Unsupervised Learning x Latent Space Crossover Special

24:31Yeah, but I don't put that in my mental framework of things. I come at this much more as a content creator or a market analyst. It really does matter to me what has product market fit because I have to answer the question of what is working now when people ask me. Do you feel like relative to the hype and discourse out there, do you feel like there's a lot of things that have product market fit or a few things? A few things. Yeah. So I have a list of like two years ago, I wrote the anatomy of autonomy post where it was like the first like what's going on in agents and what is actually making money.

25:13Because I think there's a lot of Gen EI skeptics out there that are like these things are toys. They're not unreliable. And, you know, why are you dedicating your life to these things? And I think for me, the party market fit bar at the time was one hundred million dollars. what use cases can reasonably fit$100 million. At the time, it was CoPilot. It was Jasper, no longer, but in that category of help you write, which I think was helpful. And then Cursor, I think, was on there as a coding agent, plus plus. I think that list will just grow over time of the form factors that we know to work and then we can just adapt the form factors to a bunch of other things.

25:54So like the one that's the most recently added to this is deep research. Yeah. Right. Where anything that looks like a deep research, whether it's a Grok version, Gemini version, perplexity version, whatever. He has an investment that that he likes called Bright Wave that is basically deep research for finance. Yeah. And anything where like it's like long term agentic reporting is starting to take more and more of the job away from you and just give you a much more reason to report. I think it's going to work. And that has some PMF, I think. Obviously it has PMF. Like I would say, I went through this exercise of trying to handicap how much money OpenAI made from launching OpenAI Deep Research.

26:35I think it's billions. Like the sheer upgrade from like$20 to$200, it has to be billions in ARR. Maybe not all of them will stick around, but like that is some amount of PMF that is... Didn't they have to immediately drop it down to the$20 tier? They expanded access. I wouldn't say... Which I thought was really telling of the market, right? It's like where you have a, you know, I think it's going to be so interesting to see what they're actually able to get in that$200 or$2 ,000 tier, which we all think is, you know, has a ton of potential. But I thought it was fascinating. I don't know whether it was just to get more people exposure to it or the fact that Google had a similar product, obviously, and other folks did too.

27:11But it was really interesting how quickly they dropped it down. I think that's just a more general policy of no matter what they have at the top tier, they always want to have smaller versions of that in the lower tier. Yeah, just get people exposure to it. Yeah, just get exposure. The brand of being first to market and the default choice is paramount to OpenAI. I thought that whole thing was fascinating because Google had the first product, right? Yeah. And, like, you know. We interviewed them. I straight up threw their faces. I was like, OpenAI mocked you. And they were like, yeah. Well, I actually am curious.

27:42This is totally off topic, but whatever. Like, what is it going to take for Google? Google just released some great models, like, a few weeks ago. I feel like the stuff they're shipping is really cool. It's happening. But I also feel like at least in the broader discourse, it's still like a drop in the bucket relative to... Yeah. I mean, I can riff on this. But I think it's happening. I think it takes some time. But my Gemini usage is up. I use it a lot more for anything from summarizing YouTube videos to the native image generation that they just launched to flash linking. Multimodal stuff is great.

28:18Yeah, and I run a daily news recap called AI News that is 99 % generated by models, and I do a bake-off between all the Frontier models every day. Every day? Does it switch? Yes, it does switch, and I manually do it. And Flash wins most days. So I think it's happening. I was thinking about tracking myself, like number of opens of Chagibity versus Gemini, and at some point it will cross. I think that Gemini will be my main.

28:53And that will slowly happen for a bunch of people, and then that will shift. I think that's really interesting. For developers, this is a different question. It's Google getting over itself of having Google Cloud versus Vertex versus AI Studio. All these five different brands slowly consolidating it. It'll happen just slowly, I guess. Yeah. I mean, another good example is you cannot use the thinking models in Cursor. and I know Logan and Kilpatrick said they're working on it, but I think there's all these small things where like if I cannot easily use it I'm really not going to go out of my way to do it, but I do agree that when you do use them, their models are great so yeah, they just need better better purchase.

29:35You had one of the questions in the prep what public company are you long and short and mine is Google versus Apple. That was also my combo. I feel like yeah it does feel like Google is really cooking right now Yeah. So, okay, coming back to what has product market fit. Now that we come back to my complete total sidetrack. There's also customer support. We were talking on the car about Dekugan and Sierra. Obviously, Brett Taylor is founder of Sierra. And yeah, it seems like there's just these layers of agents that'll, like, I think you just look at, like, the income statement or, like, the org chart of any large-scaled company, and you start picking them off one by one, what, like, is interesting knowledge work and they would just kind of eat things slowly from the outside in if that makes sense.

30:20I mean the episode with Brett he's so passionate about developer tools and yet he did not do a developer tool. We spent like two hours talking about developer tools and like all of that stuff and he's like I need a customer support company I'm like man that says something you know what I mean it's like when you have somebody like him who can like raise any amount of money from anybody to do anything to pick customer support as the market to go after while also being the chairman of open ai like that shows you that like these things have modes and have long-standing like they're gonna stick around you know otherwise he's smarter than that so um yeah that's a that's a space where maybe initially you know i would have said i don't know it's like the most exciting thing to to jump into but then if you really look at the shape of like how the workforce are structured and like how the cost centers of the business really end up, especially for more consumer-pacing businesses, a lot of it goes into customer support.

31:17All the AI story of the last two years has been cost-cutting. I think now we're going to switch more towards growth. Revenue. You know, like you've seen Jensen, like last year at GTC was saying, the more you buy, the more you save. This year he said, the more you buy, the more you make. So we're - Hot off the press. We were there. We were there. I do think that's one of the most interesting things about this first wave of apps, where it's like almost the easiest thing that you could get real traction with was stuff that, you know, for lack of a better way to frame it, like stuff that people had already been comfortable outsourcing the BPOs or something and kind of implicitly said like, hey, this is a cost center.

31:49Like we are willing to take some performance cut for cost in the past. You know, the irony of that or what I'm really curious to see how it plays out is, you know, you could imagine that is the area where price competition is going to be most fierce because it's already stuff that, you know, that people have said, hey, we don't need the like 100 % best version of that. And I wonder, you know, this next wave of apps may prove actually even more defensible as you get these capabilities that actually are, you know, increased top line or whatnot, where you're like, you know, take AI go to market, for example.

32:17Like, you pay, like, twice as much for something that brought, like, because there's just a kind of very clean ROI story to it. And so I wonder ultimately whether, like, this next set of apps actually ends up being more interesting than the first wave. Yeah. I think a lot of the voice AI ones are interesting, too, because you don't need 100 % precision recall to actually have a great product. And so, for example, we looked into a bunch of scheduling intake companies, for example, like home services for electricians and stuff like that. Today, they missed 50 % of their calls. So even if the AI is only effective, say, 75 % of the time, yeah, it's crazy, right?

32:53So if it's effective 75 % of the time, that's totally fine because that's still a ton of increased revenue for the customer. And so you don't need that 100 % accuracy. And so as the models and the reliability of these agents are getting better, is totally fine because you're still getting a ton of value in the meantime. Yeah. This is, I don't know how related this is, but one of my favorite meetings at, it is related. One of my favorite meetings at AI Engineer Summit, because I do these, this is our first one in New York, and I just met a different crew than you meet here. Everyone here loves developer tools, loves infra.

33:26Over there, they're actually more interested in applications. It's kind of cool. I met this bootstrap team that they're only doing appointment scheduling for vets. and like they're like this is a this is an anomaly we don't usually come to engineering summits because we usually go to vet summits and like talk to the they're like you know they're literally i'm sure it's a massive pain point they're going to pay a lot of money yeah but but this is like my point about saving versus making more it's like if an electrician takes two acts more calls do they have the bandwidth to actually do two acts more and they get hired Well, yeah, exactly.

34:00That's the thing. I don't think today most businesses are structured to just overnight two, three acts to demand. I think that's a startup thing. Most businesses. Then you make an electrician agent. Well, no, totally. How do you do a recruiting agent for electricians? Electricians are great. How do you do Lambda School for electricians? It's going to be a hilarious game of whack-a-mole for the bottlenecks in these businesses. Yeah, exactly. It's like, oh, now we have a ton of demand. Cool, where do we go? Yeah. Yeah. So just to round up the PMF thing, I think this is relevant in a sense of like, it's pretty obvious that the killer agents are coding agents, support agents, deep research, right?

34:38Roughly. We've covered all those three already. Then you have to sort of turn to offense and go like, okay, what's next? What about, I mean, I also just like summarization of voice and conversation. Yep. We actually had that on there. I just, I didn't put it as agent because it seems less agentic, you know, but yes. Still a good AI use case. That one I've seen, I would mention Granola. And what's the other one? Monterey? I think a bridge was the one you wanted to mention. I was going to say a bridge, yeah. So I'll call out what I had on my slides for the agent engineering thing. So it was screen sharing, which I think is actually kind of underrated.

35:14Like people watching you as you do your work and just offering assistance. Outbound sales. So instead of support just being more outbound. Hiring. You say outbound sales has brought a market fit? No, it's coming up. Oh, on the company. I totally agree with that. Hiring, like the recruiting side. Education, like the sort of personalized teaching, I think. I'm kind of shocked we haven't seen more there. Yeah. I don't know if that's like... It's like Duolingo is the thing, Comigo. Yeah, I mean, Speak and some of these like, you know, practice. Yeah, interesting. And then finance, there's a ton of finance cases that we can talk about that.

35:50And then personal AI, which we also had a little bit of that. But I think personal AI is harder to monetize. But I think those would be what I would say is up and coming in terms of that's what I'm currently focusing on. I feel like this question has been asked a few different ways. But I'm curious what you guys think. It's like, if we just froze model capabilities today, is there trillions of dollars of application value to be unlocked? Like AI education, if we just stopped today all model development with this current generation of models, we could probably build some pretty amazing education apps.

36:21Or how much of this how much of all this is like contingent upon just like okay people have had two years with gbt4 and like you know i don't know six months with the reasoning models like how much continuing upon it just being more time with these things versus like the models actually have to get better i don't know it's a hard question so i'm gonna just throw it to you yeah well i think the societal thing is maybe harder especially in education you know like can you basically like doge the education system probably you should but like can you i think it's more of a human but people pay for all sorts of get-ahead things outside of class.

36:54And certainly in other countries, there's a ton of consumer spend. It feels like the market opportunity is there. Yeah, and in private education, I think. Public is very different. One of my most interesting quests from last year was kind of reforming Singapore's education system to be more sort of AI native. Just what you were doing on the side while you were... Yes. That's a great side quest. My stated goal is for Singapore to be the first country that has Python as a first language. as a national language. Anyway, so, but the defense, the pushback I got from the Ministry of Education was that the teachers would be unprepared to do it.

37:31So it was like the, like the, it was really interesting, like immediate pushback was the de facto teachers union being like resistant to change. And I'm like, okay, that's par for the course. Anyway, so not to dwell too much on that, but like, yeah, I mean, like, I think like education is one of those things that everyone like has strong opinions on because we all have kids, all have been through the education system. But I think it's going to be the domain-specific speak. Such an amazing example of top-down, we will go through the idea maze and we'll go to Korea and teach them English. It's like, what the hell?

38:08And I would love to see more examples of that. Just really focus. No one tried to solve everything. Just do your thing really, really well. On this trend of difficult questions that come up, I'm going to just ask you the one that my partners like to ask me every single Monday, which is how do you think about defensibility at the app layer? Oh, yeah. That's great. Just give me an answer. I can copy, paste, and just like, you know, auto response. Honestly, like network effects. I think people don't prioritize those enough because they're trying to make the single player experience good, but then they neglect the multiplayer experience.

38:42I think one of the – I always think about like load-bearing episodes. Like, you know, as Poxet, you do one a week, and some of those you don't really talk about ever again and others you keep mentioning every single podcast. This is obviously going to be the last one. I think the recap episodes for us are pretty low-bearing. We refer to them every three months or so. One of them, I think, for us is Chai. For me, it's Chai Research, even though that wasn't a super popular one among the broader community outside of the Chai community. For those who don't know, Chai Research is basically a character AI competitor.

39:15They were bootstrapped. They were founded at the same time, and they have outlasted character de facto, right? It's funny. I would love to ask Milo Shazir a bit more about the whole character thing. Good luck getting past the Google conference. But so he doesn't have his own models, basically. He has his own network of people submitting models to be run. And I think that is short-term going to be hurting him because he doesn't have proprietary IP. But long term, he has the network effect to make him robust to any changes in the future. And I think I want to see more of that, where he's basically looking at himself as kind of a marketplace, and he's identified the choke point, which is both the app or the sort of protocol layer that interfaces between the users and the model providers, and then make sure that the money kind of flows through.

40:07And that works. I wish that more AI builders or AI founders emphasize network effects because that's the only thing that you're going to have at the end of the day. And like brand leads into network effects. Yeah, I guess harder in the enterprise context, right? But I mean, I feel we do this exercise and I feel like we talk a lot about like, you know, obviously there's, you know, kind of the velocity and the breadth you're able to kind of build a product surface area. There's just like the ability to become a brand in a space. Like I'm shocked even in like six, nine months, how an individual company can become synonymous with an entire category, and then they're in every room for customers, and all the other startups are clawing their way to try and get in one 20th of those rooms.

40:46There's a bunch of categories where we talk about an IC, and it's like, oh, pricing compression is going to happen, not as defensible, and so ACVs are going to go down over time. In actuality, some of these, the ACVs have doubled, we've seen. And the reason for that is just people go to them and pay for that premium of being that brand. Yeah. I mean, what I'm struck by is there was such a head fake in the early days of AI apps where people were like, we want this amazing defensibility story. And then what's the easiest defensibility story? It's like, oh, like totally unique data set or like train your own model or something.

41:14And I feel like that was just like a total head fake where I don't think that's actually useful at all. It's the much less, you sound much less articulate when you're like, well, the defensibility here is like the thousand small things that this company does to make like the user experience, design, everything just like delightful and just like the speed at which they move to kind of both create a really broad product, but then also every three, six months when a new model comes out, it's kind of an existential event for like any company. Because if you're not the first to like figure out how to use it, someone else will.

41:39And so velocity really matters there. And it's funny in kind of our internal discussions, we've been like, man, it sounds pretty similar to like how we thought about like application SaaS companies. That there isn't some like revolutionary reason. You don't sound like a genius when you're like, here's applications, like application SaaS company A is so much better than B. But it's like a lot of little things that compound over time. What about the infrastructure space, guys? I'm curious, how do you guys think about where the interesting categories are here today? And where do you want to see more startups or where do you think there are too many?

42:09Yeah, we call it kind of the LLMOS. But I would say... Not we, I mean, Andre calls it LLMOS. Well, but yeah. Everyone else just copies whatever. You two and Andre, the three of you call it the LLMOS. Well, we have this four words of AI framework that we use and LLMOS is one of them. But yeah, I mean, code execution is one we've been banging the drum. Everybody now knows we're investors in E2P. Memory, you know, is one that we kind of touched on before. Super interesting. Search we talked about. I think those are more not traditional infra, not like the bare metal infra. It's more like the infra around the model.

42:48Which I think is where a lot of the value is going to be. Security ones? Yeah, yeah. Yeah, and temporary security, I mean, there's so much to be done there. And it's more like basically any area where AI is being used by the offense. AI needs to be applied on the depend side, like email security, you know, identity, like all these different things. So we've been doing a lot there as well as, you know, how do you rethink things that used to be costly, like red teaming and maybe used to be a checkbox in the past. Today, they can be actually helpful to make you secure your app. And there's this whole idea of semantics that not the models can be good at.

43:26In the past, everything is about syntax. It's kind of like very basic constraint rules. I think now you can start to infer semantics from things that are beyond just simple recognition to understanding why certain things are happening a certain way. So in the security space, we're seeing that with binary inspection, for example. Like there's kind of like the syntax, but then there are like semantics of like understanding what is this code overall really trying to do, even though this individual syntax is like saying something specific. Not to get too technical, but yeah, I think infra overall is like a super interesting place if you're making use of the model.

44:06If you're just, I'm less bullish, not that it's not a great business, but I think it's a very capital intensive business, which is like serving the models. I think that infra is like, great people will make money, but yeah, I don't think there's as much of an interest from us. How do you guys think about what OpenAI and the big research labs will encompass as part of the developer and infra category? Yeah, that's why I would say search is the first example of one of the things we used to mention. We had X on the podcast and Perplexity, obviously, as an API. The basic idea is if you go into the ChatGPT custom GPT builder, what are the checkboxes?

44:47Each of them is a startup. Yeah. And now they're also APIs. So now Search is also an API. We'll see what the adoption is. In traditional inference, everybody wants to be multi-cloud. So maybe we'll see the same where ChatGPT Search or OpenAI Search API is great with the OpenAI models because you get it all bundled in. But their price is very high. But if you compare it to like, you know, Excel, I think it's like five times the price for the same amount of research, which makes sense if you have a big open AI contract. But maybe if you're just like picking best in breed, you want to compare different ones.

45:23Yeah. Yeah. They don't have a code execution one. I'm sure they'll release one soon. So they want to own that too. But yeah, same question we were talking about before, right? Do they want to be an API company or a product company? Do you make more money building tragedy research or selling search API? Yeah. The broader lesson, instead of going, we did applications just now, and then what do you think is interesting infrastructure? It's not 50-50. It's not equal weighted. It's just very clearly the application layer has been way more interesting. Yes, there's interesting infrastructure plays. And I even want to push back on the whole GPU serving thing, because Together AI is doing well, Fireworks.

46:02I was going to say, that's how it works. It's like data centers and inference providers. I think it's on the capital. I see, I see. For, again, you guys have much larger funds. So, again, I'm sure you have GPU class. Yeah, so that is one thing I have been learning in that, you know, I think I've historically had DevTools and Infra bias, and so has he. And we've had to learn that applications actually are very interesting and also maybe kind of the killer application of models in the sense that you can charge for utility and not for cost, right, where most infrastructure reduces to cost plus. Yeah.

46:40Right? And that's not where you want to be for AI. So that's interesting for me. I thought it would be interesting for me to be the only non-VC in the room to be saying what is not investable because then I won't be canceled for saying your whole category is not investable. We have a great thing where we're like, this thing is not investable. And then three months later, we're desperately chasing you. Exactly. So you don't want to be on the record. This space changes so fast. It's like every opinion you hold, you have to like hold it quite loosely. I'm happy to be wrong in public, you know. I think that's how you learn the most, right?

47:10So like fine-tuning companies is something I struggled with. And still like I don't see how this becomes a big thing. Like you kind of have to wrap it up in a broader enterprise AI company, like services company, like a writer AI, where like they will fine-tune as part of the overall offering, but like that's not where you spike. Yeah, it's kind of interesting. And then I'll just kind of, AI DevOps, there's a lot of AI SRE out there. Seems like there's a lot of data out there that should be able to be plugged into your code base or your app to self-heal or whatever. It's just, I don't know if that's been a thing yet, and you guys can correct me if I'm wrong.

47:50And then the last thing I'll mention is voice, real-time infra. Again, very interesting, very hot, but again, how big is it? Those are the main three that I'm thinking about for things I'm struggling with. Yeah, I guess a couple of comments. On the AISRE side, I actually disagree with that one. I think that the reason they haven't sort of taken off yet is because the tech is just not there quite yet. And so it goes back to the earlier question, do we think about investing towards where the companies will be when the models improve versus now? I think that's going to be in short term we'll get there, but it's just not there just yet.

48:24But I think it's an interesting opportunity overall. Yeah. My pushback to you is, well, it's monitoring a lot of logs, right? And it's basically anomaly detection rather than, like there's a whole bunch of stuff that can happen after you detect the anomaly, but it's really just anomaly detection. And we've always had that. This is not a Transformers LLM use case. This is just regular anomaly detection. It's more in terms of, it's not going to be an autonomous SRE for a while. And so the question is how much can the latest sort of AI advancements increase the efficacy of going, bringing your MTTR down?

48:58And even if it's 10 % improvement on beforehand, it's still potentially a lot of revenue. That's the way, at least, I think I would think about it now. And then a few years from now, if it's actually an autonomous SRE just replacing altogether, then that's a totally different thing. Cool. I'll look out for it. Yeah. You know, I guess switching back to overly broad questions, like what do you feel like is the biggest unanswered question in AI today that has large implications for the ecosystem. Yeah, I've been banging the drum on RL, and I think it's clear that you can do RL successfully on verifiable domains.

49:37I would say whether or not we can figure out how to do that in non-verifiable ones. So law is a great example. Totally. Can you do RL on contracts and documents? Marketing, sales, going back to outbound sales, can you do RL to simulate what an outbound, and kind of like the conversation leads to. Yeah, it's unclear. If not, then I think we'll be stuck with like, you're going to have agents in the more verifiable domains and then you'll just kind of have co-pilots in the non-verifiable ones because you'll still need a person to be the tastemaker. I have the exact same thing. I feel like it's like the, I'm trying to think of the implications where if it doesn't work, like the world could be weird where like you have like fully autonomous AI coders and like, you know, no one does any software or math or even like, you know, some areas of science, but then like to write the most basic sales email is still like like just it's always so hard to predict out the world like that is such a weird of all the sci-fi that was written you know 50 years ago i don't think anybody foresaw that future that is a really weird future yeah i've called it industrialized autism do either of you have a different one for that biggest unanswered question i guess um i don't know if this is a good answer but you know bob mcgrew we had on the podcast he was talking about like the rule of nines they have at opening ai where to go from 90 % reliability to 99.

50:52It's an order of magnitude increase in compute. And then 99 to 99.9, order of magnitude increase. And that happens every two to three years. And so I think how are we going to scale sort of accordingly this sort of next part? I think there's a lot of unanswered questions just like from a hardware perspective. And then I think as part of that, from the availability perspective, like is NVIDIA just going to continue to be dominant? Like, obviously, AWS is going hard into, what's their, Tranium chips? I'm blanking on it. Thank you. And so I think, like, there's a big ecosystem around CUDA that's obviously allowed NVIDIA to remain dominant.

51:30But just what's going to happen? And is there anyone that's going to come sort of combat that to increase the availability of GPUs? Or are we just going to be constrained going forward when we actually need way more compute going forward? Yeah. My quick thoughts, I'm the only individual named as an investor in MadEx, which is kind of really funny because everyone else was funds and then it was just me. And there's all these NVIDIA startups, sorry, dedicated silicon startups that are coming up and trying to challenge that. And the simple answer is these GPUs are the most general things possible by design.

52:12That's why they do gaming, crypto, and AI. And I think as long as the architecture seems stable, it seems like there's a case to be made for that. The only question is who will win that. And obviously, there's a whole bunch of competitors, including, I think, AMD is trying to make a play for it. But so will AWS, and so will every other. Like, Microsoft has a chip. Facebook has a chip. So who knows who will win that? It's very interesting that this seems to be such a valuable prize. It's freaking NVIDIA that you're competing with. And no one has really made a real dent there yet. So I kind of agree with you.

52:52But I think that basically it's all about stability of workload. It's a bet on the death of Transformers, basically. And if you're fine with that. And I think even a state-based model, people would agree that it wouldn't really change that much. And probably, I think the overall consensus is that you don't even use state-based models individually. You would use them in a mixture with transformers anyway. So then, yeah, just go bet on transformers, bake it into the chip, and you will have way more, basically ASICs for transformers, and that's fine. And so like prima facie, there should be a company that wins that.

53:32I don't know who will win. I wish we knew. I think that I think anyone you have to start basically after 2019 or 2020, because anyone started before that will still be too general. Yeah. Because Transformers hadn't won yet, won at the time. I have one more. I think that the most emergent one that came out of the New York conference that I did was agent authentication. I think literally the information just published, like this is something that they're worried about, which is when operator or whoever accesses your website on behalf of you, how does it indicate that it's not you, but it's an agent of you?

54:08And I think like my general philosophy on agent experience or any of the sort of like reinvention of every part of the stack for agents is they're all not necessary except for this agent offering. thing. We really need to be able to new SSO effectively for agents. Is it going to be crypto? Both crypto people are really amped about the... It's really frustrating when Sam Altman is right, but maybe you have to scan your eyeballs. You just have to. Maybe he saw this five years ago and he was like, you've got to scan your eyeballs, and the rest of us are just behind him, as usual. I love it. Now I'll move to the quickfire round where we'll go around the horn and get quick takes on things.

54:51So the first is going to be Dream Podcast guests. John Carmack. Yeah. He's six. John is like six steps away from solving AGI, apparently. So we just ask him how long he is. For us, it's Andre. For me, it's Andre. He's a listener and supporter of the pod. And basically, when I launched the whole AI engineer push that we have, he was basically the first one to legitimize it. he was like, you know, there will be more AI engineers than ML engineers, and I think that made everyone else pay attention. So, like, Latent Space only exists because, you know, he helps, he and other people help to promote it.

55:28I also had Andreas, though, because we were thinking the same thing there. I, basically, mine's a little bit cheating, but I think at some point there will, clearly, like, they're writing a book about OpenAI now, and at some point, like, somebody probably acquired, we'll get to do the acquired OpenAI episode, but if Unsupervised Learning could, like, there's clearly just, like, so many amazing stories of like the last five, six years. So do you know about Doomers? It's a play. I'm actually going to it this Saturday. Yeah, someone made a play about the board drama of last year. Really? Wow. That's cool.

56:00Let's know how it is. Let us know. Maybe we should have the director of that on the pod. I think it's a lot of fan fiction basically, but like someone will write the accounts and it will be interesting and fascinating and a lot of a lot of it will be fake because it's a complex beast, right? You're just getting an oral history of what happened. Yeah. Yeah. All right, for the next one, I figured you could shout out either like a new source you used to stay up to date or a startup that you're not invested in that you're excited about. Oh. Or you can do it again. My new source is Sean. That's what I was going to say.

56:32I literally wrote Swix's Twitter. In our Discord, we have a latest space Discord. Any link that ever matters on the internet, Sean is going to post it in the Discord so all I do I open Discord and we have like you know 40, 50 different channels bytes of it I open Discord and I'm like okay AI then I go developer tools then I go creator economy then I go stock and macro then I go and they're all there so thank you we actually met because of the Discord it was like a COVID thing because everyone's at home they just started the Discord and yeah that was the origin of Loading Space just chatting on the Discord it used to be called dev slash invest yeah it was all about developer tools investing um and then we were open ai in october of 2022 uh we're like maybe we should do a podcast and then open ai was the first history yeah uh i uh i was not prepared about the the new sources thing uh i think maybe it's hard it's really shitty to say but like just in-person conversations yeah um and i think the reason I have to be here in SF is because I make friends with people who know things and are smarter than me and we go for chats and they're nice enough to share some stuff.

57:48And so sometimes I wish, I worry that I am being used in order to put things out there that are maybe not true, but you know, so I have to exercise my own judgment as to what I think. One of the cool things about the podcast in general is just like the opportunity to take these conversations that happen in like closed rooms and try and bring them on to the airwaves. I'm curious, like, how much of what you, how much do you feel like the private discourse is similar to the public discourse? In many ways, it is surprisingly similar. Yeah. As in people at OpenAI learn about things about OpenAI from us, which is interesting.

58:27And then there are some ways which is drastically not, drastically dissimilar and those are the things I just cannot repeat until it's public. This has been super fun. I feel like we lived up to it. We were looking forward to this for a while. We want to make sure everyone around the Horn gets an opportunity to plug whatever they want to plug. So we'll leave the last word to all of us, I guess. Where can folks go to learn more about Latent Space and all the exciting things you do? We want to make sure our listeners have a good sense of everything. Yes. So we have a sub stack, Latent.Space is the website.

58:57And then please subscribe on YouTube. We're doing a lot on YouTube. We're trying to do better video and all that. He said our OKRs, and it's basically all YouTube. Come watch us on YouTube. It's very important for me personally. Even if you don't care, just OKRs. Well, we have to increase our production value. Look at this. I know. We only have three cameras. Yeah, and then Sean does a lot of the writing outside of the podcast on the newsletter. Yeah, so it's like trying to be newsletter and community and podcast and whatever else that we do. Yeah, so I guess for me, I guess there's Dayton Space, but then there's also the other big piece, which is the conference that I run.

59:42And the idea is that I think sometimes you just get the good stuff from people if you just put them in front of a lot of people. and that's really, like I'm mining people for content and sometimes you put a mic in front of them and they yap for an hour. Other times you have to put them in front of like a prestigious conference and then they drop some alpha. And so the next one for us is going to be June. It's the AI General World's Fair and it should be the largest technical conference for AI. And ours is simple. We just run a humble podcast. So subscribe to Unsupervised Learning on YouTube. Thanks so much.

1:00:18this was awesome thanks for having me it's good to see you guys thanks for coming on