much. Developing the hardware has like stagnated and it's kind of surprising when you think about it.

• 2:40:26John Coogan?

  Yeah. Can you talk a little bit about like hardware engineering one O one? Are we writing Verilog? Are we in CAD? Are there other systems? Like, like, what what does the work look like? And is this something where it's like? It's managed on GitHub, so Devin's gonna go off and write some code for you. And we're just doing fancy autocomplete. That's probably, I'm not trying to diss, it's incredibly valuable if that's what it is. But just concretize, like, what are we actually talking about here for the folks who haven't done hardware engineering?

• 2:40:54Pratap Ranade?

  Totally, right? So let's like, let's break it down. Let's take a simple example. Let's take like, let's take something like a drone, right? We've got like, you've got like the mechanical shell where you've got like your mechanical engineering CAD model, stress drain modeling. Still a lot to do, but humans got pretty good at it. We've been building physical stuff for a while. Okay, we can screw things in, weld them together. Again, not trivializing that, ton of opportunity, but that's kind of figured out. Now, inside, especially as you think about systems that are starting to go autonomous or partly autonomous, right? You're like, I mean, we've had helicopters, now we have drones, right? So what's the change? The brains of this are basically like a set of embedded systems, right? So embedded systems effectively, your computer, the green motherboard like you've got inside, except a whole bunch of them, right? You've got like one that's operating as a sensor and multiple different types of sensors.

• 2:41:39Pratap Ranade?

  So like an IMU for hardware oriented, like temperature sensors, optical sensors. So all of your sort of sensors, just like the body has, and then a brain. And you might have multiple brains, which might be onboard again in our drone example, flight computers. And then you have actions that you take, like servos and actuators. And you think about this, like, inside that mechanical shell, you've got this almost electrical skeleton, sort of like your own nervous system sort of wired together, right? And at that layer, you know, to your point, there are two things that are happening. One is all of the electrical connections to make that work. And then for certain of those chips, you're running code onboard. So to your point about the Devin, so you know, you might have an FPGA that's programmable. You're putting code onto it. And so that's sort of the, the, the sort of, the, we're currently at that inner layer. We're currently at that nervous system because there's this huge need.

• 2:42:23Pratap Ranade?

  And if you look at like the, just the kind of labor markets for a second, this is actually weirdly not surprising, but, but, but, but kind of has profound implications. The last 50 years, if you look at computer science course enrollments, they're up by 90%. None of us are surprised by that. But electrical engineering course enrollments are down by the same amount. And so you look at it, we've got this huge research, we've got tariffs, we've got all that. We've got a huge resurgence in American manufacturing, right? And now you have all these intelligent hardware companies, robot companies, space companies. And like, you have this burning platform problem where it's like, oh my God, people haven't been studying this stuff. And like, we're trying to now ship at the velocity of a software company in a hardware state, a space where stuff can literally explode without a workforce, right?

• 2:43:08Jordi Hays?

  Yeah, my favorite, my favorite example here is, is you have Sonos, which hasn't, has made like beautiful devices, but they haven't managed to like, just get like even the salt, like, like the collective experience of using a Sonos product is just completely brutal, right? And then, and then you like, look like this is a company with like hundreds, thousands of employees, they're public, and it's not even defense, like it's not critical that my speaker work, like when I want it to play music, right? It's annoying, but it's not the end of the world. And then it's like, hey, if that is hard in a controlled environment in a home, and then we need to do much harder things in the sort of these defense, critical industries, like that's a, that should be a red alert.

• 2:43:50Pratap Ranade?

  Yeah, it totally is a red alert. And that's where the, you've got customers kind of screaming for it. And, you know, at the root of it, like you have this idea that, you know, it's software, I mean, you talked about Devin, right? Like, I mean, it's never been easier to write code, right? It was like, I mean, already weirdly, Python was an abstraction over like, you know, C+ like, it's not as hard as C++. It's gotten easier and easier and now like, you're speaking in English and like, that's amazing, right? It's like the Star Trek computer. And it's a beautiful environment because code doesn't need to obey physics, it just needs to render in your browser, right? Now suddenly you're making contact with nature, as we know, you guys go outside, you're, like, nature's unforgiving, man. It's not like, we kind of like fixed a bunch, we don't have space elevators, we don't have jet packs, like, no, we have like TikTok, which is great, but like, what about all of that? And the problem is we're encountering this physics.

• 2:44:34Pratap Ranade?

  And so each test cycle, to your point about the Sonos is like, great, I have an idea, I'm going to prototype it, like, let me run it in my terminal, it doesn't compile, great, I probably made a stupid mistake. Everyone makes these, but the cost of making a mistake at that speed in hardware, like, worst case scenario, you get it wrong, something explodes, but then even on the development cycle, each time you, you're like, oh damn, the board was wrong, I need to go and re-spin it. That's like you're adding three months to the cycle. And so these timelines and cost structures, I mean, you know, we all know how like, how much the F35 program cost and over and it's like, that explains it. Like, I mean, there's a lot more that explains it, but that's like a piece of it and an important piece of it.

• 2:45:08John Coogan?

  Yeah. Can you talk a little bit about where you see the most value to be delivered in the AI stack from? It sounds like you're not doing pre-training on a foundation model. Is fine-tuning important? Is, you know, building a system on top of existing LLMs important? Are you doing reasoning? Or is it more about UI and integration into existing systems? There's so many different ways to create value in the stack right now. I'm sure it can be kind of overwhelming, but how are you thinking about it?

• 2:45:37Pratap Ranade?

  Totally. And, you know, it's a, it's a cool question because our own thinking on this has evolved quite a bit. I would say we started with a view that was much more, we kind of need to own all the pieces on the modeling side and solve the hard modeling problem. And we sort of realized like what's happening is base cognitive functions are just becoming available as an API. So like vision is just going to be available. We shouldn't work on a vision problem like go fine tune like a YOLO or whatever VLM is your favorite. You know, LLMs are maturing. But what we do find is if you think about like a person doing a work, imagine like our objective is AI is we're trying to get as good as like a medium class person, let's say, or like a junior person even, right? And we can unlock a lot of value with that. If you want to do that, now people do, you know, we think about, you, you talked about reasoning and there's a sort of like notion for reasoning in LLM land.

• 2:46:23Pratap Ranade?

  But like, if we just think about human reasoning, there's like a nuanced kind of like, there, there are a couple of things that are special, right? There's some sort of like, especially in a formal environment like electrical engineering, there are certain rules of the world that we've learned over time that need to be true. It's like gravity is 9.8 meters per second square. You can't probabilistically learn that by watching stuff fall in air and being like, yeah, my ML, no, no. I mean, there's just some like speed of light, like you're going to encounter that shit. It doesn't matter if you're a model or like, you know, it's just real, right? So there's some of these things with your hard constraints and, you know, where AI has struggled is you tell an engineer something obviously wrong, they're never trusting you again. And they shouldn't, honestly, like you, you want to fly in a safe plane. You don't want that happening.

• 2:47:05Pratap Ranade?

  So there's a piece here where it's like reasoning, but inside this sort of like structured constraint, right? Where there's a set of physics constraints that, that apply that you sort of need A to win trust the user, but B to work, right? The second piece is it's this kind of, um, Multimodality, where, again, I'm not saying we need to build from the ground up those models. But you need to make sure you're getting really clean input, right? And so that's input from, and it's weird, it's not like you're taking text input. Text is of course a part of it. And I think the L L M's have gotten so good that it gives us an ability to like really ingest a ton of text documentation. For sure, that's a piece. But now you're also looking at the thing. You're looking at it visually, you're looking at thermally, is it getting hot? You're looking at readings from an oscilloscope. So you're, and each of those things has meaning to an engineer. And the idea is, can you now tease the right meaning from that?

• 2:47:50Pratap Ranade?

  Uh, and so a lot of our work is basically on that, that, that data and fine tuning side. How do we turn all of that into a package that can be fed in to a set of models? And the other thing we found is, you know, a person is doing multiple different pieces of work. A person might be saying, hey, I'm cross referencing in some data sheets. What should this FPGAB be expected to do? Can this paint handle 10 volts at 100 degrees Celsius? Or is this thing, am I going to short out the most expensive part? So that's almost like a kind of a text based lookup. But then you're actually running a test, you're comparing waveforms, you're doing math, you're running simulations. And so what we found is we're using different systems to do the different like, um, different a- a- as agents to different pieces of the specialized workflow. So you sort of have this like meta agent that you're talking to.

• 2:48:34Pratap Ranade?

  And then you have these others that are sort of, and the line blurs now between like, what's an L M agent? Versus what's it calling, you know, we'll call tools. But those tools, if you'd talked to me in like November 2022, before chat G P T, I would have been like, these are machine learning models and companies.

• 2:48:50Jordi Hays?

  Yeah.

• 2:48:51Pratap Ranade?

  But they're just tools. Now, let's say, oh, I need a thermal recognition stapled with like, you know, the view from the waveform. That's an M L model. That doesn't need to be like a 600 billion parameter model. But it's a non trivial thing to do. And so you could look at this entire constellation as being, that's sort of the product, if you would.

• 2:49:07Jordi Hays?

  Got it.

• 2:49:09Jordi Hays?

  One quote that comes to mind is, "We were promised flying cars, instead we got 140 characters."

• 2:49:17Jordi Hays?

  I have to imagine that what you're building and other tooling like it can, has a potential, you know, the exciting potential to me is sort of getting us out of this period of stagnation, right? There's a lot of companies that are building, you know, there's companies building supersonic jets, right? And they can use your tool. And then there's all these other things that we've yet to even imagine, or we imagined in science fiction, but now we should probably think about building. How optimistic are you around, you know, AI helping to accelerate and help us sort of achieve these sort of like, science fiction dreams that we've had forever, but have never quite been reality?

• 2:49:57Pratap Ranade?

  First of all, I love the quote. It definitely speaks to my heart. It's like, you know, if you look at, and it's an interesting question, because it can feel sometimes like reading the news, like doom and gloom, "AI is taking our jobs." And it's like, you know, I'll go back to an example that I lived as a physics grad student, right? I spent a lot of time, and I supposedly came in to do physics. I was like, "Oh, I'm gonna do all this great quantum mechanics re-research." And I was basically like, a mechanic and a plumber for like, 99% of the time. I was like, "This thing is leaking. I think there's a water leak. Oh, the screw got bent." Oh, like, I was not doing, I was doing like, less than 1% of physics, right? And I was like, you know, that was the reality. And I think that's a reality for a lot of us. And so, if you could take a lot of that away, like, I think

• 2:50:39Pratap Ranade?

  what it does is, it changes, to your point, what human ambition should be. Like, what could you achieve? If, let's say it takes 10 years on average to build a startup. In the past, like, what we considered a SaaS company is now just gonna be a feature for, in the future, right? And I think, you know, original Silicon Valley was about silicon, right? It was actually hardware-based. And I think we're gonna see a resurgence, hopefully, of that. And our hope is, like, what gets me personally excited is, one of the magical moments at my last company, Kimono, was, you took someone who couldn't code, and you said, "Hey, wow, with this tool, you could like, write a web scraper." And it was like, we just got the most amazing like, customer comments. And I was like, felt this joy of enabling people to do something. And, you know, hardware can be intimidating. You're in like, a hardware lab even in college, you're like, "Oh man, this is really complicated.

• 2:51:23Pratap Ranade?

  It's really, there's a high barrier. Does it need to be that high?" You know, it's like, we're seeing kids- Cheat on their essays with ChatGPT, that's a good thing. You know, will generate more stuff. What if we could let them cheat at EE Lab with this? Like, would we have more people going into hardware? Can we lower that barrier? Like, what if you wanted to build a drone on the weekend? Like, you should be able to. Right, you should have Jarvis. I mean, the goal is to be Jarvis for, and every, kind of enable everyone to be a little bit of a Tony Stark.

• 2:51:48John Coogan?

  Love it.

• 2:51:50John Coogan?

  In your announcement post, you highlighted five categories that it seems like you're going after in the first initial rollout. Semiconductors, aerospace, automotive, medical devices and defense. Is that sorted by market size? Like, the burning need? Just, do you like the way that it sounded in that order? But I am interested to hear which of those has the, has the most immediate need or is the largest market?

• 2:52:20Pratap Ranade?

  Yeah, it's a great question. So we, we started with semiconductors, right? So that's sort of why we put it first, because, you know, the most complex, especially when you think about a lot of what we do is electrical today. Electrical engineering problems with semi. And if we take the philosophy of, we want to be a little like Nike, start by selling it to the Olympic athletes and get everyone to buy it. That was sort of the proving ground. And so we still have a few semiconductor companies, you know, that we're scaling up to. But I think that's like, we all know the household names. It's a small set that are really valuable, but they establish the credibility. That actually helped us. We had a few great companies then come in inbound based on that. A lot of that was automotive and aerospace. And it's interesting, especially if you think about like EVs and like autonomous driving and aerospace. You have a huge amount of that coming in.

• 2:53:01Pratap Ranade?

  Medical devices, we've got an early customer in there and it's like, that's, that's going really well. You know, it's, it's, it's, there's a whole like FDA angle to this that we sort of need to, need to work through, we're newer to that. But it's a, it feels like the potential for impact is super high. And so that's sort of like a little bit like the landscape. I think we're seeing a ton of pull on the aerospace side. Like, especially if you look at that industry is getting, we're going to have more stuff that flies. And then you introduce space to the mix and like aerospace and defense, like increasingly are kind of mixed. So you look at these, these things, I think that's becoming kind of a unit in some way. And so it feels like there's a ton happening there right now. But yeah, I mean, that's sort of just a little bit, there was not like a whole bunch of science behind that ordering.

• 2:53:44John Coogan?

  Makes sense. I want to get your reaction to the tariffs. It seems like you're probably an American company selling to a lot of American companies. You know, regardless of what you think about the economics, it could potentially be a bull case for your company. How do you process the news and what are you thinking about if it shifts your strategy at all over the next, you know, using this series B over the next couple of years?

• 2:54:09Pratap Ranade?

  Yeah, so you know, it's, you know, we actually do have a couple of international customers too. And like, you know, I mean, obviously it's a huge impact, right? I think the first thing we did was just like call them because we're like, are you okay? And like, especially look at these, like the margins on something like a car have dramatically changed, right? It's like, you're doing some of the work here, you're doing some of the work there, some of it in America. It's like, it's, you know, there was a lot of American factories. What percentage of the cars actually getting made here is a totally different question. So you have a ton of like, kind of a panic in the system, right? But, you know, you're right, like for us, it's been like, it's accelerated customer pull and deployments. They're like, oh no, like, we can't go ahead and have like that gross margin impact and therefore have to do this with people. We need, we need technology.

• 2:54:52Pratap Ranade?

  And so it's actually a forcing function, like if, if, if, if part of this means that US sort of quality and speed and sort of ability to manufacture needs to get up really quickly. And I think this provided the economic incentive for it and it's just not there, honestly. This is just an acceler, it's more fuel, there's more urgency than there's ever been on the customer side. So, uh, yeah, I would say like, overall, like a lot of like chaos there. But, um, net, I think like, yeah, from our perspective, good, because it means there's a huge pull. And like this problem we talked about, you know, we talked about the 90%, the, the changes in the, in, in those, those people. Like, we suddenly need to do a lot of this hard engineering in America. And, and, and, and it's, it's, it's, this, this finally put like a dollar amount on how important that problem is.

• 2:55:37John Coogan?

  How are you planning for kind of as AI technology gets better? It feels like we're firmly in the co-pilot era. There's a lot of talk about, oh, electrical engineering exam. I'm sure that these models have aced them at the highest level. And, uh, there's a prediction that, uh, you know, AI will, will earn an I am, I, I, I O I gold medal this year. And it's like 50% on polymarket. And yet I can't get AI agent to book my flight yet. So how are you planning for integrating that, taking advantage of what's state of the art and amazing and what AI does well? And then how are you building around the rough edges of the kind of innovation jagged edge?

• 2:56:16Pratap Ranade?

  Yeah, you know, we think about this a lot because I feel like the question of defensibility probably is going to come up much sooner in a company's lifetime than it's ever done before. And so it's sort of like playing with fire, which is we want to be on the glide path where our product automatically gets better as the titans go to war and the foundation models improve, right? Like, we just want to ride that wave. But if we're just, that's what we're doing, we're like, let's get documents from the internet and help you do cross-reference. Okay, that's like not, that is going to disappear super fast. And so, you know, to your point, it's tied in with like your math Olympiad or physics Olympiad question, which is, you've got your friend who's the genius, who's like really good at tests, right? And then you've got your friend who I bet is a different person, who is really good at building stuff.

• 2:57:01Pratap Ranade?

  And usually they're not the same person somehow. Like, in my experience, there's always, there's your tinkerer friend who didn't somehow get the A, right? That tends to be the way. And so we're not trying to pass the math Olympiad. We're trying to be the guy who's tinkering in the garage, right? And so the tinkering in garage problem is very unsolved. Like, you look at AI's capability there, it's like, it's a disaster. But as the base cognition gets better, you're getting better.

• 2:57:25Jordi Hays?

  But to be clear, like, when I think about the guy tinkering in the garage, my dad was a high school teacher and he taught this class called Project Make. And it was all about, it was some combination of like woodshop meets electrical engineering meets physics and, you know, you're making rockets and all that stuff. So when I think about him solving problems, it's like the tinkerer in the garage and that he would just try a lot of different things and experiment. And the beautiful thing about AI is like, I have memories as a kid of him working on one little problem, like for five hours, like on a Sunday, like trying to figure something out, whether it's around the home or in class. And like, he's basically running like a series of experiments, right?

• 2:58:09Jordi Hays?

  And so the potential of AI is like, run every experiment at once, like in a simulated environment, but like run like a thousand experiments in like, you know, 10 minutes, right? And like, when you start to think about what that can do for like accelerating progress, that's the most exciting thing for me because it's a superhuman. It's like the tinkerer in the garage but multiplied by a million.

• 2:58:30Pratap Ranade?

  Yeah, totally. I mean, I want to get your dad signed up with the sort of, we're working on like an academic condition. I want to give him free access to that, see if he could, we're looking for feedback, but I think that's.

• 2:58:40Jordi Hays?

  He's retired, but I'll put you guys in touch.

• 2:58:43Pratap Ranade?

  If he's still interested, if he's still got a garage.

• 2:58:46John Coogan?

  That'd be great. Well, I mean, thanks so much.

• 2:58:48Jordi Hays?

  No, no, no. Here's the bar for the team. Five years from now, I want to be able to design our own podcast equipment.

• 2:58:54John Coogan?

  Oh, yeah.

• 2:58:54Jordi Hays?

  The, uh, the most cutting edge. Uh, you know, we need H100s in these.

• 2:58:58John Coogan?

  Yeah, and the microphone.

• 2:59:00Jordi Hays?

  I don't know why yet, but it sounds cool. So.

• 2:59:03Pratap Ranade?

  Deal.

• 2:59:03Jordi Hays?

  Uh, congratulations. I, I do have one last question. Uh, how much do you attribute your incredible energy levels to, uh, your, you know, being, being a triathlete? Do you think it gives you an edge as a, as a, as an operator?

• 2:59:18Pratap Ranade?

  I would, I don't know. I would hope so. I don't, I do a lot less triathlon than I would like, but I feel like it does. Training the pain threshold is a useful thing. I think it's just a useful thing in life.

• 2:59:28Jordi Hays?

  Yeah.

• 2:59:29John Coogan?

  That's awesome.

• 2:59:29Jordi Hays?

  Love it.

• 2:59:30John Coogan?

  Well, thanks so much for stopping by.

• 2:59:31Jordi Hays?

  Congrats on, congrats on the milestone.

• 2:59:33John Coogan?

  For the series B.

• 2:59:35Pratap Ranade?

  Thanks for having me, guys. Appreciate it.

• 2:59:36John Coogan?

  We'll talk to you soon.

• 2:59:37Jordi Hays?

  See ya.

• 2:59:38John Coogan?

  Have a good day. Uh, let's go to the timeline. Justin Ross is, uh, quote tweeting, "Did you, did you see the colossal company? They have brought back dire wolves using ancient DNA with their first born on October 1st, 2024. They waited a couple of months to make sure that dire wolf was healthy and growing. Over 10,000 years since dire wolves were extinct."

• 3:00:00Jordi Hays?

  Can we do a deep dive on this?

• 3:00:02John Coogan?

  I have done a full video and deep dive on the company Colossal.

• 3:00:06Jordi Hays?

  Remix. Bring it back.

• 3:00:07John Coogan?

  I was emailing with the company a while back. I'll, I'll rekindle that connection. Hopefully have Ben, the founder, on the, on the, on the show. He has a, a very funny collection of investors, but some really great, uh, George Church from Harvard, uh, uh, fantastically renowned scientists involved in, uh, and they're, and they're working on cool stuff. So this post was put in the truth zone. People said, "Hey, they're not technically dire wolves. Uh, they didn't really revive, revive them using ancient DNA. It's more, uh, genetic modification of existing dogs." A little bit of controversial, but JD Ross chimes in and says, I don't care if these are real dire wolves or not. They're very cute and we should mix in golden retriever DNA and use them to hunt deer with us. And I couldn't agree more. And you know where I would love

• 3:00:50John Coogan?

  to have a dire wolf hanging out and maybe go on some deer hunting? In a wonder. I want to find my happy place. Find your happy place. Find your happy place. Book a wander. Book a wander with inspiring views, hotel-grade amenities, dreamy beds, top-tier cleaning and 24/7 concierge service. It's a vacation home, but better. Code TVPN. And I want to go to Mike Newp, who we had on the show, founder of Zapier. He says, "On the topic of AI is trained on all of humanity, why can't it innovate?" A big question that we're talking about, that question of the test taker versus the hacker. He says, "New ideas come from two places. One, noticing similarities between two existing ideas. New ideas in one area translate into another. And two, logical construction. New ideas

• 3:01:35John Coogan?

  follow from prior axioms. One is easier and bounded, and two is harder and open-ended." And Dorkesh was talking about this, like, if you've trained, a lot of, a lot of scientific innovation just comes from somebody who's read so much about the scientific literature. They put together two random studies and they find out that if you put those together, you get innovation. And then that's true in all sorts of different industries, but specifically in just, if you've read all the papers, you've read all the books, you start making connections. This is what David Senra does a lot with his show, Founder's Podcast. Go download it.

• 3:02:06John Coogan?

  Download it today. But he says, "Two is harder and open-ended. Paradigm one can look a lot like career advice at the work, to work at the intersection of two fields because it's easier to become an expert. In contrast, being an expert in a single domain requires much deeper hierarchical knowledge and innovation requires novel in-domain idea construction." This is the story of, you know, Elon Musk working in space and, and...

• 3:02:29John Coogan?

  Electric cars, maybe having both of those knowledge sets multiplies in some way. Two, he says, is harder because you don't know if innovation is blocked due to the prior axioms not existing yet, or if you just haven't combined them in the right way. We want to build AGI that can innovate due to the fact that one is bounded, search leverages ML strengths like pattern recognition, and can bootstrap from human knowledge. I think we will create AGI that can reliably do number one well before number two. Very, very interesting take, and I just think it's like an interesting question that he's clearly asking like, like, these AIs, they're blasting through all the benchmarks, they're doing all these amazing things, but we're not seeing innovation come out of them yet, or even you could think about like the joke test is like,

• 3:03:14John Coogan?

  you kind of need to be innovative to come up with a joke.

• 3:03:17Jordi Hays?

  Yeah.

• 3:03:17John Coogan?

  It needs to come from some, it needs to be new and fresh, it's not just information retrieval.

• 3:03:21Jordi Hays?

  The idea of like creatively, creativity is often just taking ideas from two different places.

• 3:03:27John Coogan?

  Yeah.

• 3:03:27Jordi Hays?

  And combining them in some way.

• 3:03:29John Coogan?

  Yeah.

• 3:03:29Jordi Hays?

  And it feels like the models do that very well today and that you can ask it to make me a, you know, song.

• 3:03:36John Coogan?

  Yeah.

• 3:03:37Jordi Hays?

  It's not doing it, you know, independently, it just like, you know, you have to sort of prompt it.

• 3:03:42John Coogan?

  This was the genius of Harry Potter Balenciaga, like the, the human element there that made that actually go viral wasn't the AI. It was the idea that combining Harry Potter, kids' story with Balenciaga, high fashion, that was funny. And then the AI just instantiated it, and I agree with you, like the idea of, of taking two disparate concepts, putting them together is where you get genius. Like, take your best performing ad and put it on a billboard with adquick.com, like that's going to perform better.

• 3:04:07Jordi Hays?

  That's right.

• 3:04:07John Coogan?

  And so, go to adquick.com, out of home advertising made easy and measurable, say goodbye to the headaches.

• 3:04:11Jordi Hays?

  Basically took the amazing attributes of online performance marketing and brought it into the real world.

• 3:04:17John Coogan?

  That's actually what they did, that's true.

• 3:04:19Jordi Hays?

  I'm serious.

• 3:04:20John Coogan?

  Yeah, that's the whole point.

• 3:04:20Jordi Hays?

  We're not messing around.

• 3:04:21John Coogan?

  Yeah.

• 3:04:22Jordi Hays?

  We are.

• 3:04:23John Coogan?

  You get a dashboard, you get all the different things that you expect when you're running a performance ad campaign online, on Facebook. It gives you similar dashboards, but out in the real world, and they do a lot to help you track the performance of your out of home campaigns. I thought this was a funny one, we'll move on to, Quake 2 has been fully AI-generated and replaced by Microsoft. You can play it in a browser, every frame is created on the fly by an AI world model, so they trained it on, on Quake 2. Had the, had the, the, the algorithm or the AI. Play a ton, generate a ton of frames and then just take the input from the controller, output of the frames. And so there's no, there's no game engine. It's just input is what you're doing on the controller.

• 3:05:06John Coogan?

  Output is the game with visual fidelity. Uh, and you can see where this is going. It's crazy. It got a lot of hate.

• 3:05:12Jordi Hays?

  Yeah.

• 3:05:13John Coogan?

  You want to read this?

• 3:05:13Jordi Hays?

  Quake dad.

• 3:05:14John Coogan?

  Quake dad, clearly a fan of Quake.

• 3:05:16Jordi Hays?

  Dedicated to the, committed to the bit says.

• 3:05:19John Coogan?

  Meanwhile, they haven't released a new Quake in like two decades. So this guy's been in the trenches forever.

• 3:05:23Jordi Hays?

  This is absolutely disgusting and spits on the work of every developer everywhere. Bold. Uh, John Carmack says, what? Question mark. This is impressive research.

• 3:05:33John Coogan?

  And I love that because he's the creator of Quake. And there was an amazing, uh, there's an amazing meme that was like, uh, John Carmack holding a white monster being like, oh, you completely replicated exactly what I did? Awesome work.

• 3:05:45Jordi Hays?

  Based.

• 3:05:46John Coogan?

  And it's like, the developer himself is like, this is cool. Uh, but he did unpack it a little bit more. And so I want to read through this. Uh, he says, I think you are misunderstanding what the, this tech demo actually is, but I will engage with what I think your gripe is. AI tooling, trivializing the skillsets of programmers, artists and designers. And that's real. My first games involved hand assembling machine code. What a code. This is why he's one of the greatest programmers of all time. Uh, and turning graph paper characters into hex digits. Software progress has made that work as irrelevant as chariot wheel maintenance. Yeah. You don't want to be in the business of chariot wheel maintenance. Not a big industry today, but building power tools is central to all the progress in computers. Game engines have radically expanded the range of people involved in game dev,

• 3:06:31John Coogan?

  even as they de-emphasize the importance of much of my beloved system and systems engineering. But maybe first person to say that, systems engineering, very, very hard. And it's a lot of, it's a huge time suck to, I mean, when he built Quake, he had to build the whole game engine. He had to build every, everything. The idea of a floor that you can't fall through a floor or a wall. You don't want to walk through the wall. You have to write all that code from scratch. Instead, now you just fire up Unreal Engine and you get Fortnite out of the box. So you build in Roblox, right? So he says, AI tools will allow the best to reach even greater heights, while enabling smaller teams to accomplish more and bring in some completely new creator demographics. People who don't know systems engineering or even programming, for example. Yes, we will get to a world where you can get an interactive game or novel or movie

• 3:07:15John Coogan?

  out of a prompt, but there will be far better exemplars of the medium still created by dedicated teams of passionate developers. And this is like the innovation concept, this idea that, you know, the, the Harry Potter Palencia game will be the one that goes viral and gets a lot of attention. If you have distribution, you can capitalize on that. But also, if you have a novel idea that AI could think of, you will have a breakout success. And so we'll focus more on game mechanics, game, like, there was this game Bellatro that took, that takes poker cards. And you're basically playing poker and trying to create like royal flushes and whatnot. But it adds all these crazy mechanics on top of it. It was a very simple game, just designed

• 3:07:55John Coogan?

  in an engine, not crazy on a technical level, but the game design was so, so incredible and so novel that it just went massively viral. And like the solo developer, basically, I think he had a few people on his team, just printed and became like the number one game of the year, or like of that quarter on Steam or something like that.

• 3:08:14Jordi Hays?

  Well, what should you do if you're printing, John?

• 3:08:17John Coogan?

  Pay your taxes, that's for sure.

• 3:08:19Jordi Hays?

  Put your sales tax on autopilot.

• 3:08:21John Coogan?

  Sales tax on autopilot. Spend less than five minutes per month on sales tax compliance. Go get started. They're back by what I mean, benchmark.

• 3:08:29Jordi Hays?

  Five minutes a month.

• 3:08:30John Coogan?

  You don't want to be bogged down. And I mean, this is true. Like, you want to be focused on the innovation that your company is doing. You don't want to be dragged into a bunch of unnecessary reports and, and.

• 3:08:40Jordi Hays?

  Yeah, if you're in SaaS, you can be thinking, your lucky stars that you're not a part of the trade war right now.

• 3:08:49John Coogan?

  Yep.

• 3:08:49Jordi Hays?

  But take an opportunity to get your sales tax ducks in a row. 25 states are now taxing software sales and Numeral helps you stay compliant. So just do it.

• 3:09:01John Coogan?

  HQ and check them out.

• 3:09:03Jordi Hays?

  Just do it.

• 3:09:04John Coogan?

  And I think that's a good place to wrap up. What do you think, George?

• 3:09:06Jordi Hays?

  Yeah, fun show, John.

• 3:09:07John Coogan?

  Great show.

• 3:09:07Jordi Hays?

  I enjoyed podcasting with you today.

• 3:09:09John Coogan?

  It was fantastic. Can't wait to do it tomorrow.

• 3:09:11Jordi Hays?

  I know.

• 3:09:11John Coogan?

  I was so worried. I, I, I checked the date in my intro and I was like, is it Wednesday already? It's not. It's Tuesday. We got three more days. Glorious podcasting.

• 3:09:20Jordi Hays?

  I know. I have a feeling there, there'll be more news this week.

• 3:09:23John Coogan?

  For sure. The, the size gong hasn't rung its last gong sound. That's for sure.

• 3:09:29Jordi Hays?

  The gong.

• 3:09:30John Coogan?

  The gong is still fresh this week.

• 3:09:31Jordi Hays?

  As long as we're.

• 3:09:33John Coogan?

  Yeah, it's great. Three, three amazing Series Bs. We got all three founders on. I think we did great.

• 3:09:40Jordi Hays?

  Was Jais a Series B?

• 3:09:42John Coogan?

  Oh, I guess.

• 3:09:44Jordi Hays?

  More like a pre-seed. More of a pre-seed.

• 3:09:46John Coogan?

  Anyway, three big, three 10-plus million dollar rounds in the tens of millions. Great to see it. Lots of money flowing into startups that we love to see, all, all working on very interesting things.

• 3:09:57Jordi Hays?

  Remain bullish on America.

• 3:09:59John Coogan?

  Me too. Me too. Anyway, thanks for listening.

• 3:10:01Jordi Hays?

  Never lose faith.

• 3:10:01John Coogan?

  We will see you tomorrow.

• 3:10:02Jordi Hays?

  Have a great afternoon.

• 3:10:03John Coogan?

  Have a great afternoon.

• 3:10:04Jordi Hays?

  Cheers.