Meta Releases Muse 1.1, GPT-5.6 Sol Reactions, New Robot Hand Alert | Eric Seufert, Bernt Børnich, Josh Lindgren, Jeffrey Morgan, Thibault Sottiaux, Sean Frank

29:18But I believe we have Eric Sufert lined up now with audio. We'll bring him in to the TV panel with him. Eric, how are you doing? Hey, guys. Thanks for having me. It's good to be back. Sorry about the technical mishap. It happens. It happens. It's great to have you here. Question. Did you rebrand Mobile Dev Memo? No, I didn't. To Heracles? To Heracles? Or is this an error on our side? This is an error on our side. It's Mobile Dev Memo. Hercules is the fund. Is that right? Yeah, the fund. Yeah. Yes. Got it. Anyway, we were just talking about Meta. They just launched Mew Spark 1.1. They're LLM. They're selling that over API.

29:58They're also selling some compute. But I want your take on the image model specifically and why that is an important technology for them, why vertical integration makes sense there. Why specifically is their image model – it feels like it has a different business case around it than a Nano Banana or a ChatGPT images. Yeah, so I think this is brilliant, right? Like this actually gives them the narrative firepower that they need to sort of undermine the skepticism that investors feel about the AI investment, right? So like I was at this dinner, I did these dinners a lot, like these ideas dinners, like a research company will bring me in and talk to like a bunch of their hedge fund clients.

30:42And like I was talking about, you know, why these investments that Meta is making right now are bearing fruit right now. Like 33 % advertising revenue growth last quarter on$55 billion in revenue. That's incredible. Like you look at Google search was 19%. Amazon, which is much smaller, was 24%. They're outgrowing everyone except for AppLovin and Reddit. And people don't believe it. And I asked somebody, okay, what would it take to convince you that these investments are actually productive in this moment in time? And they said 40%. 40 % growth on$55 to$60 billion in revenue. Where did that number come from?

31:15This is pulled out of thin air. This is what they need to do. They need to be able to point to something and say, you see that ad? That was created by our AI investments. When you talk about GEM, GEM is a foundation model. MetaTrain, a foundation model for ranking. That's important, but you can't see it. It's hard to convince. First of all, the research, a lot of the research analysts, they're really smart people, but they operate in this paradigm of like spreadsheet says this. I get it. I can understand why ranking investments would actually be really beneficial for the company, but I put a number in the spreadsheet and it spits out something.

31:46That's the tool I have to work with. And these are really smart people. I think they conceptually get why these are good investments, but they have nothing to sort of tie it to that's quantitative. I think when you can point, you can point to the ad that was created and you say, look, this ad was created with data that only we have. It's the image model that we built, the foundation image model that we built that is trained, trained, not fine-tuned, but trained on our own data. It can be verified against that. We've got our own custom evals. Everything about the training was built with data that only we have.

32:15No other Frontier Lab can fine-tune their own models for this use case. Only we can do that. And then I think if they can point to the output and they say, that ad that you saw in your Facebook or Instagram feed was created only as a result of our ability to train on this data that only we have, then I think you can kind of make the case. So I think bundling those two – integrating those two things together is like the really smart move. And I kind of – I understand like they restarted the AI efforts and this is the whole – this is the MSL rebrand. But my sense is like this might be more convincing than anything that they've been able to say with the ranking infrastructure and the transfer learning infrastructure.

32:52I'm talking about Lattice. I'm talking about Gem. So we'll see. But my sense is like if you can actually point to some output and say, look, this only exists as a result of our ability to train this model on this proprietary data that no one else has. My sense is you can make the argument more robustly. And if you ask advertisers, what is the bottleneck to spending more on meta, they will almost always say it's great creative. And so there's, there's a, there's a path to sort of just like unlocking and removing that bottleneck so that the constraint just becomes how much revenue do you have? And that will just become a proxy for how much you can spend with us.

33:32Yeah. It's like, what's your bid? Well, your bid should be the value that you get back. I mean, that's like the whole point of a second price auction is that you should build your bid, your true value, because you're going to make money if you win. But like, the thing is, they've built a lot of their initiatives, right? So, Gem, Foundation, Model for Ranking, Andromeda is a whole system for doing retrieval, and then Lattice, which is transfer learning. But like, the whole point of Andromeda was they were reacting to a lot more creative being deployed. Now, the creative being deployed, though, was created with third-party tools, This creative being deployed is being built without the benefit of the actual performance data.

34:03If you actually want this to work, you need to train it on the ROAS. You care about the end result. You care about what the person does when they go to your website or your app. And no one has that except for meta at that volume because they get it passed back to the Cappy and the Pixel. And so their ability to build this foundation model I think really unlocks a lot of value. And I think you'll probably see that show up in the revenue growth. Now, do they hit 40 % to satisfy these needs of these hedge fund people? I don't know. But my sense is if you can point to the output and you can say, look, this addresses the core bottleneck, which is we need a lot of creative, but it needs to be built with the knowledge of what actually drives the outcomes and not just a bunch of variations that clog up the system.

34:44I want to push back on that idea that no other lab can do anything like this. What about DeepMind? What about YouTube, Nano Banana, VO3 video generation? it does feel a little bit farther off. And also it feels like the hedge fund analysts that you're talking to aren't asking the same questions of Google's investments in AI because they have such an incredible business with Google Cloud Platform, and they're able to strike these massive compute deals. So they have some offtake there. But how is the situation different in Google? Because they don't have a history of tilting at windmills. They don't have an albatross around their neck, which is metaverse.

35:27That was a misadventure. It cost a lot of money. It never resulted in anything meaningful. Now, I would actually make the point that that whole rebrand was just a distraction. It was a smokescreen. They had to get away from the whole Facebook files thing. And that took everyone's eyes away from that scandal. And was it worth it? I don't know. If you achieved that, which they kind of did, they kind of did that with the meta rebrand. Maybe it was worth it, right? Also, the name, even if you ignore the actual investments they made in Metaverse and Horizons and things like that, Meta Platforms is the Metaverse.

36:01It is the place that people exist online. So the name makes sense even if you ignore that. And it makes sense for the strategic reason, like you said, to get away from the Facebook files. So they could have just rebranded and never done the Metaverse, and they'd be in a much better position. They'd have that sort of job. But you can't really do the rebrand unless you tell the story or else everyone accuses you of what you just described. Right. Yeah. I mean, you can put your money where your mouth is. Yeah. But on on video generation in particular, do you feel like we are further out of just further away from that?

36:35I was I was demoing the latest VO model and it's good, but it's still clockable as a generated. I had some cars spinning around, and it's three cars, and then it's four cars, and then it's two cars, and they're sort of melding into one another. It's an incredible video model, definitely state-of-the-art, but I don't know that that's ready to be deployed in YouTube across a ton of video ad impressions. So do you have a timeline for that, or do you have some thoughts on when that will actually be important to the business? Because you have to imagine that Instagram video ads perform better than just image ads.

37:12And so they'll try and do this. But what how are you seeing the AI video advertising model evolve? Here you got to look at ByteDance. What ByteDance is doing is incredible on this front. Right. So they put out this paper a month ago. I did a summary on Twitter and LinkedIn. But what they're doing with TikTok shop is these real like, you know, basically photo realistic 3D avatars that are selling stuff. Right. Like so infomercials and they've they've built custom models to build those ads. And those are all ads. A lot like I mean, not all of it. But like if you go on TikTok and you're looking at the TikTok shop stuff, a lot of it is AI generated.

37:48And so what they in this paper that I summarized, like they invested in, you know, in essentially fine tuning this model to make sure that there was no collision with the hands. What they were finding is that like so when you get in that uncanny valley situation where people can tell it's AI, then they turn off. Like there's a lot of research that's been done in this. If people know that it's AI, they penalize the ad. But when they don't know it's AI, the AI ads outperform the human creative ads. It's really fascinating. But so what they found was like when you saw the collision between someone holding something in their hand and the object, then people – the click-to-rate dropped, the conversion rate dropped.

38:19But so what they did was they fixed that. So they built this whole like visual interpretability model that just focused on that with an expert like in the model. And so it just addressed the hands. And so like if – but that's use case specific. Like you needed a general purpose model that's going to build photorealistic video. We're probably pretty far off of that for like all ads of all types. But I think with something like, you know, okay, well, we need human photorealistic kind of like infomercial style. I think you could get to that point now. And maybe we were there now and maybe ByteDance is there now.

38:48But I think it takes a lot of investment, right? I mean, they had something, if I remember quickly from the paper, it's been a while since I saw it, like 12 ,000 hours of live human product interaction. So, I mean, it takes a lot of data to do that, right? And so, you know, it's whatever you want to invest in. And I think if YouTube wants to do that for a general purpose, photorealistic video ad tool, we're probably pretty far off. How do you think that the market will react if Muse 1.1 is very much like a base hit on the API where they get some big companies to move over some workloads, but it's not this runaway hit?

39:26And I say that because so many models that have been good, not great, have a little demand just because there's a lot of demand for AI, but they don't sort of like have these sort of breakout revenue charts. Well, you know, they clearly are going to be very aggressive on the pricing. I mean, they talked about that today, right? And so my sense is like what you're going to start seeing is that people don't need to operate at the frontier. and you have a lot of use cases that work just fine with, and basically are just good enough, right, with some legacy model. And so it just comes down to then, okay, well, that's commodity, and so is it priced like a commodity?

40:00Like, if you think about, like, and also, like, I think we're going to see a lot more, like, people relenting from needing to be on the frontier when they've built stuff using a model that then gets upgraded. And the whole idea there is, like, well, am I going to upgrade this tool? Because I have to adapt it to the new model, right? Right. Like if I'm if I if I, you know, because essentially like the model name, like if you if you use like Vertex AI, right, you just got a model name as a variable. Like you're sending this system prompt to Google, but like it's just a variable. You could swap that out in 30 seconds.

40:31But the fact of the matter is you're sampling from a new distribution if you do that and it's going to change the output. It's going to qualitatively change the output and it might change it in quantitative ways, like with retention and engagement. And so the thing is like, OK, well, now we're talking about this big cycle. It's a new product development cycle because I have to adapt this product that I built to this new model and the output that it provides. And maybe it was working perfectly. It was working exactly as I expected it to before. Now I've got to invest a bunch of hours, a bunch of engineering time in adapting it to this new model.

40:58So even if it's just a swap of a variable name, it's still a whole lot of testing, QA, determining how that impacts long-term retention. I'm going to do A-B tests. So my sense is you're going to see a lot more people just saying, no, this works fine. This is perfect. And getting more robust output, let's say the token price is exactly the same. Getting more robust output wouldn't benefit me. Why am I going to invest the resources into adapting to the new model? Yeah, but isn't that – so if they're going after workloads that are running on old models that are working fine and it's a lot of work to switch over?

41:30It's not a lot of work to switch over. It's some risk, but it's not a lot of work. It's a lot of work to switch, but then, again, you have to go through this process of QAing and running it through your own benchmarks and all this stuff. Like the question is like how I just don't know. Like I'm thinking about a scenario where like a year from now we're sitting here and like Meta has a$3 billion AI API business. And the analysts that you're talking to are like that. Like to me, they're like that doesn't get you to 40 percent year over year revenue growth on the business overall. So it doesn't solve at least what those analysts in particular were talking about.

42:08And like zero to three billion on like a new business line would be crazy and is like, you know, only been done a handful of times throughout history over the last few years. Right. So I'm just saying like we're there's such big numbers now that there's possibility where you have like this incredible breakout revenue growth, but it doesn't actually move the needle enough that that the market still says like, hey, we're not super confident about about about like the next. CapEx cycle, right? This 2027 numbers that are coming up. Well, that's, and that's the problem with this whole business line in the first place.

42:45Like, I think it's a mistake. I think it's a capitulation. I think you're going to get much more value out of that compute if you apply it to your own core business, which is advertising. My sense is you get better growth, but like the problem is the investors don't buy that right now. Like they've got a narrative issue. It's not a, it's not a productivity or a competency issue. It's a narrative issue. And like the problem is like, you know, and you know, you cited Ben's brilliant essay from yesterday or the day before about like what Zuck should say. He should say that. Like Ben is totally right.

43:12He should say that. He should come out and say, look, we like Senator, we run ads. Senator, we run ads. When he said that I was at F8. It was like the next month. Every Facebook employee is wearing a shirt that said, Senator, we run ads. They know what business they are in. Zuck seems to be confused about it. Like, I don't understand. Here's a question. Here's a big question. That'll be interesting. This year they're going to spend, I don't know how much they're going to spend on external models. I would expect them to spend maybe$10 billion, right? Like something in the range of$10 billion from Google, Anthropic, and Opening Eye.

43:45If next year they can say we're not spending money on any external models, then that could help them with the narrative issue of saying, hey, we're basically getting, instead of having to give this money to other businesses, we're just using our own infrastructure. It's a lot more efficient. We can like token max. We can use way more tokens. We can do way more workloads. And so that's potentially, it's potentially setting. But the question is, can they actually move all the workloads that are on these other models to their own models? Well, so that's where you actually do need the frontier, right?

44:19Like coding tasks, like you actually benefit from having the frontier. But if you're talking like customer support stuff, right? Like that doesn't need a frontier model. that could use like a three or four, you know, sort of like release back model. And it'll be producing reliable results that you know work, like you've measured, you tested, and you don't need to upgrade like the customer support or like the chat bot, you know, for customer support integration to the bleeding edge model every single time. But like coding, yeah, if you're actually using these models to build models, you probably want the best of the best, right?

44:48And like what Meta is doing is really actually at the frontier with like integrating agents into the coding workflow. If you look at like their system they built called Confucius, it's like a self-learning agent like that actually helps them deploy better. They've got a whole pipeline for data science and machine learning tasks that helps them decide like, OK, which which which where should we even apply this? Where should we even do testing? Right. Because that's actually takes a lot of time. Like you just figuring out what kind of experiments, what kind of tests you want to run. They built a whole pipeline around that.

45:15That's all driven by agents. Right. So my sense is like there's where you want the top of the line and maybe their own models don't perform best there. But also, I don't know how excited investors are going to get when you say that we cut expenses. I think they really need to see the revenue growth at the top line. So my sense is you get more of that by just making the ads platform better, and they've done that. All they need to do is say, look, if they can forecast out that growth and say, look, we're really dedicated to this. This is what we're pointing everything at. My sense is you could get investors excited over time.

45:42You keep printing 33 % or whatever every quarter. You're going to get investors excited after some time. If you start saying we're going to compete with CallSee, we're going to build an AI pendant hardware. They're not going to get excited. They're going to think you don't know what to do. And they're going to think you've got all this compute capacity. You don't know how to use it. Help us understand the prediction markets play. I think the answer that we landed on was it is just in meta's nature to copy the new hot thing. So regardless of what it is, we're just going to do it. And you can see the history of these shots on goal with every new hot thing in consumer.

46:16They just build a version of it or they try to buy it. So I think that's the most simple explanation. John was trying to explain it as like maybe there's some way to do it with like there is no dollars and it's just for like social status, you know, who can be an oracle. I think that that was we got more news that maybe showed that that wasn't the case. But then when you look at again, you look at the market, like you look at the total market for like gambling. and again even if they got a meaningful amount of that market they would not really move the needle in the way they need to on the core business and they would invite all these new regulators that are now saying like you're not only trying to harvest you know my teenagers attention and making them you know sad about their life you're also getting them like it just feels like it opens up this huge can of worms for no reason it's just a totally misdirected move is Is that really the space you want to go into right now?

47:11That is so politically fraught. That is such a political hot potato. Why do you even want to touch that? I would steer clear that I would say, look, Facebook apps, that's time well spent. You connect with friends. All this gambling, you're getting addicted to that. Don't spend time there. Spend time on Instagram. It's more wholesome. Why are you going to touch that at all? Are you just going to open the door to more scrutiny? That's insane. I really have no idea why they're even talking about that. It doesn't make any sense. But they've got like, you know, look, they said we're going to publish a lot more apps.

47:37They've got the new Pocket app. I mean, it seems kind of interesting. Maybe some of this stuff sticks. I think they could just try a bunch of stuff. But why would you touch the most politically toxic area right now, like when you could just be touching anything else? Yeah. Take us through the Prosperous Society. That's originally why I wanted to bring you on. I want the thesis. I want to dig into it because I found it's a three-hour, four-part podcast series. You've written a lot about it. But introduce it for those who haven't been following along. yeah prosperous society i started out i wanted to write um an economic bull case for ai we've heard all of the you know bear cases we've heard all of the you know doom narratives around the around the economy it's going to just basically displace all white collar work you know you're going to get door dash created with a vibe coding session and so all these companies are going to go out of business and i want to make the case that's probably not gonna that's probably not gonna happen and actually there's a lot of reasons to be optimistic right and i think you know in writing that it ended up becoming you know we live in a in a sort of like very pivotal moment i think you If you look at the elections in the House primaries in New York, you look at what's happening with the New York City mayoral election, you look at what's happening in the LA mayoral election, there's this sort of moment where these sort of impulses against capitalism have become a lot more popular.

48:50There's reasons for that, and I'm not an expert on those reasons, so I won't delve into them. But I think, you know, ultimately it's a mistake to go down that path. And the thing is, like, my sense is a lot of the AI or the anti-AI narratives are actually have nothing to do with AI. Right. That's just seen as an avatar or like a bogeyman for capitalism. And so what I wanted to do is sort of like anchor this economic defense of AI, this economic bull case of AI in, you know, the sort of like liberal tradition of the Western world. And in doing so, like you could say like, you know, you could anchor it to these sort of like these great thinkers, you know, this sort of like enlightenment thinkers and sort of the economic giants that have built, you know, built this sort of intellectual framework that our Western civilization is based upon.

49:31And people can say, look, well, look, you've misinterpreted them. And so, OK, well, maybe. But if that's not the case, you're going to make them drop the mask. You're going to make them drop the mask and say, no, that's not my problem with AI. I just don't want to live in a liberal economic society based on these Western thinkers. And I think if you actually kind of force that to be articulated out loud, you make a lot of progress against the anti-AI narratives. But the whole point of the Prosperous Society is my sense is, you know, a lot of these AI investments, they're going to push the economic constraints away from production and towards just distribution, right?

50:04They're going to make distribution the binding constraint. And so, because you just have this flourishing of content creation. And so when that becomes the actual problem with distribution and these AI investments go into things like ads platforms, digital advertising, you know, rec-sys, recommendation systems, then actually commerce, the economy, becomes much more efficient. And it's a really good thing. And you generate a lot of value by pushing that binding constraint to the distribution layer. And you get then as a result, you get a lot more heterogeneous product development because you can actually reach those people economically.

50:39Right. So like what is the constraint now? It's like, well, can I reach a big audience? Right. Can I reach a big enough audience to support a business? Because, well, I've just got this kind of like blunt tool. But if these AI investments go to making recommendation systems better, digital ad systems better, reaching these pockets of people that have these very specific interests that were totally unserved before, then you enable a lot more commerce. Right. And then, you know, you support this like flourishing of people making this wide, diverse variety of goods. you get rid of this idea of like the Pareto principle.

51:11We have to serve the 20 % that supply 80 % of the commerce. Well, no, now you can serve everybody and they can pay what they're willing to pay for these things. You reduce consumer surplus, sorry, you reduce consumer surplus, you just, you create this flourishing of, of, of everyone getting exactly what they want. Right. And that's the Prosper Society. And so the way I frame it is kind of a reaction or like, call it a conversation with John Kenneth Galbraith. He wrote the Affluent Society, But this was written in the post-war economy. It serves kind of as the degrowth or handbook. And in my sense, it's like John Kenneth Galbraith is a brilliant man.

51:44I'm not saying he's wrong or he was wrong when he wrote the book, but I'm saying it just doesn't apply anymore. He had this idea of the dependence effect. Advertising actually is a way to whip up demand so we can maximize production because that was what he called the conventional wisdom at the time. You should be maximizing production. But the reality is in the time he wrote this book, 1958, you had people moving to the suburbs, getting big houses. The GI Bill helped them buy these homes. You had the idea of the suburbs was being deployed. And so people needed washing machines. They needed cars.

52:13They needed refrigerators for the first time. And so you had these big companies that made these mass market goods. They advertised in mass market media. And John Kenneth Galbraith's idea was like, well, that's just creating demand. There is no actual inherent demand for these things. It's creating it through advertising. And my point is the opposite. You know, we don't have this homogenized society anymore and we don't have people that need these homogenized goods anymore. And we have a lot more particular specific media now and we can reach people and advertise to them the things that they have demand for, for products that weren't economically viable prior to these systems, these distribution systems.

52:48And that is the prosperous society is being able to reach people to meet the demands that they have with the products that they couldn't access before with ads that they wouldn't otherwise see absent these systems. And so I think it's – my sense is like you can make a very credible bull case that that's what AI delivers to us. And it's not about wiping out white-collar labor because the reality is like that's going to create more jobs. And we're seeing that now. Like there's no justification for that skepticism. It just doesn't exist. We're seeing an increase in hiring, maybe not at the entry level.

53:21And you could discuss if there should be some intervention there. But my sense is like AI, actually, if you look at the data, and there's a Financial Times article about this the other day, if you look at the data, it doesn't support that bear case. And so that bear case should be absolutely eliminated as something that even enters the conversation. Yeah, no, I completely agree. That was an amazing speech. I don't know if I have any of those. Yeah, no, I love this idea. We've been talking about it a bunch, just more customization, the long tail of commerce getting even longer. And it feels unfathomable because it's already like, you know, specific shirts that are just for you designed and targeted to you on Facebook.

53:57We've seen that, but like it can in fact get more personalized. Well, yeah, I mean, we've seen this with content and these platforms, right? They're very good at serving you. They can serve you a video that has 50 views from a new channel on YouTube, and you'll be like, that's interesting. I will watch this, right? And it's a niche that is so small, it never could have existed in the era of radio and television and seeing that trend accelerate. It reminds me, I was wanting, you know, these like kids RC like ride on cars. I got like incredibly frustrated with these because I've tried a bunch of the different brands.

54:39I've tried spending like$800 on them and, you know,$400 and all of them just suck. Like the kids, even when you have the, you're driving the kid on the controller, the kid can still hit the gas and just like run into stuff. And, you know, it's just absolute chaos. I'm like, what is the version of this that is like, you know, you know, the top of the line version of this? Because I want to get it. I use these things a lot. And I searched around, couldn't find it anywhere. And then John just like. Within 24 hours, I got served exactly what he was looking for. I don't even know how it got served to me, but it was fantastic.

55:13Thank you so much for taking the time to come chat with us. Electric. Always a great time. My favorite, my favorite conversations. When you're on, it makes me feel like we're actually on SportsCenter. Because most people that talk about this stuff are not high energy. They're just like full-on SportsCenter. It's amazing. It's amazing. I love it. Well, congratulations, all the progress and the Prosperous Society. Go listen to it. It's a three-hour, four-part series. And sign up for Mobile Dev Memo if you haven't already. Of course, you should. But thank you so much for coming on the show, Eric.

55:43We'll talk to you soon. Take care, guys. Have a good one. Let me tell you about public.com. Investing, for those that take it seriously, So they got stocks, options, bonds, crypto, treasuries and more with great customer service. And our next guest is Bert from OneX. He's the founder and CEO. How are you doing? What is that behind you? Welcome back to the show. Thank you so much. That is incredible.

56:04Thibault Sottiaux:It's like my hand and then it's like Neo's hand. Yes. Introduce the launch today. What happened? Tell us about it. I mean, we've been cooking on this for quite a while. So super excited to finally show this to the world. and also it's just so exciting because we're so close to shipping now yeah so everyone's gonna pick this apart anyway yeah so we don't need to be careful anymore and we can just like open it up and to me it's this beautiful machine that becomes almost more art than engineering right at this point and uh yeah we're excited to show people what we've been cooking and uh excited to put it in people's hands and i think also uh it has a special place in my heart because we're working on this problem for more than a decade.

56:45Thibault Sottiaux:And one thing that Neo and One X has really been pushing is how to use highly miniaturized, high-power motors and tendons to create these machines that mimic humans. And the hands is the kind of culmination of all that work, right? It's where all the complexity comes together to meet the world. And hopefully we've created something here that can really remove that final barrier for how intelligent our models can become, right? Like so much of human intelligence comes from our ability to probe the world for truth and to really figure out how the world works through our hands. Okay, take us through the full journey of developing hands for Neo.

57:28A lot of people in tech love to follow an Elon-style playbook, just make the most simple version of something, simplify, simplify, simplify. this looks incredibly beautiful, but also incredibly complex. And so I want to understand like how you, how you got here basically like version by version. So,

57:50Thibault Sottiaux:It is a very complicated hand, but in my opinion, it is the simplest version of it that exists that is good enough to do what needs to happen. So, first of all, One X is fully vertically integrated, so we do absolutely everything in-house. And in our factory here in California, where I'm sitting right now, we do everything from designing the production processes to producing our own motors, our own tendons, the entire system, right? Sensors, electronics, everything in-house. and that allows us to iterate very, very fast. Because I do really believe in like, you have to have this first principles approach, right?

58:24Thibault Sottiaux:So start with like, what am I trying to solve? We're quite lucky in that we have humans to look at with respect to how you solve this problem. Nature did a pretty good job. So when you say you're looking at humans, what type of training data are you using? What's useful? What are you discarding from just, there's a lot of hand videos on the internet, I'm sure, people doing all sorts of things. You can do teleoperation. You can have people wear gloves and do motion capture. You can do simulation. Get an x-ray. Yeah, x-ray. I mean, there's so many different ways. Like, are you using everything? Is there one path that you found specifically valuable?

59:02Thibault Sottiaux:So I think, actually, it starts from, like, starting with first principles, right? So Wamax has always been about we want to design robots that are safe so they can live and learn among people. But also because safety is what allows us to learn. So we probe the world for truth. And of course, if our fingers break while doing that, or we break whatever we're trying to touch, it doesn't work. So you need to design these beautiful kind of like compliant, soft systems that force can flow both ways, because you're both seeing with your hands and acting with your hands. And that's really what this is all about.

59:33Thibault Sottiaux:So like, how do you create that? And you kind of have to look at how nature works. Like our muscle, nothing really moves fast. There's no gears, no, nothing like this. So you've designed this from these first principles. but we go way deeper than that i think what we haven't talked enough about yet and we'll share more about this later is like how incredibly seriously we take closing the gap towards the human and it's not to look like a human it's because we want the work system to work like a human so even like if you look at neo's hand behind me here we worked so deeply on how do you make these fingers non-linearly just like be compliant exactly like a human finger because if you get all these details right, you can take all of the video that's out there on the internet.

1:00:17Thibault Sottiaux:You can train huge role models based on this, and it just works on a robot. And that's what the 1x role model lab is about. So to enable that general intelligence for robotics, you need to design the robot so that it interacts with the world exactly like a human. And then you want to do that with the least amount of complexity possible. And that's essentially what we have here. But of course, the complexity of that is pretty high because you're mimicking a human head. Let's talk about grip strength. We got grip strength testers here in the studio. is this an important benchmark clicking these together how strong is the hand currently where do you want to go because it feels like there's a trade-off there where if the hand like the stronger you make the hand the heavier the more uh the more dangerous it could potentially be at the same time there's certain tasks that you expect a certain level of grip strength also yeah yeah yeah it'd be interesting to understand how often tasks come up in your daily life where you need like insane grip strength yeah it's pretty rare i think but certainly in you know industrial capacity or even around the home picking things up moving a chair you need to be able to grab it without dropping it it's a safety issue at the end of the day yeah i think it actually appears quite often but you don't think that much about it because you don't do it for a long period like yeah you're not grasping that hard but then something starts slipping and you tighten your grip or like you're actually using quite a bit of force so the hand is roughly the same yeah that's a good one.

1:01:39Thibault Sottiaux:The hand is roughly the same strength as an average human. Really? So, I mean, it needs to be able to do the full capabilities of a robot, right? So the robot can deadlift 150 pounds. So the hands need to hold the bar of 150 pounds. Not because deadlifting is useful in everyday life, but because it's a good metric for how capable we are. So we really worked hard to make that kind of power to weight ratio also about the same as a human. So if you look at the general hands in the market right now, this thing is roughly three times as high force as the other hands. And that is really also something that's going to enable a lot of new applications.

1:02:17Thibault Sottiaux:Because in the end, your AI will be as smart as the diversity of the experiences that you have lived and experienced. Like diversity of data is directly correlated with the intelligence of your model. And if you are a third as strong as a human in your hands, there's a lot of tasks you just can't do. Yeah. I have one more. It feels like you have jumped to the frontier of hands specifically. I saw people joking, can I just buy the hand? Obviously they're making probably rude jokes, but is there a world where you partner with other robotics companies to sell a piece of your hardware, maybe just the hand to someone else that already has a wheeled robot, but it needs a hand is there a world where you're selling parts of your technology or do you want to be vertically integrated from end to end the full experience i think there there is a world like this i do think it's very important though that like we want to we're we're about to also launch neo as a platform where we we're going to invite everyone in to build on this and having like a homogeneous platform that everyone is building on is so incredibly powerful because that doesn't exist today.

1:03:27Thibault Sottiaux:And that really allows you to do benchmarks across systems like you have in the rest of the AI community. But that being said, it's not a hill we're going to die on. Like if the collaborations are the right types of collaborations, we just want to make sure we can scale our manufacturing and get as many out there as possible and build the ecosystem and really give robotics all the love it deserves, right? Yeah, totally. We just want to accelerate the path. Yeah. Amazing. Timeline around shipping. What's the update there? I know a bunch of people that are in line that have ordered. So, everyone's very good.

1:04:02Thibault Sottiaux:So, yeah, I'll be kind to my team and not give you a specific date. But we have promised that we are going to ship this year, and we will ship this year. So, we're going to keep that promise. And it's going to be incredibly exciting. And like I said, the reason we can be so open, right? So, you can just read into that. Like I said, the reason we can be so open is that this is about to ship. So, people will pick it apart anyway. And I do think this is going to be so big, right? As AI now becomes physical, it's really hard to understand what kind of impact that will have. We're getting so much interest from, let's say, wet labs that want to have their AI for science actually design, manufacture, and run their experiments.

1:04:40Thibault Sottiaux:There's hospitality, elderly care. You have the home that we're already working towards. There's this enormous surface area, and it's going to happen a lot sooner than people think. And I think right now it's just about really growing the pie and making sure that everyone has platforms that they can work on to solve these hard problems. Yeah. Amazing. How will, I mean, the last question I have is like, this feels like a technology that even after you solve development, design, and the AI that powers all of this, it is much more gated by the real world, and thus we would see a slower takeoff. Like what we've seen with Waymo, it's everywhere in San Francisco, but as you go around the world, you don't realize that cars can drive themselves.

1:05:32whereas you know chatgbt.com was available in every country and it was just like the touring test is passed for everyone at the exact same time and that's that feels impossible in robotics in the physical world but do you have a different view of it or am i roughly correct with that

1:05:48Thibault Sottiaux:prediction the ramp is going to be slower but the total uptake is going to be way way way higher sure right so like if you think about and i'm i'm very bullish on this like um i think it's just a two to three years away, but even if it's a decade away, robots will build robots. And we're already working on this in a factory. But they won't just build the robots. They'll build the data centers, the chip fab, the energy infrastructure, get into mining and refining. And this full automation of the physical substrate that enables everything, including intelligence, that can only happen with robotics.

1:06:20Thibault Sottiaux:And that's going to look like this, right? So you need to kind of enter that curve. And I think the uptake ramp is going to be slower in the beginning, but way, way higher as you kind of like hit vertical on the curve. And I think this is also where it gets extremely interesting, right? I'm back to like how we're going to solve some of the remaining problems in science, how we're going to create an actual true abundance of labor across society. This is only possible if you automate the physical substrate. So it's going to take slightly longer, but it's also worth it because the impact is tremendous.

1:06:54Yeah, and it still should be an exponential curve because once you get to the point where five robots can make one more robot in a month, then you wind up compounding and the exponential just grows and grows and grows. Fascinating. Very exciting times. Congratulations. And thank you so much for coming on the show. I'm super excited you guys shared this. Thank you. You guys continue to have the best aesthetics in robotics by 100X. Yeah, it makes me feel much more C-3PO than Terminator, which I think is the right direction to go. The hand's a little Terminator.

1:07:29Thibault Sottiaux:100%. The hand's a little Terminator, but yeah. One should not underestimate how important it's going to be to do this together with people in a sense of like adoption needs to come through making everyone used to this technology, right? Totally. We want to make sure everyone understands how helpful this can be and really make sure that we don't hit any barriers where this becomes something that people don't want because it's such a great opportunity and we want to make sure we can accelerate the path. Yeah, VR was useful in certain pockets, but it was awkward, and it was never adopted, and it was always seen as this very niche technology.

1:08:09And I think the aesthetics are underrated, so congratulations on nailing them. Thank you so much for coming on the show. We'll talk to you soon. Cheers, great stuff. Have a great day. Thank you, guys. Cheers. Have a good bye. Let me tell you about Codex. Codex is a powerful workspace for getting work done with AI agents, whether you're writing code, analyzing data, creating content, or automating business workflows. Codex helps you move projects forward from start to finish. And we have Tebow joining in just 40 minutes or 30 minutes to give us the update on 5.6 and what's going on in Codex, of course.

1:08:38But first, we have Josh Lindgren from CIA. He's the head of podcast development here to give us an update on all things. Suited up. Podcasting, suited up, looking good, Josh. How are you doing? Welcome to the show. I'm doing well. You guys are always looking good as well. Yes. Great to have you on the show. Great to hang in France just a couple weeks ago. Give an introduction on yourself, how and when you got into podcasts, and then we'll talk about where we are now. Yeah. Yeah. It's been a wild ride. 12 years from me, I started representing podcasts 12 years ago. I was a music agent at a boutique music agency in Seattle, booking tours for indie rock bands.

1:09:16And I used to listen to podcasts all day while I was routing tours and had the idea that maybe podcasts could have agents. started cold emailing podcasters and was surprised to discover that there was a business there for me. And very surprised in that time to discover that there wasn't really much of a business infrastructure yet. So there was a lot of opportunity. Spent the next several years signing podcasters within that agency. And then in 2018, I met with 11 different agencies and ended up joining CAA. Started the podcast department here. and we have a great team of people focused on podcasts.

1:09:56The podcast department is within our greater creators department that works with all kinds of different creators like yourselves. And it's been a really wild ride. I mean, when I got into podcasting, the estimates I've seen is that the global podcast advertising industry was worth about$45 million. And Owl and Code has put out a report that last year it was worth$9.2 billion. So, you know, I expected there was going to be a lot of growth in this space. It seemed like a great growth area. Thank you. But I never expected this level of growth. I mean, it's been a really tremendous wild ride. I had started working with some podcasts around the same time a little bit later, I think.

1:10:36You were 2014, was that? Yes. Yeah. So I probably started working with podcasts in like 2016. But even then, I would meet a show that today was probably like a$10 million a year business, and they would have zero revenue. But they would have this like rabid fan base, and maybe they'd have one sponsor, which was just someone in the audience that reached out and was like, hey, can I send you some free stuff if you talk about it? And they'd be like, okay. And then fast forward to today, those kind of properties are super valuable. What are you seeing now? Like what's coming down the pipeline, net news shows?

1:11:17We've covered a lot of the evolution of formats, how podcasting obviously interacts with live streaming in our case. But what do you see coming down the pipeline? Yeah, I mean, it's been clear for a few years now that video is going to be a bigger part of podcasting. And we're really seeing that come to fruition in the past year. It's like a major inflection point right now. Now, to be clear, like, it's not the videos replacing audio. Both can continue to exist together. There was a recent study from Edison that said that the majority of podcast consumers do both. Sometimes they do audio, sometimes they do video, which that's my experience.

1:11:56I live in L.A., so I have a long commute. And so I like listening to podcasts in the car. But I also like watching podcasts at home and in the office, you know. But it's created a really interesting moment in podcasting where there are some things that are fundamentally different about digital video versus digital audio. For one thing, advertising looks really different, right? The ways you can integrate with brands looks very different versus the audio space tends to be much more dominated by your 30-second pre-rolls and your 60-second mid-rolls and so on. The video space tends to have a lot more custom integration with advertisers.

1:12:32And also discovery looks really different in video. You know, in the audio space, in terms of breaking stuff through, there's a lot more spend that is required in sort of the same way that you might market a TV show or a movie, right? Whereas in video, there's a lot more clipping. There's really seamless integration into social media. And so if you're trying to break through with a new podcast in 2026, you should have a really strong reason why you're not a video podcast or else you should probably have a video podcast. Yeah. Somewhat related to the video podcasting thing, a big trend out of can that colin samir and others were talking about was uh that many podcasts are sort of reformulating as shows uh we we've done this where we think of this more as a show than a podcast because it's a live show there's a lot else going on of course like it's available as a podcast and then you also think of like subway takes it's emmy nominated now and it's a it's very much a show but it's also an interview that's sort of like a podcast and i'm wondering how you're perceiving the definitions changing, evolving, just this idea of what does it actually take to deliver a show as opposed to just a podcast in the modern era?

1:13:49Yeah, I'm with you. I think that's the right thinking to not try and put it too much in a box, right? Because the lines are just getting so blurry between what's a podcast, what's a TV show, what's a series of reels, right? What's a YouTube channel, in your case, a live stream. I do think that the word podcast is a bit of utility for me just because it's sort of like I know it when I see it, right? People talk about podcasts, people like podcasts, but I mean, truly, the line is really blurry. I mean, you know, I think we talked a bit in Cannes about Oprah's podcast, which just moved over to Amazon, right?

1:14:22And I mean, Oprah is the queen of television, right? And this is where she's putting her energy. And, you know, who's to say, like, if you're watching it on Prime Video versus if you're watching it on your phone. Is it a podcast if you're watching it one place and it's a TV show if you're watching it the other? I mean, I don't know if it necessarily matters, but I think that it's an amazing time to be a media consumer because media is meeting us where we are. Yeah. Talk about the landscape of these podcast distribution deals that are happening. Pat McAfee with ESPN. Oprah, you mentioned, is doing one.

1:14:59There's Netflix is entering the space. Spotify went with Joe Rogan very early on. Some of these platforms just sort of get the video podcast for free, like YouTube is the default for most creators. But what are the larger companies looking for when they want to go deeper with a creator who might just not be ready to graduate from the self-serve options or maybe they don't have a self-serve option if it's a linear TV or a platform like Netflix. Yeah, it's funny. I mean, it's a really unique marketplace because, as you kind of overviewed, the different buyers in my space are just drastically different in terms of their business models.

1:15:37So it's really hard to compare apples and oranges when you're looking at one of our major buyers, say, is SiriusXM, which is a really significant satellite radio business, comparing them to Amazon, one of the biggest companies in the world, and primarily doing e-commerce. they both have drastically different things they need out of it, let alone now you have Netflix and Hulu entering the space, right? They have different KPIs in terms of what they're looking for. So I think part of the challenge and the joy of representation in this space is understanding who the different buyers are and what their needs are and understanding your client, the talent, right?

1:16:13And what they want, you know? And it's just, there's no one deal that makes sense for everyone and there's no one size fits all in podcasting. which I think is great ultimately because it means we can paint with different paintbrushes for different types of shows. Yeah. Can you, do you feel like you can identify if somebody is going to be a star based on their first ever episode? Well, I think that, I think that taste is really important, you know? And for me, like I will take bets on stuff that I think is fundamentally good. I mean, when I was a music agent, I was picking bands based on the bands that I liked.

1:16:46And I just had to hope that other people would like those bands as well at some point. And I still believe that, you know, in podcasting. I think that there is room for pace. There's certainly stuff that I don't represent that does good business, but it just wasn't right for me. And that's fine. You know, I think that as soon as you divorce your love of the medium from the business, then what's the point, right? Like if we're just here to make money, maybe we should be working in finance or in tech or something, right? Yeah, maybe we should all be wearing suits. There you go. Look, look at me.

1:17:23I'm just here to have fun. Yeah. How are you thinking about live streaming and maybe more pure play live streaming? I'm thinking about the video game creators, the ninjas, the shrouds, the folks who spend 12 hours, eight hours a day live streaming, political commentary, business analysis, anything. It's such a different business model, such a different community, sometimes much tighter audiences. but incredibly engaged. Is that a muscle you want to build? Is that something you're thinking about growing? What trends are you seeing there generally? Yeah, I think the live streaming space is fascinating, right?

1:18:04And obviously this has been happening for a while, but I think the moment we're talking about of the merging of all the different things is really playing out for live streaming too, for yourselves and for other shows. You mentioned political shows where people need real-time news. I don't think your fans want to wait an entire week necessarily to get your take on something when it develops. It's a lot of work. I think you guys know the amount of time and energy you have to put into doing this, right? It's really impressive, and I applaud you for it. But it really creates a lot of different opportunities.

1:18:34I think something else that you guys are doing really well is that you do the live stream, but you also cut this up into audio episodes and video episodes on YouTube and so on. So there's so many different ways to reach your audience. And I think as a creator today, the more that you can be flexible to meet your audience where they are, the better chances you're going to have of succeeding and breaking through. So I love to see what you're doing. And I think that you're on the tip of the spear right now in terms of the new type of experimentation that's happening in the streaming space. Yeah. Talk to me about how you're thinking about working with a celebrity or group of celebrities that wants to get into podcasting.

1:19:19It feels like there was this crossover moment where podcasting was a backwater, then it became cool. Maybe it was around COVID, but we got a whole bunch of celebrities crossing over. Some of them did extremely well, won awards, SmartList is huge. But it feels similar to celebrities launching brands where there's still going to be a power law. It's not just, it's obviously a huge advantage to have an audience already, but not every celebrity is going to have a hit podcast and vice versa. Not every podcaster is going to work on TV or wind up starring in movies. Um, how, how are you assessing, um, the, the, the reverse transition from, uh, you know, Hollywood or TV or films coming over into the podcasting world successfully?

1:20:07Yeah, I think there needs to be a reason to be for any given podcast. There was a level of experimentation, like you mentioned, around COVID, where a lot of folks launched podcasts that maybe didn't pan out. And I think maybe some of those had to do with the reason behind the podcast and the idea of the podcast wasn't as sought out. I think a good example of it working would be Julie Weidreifus' Wiser Than Me, where that was driven by her desire to hear from older women that are largely ignored in our culture. So she had a reason that she wanted to make it. It wasn't like she would just come into the space because some enterprising agent myself told her that she should make a podcast and she could make money.

1:20:50She was there for a different reason. But things I see succeeding have that reason behind them. I mean, you mentioned SmartList, another COVID project that began out of COVID, and it came together because the three of them wanted to hang out. Right. And they wanted to create something for people who were locked at home, you know, and that like genuine friendship between them is the basic building block of what it is, you know. So a lot of what I do when I talk to celebrities about podcasting is try and get to the core of what it is that they want to create and what their purpose is for coming.

1:21:21And then you can craft all the business and everything else around that central seed of an idea. What's the secret to a successful podcast tour? I mean, back to SmartList, I feel like they've been extremely successful at engaging the community off of the Internet, which is interesting because they started off the Internet, they went to the Internet, then they go back into the live tour. But what makes for a successful podcast tour? Yeah, I think that your relationship with your audience is so strong in podcasting. And it depends a little bit by format. You know, I think the level of engagement for more format-driven shows, maybe a little bit less than more personality-driven shows.

1:22:03But something that I saw really early on getting into the space and coming from a touring background, I was booking tours for podcasts. And, you know, one of the first live podcasts that I went to was an early client of mine, Stuff You Should Know, which I assigned by emailing info at Stuff You Should Know. No way. It was a really different time. But then I went and saw them do a show in Vancouver, and they had a Q &A at the end of the show. people are getting up to the microphone and this, this woman gets up to the microphone. She's like 22, looks normal and nice. As soon as she gets on the mic, she is bawling because she is talking to Josh and Chuck from stuff you should know.

1:22:35And it was a real like light bulb moment for me. Right. Cause that's a educational podcast. Right. But for her, she was explaining on the microphone that they spent so much time in her ears that she has this relationship with them. And it was like, she was finally meeting these friends that she's had for so long. and I think that's when you get people who are not just willing to buy a ticket but to travel four states over to make it to a live show and we look at data for download performance in a market before and after a live show and we see in some cases a niche show can have a really solid touring business because they're converting 50 % of their listeners in a market are turning out for these live shows and we've done analysis too where we look at zip codes of ticket buyers.

1:23:21And the number of people who are traveling long distances to come to these is pretty incredible. So I think that's the key thing is if you have that relationship with your audience, if you let your personality be a part of the podcast, people are going to want to come out for that. How are you thinking about international, just like the puzzle? Because if your business is, if your podcast is aligned to specific products that are maybe only sold in the United States. It can be hard to monetize. You might need to go on a tour. An international tour can be more expensive. At the same time, I'm sure from musicians that you've worked with, you've solved the puzzle of what an international world tour looks like that is successful.

1:24:04So how do you think the future eras tour of the podcasting world will play out? yeah i think that um the international touring is i mean you have it see it feels like it's early am i right in that or am i just not aware of there was already the eras tour of podcasting and like smart list did it and i just wasn't paying attention to their their trip to japan or something i would say there's only one eras tour but you but you are seeing a bit of international touring happening already i mean you know many years ago we sent stuff you should know to australia and it was such a wildly successful tour.

1:24:41We see a lot of American podcasts doing the UK, a little bit in Europe. I mean, one of the challenges is when you're crossing over into markets that are primarily not English language speaking markets where you might have listeners, but you might have a different type of relationship with them. That can be a real challenge, but especially going from one English language market to the next, it can really work. But you do see audiences becoming really segmented between different markets. If you look on any given day, at the charts in the UK and the charts in the US, they're probably going to look pretty different.

1:25:12There's going to be crossover for sure. But a lot of different stuff changes out, even though we speak the same language and understand each other very well. There's just different sensibilities from one market to the next, you know? But I mean, you mentioned advertisers, right? The US ad market is a big leader in podcasting, right? Because this is the consumer that a lot of brands want to reach. And so, you know, as we've built our business internationally and sign podcasters from all over the world, you know, there's still at this point a real value into having a foothold in the United States in terms of reaching audience.

1:25:45I think one of the most exciting future change areas in podcasting is going to be seeing more of these markets come alive. And if I was, you know, an investor looking for a place to start up, I would be looking at India right now, for instance, you know, right? Whereas there's just a little bit less saturation and more opportunity for extreme growth. Australia, I think, is a really interesting market. I made it out to Sydney last year for South by Southwest Sydney. And it reminded me a lot of the podcast market in the US 10 years ago, 12 years ago when I got started. And so I think there is a lot more that's going to come online for those markets as the brands locally and the advertisers in those areas start to realize that this is a great way to spend money and to reach audience.

1:26:31But it was an education process in the U.S. to get brands to spend here and trust this market. And it'll be an education process on a market-by-market basis. Last question. How are you talking to – or I don't even know if you can talk about this. But folks who work for large media companies, they have been around for the pivot to video. We're going to put you on camera. We're going to set you up with a podcast. They build an audience and they're ready to venture out on their own. We've had Ashley Vance on this show, Joanna Stern, Eric Newcomer. There's been a whole host of these folks who sort of grew audiences and learned the skills of content creation, whether it's advice or Vox or any of these platforms.

1:27:20And then they go independent. If you're having a conversation with them, how are you talking to them about why they might want to do that? or why they might not want to do that? Yeah. So every podcaster, every creator is an entrepreneur, right? Which can be really scary if you're used to getting a paycheck every single, you know, biweekly from a big media company. But it's high risk, high reward, right? Because once you launch your own show, you own that audience. And no longer are you at the whims of, you know, the executives that you work for. And actually capturing a smaller audience can be more lucrative for you because you're capturing more of the revenue that that audience drives, right?

1:28:02This is a conversation I have with folks all the time who are at legacy media companies trying to decide what their next steps look like, especially in this really fast-changing landscape where some folks are forced out when they necessarily want to make that choice right away. So it can be a really scary transition. I'm very empathetic for people who are going through it. I don't begrudge anyone who decides that they want to keep working in legacy media. I don't think that it's doom and gloom for legacy media, right? I think that there's still room for great journalists on television and on radio, print journalists and so on.

1:28:34But for folks who are entrepreneurial and want to build their own thing and own their audience, there's incredible upside and opportunity. Yeah. Yeah. It's exciting times. Well, thank you so much for taking the time to come chat with us. Great to have you on. Have a great rest. Thank you so much for having me. The godfather of podcasting. It's true. It's true. We will talk to you later. Have a good one. Great to see you. Thank you so much. Let me tell you about CrowdStrike. Your business is AI. Their business is securing it. CrowdStrike secures AI and stops breaches. Up next, we have Jeff Morgan from Olama.

1:29:05He's the co-founder and CEO. This is his first appearance for the massive Series B. Jeff, how are you doing? Welcome to the show.

1:29:13Thibault Sottiaux:Thanks for having me. Doing great. So excited to be here. Big fan of the show as well. Thank you. Please introduce yourself. Fantastic to have you on. Introduce the company. I want to get to the bottom of how the hell you got 85 % of the Fortune 500 using your product. But first, introduce yourself and the company. Yeah, I'm Jeff. I'm the CEO and co-founder of Olama. Olama is the largest network for developers to access open models. You can download Olama, get connected right away to open models like GLM 5.2, or you can download them locally and run them right on your laptop for more kind of edge, low latency use cases.

1:29:43Okay. Tell us about the round. Jordy's warming up the gong. How much did you raise? Who from?

1:29:49Thibault Sottiaux:$65 million. The lead was Tomas Tungus and got existing investors participate too. Like Ben. Awesome. Fantastic.

1:30:02So tons of GitHub stars. Why, how does this fit into like the, the value add to businesses versus just downloading the model of themselves from, from an open platform, getting the, the actual, the weights themselves, deploying things, or just going with an API? How are you talking to Fortune 500 customers about how you will actually improve their experience with something like GLM 5.2?

1:30:31Thibault Sottiaux:The power of open source is how fast it can build trust with developers around the world. It ends up a large number of developers work at companies. A lot of those in the Fortune 500 or Global 10 ,000. and open source has a special capability where you can deploy it in your own environment and not have to think about a ton of security and compliance. And what that means is, look, you can take an open model, which already has open weights, and that's kind of why open models are perfect for these use cases, and run them without any approval really as a developer and get real successful results all without having to expose your data or even incur big costs.

1:31:10Thibault Sottiaux:So, you know, that's really been the driving force of being able to get into these large businesses. And to your point, look, like, you know, just the weights being open isn't enough. You need a way to deploy them, to run them, to make sure it works on your hardware. For the cloud models, you know, you really need to make sure that you're running them in a secure environment where your company can access them. You know, a lot of businesses we talk to, especially Fortune 500, they need these open models hosted in the U.S. and in Europe. And that's just a requirement. And it's a need they have. And so, you know, put that all together, it's so surprising and incredible how fast they can get adopted.

1:31:43So what does, I mean, you say you're talking to these Fortune 500 companies, but I imagine that the fact that you have so many GitHub stars means that there's a lot of self-serve activity. When does the customer cross over to an enterprise relationship with you?

1:31:56Thibault Sottiaux:Yeah, generally it starts with the individual dev, right? They bring it to work. A lot of them use it, you know, for personal productivity and they bring it to their team. And once you're using a team, it's not a one person story anymore, right? There's a team there, everything from security to technical architects, IT teams. These folks, they need not just a product that's really easy to use and self-serve, but they need a solution that really end-to-end covers things like safety and monitoring and logging and data storage and protection. These are all components of a successful agent deployment.

1:32:30Thibault Sottiaux:That's when it becomes a multi-party environment. As we know, that's when you need a solution. And on our side, we need a team to be there to help those customers. What set of models are you most excited about for the back half of this year in the open weights world? I mean, I think with GLM-5.2, we just had another massive moment in open models. And Ollama by far, at least from what we know publicly, is the highest token volume of accessing GLM-5.2. And so I'm excited for that because I think there's going to be a series of new models that are long horizon. They're focused on these really hard agentic use cases.

1:33:05Thibault Sottiaux:And there's going to unlock so many use cases in enterprise that, you know, the prior generation of open models couldn't. You know, and the gap between open models and the frontier models is shrinking. And so, you know, I think at that point, we're able to get to these incredible use cases that just weren't there, you know, three or four months ago. Take me through some of the game theory in the open source community around those rumors that we heard that there might be export controls on open weights models coming out of China soon. If we stop getting frontier or near frontier open source models from China for free, is the next step that you would see an American company step up, NVIDIA, or maybe Meta changes their strategy?

1:33:54How are you thinking the open source ecosystem would evolve if China changes their strategy?

1:34:02Thibault Sottiaux:Yeah, we like to work backwards from our customers. What are they trying to do? And they, for by and large, you know, they may have preference on specific, you know, geographies where the models are from. But by and large, they're adopting both right there and some mix of open models and frontier models as well. And to your point, like, I think the U.S. models are absolutely stepping up. They're incredible. The Nemo Tron three ultra model is just amazing and is able to accomplish some of these long running Asian tasks. And then also, you know, one of the most downloaded models on the Lama is a U.S.

1:34:31Thibault Sottiaux:model. It's the Gemma models. And, you know, this is like a super amazing team at DeepMind that's putting them out. The new ones are, you know, agent ready, like they can run coding agent loops. They can accomplish much harder tasks. And so, look, I think it's really up to the customer. If they want an U.S. entirely U.S. built model designed from scratch, that's there. If they want a Chinese model, which is often the case, it's less about where the model is from. It's like, where does it run? And is it running next to your data, which, you know, you can deploy it locally. and then are you able to deploy it with safeguards?

1:35:03Thibault Sottiaux:And it ends up a lot of customers, they're not looking for where the model's from. They just want to make sure that they're running it properly and safely so that they can have an understanding of what could go wrong, but what could go right. And there's a lot of safety tooling that can be deployed to help with that. They have tons of appetite for that. What do you see your role as in terms of benchmarking, reality checking, vibe checking, different models, helping enterprises that work with you to make the right decision, pick the right tool for the job? Our job fundamentally is to connect the 9 million developers on Olama to the right model for the right task.

1:35:41Thibault Sottiaux:And that's step one. And so just by having that sheer volume and this critical mass of devs, we're able to already understand just from our community which models are performing right for the right tasks. That's a starting point. I think from there it's really collaborating with the model labs And we're launch partners with every major model lab and just making sure that, you know, the best parts of the model are shining through through a lot, including what are they capable for? What are their benchmarks? How can customer customers benchmark it for their own use cases? It all comes down to a lot of software tooling and, you know, a community and a network.

1:36:15Thibault Sottiaux:And that's what we built and is what makes a lot of special for developers. Got it. $65 million raised. What are you using the money for? Because you don't have the crazy training costs because you're more of a gateway. Is this headcount? 2 ,000 BDRs. Is that what you're hiring? No, it feels like you have also bottoms-up adoption with developers, so you maybe need a lighter sales force to actually capitalize on that. Yeah, what do the next 12 to 18 months look like for you? Yeah, you hit the nail on the head. Look, we put out on our site, hey, we're launching a Teams plan. We were inundated with thousands of teams that want to use Olama.

1:36:55Thibault Sottiaux:And that's the core mission. It's like, look, we've got this critical match of devs. How do we go solve problems for businesses? Back to what we were just talking about. And that takes a team. So obviously, we're expanding. We got here with 14 people to a company of this magnitude. But there's a much bigger team to the market. market. And then, of course, you know, one thing Olamide does very special for the larger open models is we host it on U.S. and European servers. A lot of the consumption of open models is going to China or is going to servers where there's no data retention guarantees. And that's so important for companies.

1:37:31Thibault Sottiaux:And so that's a compute investment we're making and really enabling, you know, every business in the world to access the most powerful models on compute that's secure and safe in the U.S. or Europe? Will we ever settle the debate on whether the gap between open and frontier models is closing or widening? Because depending on what sort of group somebody is a part of, they tend to have one view or the other. But I think in reality, it's probably always kind of going like this to some degree. But what's your view? Yeah, I think you're right. It's oscillating. I mean, I'm a daily GLM 5.2 user through Alma right now, and it's replaced 80 % of my coding work.

1:38:14Thibault Sottiaux:And I think that's going to be true of a lot of customers. As for the gap, to your point, I think it may widen, it may shrink. I think overall it's shrinking. But ultimately, customers are going to use a mix. And for the bulk of their use cases, they're going to reach for these open models because they can tune them to be much faster. They're obviously much cheaper. And there's always going to be use cases where you need the frontier. I don't know if we'll ever settle the debate. I think ultimately the gap will continue to shift. I think that's what makes it exciting, right? It's like every three months we're able to do something new.

1:38:44Thibault Sottiaux:We're able to run better agents and quickly open models will catch up and really enable a whole wave of customers that want to run open models to do that, you know, in their own environment or to customize it to the point where like they can even make it more powerful. The last thing I'll say, too, is customers are readily taking these open models and customizing them, and they're actually getting better results often than just a stock frontier model. And I think we're just at the beginning of that transformation. Very cool. Well, congratulations on the progress. Awesome to meet you. In the round.

1:39:13Congrats to the team. Thank you so much for coming on the show. And have a great rest of your week. We'll talk to you soon. We'll talk soon. Goodbye. Awesome. Thanks. Cheers. Let me tell you about Shopify. Shopify is the commerce platform that grows with your business and lets you sell in seconds online, in-store, on mobile, on social, on marketplaces. and now with AI agents. Jordi, there is a story. Oh, wait, we actually have our next guest. Guest of honor. Tebow from OpenAI. He's the head of Core Products and Platform. Tebow, how are you doing? Congratulations on the launch.

1:39:43Thibault Sottiaux:Hey, thanks. Doing well. Give us the highlights. How did you sleep last night? Do you sleep? Do you sleep at all? Yeah, I do sleep. Currently, we have like, you know, maybe five to 10 war rooms going. So, you know, it's just like a little bit. But it's intense. It's a sport. Yep. We heard you shit. And you guys like to make it hard on yourselves by launching. Every time there's a launch day, it's like 15 new things. So it makes sense that there's close to equal amount of war rooms. Yeah. Let's start with 5.6 Solve, though. I want you to identify for me what is sticking out? What are the most cutting-edge capabilities that really stuck out to you, the latest unlocks from the frontier of the actual model.

1:40:29Then we can go into codex and voice model and everything else and how things come together and how these are used. But first, just from the raw model capability, what was most impressive to you? What was most exciting?

1:40:42Thibault Sottiaux:Yeah, it's actually really hard to answer that question, because when we were looking at the benchmarks, trying it, we were just like blown away by it all. It's just better at coding, better at cyber, better at everything like long context, producing documents, better at having taste, website generation. And then for the first time, we also really cracked, I think, multi-agent setups, which we shipped as the ultra mode. And when you just see that going and you've got like eight agents collaborating together, communicating and getting the same work done like faster, it's just you just feel like, wow, this is like another way to scale test time compute.

1:41:17Thibault Sottiaux:But overall, just amazing workhorse. Feels way, way better than 5.5. And anything else for you so far? So in January, there was a project that was getting some attention called Gastown, talking about all these different sub-agents. You had poll cats and all sorts of different abstractions. It felt highly technical, and it seems like Sol Ultra is a way to abstract that away. Is that deliberate? I guess the question more broadly is, is the level of prompt engineering, are we leaving that era? Or will there always be some cycle of, you know, if you get really good at using Sol Ultra, you'll have a better experience because you'll be able to give more fine-tuned, fine-grained prompt and direction to the model?

1:42:06Thibault Sottiaux:so one thing that you see as well with solo is its uncanny ability at understanding human intent and you know you need shorter prompts you don't need to explain yourself in that much detail and so like you know just gets it and then goes and like does like a very complex thing um you know you saw the prompt for like post-training the luna model which is like super crisp uh and then it does that but it actually worked for many days and this is also like with us launching ChatGift work it's about making it accessible for everyone and you don't need to have like a PhD to use this model it should just behave like another super super smart human and just kind of get you in the moment and that's what we're striving for of course if you really push it to the limit you're always going to find new setups and this is also a very exciting space we continue to develop also Codex in the open source and we're seeing all sorts of novel ways to set up these agents and models so that you can get results in cybersecurity and all these other more nuanced and complex things.

1:43:11Thibault Sottiaux:But for everyone, you should just feel a ton of power out of the box. Talk about what was important at the product layer. Fundamentally, what I think people want out of products is to just be able to talk to their computer like a really smart coworker and be able to get things done. But then you're dealing with, you know, so many users over here, millions of users over here, trying to combine it and condense it into something that's simple. And obviously simple things end up being, you know, exceptionally complex to actually create. Yeah, so if you look at it, it's deceptively simple. You can open it on your phone.

1:43:47Thibault Sottiaux:It's chatty work. You just toggle it. And then there you go. You connect it to the things that you already have, your email calendar, you know, your docs. and then suddenly you're like, okay, wait, I can ask it to process all of this information that I had over there that I had to manually do all these things myself and it can just do all of that. And it's just like on the go and it's like on your phone in the chat you already have installed. I mean, that's the beauty of keeping it very simple. At the end of the day, we want it to be just a normal conversation between you and the agent. This is also why we decided to ship it like just in chat.

1:44:23Talk about progress in computer use. What is actually driving progress there? Is this just something that sort of comes for free with scale and model advances? Or is there deliberate data collection that's happening and some sort of flywheel that's unlocking new capabilities in computer use?

1:44:44Thibault Sottiaux:Yeah, we've done a lot of effort, bespoke effort on Windows, Mac and mobile computer use. Also phone use as well. and so there's an entire team working on this it doesn't just come for free but what does come for free is like every time we push the efficiency frontier and the model gets like you know more efficient like at thinking and acting and it just you know costs less tokens and it gets compressed in time it also gets better at computer use because it reduces the latency it reduces the cost and so the two compounds like you know we have a lot of gains that we're getting from you know also like visual understanding and every time you know it improves like the model just gets more precise so it doesn't have to correct itself.

1:45:20Thibault Sottiaux:And it was like, maybe it misclosed the button and they're just like, oh, just like, wait, I have to redo that. So every time it's like more accurate and more token efficient, computer is definitely benefits from it. And when you compare it to 5.5, it's like, you know, it's just really like three times faster. So, you know, we're not at all hitting a wall here in like how fast we can do computer is. Yeah. Can you talk about how the role of member of technical staff is evolving? Because you're talking about Soul Ultra going off and working for days at a time. And at a certain point, your job sort of evolves to, if you have a launch tomorrow, don't kick off a task that takes four days.

1:46:00Even if the model's capable of it and we'll deliver something great in four days, you need it tomorrow. And so you have to size your workloads appropriately. How are you thinking about sizing work and actually delegating the right chunk of work at this stage.

1:46:19Thibault Sottiaux:Yeah. I find your question very interesting because it actually highlights like a shift in our thinking over, you know, since we had five sixes. You don't really instruct it necessarily, you know, for a task that's going to take four days. You know, you tell it all the information that you have. So, you know, you're like, hey, I have a launch tomorrow. Yeah. And then keep track of the time and like understand that, you know, the PR needs to land like, you know, I'm in that or like by 2am. It will just like reason over it. Yeah. You're not the one that needs to manage like, you know, all of that extraneous like complexity.

1:46:47Thibault Sottiaux:Yeah. And so that's what you're seeing as well. It's like, you know, your relationship with the agent like changes over time as it gets more intelligent. And you're just like, oh, yeah, I can just talk to you like, you know, another, like, you know, super smart, super smart human. Yeah, yeah. Talk about the efficiency of the model, what work went into that, why it matters, you know, what kind of conversations you're having with, you know, big customers, all that stuff. yeah so what matters a lot right now is sitting at the frontier and you know getting the max capability when you want it but also for your normal average day-to-day task is you know being super efficient and not just for latency just because also we're seeing so like we had this era of token maxing and then you know we've been talking a lot with you know all the companies and enterprises that we're working super closely with and then they were like oh it's just a little bit you know maybe out of control it's like you know what we want is like you know we were in a highly efficient model that is, you know, steerable, controllable.

1:47:39Thibault Sottiaux:We want the right, you know, spend control dashboards. And so we also have all of that. You can look at your spend, understand the ROI, but also you can rest knowing that, you know, this is actually like a super, super efficient model. And so you get the job done with, you know, way, way fewer tokens, which, you know, to you, you know, means that, you know, you have to pay less for the same results, which is super important. And this is really the theme, I think, of the year is that, you know, that being on the efficiency of, like, you know, performance and cost. What about if you want to spend more for faster performance?

1:48:15What does the future of either ASIC enabled, Cerebrus enabled, Spark and fast mode? What do you want to see develop there either immediately or over the next couple of weeks?

1:48:27Thibault Sottiaux:Yeah, I think what we are truly working towards is a buffet of options. So for your normal interactive task, you're going to use 5, 6, so on medium or on high, and you're going to have an amazing time. If you have a really hard problem and you're trying to, for example, find a cyber vulnerability in something, you're going to run ultra, and you're going to run it for two days, and it's just going to leave no stone unturned and invent novel techniques. And you're going to be absolutely blown away by what it comes up with. but a lot of times you also just need speed for some of the steps that we're dealing with we love working off of the Cerebris version of this which is at about 750 tokens per second which is an order of magnitude faster than the default version that we have on the API and in the product today and this is just really situational or if you just want the very best and you're like absolutely no compromise It does come at a cost.

1:49:27Of course. A lot of people were feeling left out this week that weren't in the early access program. What makes a good early access partner? I'm sure your DMs are just making people that want access to the next set of models. But what makes a good partner to the product and the research team?

1:49:45Thibault Sottiaux:Yeah, we really try to go as broad as possible. It is quite a bit of effort to manage. And then also, like, we're getting all that feedback and incorporating it. and we work very closely with the folks in early access. For us, it's just really about realizing whether it is as good as we think it is. You're so close to the model, you train it, you've incorporated all that feedback, all your dreams, visions into this model, and then you've played with it for a little bit. And then when we give access to folks outside of OpenAI, it's the first time where we have an unbiased look, look, where people are using all sorts of models and different harnesses every day.

1:50:23Thibault Sottiaux:And so it's just kind of like this awesome, is it actually as good as we think it is? It's like, what are the things that we missed? And so it's that high bandwidth engagement, good feedback, and then that sort of people who have shown to be unbiased in the past and talked honestly about all sorts of models and all sorts of harnesses. How are you thinking about the trade-off between mobile, cloud, desktop, the Mac mini that went mega viral last year? Do you think that we'll stay in a hybrid pattern for the foreseeable future? Is it a person-by-person basis? Do you have a grand unifying theory of how agentic work happens in the future?

1:51:10Yeah.

1:51:10Thibault Sottiaux:The way that we think about it is no compromise. So you want to be able to use the same, your same AI partner, you know, like on your phone, on like on the go. It's just like, you know, I go walk in the park. I want the exact same thing. I want it on my laptop. I want it, you know, at home, maybe like running in a Mac Mini. And it is more that it needs to be able to have access to all the things that are important in my life and, you know, not be constrained by the physical, you know, boundaries of like, you know, it's just like, hey, I started this prompt or I started this conversation on my phone.

1:51:39Thibault Sottiaux:And it's just like now it's stuck on my phone. Yeah. We want it to be uncompromising. And so your AI partner, I think, just has access to everything all the time and just processes the information as needed. And then can act in a safe way and controlled way so that you always understand what it's trying to do. And if there is something risky, you can approve it or ask it to change tack. And there, I also think the mobile has a big role to play. If five, six years old is busy working on something and then you just go out to dinner, it should ask you for permission to do something when you're there.

1:52:16Thibault Sottiaux:You don't need to be stuck on your laptop. Fast forwarding six or 12 months, how important is voice to someone's day-to-day experience with ChatGPT work slash codex? I don't think we need to fast track. We shipped ChatGPT voice yesterday. No, I know. But, you know, you assume like, you know, oftentimes like something ships, you know, and it takes a little while. Everyone has to go on holiday break. Yeah, we need a three-day weekend. We need a three-day weekend and then everyone can test out the latest and integrate it into their workflows. Yeah, you know, open a chat with the app, like using a latest voice.

1:52:54Thibault Sottiaux:We also demoed it in the live stream this morning. And it's very, super enjoyable, like magical experience when you first experience it, but also like, you know, on the fifth time as well. it's going to be part of like you know day-to-day experience you know of like how you work with these systems we don't we don't have it yet in the desktop app but this is something that we're working towards and when when you experience it is it's like a modern day like jarvis right it's like you know you just talk to it you just walk in your room and you know suddenly it's just like doing things on your computer you know with the same level of like precision and power you know that you currently have over text.

1:53:31Yeah, it's amazing. Fantastic. Congratulations. Thank you so much. Hopefully you can get some sleep. I'm sure it's been crazy. Many big days to come. Back to the one of five war rooms, whichever one you'll go to next. Have a great rest of your day. Congratulations. And we'll talk to you soon, Teva. Have a great one. Goodbye. Let me tell you about Railway. Railway is the all-in-one intelligent cloud provider. Use your favorite agent to deploy web app servers, databases, and more, while Railway automatically He takes care of scaling, monitoring, and security. And while we bring in Sean Frank, I'm also going to tell you about Cisco.

1:54:02Critical infrastructure for the AI era. Unlock seamless real-time experience is a new value with Cisco. Sean, how are you doing? Welcome to the show. Great to see you guys. First time in the actual studio, right? Second. I did the Shopify episode. Oh, that's right. That's right. He took the time out of his Black Friday. That was great. Yeah. But, yeah, we bounced around a lot. It was a big day. That was a good one, though. Hopefully we'll do it again. Yeah. Yeah, and Black Friday was a record for you, right? Of course. Yeah, yeah. Have you had a Black Friday that wasn't a record? No, every year it's gone up.

1:54:33Every year.

1:54:34Sean Frank:And it's not going to stop this year. Up only over here at the Ridge Wallet. Ridge, broadly, right? The portfolio is growing still? Yeah, the wallet business is, it's a great business. It's like 100 million plus a year. But the growth is now like all the other stuff we do. So we have like a travel line. We have - Luggage. We do like 10 % of all men's wedding rings in America. So we have like a huge double digits at the TAM. Yeah. It's like a very boring monopoly. We sell a ton of like men's wedding rings. And they're coming for it all. Oh yeah. Soon. You won't be able to get married. They're actually going for regulatory capture.

1:55:08You won't be able to get married if you're not planning to use a Ridge ring.

1:55:11Sean Frank:Yeah. I'm like a big pro natalist now. Cause I'm like, get married. Oh, okay. So you're behind all of that. Every time I see some podcaster about the, the fertility crisis, it's you. Yeah. You're behind at funding it all. And the big thing now is like the tech business for us. So like we do like phone cases and that type of stuff. It's like 12 months old and it's like already like$100 million a year. Wow. So just adding a bunch of new random little widgets to sell. That's insane. Okay, so take me through the demand generation side of the business. Like what is actually changing? Obviously, there's AI-generated advertising, AI-enhanced targeting.

1:55:48There's all sorts of different stuff. But like from your day to day, from the platforms you're advertising on, like what has been the most material change over the last 12 months? Well, it's a big day to be here, right?

1:56:00Sean Frank:Because the big meta announcements. People were like dancing on Meta's grave like three days ago. And now everyone's stoked on it. And now you have a 1 % God candle. Yeah, totally. Is that specifically about the LLM or the image generation model? because the image generation model seems much more impactful to the advertising business than the Agenda coding capabilities. Well – Yeah. Well, I would say the Manus actually really helped unlock a lot of stuff inside the ad account. Using the ad manager more. Yeah. I think it just democratized a lot of tools that the best ad managers were already using.

1:56:39Sean Frank:But really, we just want Meta to continue to get better. Over the past three months, they've rolled out a lot of changes of the actual ad algorithm. And it was really bad for a lot of people. We just had the best Q2 all the time. It was good for you. Oh, it was awesome. Interesting. I think they're getting way... So do you think that it was actually bad for some people or they were just going through a slump in their business overall? They had business problems that they wanted to blame on the ad changes. Well, dude, yeah. I mean, what's new, right? If your business is going bad, it's everyone else's fault.

1:57:12Sean Frank:But really, they do the Meta Performance Summit every May. And they've just rolled out so many great changes to the ad algorithm that I think you're getting better impressions with better people. and the more compute and AI they throw out, I think it's just going to get better and better. And we're getting to do it like a future where the perfect impression at the perfect time with the perfect ad that's customized to that person with AI, that's coming. And click-through rates will go up, conversion rates will go up, and CPMs will go up with it. But I think there'll be a moment of arbitrage there.

1:57:42Do you think Zuck is doing enough to actually message that to customers like you? Because Ben Thompson put out this piece on Monday sort of an earnings call transcript that he wrote in the voice of Mark Zuckerberg. And his pitch was to investors, telling the investors, hey, look, we are investing a lot in AI, but it's all in service of the ads business, which is great, which we do take seriously. We have taken some side quests, done some metaverse, some VR stuff. But this investment that we're making right now, you shouldn't beat us up in the public markets because it's going to come back huge.

1:58:17We're growing really fast on the ad side. 33 % is massive at that scale. And it's going to continue to double down. But I'm wondering if advertisers are receiving that signal from Meta that it is going to get better. It is someplace that they should be spending more time and more dollars.

1:58:34Sean Frank:Yeah, we're a captive audience. So I don't think he has to message the rest of the lives. He doesn't. He can just ignore you. Yeah, like the best thing he could do is get people to spend more time on their app, right? And then better understand who those people are and what they're in market for. And if he delivers those things, the ad dollars will come. Because besides that, like where else are we going to spend money? Like TikTok shop is actually doing great, but it's still a really small business, right? Like the GMV this year in America might be$20 billion. Really? And Amazon does that like every four days or something.

1:58:59Sean Frank:So it's like it's still a very, very small business. Why is TikTok shop so small? Is it a separate panel or something? I feel like TikTok still has so many impressions, so many videos that are being served. Do you have an idea of why that business is small? I think it's not necessarily – I think it's primarily that content platforms have been a place you discover products but not where you transact like meta has done a lot of had a lot of efforts in shopping in app they never you would have thought that they would have clicked harder right it's like you have this captive audience that uses your product for an hour a day to discover things to buy and they're not buying that many products in the app yeah yeah and tiktok shop is delivering way more value than 20 billion in gmv um like a brand is like comfort hoodies.

1:59:47Sean Frank:I'm sure you guys have seen them. They're doing a billion a year right now. They're four years old. Last time you told me about them, I think it was like 400 or something. They've more than doubled. Yeah. It's crazy. And all it is, is like TikTok shop affiliates. So people posting thousands of videos a day. They take those, the best videos of it. They put it into TikTok shop, GMV max. They run that and their TikTok shop business might do, might do a hundred million a year, but the spillover is crazy. Everyone goes to Amazon. Everyone goes to your website. So like they've just done a horrible job actually capturing the value they're generating.

2:00:19Interesting. But they're getting a lot of impressions. They're driving a lot of purchases. What's the sweet spot for a price point on TikTok shop, that hoodie company? Is that a $70 hoodie?

2:00:28Sean Frank:It's cheaper, right? So like a successful product in TikTok shop is female focused, impulse buy. So like, you know,$20,$30,$40, something like that. And then you have people to make outrageous claims, right? And so comfort hoodies is like, it's a hoodie that cures anxiety. So that's pretty good. It's a pretty good value prop. That's a medical claim. The FDA might wake up to that one at some point. All the affiliates are making it, so who cares? Somebody should care, but we'll see. Yeah, a little bit of a gray area. Interesting. I want to know about when you're using AI personally in-house or someone on your team is using AI, like the models or the products, like ChatGPT, Claude, et cetera, versus you feel like you're getting AI for free because you're using MailChimp and MailChimp integrated AI, or you're on Shopify and Shopify gave you an AI feature for free.

2:01:25Sean Frank:Yeah. I don't want to talk too bad about any sponsors. I don't know if Notion sponsors you guys. They don't. Okay, great. You would actually hope that more of these companies would be rolling out AI faster and better and more useful because like you know we're using it internally a ton directly with the models and like inventory planning and buying is a solved problem okay that's like the biggest problem that is plagued yeah like uh like demand forecasting yeah like all that is like and sending up is sending a proposal to a supplier or or in your case like the actual factory to uh to understand how many you're going to sell by month when they need to be delivered what with the shipping timelines all of that's just a bunch of excel work normally yeah and it was huge teams and if you got it wrong, it bankrupts your company, right?

2:02:06Sean Frank:Like you had bad inventory or you get like shorts in December, right? Like it ruined a bunch of businesses. AI has totally solved that. Working directly with codexes of the world, right? And just putting in all of your business information. That's such a huge unlock for the global economy. That's crazy to think about. We got to tell consumers that don't like AI, your favorite brands are doing perfect forecasting. And that means that you are going to get the perfect article of clothing right before your trip to Hawaii, even though you waited until three days before to order it. You'll always have the right sizes in stock.

2:02:41Sean Frank:That is coming because of Codex. That's crazy. This is like part of what the Sufenator was talking about, right? Like one of the Eric Sufert mobile death memo. He was just talking about like, actually if you have like better advertising because of AI, it will create a like, Like, it will drive economic growth purely because you have more and more of these, like, niche businesses that might have an audience of 50 ,000 people in the whole world. And historically, you couldn't build that business because it would have been impossible to find that 50 ,000 people out of billions. Now you can. And then this is, again, an accelerant of, like, so much revenue is lost every day.

2:03:21so much purchasing activity doesn't happen because people just can't buy the stuff that they want because the brand didn't properly forecast. Uh, and, and it's still kind of doing like fly by wire.

2:03:33Sean Frank:Totally. The wrong sizes, the wrong things at the wrong time, like with how expensive it is to get stuff on a shipping containers and how long it takes. Um, and there was a lot of companies spent a lot of money trying to solve this. There was demand software that did billions a year in revenue. Um, as long as you have like a system of records, so like a clean data warehouse and you have your all of your sales from shopify amazon whatever else you port all of that into a codex and it will it totally has it figured out and if you have to make those small tweaks like oh actually last year we were on a promo this year we're not going to oh so the multi-platform thing is big here because i would have i was just about to ask you like should shopify roll out a demand planning tool for shopify merchants but they probably amazon has sharp elbows and won't give them all the data just via a simple integration yeah it all has to roll up into the harness.

2:04:20Sean Frank:It all has to go into Kodak. And so you have to get into a data warehouse and then you have to point an element at that. Yeah. So like, you know, we're not like, um, we're not like a large buyer of software. Like, you know, we, we have Shopify, we have a data warehouse, whatever else. But as long as you have those like basic things and you put it into a harness, it's like, but your it spends like, yeah, probably like less than 1 % of revenue. Totally. Yeah, exactly. Which is, which is the good benchmark. You don't want to be like building every system custom from scratch. Yeah, and people are so excited because they can vibe code everything, right?

2:04:51Sean Frank:But like, you know, judge me reviews is like$5 a month. So I'm not going to vibe code my own reviews thing, right? I'm just going to do this. Yeah, just pay that. But yeah. There's some review plugins that are very expensive. Yeah, Bizarre Voice, horrible. Like, yeah, Yapo has a bad reputation. Yeah, yeah. I've gotten fleeced a couple times. What's new in manufacturing land? Oh. you know you guys were trying to develop u.s manufacturing like way before like american dynamism was like a category like this is something that you guys have been like exploring and dabbling with for a long time but what's what's the latest yeah so like we actually worked with the government in like 2022 to get something called like a general exclusion order so like we We can very easily now get people to get banned from importing if they value that RIP.

2:05:43Sean Frank:But to do that, you have to prove that you're an important part of the American economy. So to do that, we actually bought the largest independent watchmaker in America. It's called FTS, 5-TIME Solutions. They're in Arizona. So we own them. So if you ever buy an American-made watch, I probably made it. No way. But it's a really hard business. That's crazy. Watches suck. So we do wallet production there. We probably spent two or three or four million dollars getting that whole thing set up to actually produce wallets there. But then the Trump tariffs made it really hard to get steel because there's a huge global tariff on all non-American steel.

2:06:20Sean Frank:That means everybody wants American steel, so now it's really hard to get it. We have to wait for those things to work themselves out. Look, most manufacturing is already very automated. You guys have spent time in China. I'm going back to the next month. It's like they don't have that many people in factories. It is robots and assembly and that can be done basically anywhere. And then it's just getting the raw goods to wherever you actually want to manufacture stuff. And with steel and batteries, we can't do that in America yet. So we have to build a supply chain. It'll be like a 10 year thing, but the future is going to be hyper-local manufacturing for sure.

2:06:54I like the idea of you getting into steel manufacturing. That'd be electric and just make your own steel fully vertically integrate. Is now the best time in history to start a consumer brand?

2:07:06Sean Frank:Well, I would say probably like January 2012 when Facebook ads just sold out. That was probably the best time. But now is the second best? For sure. I mean, one, it's moted from AI. Like I would hate to be trying to sell software right now. Right. And a lot of services, I'd hate to be in that business. People are going to buy stuff forever. Right. You have birthdays, you have Christmas. The American consumer is still incredibly strong. We really just had the best Q2 of all time. And that's with a war in Iran. And inflation and all sorts of stuff. Yeah. And it all actually like looking at - Consumer confidence is so low, even though consumer spending is holding, there's always nervousness about will there be a pullback.

2:07:48Sean Frank:Yeah, there's been nervousness for like six years. But I'm telling you, the Ukraine war in 2022, there was a noticeable decrease in e-commerce activity. And right now it's not happening. Things are actually ripping. So I think it's a great time. Total vibe session. Yeah. Total disconnect between what people say in the Pew Research and then what people actually do. If I had my Shopify notifications on, I would just be chiming all day right now. I think people are, yeah, it's definitely a vibe session. So it's a great time to be selling stuff. That's great. What are you thinking on the creative side?

2:08:18Are you Higgs field maxing with like all these workflows to generate endless AI videos? Are you seeing progress in AI images? What's working? We just talked to the Sufenator about this study that showed that when AI is clockable, it underperforms. But when it's not identifiable as AI, if it's just a product image and it just looks indistinguishable from CGI or a photo, it overperforms sometimes.

2:08:46Sean Frank:Oh, dude, pull up my Facebook ads library and it is tons and tons of AI-generated static ads. Okay. Right? Static. Yeah, because the statics are actually like, you can build ad factories, totally automated. So you take a Hicks field, you use an MCP, you bring it into your harness of choice, like a codex, and you can generate 10 ,000 static ads if you wanted to. And we just have that running 24-7. They get pumped into a Facebook ads library to test it, and then the winners go to a different ads library, a different ad account to actually scale those up. So the static stuff is totally solved, and I would hate to be trying to do ads without it right now.

2:09:22Sean Frank:I actually built a spreadsheet yesterday or a presentation slide by hand, and I felt like I was a caveman. That's what we're working with the ads of the past were like. Video, we still do a lot of it. It's mostly just cut scenes and a hypercut. So we want to have motion or somebody talking or whatever. We'll do a lot of that. But it went viral yesterday, the Seinfeld fully AI episode. That is really, really good. It's getting very close to actually being indistinguishable. I thought it looked really good. I thought the editing pacing was wildly off. Yeah, I agree completely. I thought there was like the gaps in the humor, like the pacing is so key to that.

2:09:58It was like, but from a fidelity perspective, it looked indistinguishable from the show.

2:10:03Sean Frank:Yeah, so it's like, it's very inhuman in the way they talk or whatever, but like that's going to be fixed. Like that's coming in two more model updates, I'm sure. And then it's like, yeah, all video will be. What about using AI either to write deterministic scripts that can assemble hypercuts in different, Because if you have a picture of the wallet, a picture of a person putting it in their pocket, a person stepping out of a car, a person on a beach, you might want to sequence those 1-2-3-4, 2-1-3-4, 3-2-1-4, and get every possible variation on those different video clips. Are you using AI? Do you already have a system for that?

2:10:41Is that already automated? What's the future of that?

2:10:44Sean Frank:Yeah, that's still very human in the loop. Interesting. So we have like, you know, two amazing editors who would do all the hypercutting themselves. And now they are using Hicksfield and just getting hundreds of more variations going through those in the upcoming rooms. Got it. Got it. And they can probably even do some like style transfer and filtering on top of the raw footage that they have to like. Yeah. And sometimes like, you know, it's a robot. It'll make stupid decisions. It's like it'll it'll go like, you know, wallet something, you know, falling in the ocean. It's like, what the hell are we doing?

2:11:09Sean Frank:Yeah. It's just complete hallucination. 5.6 people are reporting that it's working on video editing workflows now in a way that a lot of other models haven't. Yeah. I wonder how that will actually play out because there's one world where you're just literally opening Premiere Pro and saying, like, move the mouse cursor and make the cut in the footage. And then there's another one where you're, like, editing the underlying file and then you're watching it in Premiere Pro because most of these video apps, they sort of represent the file as, like, a structure of folders. or a bunch of JSON or something.

2:11:43So you can manipulate things multiple ways. But it will be interesting to see where that goes, even if it's just for the reconfiguring sequences and whatnot. Are there any vibe-coded e-commerce plugins or add-ons or tools or software that have stuck out to you as, wow, this thing, it was in the$1 ,000 a month category. Now it's in the$5 a month category or, or this is a new capability that's unlocked. That's still something you wouldn't roll your own, but you would buy outside.

2:12:20Sean Frank:Uh, you know, not really, but like a lot of the playbooks that people share, it's like, you know, how to build landing pages in one prompt or whatever. Sure. And like, that is going, that's like going to one-shot companies like Shogun or like, there's all these like landing page builders and it's like, they're just, you know, drag and drop tools, but you're getting way faster, way more responsive, way better stuff just out of codex. And it's like, it's completely on brand with your assets. And it's like, look, that is vibe coded, right? And we're going to launch 50 landing pages next week. And it's all vibe coded stuff like that.

2:12:48What's the value of landing pages these days? Is that critical to the funnel? Is that critical to the... Oh, for sure. Yeah.

2:12:54Sean Frank:Dude, you guys had Hermosi in here like two days ago. I listened to Finn. He's got 1 billion. Now he's going to get a landing page for every human on earth. That's actually where we're going. Yeah, basically, right? Census records. But it's like, you need the offer to get the click. And then you need the landing page to inform them. And then as fast as you can get them to making the purchases possible. In sales, they tell you to use the person's name a lot. I'm really happy that you're here, Sean, because I want to talk to you about this. Do you think we get to the point where digital platforms end up in ads and landing pages using the individual's name to an extreme degree?

2:13:34Because you get down to targeting one person. These would block that a long time ago. Yeah, no, but would eventually there's like a – Heck, yeah. There's a flipping point where maybe it just is so effective that it makes sense for Facebook to enable.

2:13:48Sean Frank:Well, all AI cold email right now already puts your name in there. And there's been beta tests rolled out where they're using people's faces in the ads. It's like – Oh, yeah, we saw that on – remember? Yeah. I think they were trying to sell a pair of the metaglasses where it's like showing like you calling your, you know, and they can tell like who your significant other is just based on your activity on Instagram. Yes. Facebook has all that information. It has your face. It has who you're talking to. It has who your wife is. So it's like they look hyper personalization is coming for the entire web.

2:14:22Sean Frank:And you know, if you're going to be shopping, it's going to show you what you're going to look like in the clothes or what your dad's going to like when he gets the wallet. I definitely think that's happening. Yeah. I mean, if the price of a cold call goes to a penny do you think you'll be cold calling people something just came across my desk i got a wedding ring here for you we've talked about it yeah there's a thing called uh like uh ringless voicemails yeah we're like you know they'll just mass drop those off and they put people's names in there it's like hey john we got this thing for you right and it's like you know it's no it's one way but yeah the two ways definitely coming interesting what's happening in luxury LVMH and caring are down like 25 and 20 ish percent.

2:15:02Sean Frank:Well, we talked about the last time I was here. I was like, I'm like, Oh yeah. Gucci's getting crushed. And, and it's like, yeah, it's going to continue to happen. Why is that? You know, it's, I think it's just a generational change is really what it comes down to. Like each one of those brands have good assets, but like Richmont is, is still tearing, right? Hermes is doing great. Coach is on a generational run. The best performing stock of the past two years. I think last year it beat NVIDIA in performance. No way. Coach? Yeah. So it's Public Trade Under Tapestry. You should pull them up. They own Kate Spade too, but Kate Spade's nothing business.

2:15:37Sean Frank:So it's just a generational rotation. Ralph Lauren, also on a tear. You talk about American Dynism, there's American luxury. America wasn't old enough to have luxury brands, but like LVMH bought Tiffany's. And now it's like, look, Ralph Lauren's crushing, Coach is totally crushing. And I think the old stodgy LVMHs of the world, the Gucci's of the world, one, they got overexposed. Like they really rely on the middle class. And if you ever look at like their sales demographics, it is like 80 % of the revenue come from people making under$102 ,000 a year. And it's like, that's just a big disconnect when you're trying to sell whatever.

2:16:10Sean Frank:Right. So there's going to be a shift towards like, you know, true luxury. There's also some concern that like L. Catterton is just personally investing in all the great assets and not bringing them into the portfolio. Like they own Chrome parts and they haven't brought that into LVMH. Oh, interesting. Yeah. Okay. Well, but when you say personally investing, it's L. Catterton is investing. Got it. Okay. And L. Catterton is the investment vehicle. Of LVMH. Yeah. Yeah, that makes sense. And I know that they do a lot of deals in the private equity world, but. Oh yeah. Why doesn't LVMH, like you imagine the RNOs are like, yeah, we want to own the hottest.

2:16:46You would think they would do everything they possibly could to own Chromeheart.

2:16:50Sean Frank:There's a divestment in brands right now. They're actually trying to push stuff out of their portfolio. I think they just liquidated Off-White, right? And Off-White ended up being a Target, Costco brand. Yeah, there's photos of Costco, Off-White, big Paladin delivered. So they're actually doing a divestment right now from brands. And Tapestry just divested from Stuart Weissman. So like they're actually trying to go like bigger down on winners. But yeah, then there's just like a whole, like, you know, Matt Happy's a great brand. It's invested via Al Catterton, not inside of the portfolio. And the whole idea was there was supposed to be a scout fund and then bring it into the main portfolio.

2:17:25Sean Frank:But if you're, there are no family and you own 90 % of Al Catterton and only 45 % of LVMH. It's like, what's the incentive? Interesting. Yeah. Yeah. But you look, I mean, you could like Richmont owns Cartier. Cartier is having a great time. You know, they own Van Cleef. Van Cleef still having a great time. But both of those are way more true luxury brands than an LVMH. Yeah. Have we hit peak Timu and Shein? Oh, yeah, dude. I mean, Trump got rid of Section 321, De Minimis. That totally crushed those brands. It's like, I mean, you know, Timu. Where do you go if you want to shop like a billionaire?

2:18:03There's nowhere else to go.

2:18:06Sean Frank:Fuck, you're right, man. I don't know. Bridge.com. No. Look, I mean, they're still huge. They run a lot of ads and like Tmoo's publicly traded under like PDD or whatever. So they have a huge business in Latin America. They have a huge business in Southeast Asia. But like their whole arbitrage was just flooding into America with low cost goods. Direct from the factory. Yeah. And it just kind of blew up. It's gone. Interesting. Have you been surprised that live shopping has been slow in America? no i was predicting this from china oh if it's big there it's gonna be big here in a year and it feels like it's been very slow but what have you seen on the live shopping yeah look people are very excited about whatnot yeah uh and they are putting up impressive gmv growth but it is very much dependent on like the trading card bubble it's like that's that's what it is yeah right so it's live shopping in america this is what i was saying yesterday it's like it's effectively, I'm not going to call it gambling, but there's some speculation happening.

2:19:11There's a massive, I would say, spec. You would want to figure out what percentage of GMV is driven by speculation. And I would expect that it's significant.

2:19:21Sean Frank:Yeah. People aren't going on there to buy their everyday essentials, right? They're going on there for the excitement. It is an auction. Whereas in China, there's live shopping where you can buy a tomato. and that's just not happening. And women are buying dresses and it's the whole thing. Yeah, of course, the whole person picking up one piece of clothing, putting it down, putting it down, the next one. Like we've seen that video and we have yet to see that in America. Yeah. Why is that? I think, I mean, dude, Americans can't watch anything at the same time, right? Like we are also like consumption-based and like on-demand everything, right?

2:19:53Sean Frank:Everything is catered to us all the time. I just don't think there's any value of it actually being live. We're doing TikTok shop lives and we drive like three to$400 in revenue per hour that we're live. So it's like some people are buying stuff when it's live, but the real value is like getting all that content and just running it whenever you have four hours at night to go log on to something. And I really just think it comes down to there's a lot more people in China and they're spending a lot. The screen time per person is still way higher over there. And just it developed over there. It's more of like a native sport.

2:20:24Yeah. Have you looked into advertising on Netflix?

2:20:28Sean Frank:uh we have looked at it uh the cpms are not very good okay and here's the thing is we buy a lot of tv ads yeah and we buy them like um like directly through the networks so like you know fox will have something like we just got an email for the world cup and it's like you could run a 30 second spot during the world cup the usa game and it was like a 25 cpm right um and netflix they you'll get a lower tier of consumer because it's price gated right it's the lowest tier of consumer gets the ads and they won a$45 CPM. Right. It just, it doesn't make a lot of sense. Yeah. That makes a lot of sense.

2:21:01What about infomercials? Have you ever thought of running one? It's like a full hour, middle of the night type of thing. I've wanted to get, I've wanted to, it feels like a bucket list item on an entrepreneur. Well, you have the studio, bro. Let's shoot one. We should shoot one. I'm down to be. One hour pitching you a three hour live stream. I interest you in hitting the subscribe button, potentially leaving us five stars. I want a hyper-personalized infomercial, though, where somebody's just like falling asleep on their couch. It's 1 a.m. and you're like, hello, Sean. I feel like I've seen some of those YouTube experiments ads where they didn't gate it.

2:21:44And so if you didn't click skip, you'd wind up watching like 12 minutes of an advertisement.

2:21:48Sean Frank:Oh, dude, you know, Ikea did that, but it was like 12 hours. We're going to read every product we have, but please click skip. Fantastic But you've never done an infomercial No, but I met a guy one time who made like His whole business,$80 million a year Was selling hoses on infomercials And he's like, yeah, I have a great hose And I just sell it on infomercials And then he gets it into Home Depot or whatever Look, you can make a lot of money in a lot of different ways But you've got to focus a little bit You've got a good thing got it Right now I'm trying to sell a bunch of random accessories to men And my goal is to get to a billion a year in annual revenue I'm like three or four years away And if I do that, my life's good Fantastic Well, thank you so much for coming on the show.

2:22:26You want to close it out with us? Yes. All right. We got one last advertisement. It's for MongoDB. What's the only thing faster than the AI market? Your business on MongoDB. Don't just build AI. Own the data platform that powers it. Thank you so much for coming on the show. Leave us five stars on Apple Podcasts and Spotify. Sign up for a newsletter, tbpn.com. And we will see you tomorrow at 11 a.m. Sharp. Goodbye.

2:22:54Thank you.