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

30:12We're releasing 2 ,000 head-to-head battle results for public review. So anyone can go see these and decide for themselves, hey, did the folks at LM Arena get this wrong or are they happy? Early analysis shows style and model response tone was an important factor demonstrated in style control ranking. 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. Yeah. Um, or they might just be like, Hey, I like it. Some people want it. Yeah. Some people want a super short answer.

30:45Yeah, 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, uh, like the open AI 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 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 Mollick says the Llama 4 model that 1LM arena is different than the released version i have been comparing the answers from arena to the release model they aren't close and so what he did was he was he looked at the the actual results that were posted on lm arena and then same query on the llama 4 model that was released and this is evidence that they that they went to lm arena with a separate model yeah which is controversial it's not what you want to do i mean it doesn't inspire aggressive approach cotton yeah but uh you gotta be interested to see what jeff thinks about all this and so uh ahmad says seems like there was a lot of truth in this leak from two months ago llama four is beyond disappointing it's a model that shouldn't have been released um and this is from probably blind or something meta meta gen ai organ panic mode it started with deep seek v3 which rendered llama four already behind in benchmarks adding insult to injury was unknown chinese company yeah i 5.5 million training budget.

32:15And there was that meme of Iron Man being like, they built this with screws in a cave. 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. Save both. 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 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.

32:57That actually backfired months earlier. The demo was pulled after only three days amid criticisms that it confidently generated false information. And if you remember GPT-3, 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. And once ChatGPT 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 Leon Lacoon is involved in. They were hard at work on large language model they believed could compete.

33:30Llama One was the fruit of that effort. A set of models ranging from 7 billion to 65 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. Unlike OpenAI's headline-grabbing GPT-3, Llama wasn't offered as a public chatbot or API. Instead, in its initial release, Meta made the model's weights available on a case-by-case basis to academic researchers.

34:07So you would just email them and say like, hey, I'm at Stanford, like, 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 GPT class model in raw form.

34:36And 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. He's in the waiting room. Let's bring them in. Jeff, how are you doing? I'm doing. That'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.

35:19For sure. Yeah. I'm Jeff Huber, the co-founder of Chroma. We're 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. Can we go to this post from Sean? He says, unpopular opinion right now, but Lama's four 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?

35:57Yeah, yeah, for sure. I think Silicon Valley has a tendency to be extremely intellectually shallow. This is both a strength and a weakness of the Valley, to be clear. In our view, AI is not this deus ex machina, this technical machine god, where all of the information of all time is always going to be in the weights of this model. This is really just a new form of computing. And so in the same way that we have a memory hierarchy in classic computers, 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.

36:33We have the actual sort of transformer attention heads. We have the context window. We have the retrieval system and tool use. 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. You know, I think like 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.

37:07Of course. But you know, 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 a real system depends 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 a haystack tests, like are not actually that representative of like real world utility and reliability of long context windows.

37:46You know, they mentioned in the training for Llama 4, they don't even have passages that are longer than I think 250 ,000 tokens. And so anything for X-50 ,000 is just synthetic data that's just made up. And so what Sean is saying is that like, well, what 10 million tokens is finally, a context window for Lama 4 is finally going to put to rest, is that long context windows are all unique. The 10 million context window length is going to finally, hopefully, 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.

38:16Should we amanitize the eschaton? 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. You explained that to me a while back. I had fun with that. So let's talk about Lama4. How should startups be thinking about Lama4 as a tool in the toolkit against the other options that they have? Yeah, I mean, I think Twitter is equipped to, and research in general, 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.

38:57You know, we've seen, you know, going all the way back to sort of the slack in 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 sort of very best open source like chat experience for consumers. 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.

39:35And, 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 can build your startup on GPT-4 and it's amazing. And then there's a new version out and opening it deprecates the old version. And all of a sudden all of your prompts don't work the same. And so open source models are going to continue to play an extremely important part in the ecosystem. Now, obviously, the DeepSeek R1 launched a few months back. It totally took everybody from surprise. I think we're still in the early innings of this stuff where good ideas can come from anywhere.

40:14And oftentimes good ideas do come out of the sort of groupthink, you know, context of Silicon Valley, right? So, you know, but yeah, I wouldn't bet against that. 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? I mean, the bull case for LLAMA for meta is that it's actually more equivalent to how meta open source its data center kind of layout and right. And that's the bull case for meta is actually in industry, sort of forms around that and because the standard, right?

40:58That's sort of why, you know, what argument for why they did it. In terms of like the Red Hat 4, you know, I think that like Red Hat 4 works well for operating systems. But I don't think of an LLAMA 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 read it about that some more. I'm not sure. Yeah. If you're running meta AI, what would you do from here?

41:26Not to put you on the spot or anything. Yeah, to be clear, I'm not running meta 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 on what developers actually need and want out of models is also very important. 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 in 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?

42:02The developers actually want out of models. and so like if you want to create a groundswell of developers that like love your tools like do the developer experience part like meet them where they are and like give them all the hooks that they need and don't just stop at like hey look you know we hit stand-of-the-art benchmarking aren't we special 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 5 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.

42:38Like it feels like there's kind of a bifurcation of the market and maybe the opportunity is actually 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. I mean, focus is probably always a good, you know, lesson for all of us, right do less and do it better yeah um and so you know presumably it's also true for meta i think also obviously unlimited capital can both be a blessing and a curse in that way um uh yeah again like focus on developers yeah 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 um you know you don't need to beat um you know gpd5 on some Yeah.

43:23Do you think that part of the narrative that we're seeing around LAMA 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? I mean, you know, I, you know, so you mentioned a moment ago sort of the, you know, immunitizing the eschaton, right? You know, around history, you know, every exponential that we've observed eventually results in a sigmoid curve. You remember early COVID, right? The fur of like, oh my gosh, the Twitter guys doing their thing where they're like, well, if double the amount of people get it every day, everybody on earth will have had it seven times in the next - Yeah, 100 billion people will have it.

44:00Yeah, exactly. Exactly. And so I think that there are laws of physics here. I think that there are diminishing, they're clearly diminishing marginal returns, right? We're sort of spending 10X on compute. We're not getting 10X or better models, at least evidently not yet. And so So, you know, the transform 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 the technology and sort of sort of boil it down to, oh, this is sort of just dumb pattern matching, right?

44:35By 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. Yep. So yeah, new things are definitely needed. And, you know, I think that like an inference 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 computer architectures are and operating systems and kernels like a pilers 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.

45:04From 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 work for a year when, you know, they could be working at Chroma or any of these other labs. I mean, yeah, you know, airplane red dots.png, right? I guess like if I was affected by that, I wouldn't know it. Yeah. Can you take us through some of what Chroma 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 Yeah, I mean you've heard left and right on the internet now for like three years all about this acronym rag I don't know why anybody would ever name something rag.

45:54That's 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 got to teach it about your data. You got to 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 going to get 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.

46:28And that's the problem that retrieval solves. 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 of beta generation, or it's, you know, using retrieval, it's sort of a 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 Like unstructured data is like 10 times the size of unstructured data.

47:00We have 10 times more unstructured data. And then you consider like the real world, right? If we were 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. And like, it's just sort of like, you know, going to be a thousand X, 10 ,000 X, a hundred thousand 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 an agent, you can call a robot.

47:33You know, I don't love any of these terms. But like, really, the goal here, ultimately, I think, for anybody who's building 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. 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 and reliably?

48:04And 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, we think that retrieval plays a key part in kind of how that happens. 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 mentioned artificial intelligence directly, find that uh or i could try and fine-tune llama 4 on it and maybe it just hallucinates like oh yeah john was talking about this randomly uh how how would i how would i uh use chroma to create a more definitive index of every time john or or guest has talked about artificial intelligence or or llama in you know hundreds of hours of video yeah is that something you could do Yeah, we're seeing some kind of fun things today where 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.

49:18They're loading it into a tool like Chroma, hooking up to a language model, and they're giving end users the ability to chat with John and 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? Or maybe they don't even say llama. They say the latest release, the latest AI from Facebook thing, right? Yeah, exactly. Llama.

49:46Yeah. Like the search is good enough that it can like find all the relevant things that you've said and then the elephant can like respond as you because it kind of ground itself in the things that you've said before. Yeah, 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. Fuzzy search is really useful when people like are not, you know, experts in their own data, right?

50:17Instead 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. It's not a panacea again. We're not monetizing the eschaton here. We're not too teanic, right? But it was like a very powerful tool and people are getting a lot of value out of it. Yeah. I'm curious your reaction to AI 2027. If 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.

50:54I'm clear. I'm curious to think how you processed just the forecast generally. Yeah, maybe maybe take it from there. 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 health care, better legal representation, you know, better financial services than like billionaires have today. I think that's like entirely possible.

51:32And that's impossible with the model 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. And, you know, I'm just like not that, frankly, that interested in like secular eschatologies about, you know, apocalypse in the end of the world. Right. Like there's a natural tendency for all humans to believe that, like, we are the chosen ones living in their special time and the last days.

52:06Right. You know, even Fukuyama. Right. You know, wanted to, you know, sort of like end history. Right. And so natural human tendency, you know, this is again, the immunitizing 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 people that have died, you know, across the different world wars and different, you know, dictatorships like it is oftentimes it's like messianic complex that leads to a lot of that. And so I don't know. I'm just like, I think it's I see it as entertainment more than anything else.

52:40Yeah. 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? Yeah. Yeah. Wall Street Journal, if you're watching, send me an email.

53:11Yeah. All that's very doable today. I think that the reality is that your classic, the future is already here. It's just not evenly distributed yet. Any technology of consequence, even if generationally important, still takes decades to roll out. That's just the same is true here. 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. Thanks for coming on, Jeff. 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.

53:46Going to talk tariffs, going to talk industrialization, another theme we love on this show. We have some big news. And I just want to know, was this fundraise announcement always intended to go out today? or did they bring it up? Oh, because of the tariffs. Because of tariffs and everything. It's entirely possible. Just too good. 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 Tonsing, Founders Fund, Lux Capital, Andreessen Horowitz, and others, The best time to build this business is right now.

54:32Yeah, no joke. But the real work began decades ago. And they launched a beautiful - And he just decided, I'm going to get every big fund. Yeah. I'm going to just get them all. Yeah, it's great. He ran a process. He says - Yes to everyone. I'll take a bit from everybody. And it's great. They put out a four-minute video produced by Jason Carman, 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.

55:08Well, they sat down and 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. Hey, how are you guys? 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? Absolutely. So my name is Jay Malik. I'm the CEO of the Advanced Manufacturing Company of America. We call it affectionately AMCA. 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.

55:49So that's both existing and new systems, you know, the stuff that Boeing makes and the stuff that Andrel is going to make. 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? Yeah, so first, let me just start at a high level, right? When we talk about the aerospace and defense crimes like Lockheed or Boeing, they don't make anything today.

56:23They'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 the 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.

56:57And so 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 see in a cockpit, for example.

57:30And so we're focused on things like switches, panels, displays, power units, things that are critical to the pilot if it's a manned system. And if it's an unmanned system, critical to communication and executing on the mission. So those are the areas that we're mostly focused on right now. 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 everything in the news? 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.

58:10You know, didn't want to cover anything. And so we basically said, I'm not sure if I'm going to curse on this podcast, but F that. And said that this is actually the best F-ing time to take our company public. So we just did it. And so, yeah, it was it was planned, but but obviously timing is definitely in our favor. 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 structure of the business generally? Yep. So we're going to be, we've already acquired one business that is a critical avionics supplier, which you saw a video or some people may have seen a video about.

58:54We're going to be acquiring probably another two to three of them over the next 12 to 18 months. We're also going to be doing our own clean sheet design and development of adjacent products in this space with our own manufacturing and engineering talent. So it's a hybrid approach. I'm a firm believer that especially in this area of the supply chain, 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. That's not going to achieve what companies like Andruil want to achieve 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.

59:43And as 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 percent and increase pricing to and hopefully flip the business in three years. 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. Yeah, it actually goes deeper than that. So I would say the one thing that I have learned building this business so far, I believe it's still early, is that owners don't really necessarily care just about the time horizon and your ability, obviously, to underwrite the deal.

1:00:19They also care about, one, not selling to MBAs, not selling to traditional finance people. You'd be surprised. 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. And so our entire team are engineering and manufacturing folks. We spent our entire careers, you know, designing things for SpaceX, manufacturing things.

1:00:53We're also young, which I think people like to see when they're selling their business. They know that just looking at the person across the table, that they're going to be there for the next 20 or 30 years. So I'd say all of those things combined make it a pretty strong pitch for wine to sell to us. Did you have this idea in mind or a rough idea of it when you decided to go back, enter your next chapter? I remember it felt like a year ago when you decided to move on from active investing. It felt like I just remember that instantly you shared it and it just was everywhere. And because people at that time, it was like every non-deep tech, hard tech investor was starting to pile into the category.

1:01:38And 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, kind of the origin. What am I doing? getting in this week. Yeah. I'm curious, like how, how the idea and the opportunity came together. Yeah. So I, you know, I spent three or four years, obviously my career at countdown, um, when I was 24 years old, you know, I started the firm. I spent a lot of time, you know, with, 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.

1:02:11And so I'd spend, you know, three or four years in the space. Um, 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 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 the mom and pop advantages with the spirit, the culture, the talent of a startup. When you're venture investing three or four years every single day, your mind is just like, startup, startup, startup, new things, new things, new things.

1:02:58You're not even able to think about what does the future look like using something that already exists. 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 key themes, and then started to iterate from there. Talk to people, talk to customers in the industry, talk to people at companies that are already 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.

1:03:36And at the same time, I know a lot of people who are in the traditional world. And I should use that to the maximum advantage that I can. I have one last question, then I'll let you go because I know you're busy today. Charlie Munger criticized Transdime 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 Transdime model? Trans-Time is actually a phenomenal business, and it's actually not the cause of any of those issues.

1:04:16The cause of those issues, certification, lock-in, et cetera, et cetera, has to do with decisions that were made 30 years ago at the top of Boeing, which is a paper right here 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 Transyme 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 partnership with the customer to reverse that type of decision-making and culture.

1:04:59so yeah my answer to that is i think trans time is actually a great business they have they have run businesses very very well they're in an environment that 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 apps well that's a fantastic answer thanks so much for hopping on on short notice uh congratulations on the round and uh we'll have to have you back yeah i have so many other questions we can talk for yeah very excited for you and the team and excited to have you back on the show soon.

1:05:29Thank you. Let's do it. Take care, guys. Talk to you soon. Bye. Well, we are moving on to someone from FAI, the Foundation of American Innovation, I believe is what they call it, FAI.org, the FAI.org. I've been to a couple of their events, very fun. Gary Tan spoke at one, Trey Stevens spoke at one, 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 in very good spirits and kind of like taking pictures of everyone it was a lot of fun anyway welcome to the stream boom how you doing hey man how's it going it's good what's going on thanks for hopping on uh your hair game is on point as usual chill week chill week for you sleepless nights probably on maybe eight hours over three days you should get an eight sleep go to eightsleep.com slash tbpn I have a helix no we'll get you to switch no it's great to have you on what's running through your brain there's a bunch of things we can talk about but where should we start oh just the contagion effects and potential collapse of the world economy simple stuff like that you know US primacy Are you a, is there any element of cautiously optimistic about this for you or are you just totally blackpilled on it?

1:06:58I mean, my white pills are Lucy's, so I do have some of those. But, you know, you're going to need a higher milligram for this week. Well, walk me through 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. Sure. So I'm chief economist for the Foundation for American Innovation. Ripping the swag here. FAI. We are a tech policy think tank in Washington, D.C., originally founded to bridge Silicon Valley and the D.C. 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.

1:07:44and um you know i think we we kind of or at least associate it with the sort of tech right with with you guys like yourselves like i'm rooting for y 'all and uh hopefully martin scurley's bloomberg terminal killer takes off so then we can combine combine you guys and completely disrupt bloomberg um 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. Um, but, uh, you know, Elon Musk today called Peter Navarro, Peter retardo. And I kind of, I kind of, uh, you know, definitely, uh, hard to argue with.

1:08:25Can you talk about the, the bridge between Silicon Valley and DC? Uh, it feels like that bridge is massive at this point. There was a moment where, 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 was a moment when big tech and DC were tightly intertwined. It just happened to be with the Democratic Party. Now it happens to be with the Republican Party.

1:09:04Um, but what is, what is the state of the bridge and how did we get here? Yeah, I think it's almost like a qualitative difference. So if you think like the last 80 years, the power structure in the U S is being sort of either wall street or like West Texas oil. So we either get like Rex Tillerson or Jamie Dimon. Sure. And, you know, since the internet took off, you know, there's this new, new wealth on the West coast. And, um, 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.

1:09:48Sure. And 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 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, back in the day, I used to do like supersonic policy and worked early with Boomi Aerospace and it's good that they're getting a hearing now and maybe I'll be able to fly to either coast in a couple hours rather than...

1:10:22I'd love that. So there's 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 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. 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.

1:11:02And you do see reciprocal tariffs, but 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? 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. But then you have other people like Stephen Moran and Scott Bessent and J.D.

1:11:43Vance himself as well, who at various points talked about the curse of the U.S. 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. Yeah. 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.

1:12:20This is about resetting global financial imbalances. And 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 emerging calls. And, you know, I think mortgage debt is now back to its 2007 levels. So it's less to me about like the mood or the ideas behind the policy, but the execution. yeah but they are there this is a rug pull of you know rugged uh can you talk about uh you know the value of the yuan has been uh 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 yeah so you know china was a currency manipulator through throughout a lot of the 2000s and early 2010s, but that really hasn't been the main way that they cheat.

1:13:22They cheat by basically suppressing household consumption and having these 60 % savings rates. And so they end up building these ghost cities and whatever technology they enter, whether it's cars or telecom equipment or pick your poison, they just overproduce it to the maximum, drive down the cost worldwide, and then have to find these export markets to dump it. And the way that The way that we're ever going to resolve this is, especially now that the US is going to have 100 % plus tariffs on China and Europe doesn't want their shit either. They need to build up their domestic economy. They need to reduce their own savings rate, raise the standard of living of their households, introduce some basic social welfare programs or something so that they actually have a domestic consumer base.

1:14:11and 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 um then it's a win-win situation if instead they double down on tariffs and trade war um you know i don't see i don't see we just exacerbate the the uh the contradictions in the economy and don't get to a resolution. Ben Thompson has been advocating for a rethinking of the CHIPS Act, mainly shifting from export controls, removing those, and instead taking a more Operation Warp Speed approach where the U.S.

1:14:57government is potentially a massive buyer of domestic-made three-nanometer, five-nanometer chips. 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 i'm not opposed to the idea um the thing about like you know nvidia's chips is their their kind of 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 uh loyal uh 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 uh you know these companies have had corporate social responsibility policies but not corporate patriotic responsibility policies and and technology is becoming geopolitical and you sort of have to pick your side and so you know every time we introduce an expert control nvidia's two weeks later has a new chip that just gets under the line of what's being controlled and the latest one is the h20 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 surge being 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 um 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 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 can you talk about uh putting the the trade wars in the context of like this race for super intelligence 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 um you know there's trade war in in the year 2025.

1:17:27No I 100 % agree with that take like um 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 data, China maybe even has an advantage because they don't have privacy laws and they can just scoop up everyone's genome or whatever. And then it comes to energy and chips.

1:18:04The export controls exist because right now our only structural advantage is the chip and hardware stack where our install base of NVIDIA data centers is a huge portion of the world's. China's been basically cut off since 2022 and 23. Then when it comes to energy, you know, China added 446 gigawatts of energy last year. It was a 20 % 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, um, you know, the, the chips are, the chips is the short run bottleneck. So that's why we need to lean into that.

1:18:41And then the long run is like, how are we going to supply the energy? And then as the stuff diffuses, you know, to the people who worry about the industrialization, it's like, it's true. The last 40 years we've specialized in, you know, higher education, knowledge work, legal management services, Hollywood, you know, the creative class, all this stuff that is going to like be deflated. And China will have the factories that will become fully automated and do 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 innovation in bits will be their innovation in atoms 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 uh production we need to lean into automation and robotics uh how do you think about job creation uh as part of reshoring uh and and increasing domestic production in the context of uh 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 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 uh it's not going to be this nostalgic vision of like 1950s where we're all going into the factory um and that's just like a structural thing we're not that you know ai is going to do that for a lot of stuff probably you know most stuff at some point and we're gonna have to figure out what the new jobs are like i saw on uh you know i saw a video of like professional back scratcher yeah you know i know in the bc world those exist already but like uh but this was like a woman of long acrylic nails and so you know maybe we could start crowing our nails out um crazy so the 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.

1:21:04There's clearly a lot of high skill labor that is not getting displaced anytime soon that could... That's not millions of people. Yeah. Well, it might be if we're manufacturing a Dyson sphere with a million robots or something. I don't know. I could see a world where, yes, there are a million jobs in the manufacturing sector, but it's all at the higher level. But if two million traditional white collar jobs get evaporated you know in the interim there's clearly some big uh big questions we're gonna have to be thinking about yeah uh do you have strong opinions on unitree or any of these other chinese robotics companies that are trying to he's just like i love them uh yeah uh i'm curious if you've written about it if you've had you know policy recommendations that your fai have have made around uh you know some of these more hybrid sort of dual use um well everything's dual use in china but um what do you think about the unit tree is really impressive and you know i've seen it do like kung fu and it it does break dancing better than that australian lady oh yeah um yeah and but 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 U S that's number one.

1:22:27And number two is like, yes, we have the data centers and the better models, but China, you know, has, uh, 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, um, 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 We also probably need like a batteries act to compete with that because that will be the thing. It's fine if, you know, Anduril builds a drone factory, but where are these batteries going to be coming from? Yeah. Not asking for financial advice, but where specifically in America are you long?

1:23:07You know, areas that could be that sort of American Shenzhen or maybe it's multiple places. I'm curious what areas, you know, different regions in the United States do you think benefit from reshoring most intensely? In recent history, it's been sort of 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.

1:23:47Longer term, this is also not something that the U.S. can do alone. We're going to need almost like a North American plus production frontier. Let's figure out the thing with Canada. Do we need their lumber? Do we want their bags of milk or not? But 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 U.S. 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 do have like, I'm not a technological unemployment guy.

1:24:34I think new jobs get created, they'll just be very weird, not necessarily in the sectors that matter the most. The purpose of heavy industry and robotics is more military. And do we control the supply of core goods and services? 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%. 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 wins lately.

1:25:18We've helped us to build in Utah. There's activity in 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 base 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 generators rolling in, like that investment makes way more sense. If you know that after that, you know, GPT-7 is trained, that you get to put your energy back into a grid and have customers for it.

1:25:59Uh, so that needs to be fixed. Other energy sources, you know, I think enhanced and advanced geothermal are, they were underrated. I think that people are starting to finally wake up to the potential, you know, with, with like real, 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. Um, and then with nuclear, you know, there is this case before the courts that, um, I think is Texas, Utah versus the U.S. government, the NRC, that argues that the NRC doesn't have jurisdiction over small modular reactors.

1:26:34And I think there's a good chance 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 nuclear regulator. And so that could happen sooner than people realize. That'd be fantastic. Do a bunch of young founders building small nuclear reactors, does that scare you? Does that keep you up at night? Or do you think the technology is solved? Doug Bernhard at Radian isn't that young. He's got kids. I trust him with my life. Yeah, basically, I think it's a big requirement.

1:27:09You should have to have kids to be a nuclear founder. He worked at SpaceX. He's got a pedigree. I love that company based in El Segundo. the big problem with nuclear is it it's it doesn't really pencil out without like large government support yeah and um and so i would love to see like the 600 billion in tariff revenue you know be given to doug bergham 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 um but it does need it will need like some kind of fixed capital backstop to make those investments, at least with the current technology.

1:27:51I mean, given what you're kind of optimistic about Doge, it seems like you're pretty bearish about the tariffs. 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.

1:28:28Yeah, 100%. You know, the state capacity and competence is really, you know, it's the jagged frontier. There's places that have a lot of it places that have a little of it uh you know i would have more you know i would have more trust in a burgram or like a chris wright of actually you know executing on something like that um it wouldn't be the pete buddha judge slush fund where it's just filling potholes in in indiana um they they they would know how to cut through the road 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.

1:29:08We need to keep our potatoes and our gravy separate. 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... 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? I think what I find most impressive about DeepSeek is less that the model they put up, but just that they sort of have imported a kind of Silicon Valley model of like, and that came from their CEO being like a hedge fund manager doing this as a side project.

1:30:02It's very, you know, Sam Altman wasn't a hedge fund manager. He was a VC, but sort of analogous, right? 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, 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. But, you know, it's a fun take. They've been great at, you know, publishing what they're doing and everything sort of has checked out.

1:30:46But they don't have the chips and 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. Um, the commerce department has, Howard Lutnick has said that he's going to export control at age 20, but they're so distracted by tariffs. They haven't prioritized it. And the time is kind of running out. Uh, what's going on with TikTok? Uh, we've been following, uh, poly market around a new band before May. There's markets around, um, you know, potential buyers, things like that.

1:31:27do you have any insight uh that you can share around the latest there it feels like again one of those things it'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 uh but at the same time it feels like something that we were supposed to have answers around by now and we definitely don't yeah totally i mean fai we led the charge to ban TikTok over a couple of years. And I fully support it. I also enjoy TikTok. But I do notice that like between my barbecuing steak videos and like funny memes, I'll get like a Pyongyang tourism board video now and then.

1:32:16It's like, well, 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 you know oracle maybe being part of this uh and i think trump still wants it to be part of the new sovereign wealth fund um and actually as sort of zanian 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 um the interesting thing here is like, you know, people have pointed out that, you know, Trump is sort of placed fast and loose with with the Constitution, with the law and stuff like that, you know, and a matter of fact, all the people he's fired, totally constitutional.

1:33:04The biggest, the most unconstitutional thing he's done today is not enforce the TikTok ban. 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 I would just doubt it is is China has very strong expert controls like the reason to talk 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 the offices but they have to completely re revamp the algorithm which is like the secret sauce of the thing now tick tock is in our building in DC so I can uh I can try to plant a bug for you if you want sounds great well fantastic Polymarket has the chance of TikTok being on the App Store on May 1st at 97%.

1:33:50And who will acquire TikTok? Oracle's 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. Yeah, and get some sleep. Yeah, get some sleep. We'll work on getting you an eight sleep. Yeah, yeah, yeah. Start putting in some proper sleep scores. I want to see a hundred for a week straight. I think, uh, yeah, less red light from the stock market more. Yeah. Yeah. More. Um, no, but go, go get some sleep. Uh, thank you for, for coming on and, uh, yeah.

1:34:24Looking forward to the next one. Yeah. Talk soon. Bye. Later, man. Cheers. Next up, we have shield coming back on for a second TVP and 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 Shield 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, Deep Sea. There's like seven different really important questions.

1:35:01Maybe we'll talk about it with Shield. Maybe we won't. But let's bring him in to the studio and welcome him to the show. Welcome. Boom, back with a suit. Looking great. How are you doing? Looking good. Looking good. No, no Apple watch. 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. Yeah. The tariffs haven't hit the secondary market yet. No, it's a great buying opportunity. This is financial advice. Go to get bezel.com, download the app just for shield. Just for you, not for the listener, for you specifically, you specifically i want to see uh an adam r piguet or or royal oak on you something like that um well uh you've had a bit you i feel like you've been uh the timeline's been in turmoil and you've been at the center of it i guess i guess chamath knows who you are now now that that people reminded him that he would use your content in his newsletter yeah um but That was so funny.

1:36:03The whole thing. The whole thing was funny. I'm sorry. I mean, honestly, probably good metrics, I'm sure, were up into the right. Elon Musk's flowing. The creator payout this month. Elon Musk's flowing. It's going to go from$200 to$100. Except he'll pay for screenshots of his content with just, this is why I can't believe this app is free. And this is why I'm never deleting this. I'm never leaving this app because of the interaction. Yeah, exactly. Anyway, can you give us just 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.

1:36:40Yeah, wow, right into it. Okay, I'm kind of like I've always been more of a free market kind of guy. An American. And I think free market American. Yeah, American. I've been an American guy. And I tend to think competition makes us better. And I also spent time living in protectionist India. Sure. 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 two local car manufacturers and the cars were like built in the 50s and they like didn't get any better from the 50s until the 90s. Because India had so much protections on their local car industry.

1:37:25And 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 U.S. shipbuilding industry. so like the jones act basically says that if you if you're shipping goods between two u.s ports you need to use a u.s built ship crewed by u.s citizens and owned by u.s citizens so like it's super protectionist to the u.s shipbuilding industry and u.s ships suck 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 exists because of the jones act so anyway so i think like all these things like i'm totally anti-protectionist um there's a question of like what is trump doing is like with it's not really a reciprocal tariff 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 um 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 latnik saying like we need millions of Americans screwing in tiny iPhones or whatever.

1:39:15And 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 putting these tariffs in place to reshore. And I personally don't like that. Isn't it fascinating too? I'm sorry, go ahead. There's this focus on trade deficits, but we're completely ignoring 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 yeah i guess i guess that like a lot of people in switzerland are subscribed to netflix and we're just like completely ignoring all of that yeah and and you know yeah i have a And we're the richest, most prosperous country in the history of the world.

1:40:13It'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. We can afford it. Yeah, so the steel man here is like, 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 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.

1:40:50And there's dual use. And there's a million different factors. So how do you walk through that specific example narrowly? Let's take away the blanket tariffs. Walk through that for me. And how would you solve this in a more free market, more progressive fashion? Yeah, that's a great question. So first, we have tariffs on every country, not just our enemies with Trump. But China specifically, I do think China is playing unfairly. And they're our enemy. And we shouldn't let our enemy get data on the United States. That could be really bad. There definitely are national security issues with drones.

1:41:28I also think we should ban TikTok. Sure. And so I think those things can be dealt with, but they have nothing to do with tariffs. Yeah. I guess one of my scenarios would have been if I could replay everything with everything I know now, maybe you see what's happening with DJI and GoPro and you say, hey, we are the richest country in the world. 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. Totally. Essentially backstop GoPro, let them get down the learning curve. Hey, if they make these drones in America, we're going to buy them even more and let us develop that.

1:42:13And then we are competitive and we say, hey, it is a little bit, we're still shifting the invisible hand, putting our hand on top of the invisible hand, but 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 incentives. Elon did a great job taking advantage of it. Like, and we got a great product, you know, it sold really well eventually. 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.

1:42:46Like they enable, they subsidize U.S. chip manufacturing that are critical for military systems and other stuff. I think they have made some moves away from foreign chips. And so 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 ideas you mentioned, John, are spot on. And by the way, we helped Tesla along the way. We loaned the US taxpayers, loaned$500 million to Tesla. That kind of thing I'm totally in support of. Totally. Enable US manufacturing to be better, to compete on an even playing field by being more innovative, not by blocking other countries from competing.

1:43:29Yeah, yeah. Jordy? 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. Circle's still at 86 % on Polymarket for this year. Yeah, they might just be like, you know, crypto, we were born in the darkness. We're going out. 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 take on the IPO or dug into it at all. And you don't need to have any knowledge to have it.

1:44:18You don't need to have any knowledge to have a take, by the way. Yeah, no, I would say like on Circle in particular, like I saw all the same stuff you saw um coinbase gets half of the revenue from circles 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 stable coin hype and i bet if circle was public at that point they would have gotten a huge bump for no particular reason totally yeah um but i think overall stock market yeah like what does what does polymarket say about carna is there a market for that oh i don't know jordy can you look at all right i think officially pulled their it pulled well like the thing is these tariffs are especially especially bad for clarna 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.

1:45:30Yeah. So like you're not buying that extra$2 ,000 item that you didn't exactly need. Yeah. And that's what you were BNPLing anyway. Yeah. So I think we've seen a firm stock. Oh, yeah. I think our firm stock got cut in half. 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 fascinating. This is a case with 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.

1:46:05And Circle obviously is, but 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 stable coins 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. 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 process it any differently, but. Yeah, I think it's certainly less less hyped than all the others. the ceo jeremy allaire i um i went to a stable coin conference a couple months ago and he spoke and so he's very sharp um 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 oh cool um and then and then launched circle whatever 10 or 15 years obviously not 15 years ago.

1:47:06Bitcoin didn't exist, but yeah. That was the best time to launch a stable coin before Bitcoin. Getting really early. I mean, there were digital gold companies. Here's the bull case for USCC and here's my bull case. Sure. So Tether is like the most profitable financial institution ever, right? Like it's literally, what are they? Is it$8 million? It's like$50 million per employee or something. I forget the actual, You probably shared it at some point, Shiel, 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.

1:47:43You 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 they're dominant from a market cap standpoint. The second biggest stablecoin is USDC at a$60 billion market cap. And a market cap is obviously just one-to-one with the supply. And then you go down the list. The next one is DAI, which is also run in a very crypto-native way from what I know. And then 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 two billion dollar market cap and below that is paypal usd usd which is an 800 million dollar market cap and so to me i'm looking at circle and it's like here's like the power law winner 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.

1:48:54Like it's a pretty good ticker. I mean, the crazy part is we talked to, we've not super sophisticated, but it, you know, brand matters. I mean, we talked to Zach Parade, uh, plaid and we were like, if you had, you know, full authority, you were like the president, could you speed up wire transfers and 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, and all the, the pitch about just, Hey, it's just going to, 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 chances.

1:49:26What's your read on any sort of predictions on venture right now? I think 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 yeah denominator effect yeah 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 then i I want to kind of ask more about portfolio stuff.

1:50:11Yeah. 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've 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? Yeah. So, you know, every... Yeah, yeah. You don't have to be...

1:50:48You're living up to the vulture capitalist name. I like it. Making money. Yeah. How do you even think about... There's going to be some enterprising founders that are like, look, I'm building a startup around 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 deglobalization maybe it's too early to make um bets but um yeah how do 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 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.

1:51:41I saw you guys have Jay Malik coming on later today, which sounds like he timed that perfectly. Yeah, it was crazy. Yeah. Like literally. 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. So, you know, it's mostly stay the course. I think people are saying, okay, venture capital dollars are going to decline. But as you know, the way it works is we raise a fund every few years. Yeah. And we have plenty of capital. So it's not like there's some impact on the markets today, and that means we don't have money tomorrow.

1:52:26It's like if there's any impact, it's a few years out. So 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, that makes things difficult. And like they're thinking on an IRR basis, like has their opportunities have declined if they can't, if the companies don't get out in a reasonable time. Yeah. So mostly just texting founders in the portfolio. Have you seen this with a screenshot of the market? That's just what I always do.

1:53:02Yeah, exactly. I want to get your reaction to this post from Semmel 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 early 2022, VC 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? No, I love Semmel, but I don't know if I buy that. Secret is already pretty high, right? That's the thing. Please. Please. Please. Don't tell the founders this. Don't tell the founders.

1:53:47It's like, wait a minute. I can raise my safe by 50 % with one stroke of a pen? Let's do it. Yeah, it doesn't make sense to me. because so we started this fund in 2019 and actually like the seed valuations, 2021 was an insane time, especially in FinTech. Like everything we were investing in seemed like it was like turning to gold and then maybe turning to shit afterwards.

1:54:15But actually like seed valuations have actually increased from that time. And it's basically kind of been 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, and the problem is if you're a multi-billion dollar fund and you write a$2 million check to a company and you invested in the wrong company in the category, 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 of a small amount of money so i don't know i'm skeptical that this is going to happen again uh or that it's going to really 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 carta uh give us the data in a year i love his stuff uh can you talk about uh there's this meme of like, oh, for a while, if you're building a consumer or something, like you're gonna get steamrolled by what if Google builds it, right?

1:55:29And 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 an idea that, oh, Amex or Visa or JP Morgan are going to build this and has that ever actually happened in practice well yeah and even yeah actually on that i'm curious like open ai wants to run your entire life yeah have you heard any sort of like rumors or is any concern around people saying oh i'm building a consumer agent you know uh for financial consumer financial services yeah but then open ai might be like oh by the way we launched a partnership with chase and or we launched a partnership with cash yeah we can analyze your credit score now with an agent and that that model that that rapper company got got steamrolled yeah what's your take on all that okay so first thing i think you said was the rest invest situation yeah where um and so i thought it was really funny because you guys watch silicon valley the tv show oh yeah so good and there's that obviously there's a the phrase rest invest i learned it from that show um and it's certainly playing i had no idea that that that phrase was like popularized in some way by the show oh yeah yeah i thought it was i thought it was a 2021 like big tech thing no no no no this was the thing going back like a decade if you haven't seen it you got to go back and watch it's so so i never could i never could get into it because i it was just too close to reality like the most like it was not like i I watch TV because I want to not think.

1:57:11Yeah, totally. Watching Silicon Valley is like, oh, that's an email I need to reply to. Exactly. I should follow up with that founder. 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 I knew him and he's like actively poking fun at me every single episode. That's amazing. It was great. But yeah, it's very silly that Google would let this even leak out. I don't know how that happened. Totally. It's crazy. I mean, the things you hear out of Google are so crazy.

1:57:45It's wild. I think 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 had stuff like this, but not now. Okay, so that was topic one. But I think topic two was like, what if X company builds this? And is that the case in FinTech? I don't think so. In fact, you actually had, look, one of the sponsors, Ram. So Stripe had built Ram. Stripe had a corporate card. And it didn't work. They ended up investing in Ram and deprecating that card. So I think people have tried to do stuff.

1:58:26There 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. 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, OK, like, we're not charging 2%. We're going to charge you 25 bps. but the reality is that the service offered by somebody who's charging 2 % is different than what they offer at 25 bps and the 25 bps solution was fairly easy for vanguard to build and vanguard became by far the largest robo advisor in the world got it um but i'm not i'm not afraid of that in general um infant too much do you think that uh do you think uh Humanoid robots present an opportunity for loan sharking as a service.

1:59:25Come break your legs autonomously. Break your kneecaps autonomously. It's like, hey, we're going to offer you this great raid. Whatever. It's secured against your kneecaps. It's secured against your kneecaps. It's funny. 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. What do you mean? like obviously the use cases for lunch sharks yeah yeah um i mean i was talking to a sales guy i'm curious like my thought goes with um uh the do you think that ai can can get is already or could get materially better at underwriting than than 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 what's the uh what's the public company that was sort of promising this for a while something um i mean there was metro mile which was better underwriting upstart but even metro mile was better underwriting for your car insurance based on how you drive they put a gps tracker and uh 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 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 phone and it like checks if you're breaking hard and where you're driving and stuff like that So I think that there are opportunities to be used in insurance.

2:01:16In underwriting for loans in particular, it can be tricky because the regulatory framework in the United States, Equal Credit Opportunity Act, Burkard Reporting Act, et cetera, you're not allowed to discriminate on the basis of race and gender. and some of these other things are eyed to that. So that can become tricky. And you have to give people the reason why they were denied. It's adverse action notice. So you can't have a black box model that's like, here's all the data. They just give you a massive matrix of weights and they're like, this is why you were denied. Figure it out. Totally. so that tensor number 76 was activating for you so get out of here 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 model um and so so they're 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 yep um and yeah so anyway 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 gonna like be a step change in underwriting yeah makes a lot of sense uh jordy last question you want to let shield get out of here no this was great.

2:02:49Always a pleasure. Always fun. Super fun, guys. Looking forward to the next one. Yeah, this is great. Likewise. Have a great rest of your day. Godspeed. We'll talk to you soon. Well, we got some breaking news. Another massive funding announcement coming in to the studio. Victor from Craya. Is that how you pronounce it? Craya is coming in. AI video company that just announced a massive fundraise. Let me look up if I can find the details of this fundraise so I can get everyone up to speed before we bring Victor in here. The website is kreia.ai, K-R-E-A, and they just announced a huge funding round,$83 million, just a couple million over Jay.

2:03:39Not that it's a competition. They got Andreessen Horowitz, Bain Capital in the round. The past 14 months at Crea 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.

2:04:17CREA is the work of a small, talented group of imaginative, incredibly 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.

2:04:58While AI is powerful, transformative, and is going to radically change creative work, creatives aren't going anywhere. 40 ,000 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.

2:05:31No, I am reading this on the screen. Paper usage. and old tools and workflows. Do we have Victor in the waiting room yet, by the way? Not yet. 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 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.

2:06:06That'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. We're bringing Victor into the studio to tell us more about CREA and the fundraising. So welcome to the stream, Victor. You here? Yo. How you doing? What's going on? yeah i'm here great uh can you give us a brief great great to meet you guys fantastic uh is uh is the office gonna change with this new fundraise i gotta ask are you're uh you guys gonna stay posted in the living room do we have you victor i think we might have lost you seems like we're having some technical issues okay well we can hear it see and hear you now far away from the Wi-Fi router.

2:07:01I mean, that is the issue with working at home. Complicated Wi-Fi. You need the enterprise solution soon now that you have the big Series B done. So very soon. Yeah. Oh, shit. They are doing another meeting, so I'm going to steal Diego's room. This is great. I love getting the tour. I love getting the tour. You guys want to see the office? Yeah, please. Let's just do a tour. Anything that you can show us. You can turn around. Oh, okay. There you go. No API keys, hopefully. Mexican music going on. That's good. That's fantastic. Real life. Yeah. Wow. Hey, guys. How are you doing? Congratulations on the milestone.

2:07:37Looking great. Wow. You guys said you guys were not kidding about the living room, but you've really built it out. I love it. That's amazing. It's looking good. That's good. Nice. Why don't you introduce yourself? John was going to ask you that, and then I cut him off. No, you're all good. Yeah. Sorry about that. No worries. oh here we go so my my background my background yeah like i guess on my background like the tldr is i growing up i was very interested into creative things of all kinds i mainly had 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 so that way i explore like many different things from graphic design 3d graffiti art i also had like a big passion for that and and at some point i was that was in 2015 i was in i was just like finney 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 like math and i guess that what i like about math is kind of like the challenges that it poses and like the interesting yeah like i guess i like i i love challenges and math put like 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 audiovisual systems engineering it was kind of like this degree where they showed you how a microphone works how mp3 encodes audio how mp4 encodes video, etc.

2:09:47And that's where I met Diego, my co-founder. That was like 10 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 3D as well. But he also loved programming and he also loved engineering. So we both ended up like 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 my end 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 email generation that's when i fell super deep into the rabbit hole 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 ended up the good old days the good all day.

2:11:02Do you have a first question or? No, go for it. 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? All three. I think that up until Until recently, there were two very well-defined blogs of users. One of them, it was the consumer type. It was people who this technology gave them a zero to one when it comes to creative freedom or to 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.

2:11:53and 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 um then we had the professional and and the professional it was that user that did have a creative background and that he was using our technology i mean our platform to speed up some of their processes uh these speed ups like that vary depending on the industry. Like 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.

2:12:47So 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 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 do you think the broad consumer awareness is today i mean i 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 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 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 uh very easy 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 i'm the best person to have like a good sense of what is a current adoption because of how deep we are in the SF bubble yeah 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 just like saw that I was like talking on the phone in Spanish and she was from uh Puerto Rico so she started like uh talking with me and asking asking me 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 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 as 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 dii 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 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 how do you how do you think about prompt engineering long term is it is it you know i remember 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 And now it feels like it's getting easy enough to prompt a lot of these tools, I'm sure like Kriya, that maybe it's just not necessarily, maybe it's a skill set, but not necessarily a job.

2:16:05But I'm curious how you think, do you think that prompt engineering will still matter in five or 10 years or it'll just be super intuitive? I mean, prompt engineering at the end of the day, 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 it's 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 And I do feel like this is gonna, like in the future, most software that we see out there has been created by a very big percentage through problem engineering, through steering AI models towards whatever you want to accomplish.

2:17:03And I see this on the visual space. Like 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 typing up Roman and just like getting an image. I think that this new model from OpenAI kind of shows that. Yes. Speaking of the new OpenAI model, it seems like they've evolved the actual underlying algorithm. It's not purely diffusion based. Are there new buzzwords or keywords that, have you reverse engineered any of how they're doing that? 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.

2:17:59It 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? I don't have a I mean I have some intuitions but I'm not like super I don't have high confidence on how it works it seems like there's some auto-aggressiveness going on and we have already seen similar things with croc image generation but I feel like to me what it's 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 this is an image model that is able to reason and it's able to understand instructions like it's able to understand here's like the picture of my dog turn it into studio ghibli yeah and and like this this is like something new this is like something that previous diffusion models were not good at 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 a thing about like what you want to do and what is the instruction that the user wants and how to accomplish that goal.

2:19:06Yeah, yeah. It seemed like there was like how, it was like everything that style transfer should have been plus 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. But anyway, congratulations on the round. Thanks so much for stopping by. And thanks for the office tour unexpectedly. That was really fun. But we'll let you get back to work. I give our best to the whole team. And we'll talk to you soon. Sounds great. Thank you so much for having me. Thanks a lot. Talk to you soon. Bye. Very interesting. We got Leaf coming on from public.com.

2:19:42I'm curious if he's been sleeping at all. 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. 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 Leif in the studio, breaking it down for us, and we will bring him in right now. How are you doing, Leif? Welcome to the stream. Boom. What's going on? Great to finally have you. Nice. What's going on? Let's go. I had my caffeine already, so that's why I'm like... Good. Fantastic. Good.

2:20:20Somebody was commenting yesterday about our caffeine consumption. and I was like, yeah, it's easily 500 milligrams plus at this point. John, that's 500 milligrams during the show oftentimes, but he's built like a horse, so he can take it. How are you doing? We were just joking about whether or not you had slept at all the last week. I know it's been busy. I'm sure it's been a busy time for you and the whole team. It's been busy, but our systems have been up at least compared to other folks. so that's great 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 have 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 yeah i mean generally speaking just like a mini step back is like this generation of investors like called especially millennials like man they have been through market cycles like crazy in the past five years right and oh yeah or even just like through their lifetime and i'm 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 the market you know yeah and so on and i think especially like the march 2020 drop where like circus breakers hit and so on crazy 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.

2:22:14And so whenever you see these like massive drops, this is really when we see some of our best days. Yeah. My reaction - Yesterday was like, you know, one of our record days in just deposits, for example. And yeah. Yeah. Well, my reaction, 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. uh but of course like you it's very serious can you actually break down the mechanics of what it like the like what exactly is happening and and what what truly triggers the the circuit break yeah this is 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 um i believe it's seven percent and then 10 and 15 or so, essentially they paused the markets and that didn't used to exist in the past, right?

2:23:10Yeah. 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. Yeah. In Japan, don't they have lunch break in the middle of the... They do. Not just in Japan. Other countries too. 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. 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.

2:23:45What 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? Journey to speaking, I think it's definitely coming. It will also come to public at some point. Right now we essentially have 4 a.m. to 8 p.m. 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 there's a regular opening between your 9.30 and 4 p.m.

2:24:28That's the most liquidity. It's when 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 a.m to 9 30 and you know 4 30 to 8 p.m and then you have overnight which is like the new thing 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 all i give you have not as 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 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 market 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 9.30 market opens and it goes, goes down and everything normalizes again.

2:25:55Right. 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. Can you talk a little bit about information diets? 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 stock trading that happens, whether it's earnings day or jobs day?

2:26:35What are the big reliable sources of high liquidity in the market? I don't know if I have a good answer there. My gut reaction would be just from internal measures like monday mornings because you have all you have a lot of cute orders from the weekend and stuff like that yeah it makes sense you get executed at the open okay um because not everyone will trade pre-market and stuff but spreads are wider and all this all these things um but um specific days not really sure to be honest maybe like big tech earnings too is kind of like a season for generally speaking exactly like it's always like it's often just driven by market events right at the end of the day um people will trade when they see opportunity yep 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 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 yep 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 uh you know if markets are in the news you get inspired by something and that might drive action and that's what we see yeah 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.

2:28:10But do you see a lot of demographic differences, you know, sort of like Gen Z's, basically like bonds for me are just like, you know, GameStop, right? Like, I always know it's gonna be worth something. It's a store of value. It's a store of value, right? But I'm curious if you see sort of pretty specific activity across different demographics in terms of interest in these different types of assets? 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. But then I think what's interesting now is that so we've launched multiple yield accounts, essentially.

2:28:47So 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 your your bond account, which 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 a lot of people are using those to just put money into the markets, waiting for these moments of, of like, of opportunity.

2:29:24Right. So what we've seen in the last few trading days, essentially, is that people cycle out of the yield accounts and into stocks and ETFs because they essentially had this cash lying around. And we're like, OK, you know, I think 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 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.

2:29:53But 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 you're seeing younger generations using it less as a, hey, I'm going to now actually hold the bond to maturity 10 years from now. And more use like these account types that we've created for, you know, just like earn some yield on your stuff, you know, until you actually see other opportunities. Yeah. 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 obsessed with this specific stock.

2:30:34It'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 uh to help people leverage all that data with ai but um i'm curious what you're seeing that's a great layout jolly by the way thank you my pitch you know thankful sponsor yeah but uh uh yeah 100 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 teflas 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 has happened is that it's much more proactive than just you kind of have to pull information.

2:31:43And 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 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 granular breakdown on that. And so it's much more the pushing versus the pulling. And I think that's also just generally where it's going. But what's awesome to see is that these bite-sized contextual moments where I can be super fast, where it's just really great at summarization and can also go against biases.

2:32:27So 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 QA built in and a little bit of taking the bias out that maybe one writer will have or something. Yeah. Speaking of data quality, what do you think? Yesterday, Walter Bloomberg shared some news that wasn't quite accurate and moved the market trillions of dollars. maybe helped us avoid whatever it was Black Monday, Kramer was calling it.

2:33:07What do you think is, 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, 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 gonna react really quickly?

2:33:40And now retail investors are so ready to act on information. 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 a millionaire within a few hours. But I'm curious if you've thought at all about how, yeah, just, I don't know if there is a solution, right? Yeah, but I think it's, I always come back to who are you building for and therefore what behavior is your product inspiring? And generally speaking, 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 can buy a meme coin, you can do options trades.

2:34:31But 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, all the fixed income offerings that we now have, etc. and i think there are just certain design decisions that that um impact in the end the behavior of like like of these users right and yeah therefore in the end i think that is much more important uh uh for people to make healthy investment decisions than necessarily you know uh 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 yeah 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 end up being more of a gambler automatically just because of 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 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 hiker account into, you know, Amazon stock or whatever, because they see an opportunity that both to then also hold it for long term and so on.

2:35:56So I think that's much more the issue, so to say, than those accounts. I have a bunch of other questions, but I think we're over. We'll have to have you back on very soon. I know you got some big stuff in the works. Thanks for coming on. Yeah, I'm excited for the announcements. This will be great. We'll talk to you soon. See you, man. Bye. 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. What is this, a round for ants? I don't want to talk too much trash. It's great. It still gets a size gong hit. But it is funny. We've seen a bunch of huge rounds today.

2:36:39It's a good day in the markets. The markets, the public markets are down, but the private markets are ripping. let's bring in the founder and CEO of Arena AI. 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 are you doing? Boom. What's going on? Nice to see you guys. It's great. Would you mind with just starting with a little introduction on who you are, the company, and maybe a little bit was really interesting too.

2:37:14So I want to hear about that. Thanks. No, that's awesome. Yeah. So I'll tell you a bit of that company. It's Atlas AI hardware engineer. The company's called Arena. We're based in New York. 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. Switch gears, did a brief stint through consulting. So I wore a suit for a short flash of time over there. Bring it back. Yeah, it started right during that financial crisis too, which was a wild time to be starting a job. But then sort of missed tech, moved out of San Francisco.

2:37:49The first company to your point was in 2014. It was called Kimono. The idea was to make it really easy to write a web scraper. It was pretty popular. 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 in 2019. Very cool. Can you take me through the founding of Arena? 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 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?

2:38:23All that stuff. 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. Oh, wow. And so we said, well, you know, if you think about like our view on enterprise problems, if you think about the B2B 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?

2:38:55And 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 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, we need to go really deep with a customer. 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 start top down and the the origin of the company was actually more let's say um less vertically opinionated we you know had a depth and reinforcement learning and transformers were like let's go and apply that for enterprise problems so we were not as uh 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 and like post chat gpt we were like look i i don't think for a small company playing in horizontal AI is really a winner's game.

2:39:54But we found that there was this beautiful intersection that went back to sort of my days as a physicist, where two different technical fields together with applied physics, electrical engineering, and AI. Now you have an interesting customer set where you look at a hardware test lab. It actually hasn't changed in a long time. The incumbent competitor set are three companies from the 80s. It's weirdly the underpinning layer of technology on which all of our software runs weirdly hasn't changed that much. Developing the hardware has like stagnant and it's kind of surprising when you think about it.

2:40:26Yeah. Can you talk a little bit about like hardware engineering 101? Are we writing Verilog? Are we in CAD? Are there other systems? Like what does the work look like? And is this something where it's like it's managed on GitHub so Devin's going to 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 folks who haven't done hardware engineering? Totally. Right. So let's break it down. Let's take a simple example. Let's take something like a drum, right?

2:40:59You've got the mechanical shell where you've got your mechanical engineering, CAD models, stress drain modeling, still a lot to do, but humans got pretty good at it. We've been building physical stuff for a while. We can screw things in and weld them together. again not trivializing that ton of opportunity yeah but 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 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 So like an IMU for how oriented, like temperature sensors, optical sensors.

2:41:43So all of your sort of sensors, just like the body has, and then a brain. And you might have multiple brains, which might be on board 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 on board.

2:42:11So to your point about the Devon. So you might have an FPGA that's programmable. You're putting code onto it. And so that's sort of the, we're currently at that inner layer. We're currently at that nervous system because there's this huge need. And if you look at like the, just the kind of labor markets for a second, this is actually weirdly not surprising, 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 it. But electrical engineering course enrollments are down by the same amount. And so you look at it, we've got this huge research.

2:42:44We'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 you have this burning platform problem where it's like, oh, my God, people haven't been studying this stuff. And we're trying to now ship at the velocity of a software company in a hardware space where stuff can literally explode. without a workforce right so 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 no 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?

2:43:36It'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 and 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 red alert. Yeah, it totally is a red alert. And that's where the, we'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, talked about Devin, right? Like, I mean, it's never been easier to write code right it is like uh i mean already weirdly python was an abstraction over like you know c plus like it's not as hard as c plus plus 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 um 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 contract 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 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'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.

2:45:00I mean, you know, we all know how, like how much the F-35 program cost and over-end. 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. 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 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.

2:45:54So 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 the value with that. If you want to do that, now people do, you know, we think about, you talked about reasoning and there's a sort of like notion for reasoning in llm land but like if we just think about human reasoning there's like a nuanced kind of like 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 to encounter that shit.

2:46:48It doesn't matter if you're an ML 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 want to fly in a safe plane, you don't want that happening. So there's a piece here where it's like reasoning, but inside this sort of like structured constraint, where there's a set of physics constraints 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 multi-modality 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?

2:47:25And 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 LLMs have gotten so good that it gives us an ability to 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. And each of those things has meaning to an engineer. And The idea is, can you now tease the right meaning from that? And so a lot of our work is basically on that data and fine-tuning side.

2:47:54How 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 FPGA be expected to do? Can this pane 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, different as agents to different pieces of the specialized workflow.

2:48:30So you sort of have this, like, meta agent that you're talking to. And then you have these others that are sort of, and the line blurs now between, like, what's an LM agent versus what's it calling, you know, we'll call tools. but those tools if you'd talk to me in like november 2022 before chat gpt i would be like these are machine learning models and companies yeah but they're just tools now let's go i need a thermal recognition stapled with like you know the view from the waveform that's an ml 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 can look at this entire constellation as being that's sort of the product if you would got it um one one quote that comes to mind is uh we were promised flying cars instead we got 140 characters um i i have to imagine that what you're building and 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 company's building supersonic jets, right?

2:49:33And 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? First of all, I love the quote. I think 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.

2:50:08And 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 going to do all this great quantum mechanics 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, 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 what it does is it changes to your point, what human ambition should be like, what could you achieve?

2:50:44If let's say it takes 10 years on average to build a startup in the past, like what we what we'd considered a SaaS company is now just going to 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 going to see a resurgence, hopefully that more 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.

2:51:15And 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 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 chat gpt that's a good thing you know we'll generate more stuff what if we could let them cheat at e-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 ever kind of enable everyone to be a little bit of a tony star i love it uh in your announcement post, you highlighted five categories that it seems like you're going after in the first initial rollout.

2:51:59Semiconductors, 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 most immediate need or is the largest market. it? Yeah, it's a great question. So we started with semiconductors, right? So that's sort of why we put it first, because, you know, the most complex, especially we 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 to the Olympic athletes and get everyone to buy it.

2:52:36That 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 established 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 um medical devices we've got um an early customer in there and it's like uh that's that's going really well you know it's it's it's um 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 um 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 gonna have more stuff that flies um and then you introduce space to the mix and like airspace 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 uh but yeah i mean that's sort of just a little bit there was not like a whole bunch of science behind that ordering yeah makes sense uh I want to get your reaction to the tariffs.

2:53:47It seems like you're probably an American company selling to a lot of American companies. 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, using this Series B over the next couple of years? Yeah. 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? You know, like, especially look at these, like the margins on something like a car have dramatically changed, right?

2:54:25It'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 car is 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. And so it's actually a forcing function.

2:54:54Like if part of this means that U.S. 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 accelerator 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 changes in the in those those people like we suddenly need to do a lot of this hard engineering in america And this finally put like a dollar amount on how important that problem is.

2:55:36How 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 there's a prediction that, you know, AI will earn an IOI gold medal this year. And it's at 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?

2:56:16Yeah, 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 um you know to to your point it's tied in with like your math olympiad or physics olympiad question which is you've got your 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 and usually they're not the same person somehow like in my experience they always do 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.

2:57:23But as the base cognition gets better, you're getting better at the viewer. To be clear, 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 some combination of woodshop meets electrical engineering meets physics, and 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.

2:58:06And like he's basically running like a series of experiments. Right. 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 tinker in the garage, but multiplied by a million. Yeah, totally. I mean, I want to get your dad signed up with the sort of we're working on like an academic edition. I want to give him free access to that.

2:58:38See if he could even, we're looking for feedback, but I think that's, he's retired, but, but I'll put you guys in touch. If he's still interested, if he's still got a garage, that'd be great. Well, I mean, thanks so much. Here's the bar for the team. Five years from now, I want to be able to design our own podcast equipment. Oh yeah. The most cutting edge, you know, we need H one hundreds in these things. I don't know why yet, but it sounds cool. so 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 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 yeah that's awesome love it well thanks so much Thanks for stopping by.

2:59:31Congrats on the milestone for the Series B. Thanks for having me, guys. Appreciate it. We'll talk to you soon. See ya. Have a good day. Let's go to the timeline. Justin Ross is quote tweeting, did you see the Colossal Company? They have brought back dire wolves using ancient DNA with their firstborn on October 1st, 2024. They waited a couple months to make sure that dire wolf was healthy and growing. Over 10 ,000 years since dire wolves were extinct. Can we do a deep dive on this? I have done a full video and deep dive on the company, Colossal. Remix. Bring it back. I was emailing with the company a while back.

3:00:09I'll rekindle that connection. Hopefully have Ben, the founder, on the show. He has a very funny collection of investors, but some really great, George Church from Harvard, fantastically renowned scientist is involved, 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. They didn't really revive them using ancient DNA. It's more genetic modification of existing dogs. A little bit of controversial. But J.D. 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.

3:00:47And I couldn't agree more. And you know where I would love to have a dire wolf hanging out and maybe go on some deer hunting? In a wander. I want to find my happy place. Find your happy place. find your happy place book a wonder book a wonder with inspiring views hotel great amenities dreamy beds top tier cleaning and 24-7 concierge service it's a vacation home but better And I want to go to Mike Noop, 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.

3:01:23He 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 follow from prior axioms. One is easier and bounded, and two is harder and open-ended. And Dworkesh was talking about this. If you've trained 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.

3:02:00This is what David Senra does a lot with his show, Founders Podcast. Go download it. 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 Elon Musk working in space and 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.

3:02:42We 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 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 you kind of need to be innovative to come up with a joke.

3:03:17It needs to come from something, it needs to be new and fresh. It's not just information retrieval. The idea of like creativity is often just taking ideas from two different places and combining them in some way. And it feels like the models do that very well today and that you can ask it to make me a song. It's not doing it independently. it just like, you know, you have to sort of prompt it. This was the genius of Harry Potter Balenciaga. Like 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.

3:03:54And then the AI just instantiated it. And I agree with you. Like the idea 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. That's right. And so go to adquick.com, out of home advertising made easy and measurable. Say goodbye. AdQuick basically took the amazing attributes of online performance marketing and brought it into the real world. That's actually what they did. That's true. I'm serious. Yeah, that's the whole point. We're not messing around. Yeah.

3:04:22We are - 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 Quake 2, had 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.

3:05:00And so there's no game engine. It's just input is what you're doing on the controller. Output is the game with visual fidelity. And you can see where this is going. It's crazy. It got a lot of hate. Yeah. Quake dad. Quake dad. Clearly a fan of Quake. Dedicated to the, committed to the bit. Meanwhile, they haven't released a new Quake in like two decades. So this guy has been in the trenches forever. This is absolutely disgusting and spits on the work of every developer everywhere. Bold. John Carmack says, what? Question mark. This is impressive research work. And I love that because he's the creator of Quake.

3:05:35And there was an amazing meme that was like John Carmack holding a white monster being like, oh, you completely replicated exactly what I did. Awesome work. Based. And it's like the developer himself is like, this is cool. But he did unpack it a little bit more. And so I want to read through this. He says, I think you are misunderstanding what this tech demo actually is. But I will engage with what I think your gripe is. AI tooling, trivializing the skill sets 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.

3:06:09And 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, even as they de-emphasize the importance of much of my beloved systems engineering. Maybe first person to say that. Systems engineering, very, very hard, and it's a huge time suck. I mean, when he built Quake, he had to build the whole game engine.

3:06:44He had to build 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 out of a prompt.

3:07:16but 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 the Harry Potter Palenciaga 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 couldn't 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 takes poker cards. And you're basically playing poker and trying to create like royal flushes and whatnot.

3:07:50But it adds all these crazy mechanics on top of it. It was a very simple game, just designed in an engine. Not crazy on a technical level, but the game design was 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 a quarter on steam or something. Well, what should you do if you're printing, John? Pay your taxes, that's for sure. Put your sales tax on autopilot. Sales tax on autopilot. Spend less than five minutes per month on sales tax compliance.

3:08:26Go get started. They're back by what you're doing in your benchmark. Five minutes a month. 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 sales tax. Here in SAS, you can be thanking your lucky stars that you're not a part of the trade war right now. Yep. 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 go to Numeral HQ and check them out. Just do it.

3:09:04And I think that's a good place to wrap up. What do you think, Jordan? Yeah, fun show, John. Great show. I enjoyed podcasting with you today. It was fantastic. I can't wait to do it tomorrow. I know. I was so worried. 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. I know. It's going to be fantastic. I have a feeling there'll be more news this week. For sure. The size gong hasn't rung its last gong sound. That's for sure. The gong will keep ringing as long as we're on this beautiful. Yeah, it's great. Three amazing Series Bs.

3:09:37We got all three founders on. I think we did great three of a kind was Jai's a series B oh I guess a series B size more like a pre-seed more of a pre-seed anyway three big three ten 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 working on very interesting things I remain bullish on America me too me too anyway thanks for listening never lose faith we will see you tomorrow have a great afternoon have a great afternoon cheers