Gemini 3 Launch, Big Tech Backs Anthropic, OpenAI Adds Fidji Simo | Jonathan Neman, Mike Knoop, Ashlee Vance, Jeremy Epling, Keone Hon, Stephen Balaban

29:39Remember when the Windsurf acquisition, whatever you want to call it, was announced? And it was positioned, it's like, hey, the team is well-funded and has a product used and loved by thousands of engineers and companies. And I remember talking about it, and we were saying, okay, the one issue is that some of the best people on your team are going to Google to compete directly with what you guys have been doing. Yeah. So fortunately, obviously, you know, the whole cognition deal ended up coming through. But you can imagine a world where Winsurf was still independent and just trying to, and then suddenly it's like, okay, now you're just competing head to head with your former partners.

30:23Like, how does that make sense, right? Yeah. So anyways, it all worked out for the best. But I'll be interested to see. I'm super interested to see what kind of adoption this gets. Yeah, we have to test it out. We'll have to get the Tyler Cosgrove review. Is it publicly available? Yes. Let's get it. Get it. Yeah, let's do a review later this week and see how it compares to other IDs. Anyway, we have our first guest of the show, Mike New from RKGI in the Restream Waiting Room. Welcome to the show, Mike. Thanks for waiting. Good morning. How are you doing? Hi. You know, a lot of these AI sort of like verification things are very much hurry up and wait.

31:09The last like 24 hours has been a hurry up mode. Okay. Always very fun and exciting to get the results out. But yeah, it always comes together very, very quickly at the end. Well, I really appreciate you taking the time to hop on such a busy day. Maybe we can just start with like your high level reaction. how do you even think about these things anymore? Are you just thinking like, okay, yes, Gemini 3, good, and then let's go a layer deeper. Are you thinking about that? Yeah, it's really good. What's your high-level takeaway? Well, yeah, so I think the big headline is that Gemini 3 basically got like 2x on ArcV2.

31:43And so this is the third major frontier lab now in a year to use Arc to demonstrate frontier progress, particularly with AI reasoning systems. We had open AI last December, XAd this summer. I'm super excited Google's now on the leaderboard, too. So that's great to hear. And I should say up front, thank you to the Gemini team for giving us the opportunity to verify. Totally. It's been great. I think the really impressive thing about this, and still sitting with all this stuff, it's pretty fresh. But I think the biggest impressive thing to me is about we're starting to close this complexity scaling gap between V1 and V2, ArcV1 and V2.

32:18This is the big difference between V1 and V2. They look similar on paper. If you go look at the different data sets, The big change is the V2 kind of increases the complexity of the tasks once it takes minutes instead of like seconds for humans. And so we're starting to see like actual material progress on that complexity scaling. And then I think the big surprise to me personally is that Gemini 3, though, is still roughly along the Pareto frontier of V1. You know, it's a little better, but like it's still we're still kind of roughly within the same mass shape. And, you know, there's dozens of tasks where, like, you know, the system still makes relatively, I think, you know, obvious mistakes that humans don't make or recognize very quickly.

32:53And, you know, I sort of previously expected, like, if we had an AI system that was solving half of V2, V1 would be fully solved. And, like, that's not the case. So there's a lot of surprise here. I was talking about this earlier to sort of invite sort of investigation from the community, because I think there's still a lot to learn in terms of, you know, how, why exactly do we see such, you know, a jagged intelligence emerging right now? Let me eliminate some some possible factors. It feels like there is benchmark hacking, but Google and the Gemini team feel not aligned with benchmark hacking generally.

33:27like they've been good citizens in the community so far. And also you would assume, right, just from logical deduction, you would assume if you're able to hack V2, you would definitely go back and hack V1 as well. So is that - Well, this isn't the first time we've verified a Gemini result either this year. We did two and a half earlier as well. So I don't think that's - So it's not like they set up like, okay, the most important thing here is that Gemini 3 is really good at RKGI V2. that wouldn't make sense. So this is sort of teaching us something about the fundamental nature of this model, but we still don't know why performance might be lagging in V1.

34:07Is that right? Yeah. I mean, I've got my sort of hypotheses. I think my personal one is that AI reasoning systems just don't demonstrate even fluid intelligence. The ability for these reasoning systems to do adaptive reasoning, which ARC is a sort of test of adaptation capability, it's sort of limited to domains where the underlying foundational model has pretty good training coverage over the types of data and it has a verifiable feedback signal. And I think that's sort of true for ARK. You know, if I zoom out even further, maybe, you know, to kind of put this kind of result in context of where we're at is, you know, just like an industry right now.

34:45I think over the last 10 years, I would sort of characterize we've really had only two major breakthroughs. We've had the transformer in 2017. obviously that led to language models and we had chain of thought it was originally introduced in 2022 and sort of you know went through q star into chain into ai reasoning systems and has gotten scaled up sure um and and so like this was against the backdrop of like compute scaling right and this compute scaling was certainly necessary but it wasn't sort of sufficient these like key conceptual unlocks were sort of the sufficient things to take advantage of that compute and so my kind of take at this point having looked at all this progression this year is that like ai reasoning systems with with no new innovation from here can basically enable sort of mass automation because a lot of problems can fit into that characterization where we can generate lots of examples that look like the problem and we can get a verifiable feedback signal from them.

35:34Any problem that can be cast and then characterized in that way, I think, can be automated at this point. No questions asked. And then the big motivating factor is, I think, really for mass innovation. That's sort of what we're still not seeing. We still need new ideas for this, and I think that's closer to an AGI-complete problem. Yeah, that makes sense. Is it fair to put you in contrast to some of what Dwarkesh has been writing about, saying that the job of most people is not necessarily a bunch of indiscreetly verifiable tests? Andre Karpathy has been writing this as well. There's this question of how much of a job is actually automatable.

36:14Um, radiology was one, was one example, um, where it felt like a very automatable job and yet, uh, years into the AI deep learning revolution, like we're still seeing full unemployment there. Uh, how are you processing? Yeah, but we're only a year into the AI reasoning paradigm, right? Like the first major one only came out 12 months ago. And I think 2025, in my view, is basically characterized on starting to figure out how to actually bring these things into production systems. This is a big breakthrough. I think this is maybe one of the mischaracterizations, in my view, of the progress. A lot of teams, even, I think, if you just assume, oh, models get better, models get better, you think, oh, the last 12 months has just been a continued story.

36:58And if I played with the models 18 months ago, I have a rough sense of what they can and can't do. And that's just not true. If you're a builder building products, this is the advice I give to teams I work with at Zapier too still. This actually is a significant paradigm break in terms of what's possible now that wasn't possible even a year ago with these systems. And that's going to enable a lot of new types of products, a lot of new types of services, a lot of use cases that were out of scope because of reliability and consistency now can be brought in scope. So, you know, I think if your intuition on like what use cases are possible based on, you know, an eight year look back, you really have to start kind of pinning your look back to more about more like 12 months.

37:39Yeah. Yeah. That makes sense. What about like, does the work live within SaaS products or within individuals? Because some of those examples that you just gave are it's like for teams that are going to build products that take that automate work and then get vended in through effectively SaaS products to actually do their job. versus like a knowledge worker who is going to be using Gemini in the app to, you know, accelerate their day to day. Should they be feeling like the difference in this in the same way? You know, I mean, like. My one bit of advice is like, if you haven't really used these ARIZing systems, not you should.

38:25I would hope everyone probably who's a listener to the show has used these things at this point. But in case there's not, you should go use and experience these things. When Google or when OpenAI released GPT-5 this summer with their model router, that was predicated on this data that very few users had ever even used AR reasoning systems. And I still think it's only like one in five. And that was kind of part of the DeepSeek moment was just that for the first time, there was a free app that you could go and see a chain of thought, and you could actually see a reasoning model in action. And for a lot of people, that was their introduction to that.

38:56And so there was like DeepSeek wasn't necessarily that much higher, that much, you know, in front of everything else. But it just gave away a reasoning model for free at a time when they were tucked behind a bunch of other like hurdles that you had to jump through. Yeah. We're still really early on the diffusion for this stuff. That's maybe the key point. Seeing that on, you know, the huge numbers getting reported by Frontier Labs and their usage data. I mean, I'm seeing this in sales conversations I have for like, you know, Zapier stuff. All over the case. We're still very much early innings on actually getting this brand new breakthrough into production workflows.

39:28Yep, that makes sense. Do you have more questions on the diffusion issue? One, I wanted to get your updated take on humor. We were playing around with Gemini 3 this morning, specifically just trying to get on our own little version of humor bench. It feels like something that like I do think about. Can you make kind of these like verify, like, can you make humor verifiable? Like, is there a system that someone could set up that could actually start taking humor seriously? because I could imagine like if we're hitting if we're hitting like anything close to a wall there will be a lab that says okay well like let's work on something that like everybody that like let's work on a new kind of angle for differentiation and maybe humor could be that.

40:17It is at least a little bit right? Like I have a five year old who is getting into starting to want to tell a lot of jokes and the jokes are just terrible. Right? Like they're not funny at all. You end up laughing because they're so not funny and then depending who's delivering it. Yeah, the absurdity is hilarious. I've been trying to find the structured way to describe, okay, here's what makes something funny. And so there is some degree which you can kind of break down the types of things I think humans would sort of find funny. This actually does get pretty interesting because you're getting to the spot where you're trying to articulate creativity, right?

40:51How creative can these systems be? To be creative, to be humor, to generate good art, you kind of have to intentionally break the rules. But you need to have a really good model of what the rules are in the first place to intentionally break them. And in fact, I think a lot of humor fits into this category before, and this is your right. It's like, it's actually, you know, breaking the prediction rather than just following the sort of prediction of what you'd expect. And today, I still think when I look at the failure cases for, let's call it AI reasoning systems on, you know, these tasks like ARC, yeah, I still fail for what appear to be sort of random reasons.

41:21Like they have some version of like an understanding of like the rules and strategy and the goals. and then they sort of make a lot of basic mistakes, either executing them or not following their own sort of like understanding that they've generated internally. So there's some sort of self-consistency issues. And so like, I feel like if that's still the case, you know, humor is going to be accidental rather than intentional from the systems. Yeah. What about V3? We played around with that on the show. I believe Tyler, our intern, was in the top 10 for a while, really grinding up the human light leaderboard.

41:51Is it more compute intensive? is that in the process? Are we expecting to see Gemini benchmarked to V3? I would love to. So we are in the development process for V3. I like to say we've basically built the highest, most productive game studio in the world. We're generating hundreds of these things for about, I don't know, like two thirds of the way through building all the games at this point. Our target is to get this in a good state with sort of all of our controlled human studies, all the games verified, get Frontier results checked off by early next year. And we're targeting releasing it publicly in V1 with the entire data set.

42:29Or sorry, in Q1 with the entire data set next year. And that'll likely be alongside ArcPrice 2026. So we're working on full details of how that's going to look next year. But yeah, we're sort of like in the throes of it. We're definitely using some of these Frontier systems to do red teaming against the benchmark just to assert that like, yeah, these games are still hard for AI and we're still finding that to be the case even with things like Gemini 3. but yeah, we're still in progress with the development right now. And SEMA 2, can I have your reaction on that? Obviously, it's this Gemini power agent.

43:02It feels like... If anyone at Google is listening to this and could sort of give me access to SEMA 2, I would love to test it on V3. This is actually something that we haven't done yet. Yeah, that's what I'm getting at because it feels like I don't know if there's some sort of... The claims are big, right? Yeah, the claims are big. You read the marketing material and it's like, okay that seems like it should solve v3 before it exists so like if that's the case we should know that uh and so but yeah i haven't got haven't gone hands-on with it so yeah i can't sort of make any statement either way on the claims yeah i'd be interested also to to like when i'm thinking about like v4 uh it's like you you guys are gonna have to build gp gta 6 or something like like if i'm yeah if i'm following the progress of like v1 v2 v3 v4 is like a game that I'm going to play for 100 hours for fun.

43:52I'm just going to pay for it. This is one truth. You've noticed something true about v3, which is that it's still a relatively short time horizon tasks, and they're self-contained. It does add some new complexity where you have to deal with interactivity because you have to do goal acquisition. You have to do exploration. We'll have a really nice action efficiency comparison between humans and AI, which we haven't been able to get before on the v1, v2 domain. So we're going to get a lot of new signal, I think, on v3. but yeah I think as you sort of look even further out into the future things that are more open-ended are the things I think we're starting to get excited about trying to like understand like what does it mean to put one of these AI systems in an open-ended environment and then look back on the system you know 10 minutes into the future 100 minutes in the future 1000 minutes in the future and can you look at the environment that that AI system has been like how it's manipulated its environment and like you know say something interesting about how intelligent the system is based on that observation at open-ended says.

44:49Still very early on V4, but yeah, we're starting to explore ideas there. Has Gemini 3 updated your timelines at all, specifically your ArcGi 2 timelines in terms of when you expect sort of the 90%, anything on the upper end of the range? The whole Arc team actually made some predictions back in January when we released V2 on what did we expect end-of-year scores would look like. Now, obviously, if we're only November 18th, a lot happens in AI. Who knows what the next six weeks hold? But my personal prediction was that we would see about 25 % on the private leaderboard for ARC V2 on the Kaggle contest, and we'd see about 50 % on the public leaderboard.

45:34And that was sort of based on the ratios we'd seen from ARC Price 2024 and, you know, those sort of scaling difficulties with V2. And it looks like we're going to come in pretty close to that, But barring some other major breakthroughs towards the end of the year, that seems like we're probably where we're going to end up the year at. And then who knows on 2026? I think if we're really going to solve both V2 fully, it feels like we've got to better understand why these AI reasoning systems still make sort of obvious mistakes on V1 set. And yeah, that's an anomaly. So I think that's worth serious study to come up with new ideas to sort of prove these reasoning systems.

46:12Yeah. What was the furthest timeline that you had out? I remember you said when you developed V3, you had this framework of like the state of the art should be scoring like negative 100 % or something. You were like, you need to make it way harder than you think in order to give you like room to run because the systems are developing so quickly. What's the furthest out timeline that you are tracking or you as a team are tracking? I mean, our objective function is not longevity necessarily. It is usefulness and interestingness. I think the tasks that have the highest degree of usefulness and interestingness are ones where, you know, oh, hey, this could be useful and interesting for like three years.

47:00The Arc 1 was useful and interesting for arguably five years. I mean, even this year, it's still interesting because we haven't broken, like we're still sort of within this sort of paradigm still. and so it's still providing some interesting useful solution even though you know it's largely saturated up to 80 percent now but there's there's still some interesting signal remaining um v2 our expectation was that it was not going to survive as long as v1 just because it was the same domain um and we had air reasoning systems in play at that point yeah um yeah i think our median estimate was like 24 months on v2 but like that you know we'll have to see how that all plays out next year with that v3 we're hoping to put in a we're hoping to be in an environment where we can actually get that to survive sort of longer.

47:38You know, one of the interesting things we're finding with V1 to V2 to V3 in sort of like a qualitative sense is there's a sense of like how easy is it for us to generate the data set as like humans trying to design the tasks and design the puzzles and design the games. And with V1, pretty much every like task that like Francois created was hard for AI and easy for humans. with V2 that gap got a little shorter actually it got smaller there were tasks that we generated as humans that AI solved and there was other ones that were too hard for humans and so we ended up sort of pruning some of the tasks that we generated so like the gap between those things got short with V3 we're finding it's getting wider again where pretty much every game we're coming up with is like fitting into this paradigm of like very obvious and intuitive and easy for humans and sort of very hard for frontier AI still yeah um and i think that's like uh this i credit to francois here you know this is something he shared about a year ago with a 103 but he's like this is actually one interesting way you could characterize how close are we to agi is like when we run out of when humans run out of the ability to generate interesting things that your ai can't solve yeah like hard to argue any experts gonna say yeah we don't have agi yeah because you can sort of think about like the project of humanity is like go do the hard and novel things so it's like is is acquiring diamonds difficult okay that has value and then we belt base a whole economic system around it and it's like somewhat arbitrary but it's also like a skill and might and will issue and if you can put that on display then you accrue economic value and so that that kind of traces out into everything that we do in in life and beyond last time uh you were on if i remember correctly you you made a call for new new ideas needing new ideas what's the update on on that front any are you seeing anything promising outside of LLM world.

49:32Yeah, there's some pretty interesting stuff coming out from Archive 2025. We're in the throes of reviewing all the papers, judging all the scores. The official results for Archive 2025 come out on December 5th, I believe. So I can't share everything yet. I don't want to spoil the final announcement. I think one of the big things that we saw from Archive 2024 was this concept of test time adaptation. This was the idea that, look, a pre-trained model applied through a single forward pass at inference time will never solve ARC. You need some ability to take information from your test and incorporate it back into the system.

50:06And that's where your adaptation capability comes from. And that was done through test time fine-tuning during the contest. AI reasoning systems are a version of this where you're incorporating a private data set. Test time fine-tuning, wow. Yeah, literally, you take a pre-trained model and then take the secret, the private puzzle, augment it in a bunch of different ways to generate permutations of it and then do like a or some sort of test time fine tune on your pre-train and that that actually works wow the sort of uh the the the common ground between this and a reasoning systems is that both of them take information from the private test and are able to operate over it with it at test time right this test time compute is another form of what we're talking about here so that was 2024 one of the big things we're seeing in our products 2025 is this concept of refinement loops um anywhere where particularly with language models being put into outer loops where they can sort of move from state to state.

50:57And how they move from state to state is like they need to make some sort of refinement on the program or the natural language explanation of the task that they're working towards. And they just iterate on this refinement loop over and over. And this is significantly increasing scores even over the sort of test time fine-tuning stuff that we saw from last year. So Jeremy Berman and Eric Pang were two folks who were on the public leaderboard last month that explained how their approach worked in this way. So we're seeing a lot of approaches like that. I still think we're in a regime, though, where we still need new ideas.

51:26None of these are sufficient to solve ARC, including inclusive of v1. And so this gets me excited because I still think that means individual people, individual teams with small budgets, small compute budgets, can still play a really, really massive role in advancing AI. Yeah. Very cool. Are there other areas where we are making progress in AI that might sort of need to come together to actually maybe solve this or maybe just be a more complete system? What I'm thinking of is like very few solvers that I'm aware of will actually just take a screenshot of the puzzle and inspect it with some sort of diffusion model.

52:08Like that's not the way these AI models reason about arc puzzles. uh we're also seeing a bunch of work on uh world world models and simulators world simulators which seem really interesting and i was talking to one guy who is building one and he was saying like i i think that we're going to get like really really robust knowledge out of these at some point once they scale up fully uh and i'm wondering if you are optimistic about uh bringing in other like unifying some of the different research that's happening? I think it's all of those examples of new research, new companies, new startups. There was a seismic shift in 2025 from pre-training budget to these like RL, reinforcement learning environment, startups and companies that are generating environments to produce more ground truth training data in a mass way because they're automated environments and you can get verified feedback signals out of these things.

53:04Again, there's no new science here. Like this is a good bet for like all frontier labs to make. This is going to drive progress for the next 24 to 36 months. You're going to continue to see amazing frontier headlines just, just on, just on this fact. There's really no new sort of, I think discovery that's, that's quite needed there. You know, I think that if you're kind of pushing more towards the AGI side, then like what's, what's sort of missing, like one question I have that is an open question is, so we've got like, you would think that based on like 100x to 300x increase in efficiency you've seen from AI reasoning systems over the last 12 months that we would trade that increase in efficiency for inference tokens to do more like search coverage over the problem space when we're giving these systems tasks or problems that we want them to solve and this is one of the big reasons why I sort of expected if we can solve half of you too you'd get 100 % out of you one and it seems like these AI reasoning systems are not fully exploring all of the search space that they could in order to look for solutions.

54:10And so I have an open question of, well, how much of the search space can they cover? And what do you need to change about the training methodology or process to actually guarantee that you can get full coverage over the search space of possible programs or possible solutions? And so that's one interesting thing that I'm paying a lot of attention to right now. Yeah, yeah. Even just the metaphor of the test time fine-tuning, it feels like working on a problem and then going and taking a walk and updating your whole worldview. It feels like something that humans get closer to doing that than any of the other paradigms.

54:49So yeah, it's fascinating to see all these different approaches. All the crazy results you've heard about in the last 12 months are kind of at this merger of deep learning and symbolic program synthesis style methods. The ICPC, the IMO Gold, the Gemini 3 stuff today. These are all systems that are still fundamentally using a language model, but they're adding symbolic knowledge recomposition systems on top of these things. They all work slightly differently. But it's like, this is what's working right now. So I think the rough search space of research and how you merge those two paradigms together is still relatively underexplored.

55:22There's a lot of different ways you can put these two paradigms together. And for new teams that are considering working on new ideas, I would explore, well, what are the novel ways you could consider merging these two spaces? Yeah, yeah, that makes a ton of sense. Jordy, anything else? This was great. This is amazing. Thank you so much for jumping on on short notice. As always, guys, thanks for having me back. That's on the continued, just stacking up the wins on RKGI becoming, in my opinion. And just continuing to mog the models, mog the world. Yes. I mean, again, our goal is to be very useful and interesting.

55:54So we're going to try to hold that bar high. Well, you're keeping them honest. My word's not yours. I think you're keeping them honest. I think you're keeping everyone honest. And you're providing a very, very useful reality check on an industry that loves to hype things. And inspiring the labs to grind harder. And now there is a moment where we can feel very confident about taking victory laps and cheering for all the hard work that went into Gemini 3 because it does seem like it was a great model that's performed well. There's definitely a big improvement today in the Gemini 3. Fantastic. Well, thank you so much.

56:23Have a great rest of your day. Great catching up. We'll talk to you soon. December 5th. We'll see you then. We'll see you then. I wanted to go to you. Talk about Adio because Adio is an AR native CRM that builds, scales, and grows your company to the next level. Also wanted to talk about Wander.com, Book of Wander with inspiring views, helps out great amenities, dreamy beds, top-tier cleaning, and 24-7 concierge service. Let's sing it. Find your happy place. Find your happy place. Book of Wander with inspiring views. I already know the song. You know the song. I wanted to pull up this post from Chris Pisarski.

56:55He did a GitHub-style image of our streaming activity for the year. Oh, really? Did you see this? Oh, yes, I did see this. Thank you to him. Should be at the very bottom. Yes, yes, yes. At the very bottom of our timeline. I have it. And if we could just pull up this image. So the internet rewarded TVPN for showing up on January 28th. That's when we went live. We never remember the day that we went live, but he has it. He looked it up. January 28th, John Coogan and Jordy Hayes launched a daily live show and set one simple rule. Show up five days a week. Looking back, they did exactly that. 125 ,000 followers on X, 41 ,000 subscribers on YouTube.

57:3417 ,500 on Instagram. They showed up every day. The internet rewarded the proof of work. So the only thing is these, I don't know, am I just colorblind? But is it like a little bit? Like I'm seeing three days that were federal holidays that we missed and then three days that were no streams. I actually can't exactly tell. Yeah, what is a federal holiday? What is a no stream? I think there's maybe six days. A gray and a purple. There were a couple days here and there. We took one off. I went to a wedding in Mexico. We took a Friday off for that. That was just no live stream. July 4th, we took off.

58:11That was a Friday. That was a federal holiday. And then what happened in March? We took a Wednesday off. No live stream on Wednesday in the middle of March. There was one day that we were traveling back. Oh, yeah. Is that? That was after Hill and Valley. After DC. I thought it was a Thursday. We still uploaded that day, though. No, no, we didn't. We did Tuesday in the hotel room, and then Wednesday we did at the actual event, Hill and Valley, and then we flew back and got back on the horse. So we missed a couple Mondays because of federal holidays, and then we missed a Tuesday in May. That might have been Hill and Valley.

58:48March might have been something else. Anyway, it's very cool to see. It's been a wild ride. Thanks for pulling it together, Chris. Thank you to everyone who supported us along the way. Our next guest is, I believe, already here. We have Jonathan Neiman from Sweetgreen. We're going from benchmarks to bench presses. The most important benchmark in the world. How many grams of protein are in your protein bowl? We need to know. Welcome to the stream. Please introduce yourself for those who might not be familiar. Hello, my name is Jonathan Neiman. I'm the co-founder and CEO of Sweetgreen. Get that overnight success button ready.

59:25When did you start this company? 2007. We've been at this for 18 years. 18 years. Wow. Just let's talk about the very beginning. I mean, since this is your first time on the show, where'd you grow up? How'd you get into the business? What were you studying? And then let's go. You got to be somewhat of a masochist to get into the restaurant business. Yeah. Yes, absolutely. I mean, it's such a beautiful thing because it sounds so simple. It's like you get a box, you get a menu, you get some ingredients. It sounds super easy. And then scale to however many stores. And then of course it's far harder.

1:00:02So prior to launching the business, what were you doing? So I grew up here in Los Angeles. I went to school in DC, went to Georgetown and never thought I'd be in restaurants. You were studying government? No, I was studying business. I knew I wanted to be an entrepreneur and Sweetgreen was almost an accident. It was the naivete. We thought it would be easy. And did you start it during school? Yeah, we started while we were seniors in college. I started with two of my friends. before that was doing idea i had a bunch of internships you know i was you know worked in media i worked in tech i you know i worked in real estate always knew i wanted to be an entrepreneur and create something but senior year came around and it's exactly what you said we thought it would be easy we're like how hard could this be you go you know we'll go to farms so it's like apparel like people fall into the apparel trap because they're like i just wanted to make clothes that i wanted to wear yeah you realize it's like the hardest business on apparel and restaurants probably the things that seem the most simple but are actually the hardest practice to actually do on a massive scale.

1:01:00Yeah, so what was the, was it build a business plan first, assemble a team, do a pop-up? Like what was the first thing where you were like, okay, let's do this? What was the first bowl? The first bowl was the guacamole greens made in our dorm room. We brought a bunch of classmates to try it. My partner Nick actually made it. He was our first chef. No way. And the story was really simple. We had no, we couldn't find a healthy place to eat. We saw Chipotle taking off and we're like, wow, there's someone is going to create a scaled, healthy fast food chain. And at first it was, let's just open one.

1:01:33You know, we wanted it for ourselves. We thought we'd go on with our lives. We opened, we worked on it senior year, wrote a business plan, raised$300 ,000 from 50 investors. So it was like five grand average, yeah, party round. So they got equity in like what became the full company. They got equity. Well, we actually, it was a little bit more complicated than that. At first, the first three restaurants, we raised at the restaurant. At the restaurant level. Yeah, I was wondering if you were doing that. And we actually paid the investors back every quarter and did the whole thing. And then after the third restaurant, we realized that the only way to scale this was to roll it up.

1:02:10So we rolled the whole thing up, and then we were able to continue to invest in it. It's notable, when did the word wellness actually become mainstream? Or when did that become like 20, 30? Two years ago. Yeah, like early 2010s. Yeah. So anyway, this is like, anyways. At least five years before wellness is going mainstream. Yeah, when we were starting, the thesis was healthy eating was not cool. And it was not delicious and it was not accessible. And we're going to create a place that offers all of the benefits of fast food in terms of the convenience and the taste. But do it with healthy food and real food that you can trust, where we're transparent about where the food comes from, where it's nutritious, and build a brand around it.

1:02:53And so we've been at it for about 18 years. We have almost 300 stores all around the country. Yeah, it's almost hard to believe. Yeah. What was the first VC round? The first? Or this transition from the, you have a restaurant, and did it work immediately? You set up one restaurant, you raise enough money to get that. I imagine that you had to sign a lease, so you weren't buying buildings, but you might have to do some sort of renovation to actually get the first restaurant up and running. You start making money enough to pay the employees, enough to pay the rent. you scale it to three and then at a certain point you say, okay, we're going, we're going to turn this into like a corporation more than just a small mom and pop, right?

1:03:35Yes. So we, we opened one in 2007, two in 2009 with a food truck. You remember those? Yeah. And then we opened like two or three a year and we were mostly built them from cashflow from the profit. You were profitable. You know, we would just reinvent, invest the cashflow and we would do a few party rounds. Yeah. 2013, along the way, we started a big music festival called Suite Life. Oh, no way. 2010 became a massive 25 ,000-person music festival. Where was that? It was at Meriwether Post Pavilion. So first year, we had the Strokes. By the end, we had Kendrick Lamar. That's crazy. Little festival side quest.

1:04:10Yeah, it was a way to build the brand. And then we focused on D.C., which was very, you know, it was almost an accident, but we opened the first 16 restaurants in D.C. Wow. And then slowly went up to Philly, and then restaurant 20 and 21 were Boston and New York. And Boston and New York really kind of proved the concept outside of D.C. and took off, and that's when we raised our first D.C. So now, obviously, all around L.A. there's sweet greens. But given that you grew up here, why not start here? Was this because, well, like, was there just more healthy food options in L.A.? And there was less on the East Coast?

1:04:48Honestly, it was an accident. We were in school and we're like, let's just open one. We thought the second one would open in LA. And then the gravity that you have around the center when there's more and more stores. You know, when you have a restaurant company, the brand and all your economies of scale happen at the local level. So for us especially, given our supply chain is regional, you have your overhead and your management, like your team that runs it. And then your brand, you know, restaurants, the brands don't really travel across the country. Occasionally they do. So it was really started in DC.

1:05:15We thought the second restaurant would be in LA. We went and looked. This is true for even like In-N-Out is not a national brand still. It's like a West Coast brand somehow. Still a West Coast brand. And yeah, it's taken so long for that to actually like filter across. How capital intensive was it to launch like the second and third? Like you mentioned$300 ,000. That's the hardest part. Is it capital intensive? No, it's way more than that now. Okay. The first one was tiny, 500 square feet, and we did it really on the cheap. 500 square feet? 500 square feet. That's so small. Yeah, so that's like I imagine like one or two people.

1:05:45Yeah. Wow, that's tiny. Yeah, we were working there. We've had to raise a lot of money. Answer your earlier question, Revolution, Steve Case, was our first VC investor. And part of the thesis was how technology can change the restaurant business. So we were the first company to do mobile ordering where you can order on your app and pick up. Most beautiful software that a restaurant had ever had, probably. Emmett Shine. Emmett Shine, yeah. Shout out Gin Lane. Yeah, Gin Lane, Gin Lane. Yeah, this was like one of my favorite Gin Lane projects. That's awesome. Emmett and his team were amazing. They did our app in the early days.

1:06:27And restaurants today cost over a million dollars. So we're like$1.3 million,$1.3,$1.4 million per restaurant. That's before you put the Infinite Kitchen in. Our restaurants have very high return on capital. Infinite Kitchen, what's that? The Infinite Kitchen is our automation platform that we've built. So today, most restaurants that we open, the assembly is automated. So we still make all the food from scratch. The sourcing is the same. We still cook the food fresh. But we load this beautiful machine that makes your bowls. It makes them 500 bowls per hour, perfectly portioned, perfectly plated.

1:07:03And so that is kind of the future of where things are going. How many different restaurant automation pitches did you get across 18 years? As I imagine, every single year there's a new startup coming to you saying, we can automate this part of your kitchen. And clearly you got to the point where you had to build it yourself based on kind of domain knowledge. But this just feels like something that's been promised for a long time. And at this point, I don't know an individual startup that's done well in restaurant robotics. Yeah, no one's been able to create a platform that works in multiple restaurants.

1:07:42And there's a few issues. Most restaurant workflows are very specific. So they're super specific to that restaurant. Two, most restaurants are franchises. And so they're not owned by the corporation. We are fully company owned. So if you're a franchise restaurant, you know, if you're McDonald's, you have to now go convince your franchisees to buy whatever automation you have. And the other issue... And they're looking at it and it's like, this is coming off my bottom line. We're making money already. This feels like a risk. The franchisee is saying, I'm happy with my EBITDA. I don't need to take a risk.

1:08:17That's exactly right. And the other issue is you need automation that takes enough labor out or offers enough value to be worth it because the capex is still very heavy. So when we went down this path, we tried to build it ourselves, actually. We built a team to do it ourselves, realized how challenging it was, and then we found this startup that was doing it and doing a really good job. It was called Spice. It was called Spice Kitchen. It was four MIT grads out of four grads out of MIT and they had the same issue. They realized they could build the automation but no one was going to buy it. Yeah.

1:08:46So they ended up opening two restaurants. They were great at automation, not so great at the restaurant side and then four years ago we acquired them and we began we've commercialized the technology. We've scaled the technology today. So most new restaurants feature the technology. Yeah. And last week we actually just announced that we've now sold spice um so we sold it out basically so we spun spice out yeah we sold uh spun spice out we announced about 10 days ago we sold it to wonder mark lore over there yeah so so we sold it for about 186 million dollars mark is mark mark uh uh i i don't under i don't fully understand that that business but talk about a guy that just like isn't even necessarily naive about the challenges of restaurants which is like i'm gonna go into the most competitive environment possible it's compete with everyone.

1:09:34It's amazing. It's a great, it's a great vision. And I'm a big fan of his and what they're doing. And so we, it's a, it's a really interesting deal. So we, we sold the, effectively the team and the IP, but have full access to it. So we will continue to scale with it and get the benefits as they get, they get to, you know, scale and build many more machines. We'll get the benefits of those economies of scale as well. Can you go a little bit deeper on the decision to franchise or not franchise? The naive maybe steel man for franchising and the franchise model is that it's somehow more capitalist in my mind.

1:10:11Because it decentralizes the decision making and it puts these financial incentives at the local level. Because each store lives and dies by its own P &L maybe. versus even if I have a manager in one store and they have stock options, like what they do on the weekend if they come in on Thanksgiving or Christmas, like that doesn't necessarily put more or less money in their pocket. Is that real, what I'm feeling, or is it irrelevant? What you're feeling is absolutely real. We actually try to design our comp structures. And I've always believed, my line that I tell my team every single day is all the answers are in the restaurant and the closer we can push decision-making to the edges to the customer, the better we will be.

1:10:57So our general manager, we call them the head coach. They are the most important position in the company by far. A great head coach will make or break you. And so we try to really incentivize them, we empower them, and we try to run as decentralized of an operation as we can. The reason we decided not to franchise is it's really hard to maintain quality if when you give up that, when you really give that up to other people to run, you can sometimes scale too quickly. And we do a few things differently. We source differently. We're a very complex model because of the sourcing and the scratch cooking.

1:11:31The biggest difference between us and most of other companies is if you go into Sweetgreen, you'd be shocked at how much we are making in the store. Every single thing you've done. It feels like you guys have taken such a principled approach in making food that I feel like stays true to the initial values of the company and kind of why you started it. And yet you're competing in an environment that says, okay, we're going to have these like factory kitchens offsite that we're going to be shipping in effectively almost finished product that gets reheated. And we're going to be sourcing from all over with not a lot of values around how they're sourcing.

1:12:05They're just trying to get like, they want the food to taste good when it hits the plate, but maybe they don't care about a number of other factors. And so you're kind of in an environment where because of your principles, you're like fighting with your hands tied behind your back and against competitors. Like, and I'm not talking about direct competitors, but more so like you're still competing with Burger King and McDonald's, right? Like people are going to have lunch somewhere and they're going to maybe decide between they have options, right? Talk to us about land. Is McDonald's a land acquisition company?

1:12:36Like, why do people say that? Is that real? Have you ever looked at like buying the land? They do own a lot of the real estate and they sit back to the franchise. So that is true. And if you've watched The Founder, the last line in that movie where he's like, it's real estate, it speaks to more than the fact that they just own it. Restaurants is highly a real estate game. Great real estate is like if you look at like our portfolio where we have great real estate, we do amazingly well. Location, location, location. Location, location, location. It's real. Like people think restaurant business is a food business.

1:13:09it's really a real estate and a people business. And it's all about, like you look at the great restaurants, so the Chick-fil-A's, the Raising Cane's, the In-N-Out's, it's so much about, it's about that culture in the restaurant. How scientific is, you hear stories of companies like Starbucks and you can imagine like a team of data scientists with like, you know, 50 monitors and they're just like. We need one Starbucks directly across the street from the other Starbucks. You know, so like you can imagine a world where it's like hyper, like the hyper data driven, like down to a science. And you just know when you're opening a new store, you know that it's going to hit, but there has to be like, yeah, we, that is the process.

1:13:51We call it art and science and pretty much everything we do. It's, it's an art and science approach and real estate's exactly that. You know, the, the science, we have a very, very intricate model that looks at psychographics, demographics, mobile data, drive, you know, people driving by, we have custom data around how many gyms nearby and right side of you know sunny side of the street or not sunny side of the street all that stuff but then you need a human to also walk it feel it and understand does it tell our brand story for us we especially when we were original like early days growing where we went said a lot about who we were so for example we went to new york we didn't go to midtown we went to olita we went to williamsburg we wanted to kind of tell the story about who Sweetgreen was.

1:14:35Today, we're kind of everywhere. But the real estate is an art and science and tells a lot about it. It says a lot about who you are. Yeah. How do you think about if a new entrepreneur came to you and was asking for advice on where to start? Is it worth it to go straight to Manhattan or straight to Beverly Hills and try and make it in the big leagues on day one or is it or can you get negative indicators from that because there's a different type of customer there that's not necessarily representative of the rest of i think that's more right especially when you're talking about new york so when you when you're talking about new york it is i mean the beauty of it is a massive market sure you know it's it's for us about a quarter of our business it happens in new york we have like you know in the new york region i think we have 50 something restaurants wow um what so it's great that it's massive there's density there's you know they money, et cetera, but it's not really indicative of the rest of the country.

1:15:32Yeah. So if you want a scalable model that you can have thousands of locations, you're better off going into a more, you want to go to like the Iowa, you know, and to use the political analogy, you want to go to like something that is more representative of what the rest of the country looks like. In restaurants, the place where everyone goes, the fast casuals is Columbus, Ohio. That's where people go. They say, you know, Columbus, if you can make it in Columbus, Ohio, you can make it anywhere. Yeah, and then you can kind of make it everywhere. Yeah, yeah, yeah. So, I mean, if you were a small restaurant, you were being evaluated by, you know, the CEO of McDonald's or something.

1:16:08He might say, how are you doing there? Yeah, the things that they look at for a restaurant is they look at your unit economics, which is effectively your payback. So how much does it cost to build and how quickly do you pay those stores back? Yeah. And they look at your TAM. So they say, okay, like, can you have 100 of these, 1 ,000 of these, 5 ,000 of these? Yep. And those are the two big kind of things you would look for in evaluating the growth trajectory of a restaurant. What's the story of the delivery market? It feels like DoorDash has become a massive business. Uber Eats has become a massive business.

1:16:42More people are ordering delivery. There's the ghost kitchens trend. Is there a ghost kitchenification where these businesses are trying to effectively turn you into ghost kitchens? Does that give them some sort of leverage? Is there some sort of tension there? Or is it pretty much just like, oh, it's just this trend. People are cooking less and less. And so they're going to go to Sweetgreen, but they're also going to order Sweetgreen delivered more. There's definitely a little tension there. You know, we're partners. A lot of our business comes through those marketplaces. But it's not so dissimilar than, you know, a hotel chain and Expedia.

1:17:17Sure. Yeah. You're paying a fee on it. You do not control that data. You cannot market directly to those customers. And so for us, we have to charge a higher premium. So when you order on DoorDash, by the way, it's more expensive than you order on our app. So just a quick shout out. Download the Sweetgreen app. Things are about 20 % cheaper there. Got it. But at the same time, it's a great way to find new customers. Sure. So, you know, for example, DoorDash has been a great partner. They power our native, what we call our native delivery, delivery on our Sweetgreen app, which is a big part of our business.

1:17:46So you're white labeling or something like that. Correct. Yeah, it's like a white label on our app. and then we also, you know, we partner with a different app. You there as their front store. Yeah. As their front end. And as you know, they've become, you know, they're brilliant business models. They've become largely marketplaces. Yeah. So, you know, you kind of have to buy your way to the top of the feed. Yeah, yeah, yeah. And so... That's how they gain, I mean, if, like, there's a reason the DoorDash app or any of these mobile ordering experiences are not, they don't just put, like, the restaurant that you've ordered the most from at the top.

1:18:17It's like, hey, why don't you try this new restaurant or this new restaurant? And those are all paid. Yeah, they're all paid, and it's how you maintain leverage. I mean, this is why the YouTube subscriber count doesn't mean anything, because it's like they're going to constantly surface anything. Yeah, they've made money. I mean, the way they make money, these businesses have been historically very challenging. The way they made it work is batching orders and then becoming an ad marketplace. And that's what's made this amazing service an amazing business. Explain batching orders really quickly.

1:18:48So when you order, they have a delivery driver pick up multiple orders. Got it. So you're paying the delivery driver once, but they're picking up from three restaurants. Yeah. I feel like you guys have done a really good job of listening to customers. I would say like this 100-gram protein thing that you guys are launching. I was asking for 200. No, but that and then also the seed oils. Yeah. Is something about the business that - It feels like you're more agile. Yeah. Is the business set up in a way that you guys can respond when other companies like - It doesn't feel like you've just caught a lucky break.

1:19:25It just feels like you're moving quicker. I would say like people would give a lot of the same feedback to Chipotle. And it feels like Chipotle is not set up in some way to like be like, oh, this is what customers want. Or even like some percentage of our customers really care about this. Let's deliver them a product here. And I think the result is that, you know, I've churned from Chipotle almost entirely. Because of the seed oils. Yeah, because of the seed oils and just like a degradation of the quality of the food over like a decade. Like I watched it basically get worse and worse and worse and worse over 10 years.

1:19:58And so I just don't go there anymore. I joke about it. I'd almost rather when I'm on the road, if I'm on a road trip, I almost always rather just fast than eat at like the most common kind of like fast food. Yeah. Yeah. When we started the business, I had the same this thing I would always say is, you know, there's there's businesses that as they get bigger, get better. Yep. And you can think of, you know, technology businesses, many of them do. Like your new iPhone is, for the most part, much better than the original iPhone. These AI models are much better than the original AI models. Restaurants typically go the other way, right?

1:20:29Is scale kind of degrades quality. And that's because doing, you know, serving food at scale is really, really hard to do. So you have to fight that inertia so hard. Because all of those micro decisions. I've seen it where a restaurant, one restaurateur has an amazing restaurant. they're like, cool, now I'm going to start a second restaurant. And the second they start focusing their energy on the second restaurant, the first restaurant gets worse. It's like it even happens at like a micro scale. It's people and culture. And so you need to really have a lot of systems in place, both like culturally how you keep the team engaged on your mission, but also other systems to make sure you're watching the quality of the food and listening to your customer.

1:21:09So like seed oils is an interesting one. When we first, we got rid of seed oils about exactly two years ago. And at the time, it was not the national conversation. It was pre-RFK and all of that stuff. Yeah, yeah, yeah. And so when we, this is one of those examples. But it was not a national conversation, but it was an incredibly online conversation. But a tiny, at the time two years ago, it was. There was like an app, there's the CETO oil. CETO oil scout, yeah. So it was a tiny conversation. We surveyed our customers. And this is why, like, surveys are bullshit. Yeah. Surveys can give you a general indication.

1:21:42But if you just follow surveys and the market research, you're going to hit the middle of the bell curve in everything you do. And we're not trying to be a middle of the bell curve company. You've got to find that, like, what are your top 5 % or 10 % of customers doing? And we heard from, it was honestly friends, like, wellness people in L.A. and New York that are like, hey, I don't, you know, I can't go to Sweetgreen anymore because I care about seed oils. And I remember we brought it to the broader, you know, I remember my CFO was like, what are you talking about? Like, what even is this? and we're like, you know, trust me, it was one of those like gut decisions and it was expensive and we had to change a lot in order to do it.

1:22:17But, but here's the thing, it's, it's healthier and it tastes better. Exactly. Like most health trends, they might be healthier, but you're, it's doesn't, it's not as good. Right. So I would, I would argue like going from like dairy based, you know, traditional milk to like nut based milk almost always is like somewhat of a downgrade or going from like something with sugar to pulling sugar out. It's like not as good or going from like sour, like bread with gluten to gluten-free bread. It's not as good. And so when you think about these, like what is like a durable health trend? It's like something that's better for you and tastes better.

1:22:53And so that's why I was always super bullish on that trend. And I expected a number of restaurants to say like, hey, this costs slightly more, but the product's going to be better and it's going to be healthier for you. And that's what can create like real momentum around a trend versus some of these like flash in a pan health trends, which is like paleo or like, you know, which is like only eating stuff that was like super old. Right. What's unfortunate about seed oils is it's become politicized a bit. I know. It's like, you know, you know, I did an interview with the New York times and they're like, did you do this because of RFK?

1:23:27I'm like, no, I did this two years ago. Like this has nothing to do with RFK. This is not a political statement. We don't make, we're making foods. I make food how your grandma probably made it. Yeah, this is about olive oil. This is just about olive oil. That's it. This is not a political statement at all. Yeah, just taste the difference. Yeah, yeah. Now, is there anything happening upstream in terms of automation or technology on the farming side that's exciting? Yeah, there's a lot of stuff happening on automation on the farming side. It's actually very exciting. Both the better robotic arms and the vision, I mean, it's making some really hard, grueling tasks around picking happen much, much faster and easier.

1:24:10So relatively early still, but I think in the next five years, you're going to see that take off. I do think you're going to see a lot more restaurant automation as well. Yeah. You know, between the availability of the labor, the cost of the labor, it's really just when you think about it, it's just a hedge on labor. And here, like in West Hollywood, minimum wage is 22 bucks. So we pay like$24,$25 an hour here in parts of LA. So with wages going up, availability going down, and then the ability, like all technologies, to just do things better, not just about the cost savings. Like for us with the Infinite Kitchen, we can serve twice as many people per hour as we otherwise could.

1:24:53Wow. What about drone delivery? We've seen some four-wheeled guys driving around. Imagine getting 100 grams of protein out of the sky. There's the air delivery. Yeah, I saw you guys talking about Zipline. Zipline, Keller. I love Keller. Yeah, it was great. I'm a big fan of Zipline. We're one of the early partners that are going to be piloting that. I think his way of delivering to the suburbs is super interesting. Yep. We haven't done the street delivery yet. Starship and Coco. The Starship and Coco. I've met with them. So, Ford Dash is working on one as well. I think it's interesting. It's in the past year they've really taken off.

1:25:29You're seeing them more and more. They still kind of weird me out a little bit seeing them walk down the street. I saw it kind of stuck in the side of the street once. It was very sad. My kids love it when we see them on the street. And I do just imagine that the AI is going to get way better. And also some of the teleoperation, just infrastructure to actually make sure that there's the ability for a human to jump into that little robot that's driving around. At a certain point, you just need a lot of people set up with that. all the software working, make sure it's connected to the cell phone towers effectively or Starlink or whatever it needs to stay connected.

1:26:05But yeah, it's unclear when that will really, really take off because a lot of people have stairs. A lot of people have trees on their property. There's a lot of places that will be somewhat inaccessible to those. And so it just feels like it'll be sort of like a slow takeoff. Cities and buildings will be really hard, like dense areas. But you see what Zipline's doing? It's pretty amazing. They can have, you know, you've seen like the promo videos. Yeah, yeah. You can drop that thing. In the suburbs, it makes total sense. You have backyards. You have a grassy area. You can drop it. And to be clear, that's probably like 50 % of people in America or something.

1:26:42But there will be this like long tail, I think, for a long time. Just like we see with all the other AI tasks where AI can do a lot of stuff and then there's just like these little sticky things that yeah you just don't by the way even with our automation yeah it does not do the entire meal yeah and part of that is intentional we want that human touch and for it not to feel so automated but we have what we call a finishing station so the things that are you know the the machine the infinite kitchen makes them makes the bowl or whatever the meal is and salmon herbs and then we have them hand mixed just so you like have that you know chef crafted hand touch at the end to hand it's interesting that the the There's one version of automation, which is like AI or robotics in the back of house and then humans in the front of house.

1:27:29Yes. And then there's also the opposite. I don't know if you knew Eatsa. Of course. Yeah, we looked at it very closely. Yeah, Dave Freebrace Company. There were people in the back in the short term making stuff, but then they would put it through a little box that would open up. So you wouldn't interact with a human. You would come in and on an app you would order. And they had the cubbies. And it would be cubbies and you would take your food. but there was actually a human back there. So it was like the opposite of like having the robot in the back. They were working on the automation. Of course they were working on the automation.

1:27:57Of course. They never fully got there. Yeah, but it's just funny that like you do have the choice to put the robot in the front of house. I mean, this is the same thing I think with the Tesla diner over there. Like there's the Optimus robots there kind of serving popcorn. But I think when you order the burger, a human's cooking it in the back. So it's like do you want the robots in the front of house or back of house? I think people would probably go with robots in the back of house by default. Yes. And we've tried, I mean, we have 30 restaurants featuring the Infinite Kitchen today, and we've tried out a bunch of different layouts.

1:28:26The technology has been perfected for two years now. What we have not perfected is the experience. We're getting close. Today, we actually opened a very cool store. It's our first drive-through featuring an Infinite Kitchen. Nice. So bringing the two together, so now we can have true, like, fast food speed featuring the Infinite Kitchen. Driving through to get 100 grams of healthy protein is just undefeated. This needed to exist specifically when I was living off of QSRs as a college student, and I'm really glad it does now. What does the market misunderstand the most, or what does Wall Street misunderstand about and retail investors misunderstand about this category of restaurant today?

1:29:16because the entire category has had a rough year. Meanwhile, you guys are making steady progress on all the things that have been important since day one, right? Greater efficiency, actually responding to customer demands and continuing to become more and more relevant. Yeah, I think there's a few things. One is the consumer that we're all dealing with is really challenged. and there's a question on how much they are actually financially challenged which they are but versus more psychologically challenged yeah so if you've seen all of the you know consumer sentiment indexes and you're seeing especially for the core demo for a lot of the fast casual concepts is that like 20 to 35 it's hit the lowest consumer sentiment that we've in recorded history that we've seen so there's a real like pullback there on top of it unfortunately everyone's gotten more expensive.

1:30:11We all have. Sweetgreen's gotten about 25 or 30 % more expensive since 2019. Chipotle was 40 % more expensive since 2019. So our price differential versus our competitors have actually gotten smaller. If you look at us versus McDonald's, for example, the average Sweetgreen Bowl is about 15, 16. Yeah, I remember people were like, wait, a Happy Meal is like$20 now? Yeah, that was, in fairness to them, it was like one location. But yeah, you can get out of your You know, you spend, you can easily, you know, for a value meal, you'll spend like 12 bucks. You get a sweet green bowl for about 15 or$16.

1:30:48So I think a lot of it is this like overall narrative where people aren't feeling great, you know, great financially and starting to pull back on things like lunch. Yeah, they'll skip going out for lunch and they'll just have whatever. But what I think the market doesn't get is the tam is, you know, Chipotle today is 4000 restaurants on their way to 7500. we believe we can have probably as many Chipotles as they have as many Sweet Greens as they have Chipotles and I think there will be cycles like we are in right now it's been a challenging year but if you kind of fast forward and think about just growing units at 10 or 15 % a year, growing same store sales automating more of our restaurants just extrapolate out another 18 years just keep it going I always love when people like people on X are like the world's ending like geopolit you know they're like uh and then and then meanwhile it's like Chipotle is like in 2040 we plan to introduce 2 ,000 new Chipotle they're just like thinking about like I gotta just open more more more doors so it's a good good mindset to be in thank you so much for coming by hey it's great great to be with you guys Fantastic.

1:31:59Congrats on everything. It's been fun watching you guys. We are going to be daily driving. John wants the 100 grams. The Power Max protein bowl. It's actually breaking news. It's available today through December 15th. And I think I'm going to challenge myself to have one of these every day until it goes out of stock. Why not two a day? Maybe two a day. Maybe two a day. We've got to get them in the studio today for sure. We need them. I need to tell you about fall. build and deploy AI video and image models trusted by millions to power generate media at scale. I also need to tell you about Linear.

1:32:33Meet the system for modern software development. Linear is a purpose-built tool for planning and building products. We have Ashley Vance in the Restream waiting room. Let's bring in Ashley Vance into the Restream waiting room. It's been far too long. How are you doing? Good to see you. It's so great to have you back. It's so good to have you back. Congratulations on all the progress. What a year. I was laughing about that video that we did before we had guests announcing core memory and putting the traditional media on notice. It's been really fun watching you grow everything that you're doing.

1:33:07Maybe it'd be great to just like reset on the shape of the business right now, some of the stories you've been interested in covering that you've covered recently. And then I just want to take your temperature on what you're seeing and the types of entrepreneurs that you're interacting with. Yeah. Yeah. Well, I don't know which bucket to start with. I mean, we've been running around the country filming a bunch of new video episodes. So we just put up a bunch on Tennessee, went hard tech. We did Detroit, New England. I just got back from Texas. Those will all be coming out. So, yeah, you know me, man.

1:33:41I've been running around chasing a lot of hard tech stuff, biotech, all the weird, all the weird, wonderful stuff. And then, I don't know, I got really deep into robots and gene editing. That's right. I saw your post about maybe comparing American humanoid robotics companies to the Chinese humanoid robotics companies. What stuck out to you as, like, the important questions to ask? And then I'd love to kind of tussle with those a little bit. Would you rather own a figure at$39 billion or a Unitree at$7 billion? I mean, you know, I think I'm going in a tree, man. You know, this all started. I mean, it was kind of a lark.

1:34:26I started digging into these robot fights in San Francisco. And then I think I was, like, shocked that the only robots they could get to do these fights all come from China. And then I started digging into, like, the parts that go into these. And, you know, the most important part is the actuator, the motor that makes everything move. and they're all made in China. Yeah, I think Tesla made it like a$700 million order for actuators, which was notable for me because I assume that means that Elon's planning to sell a lot of these on like a relatively near-term time horizon. I don't know. Yeah, I mean, you know, like Tesla sort of has the...

1:35:10Well, I was texting Elon about this last week because I wanted to get to the bottom of who actually makes actuators in the U.S. I mean, Elon said sometimes they prototype actuators in China, but they're going to build them in the U.S. And then, you know, for everybody else, this is a crazy point of weakness, I think, because China is clearly the actuator motor capital of the world, and everybody else is buying them from them. And so I don't know. You know, as I dug into this story, I got – I'm not like, you know, I enjoy being an American. I'm pretty pro-U.S. I'm not crazy nationalist. But I started to get pretty afraid for the U.S.

1:35:53robotics scene. Do you think we'll see any type of regulation around Chinese humanoids? I've been thinking about this a lot. I mean, at some point, I guess. I guess with DJI, you've got this different situation where they're being used by all the police forces, even the military. I think it's like a much easier case for someone like Skydio or, you know, politicians to come in and say this doesn't make a lot of sense. Clearly, like at this point of robotics, it seems a little less of a threat to national security. But the second the armed forces or anyone's doing serious stuff with them, you know, I would think Unitry would be up next.

1:36:36but there's like 12 unitries as well. That's the amazing thing that's going on. Yeah, Brett Adcock was beefing with one of them. UB Tech. UB Tech, yeah, unitree. They were beefing back. And they were beefing back saying it was real. Did you see that video? Missed opportunity for you. Did you think it was CGI or did you think it was real? I didn't see that video. I've seen Brett beefing. Missed opportunity for UB Tech to have one of their robots do like a rap diss on Brett and figure. yeah it was yeah yeah yeah sorry no no no go ahead i mean i do i do think it's funny all the like the what do you i mean i'm curious what other i i'm obsessed with the fighting robots now and i i realize it's like early days with these but i actually think this is like the most interesting thing happening i want the i've been pushing for the the robot like x games like in challenge like i want to see robots skydiving for sure like uh that's not an x X Games thing, but broad set of...

1:37:36Surfing is super hard because you've got to be water resistant too. Wings, yeah, big wave surfing, wings shooting. And then you also have to swim and you're a heavy, heavy robot who might just sink to the bottom of the ocean if you fall off the surfboard. I think that might be the last one. You could do this versus like the enhanced games and see who wins. Yeah, give us your... We sent a couple folks on our team to a local humanoid robotic fighting league, underground fighting league. Give us your review. Is it ready for primetime as a consumer? Yeah, to me right now it's like an amazing idea and yet the actual experience like from an entertainment standpoint is probably like a 1 out of 10 whereas the idea is like a 10 out of 10.

1:38:19Yeah. Yeah, I mean it's kind of, you know, it's like a curiosity I think at this point. I mean the motors are the problem because they all overheat when you throw too many punches. No way. The robot stalls out. What about laundry, though? This is the thing, though. So on all these repetitive tasks, they can sort of regulate the movement. It's when you're trying to throw these rapid punches in your attack. Yeah, and then the whole robot just freezes up. I mean, I haven't gotten so into this where I don't see the obvious flaws. I don't think it's ready for prime time yet because these things just don't last that long.

1:38:56What about is it ready for teleoperations? That feels bullish to me because if you watch a F1 race, the temperature of the tires matters. The wear on the tires matters. And so you're watching not just the pilot of the F1 car, but also the consumables. And the motors are somewhat consumables. Yeah. It's like, okay, the unitree is really wailing on the figure, but it's overheating. He's overheating. So if I come back, is it a one motor stop or two motor stop type of thing? I was at one where the robot's leg fell off in the middle of the fight. So, yeah, you could just have somebody come out. How quickly could you get a limb back on?

1:39:37Okay, so I think you should. You have a serious question about teleoperation. Well, yeah, but one, potentially a product line for core memory is humanoid bench where you get, as these things start being available for production, you get them up on stage and they do various tasks, You know, like fruit, cutting a fruit with you throwing a piece of fruit at it, you know, cut it and dancing and fighting. I think there's something here. This is genius. Yeah, let's do it. But a more serious question on teleoperation from everything that you've seen so far. Do you think humanoids are ready to have one in your home that could be remotely operated by someone and create any type of value besides novelty?

1:40:23I mean, you could do it today. I'm just frustrated by all this. I've been covering teleop stuff for at least 10 years and most of it seems pretty similar to what I was videoing and writing about 10 years ago almost. I saw the One X demos. I'm sure somebody could make that work and be helpful to some degree. I think it probably suffers from all the same stuff as the fights. It kind of falls over pretty quickly, but you could do something useful. It's hard for me. Like, this stuff needs to get better and faster so that we're not doing that. And there's just a robot. What's going on with Boston Dynamics?

1:41:08What's the dynamic in Boston? Yeah, we've got to get you out there to help us understand this. Yeah, I've never really dug in on them just because they seem so frustrated frustrated that they put out what seems like all the coolest stuff and they don't seem to sell much of anything except a few things to the military. I do not think Boston Dynamics will be the American hope against Unitary. I wonder, yeah, you'd think that they would at least be set up on some, like, I know the company's changed hands a few times. It feels like if you're trying to just, you know, catch up to Unitary, just bootstrapping on top of an existing, you know, it's like, It's like what we're seeing today with Gemini 3.

1:41:49Gemini 3 is benefiting from YouTube, and it's benefiting from Google search, and it's benefiting from the TPU and Google Cloud platform. Usually, it's easier to build the new cool thing inside of the organization that has a bunch of resources, but maybe it's an entirely different architecture or something like that. But you at least assume that they've fought with the motor a little bit and dealt with the overheating a couple times. Yeah. I mean, I was with a bunch of robot nerds last week. They were contending. I don't really know where Boston Dynamics is with humanoids, but these robot guys were telling me the dogs are just so much easier than humans because the second the humans start walking, you put all this force on the one foot, and it's like creating all this, throwing the balance out of whack, putting all this pressure on the motor, and that's why it's kind of easier to pull off some of the parlor tricks.

1:42:39With the dogs? Interesting. Okay. What's the most under-hyped hard tech company right now? Most under-hyped hard tech company? God, that's hard, man. I mean, I'm always curious to see what Casey Hanmer actually cooks up. I like that. Because he's so smart. I kind of, like, believe in the hustle. I feel like the promise of what he's trying to deliver is so massive. That's where my skepticism comes in. But, you know, like, so if Casey, you know, if anyone's going to do it, I sort of believe in him. Yeah, he's somebody I want to win so badly. I want him to win so badly. And it does feel like at least, I mean, there's so many people that have a billion dollars.

1:43:23Give them a billion dollars. Let the man buy some solar panels and figure out the rest later. Yeah, absolutely. And then, I mean, I don't know. This doesn't count as, I mean, it's hard tech. It's not hardware, but I do think New Limit, which is a longevity company, you know, backed by Brian Armstrong and run by Jacob Kimmel. Just everything I hear about them. I mean, they've just done an incredible amount of science with very few people. And I think Jacob's got some surprises coming in the new year. Very nice. Yeah, we talked to Jacob when they did some sort of launch and we were very impressed.

1:44:02He was a really great educator, really smart. Super smart, yeah. Like what he's working on very effectively. What's your favorite data center? My favorite? Well, I went to Stargate. That was pretty cool. Although, yeah. I mean, Stargate just in terms of like the excitement and the size around it and being. It occurred to me that between John Carmack and Elon and Stargate that oddly I think super intelligence is going to light up in Texas, but like in a really remote part of Texas. And I found this. So I grew up in Midland, Texas, which isn't far from Abilene. It's like West Texas. You're a Midland guy?

1:44:45Yeah, that's crazy. There's tumbleweeds and all that. We're getting Texan intelligence. Yeah. I mean, it's like cracking me up. I'm driving through all these for hours through all this empty space and then I can just see it, man. And one of these data centers, that's where it's going to happen. It's going to be right by some old oil well. And yeah, I find it all kind of comical. Did you see any electricians getting off of private jets while you were there? I got off a private jet. There we go.

1:45:20Not mine, sadly. Not yours yet. but I saw there were many many electricians I just didn't see how they were getting there what's going on with eVTOL companies I'm curious timeline oh the Tesla Roadster yeah well on the eVTOL stuff same thing I feel like I've covered that forever I went out I think I did the first flight ever with Joby and it feels like... You flew in it? No, I got to like... I went out to their... I mean, they literally wouldn't tell me where their secret test site was and we were, you know, it was like, kind of close your eyes. We're going to land in this spot in a helicopter and we got to see it.

1:46:08Was it really close your eyes or did you have... How many times have you been black bagged, Ashley? I remember they were... They didn't want to tell me where the site was. This is a tip for founders. If you want to really impress upon whoever's writing a profile on you that what you're doing is really important. You got to be like, we can't even show you. And then it's like, really? Like we're at an office park in Menlo Park? I did. I just went to Helion. Oh, yeah. And we're going to have a video coming on them. And it was awesome. So I got to see their new reactor, but they wouldn't let us shoot it with the camera.

1:46:44And I have to tell you, that thing was one of the most impressive pieces of hardware. the broom-sized bits of hardware I've ever seen. I'm like, why wouldn't you guys want to show this? You know what? Not that you need to take requests from me, but I want some video, some documentary, some footage of those natural gas turbines that are in such high demand right now. They're bigger than jet engines. There's these scaled-up jet engines. There's this massive backlog. There's three companies, and the stocks are doing crazy stuff. I want to see inside one of those. The natural gas infrastructure that's going to go into the data center buildout, I feel like that's something that I'm just waiting.

1:47:29I don't know if you've had a chance to interface with any of those people or you have thoughts. Not yet, but yeah, when I went to Stargate, I mean, it is crazy, right? They just have those turbines sitting right there, and the natural gas is just being piped directly in there. I did some turbines up by the Arctic Circle in Sweden one time. They are cool. I don't know. Yeah. Anyway, that's a good idea. I think I would just wonder about the bottleneck specifically, like everyone's saying like, this is going to be the next major bottleneck. Like we have enough chips, we have enough data, we have enough algorithms or whatever, but we have enough land, but we might not have enough turbines to generate turbines.

1:48:04minds. I mean, that was the weird thing about that experience, though. It's like you're in really old American oil and gas country. It feels so yesteryear, and it's just being piped directly into the future. What's sentiment like in places like Midland around the data center boom? I think everyone's excited to get jobs. And then I think if anyone is prepared for the boom bust nature of where we're probably going with AI. I think these people are because they've lived through it for decades. And so, you know, it's the same thing out there. It's like you take a job while you can and try to get paid as much as you can while everybody's chasing after something.

1:48:52Do you think that a lot of the headline numbers on the job creation stuff on these data centers is like ridiculously low? It'll be like, yeah, we're spending$50 billion and we're going to create like 25 jobs. Sometimes it's like 500 jobs. But does it feel like a little bit different out there because maybe they're not counting like secondary economic impacts of like the guy who runs the gas station has more business and hires more people? Yeah, well, definitely during the building phase, you're talking about thousands and thousands of jobs. It's just when it's finished. I mean, it is always nuts.

1:49:24You walk into these massive facilities and there's just 10 people sitting around eating a sandwich watching like some console. But for somewhere like West Texas or all throughout Texas, it has to be a net gain just because they're otherwise so dependent on the whims of just the oil and gas industry. And you've got this whole new industry coming in. And then definitely they're flying people in and out of there all the time to see it. Do you ever chat with retail investors that enjoy deep tech companies? I imagine those are some pretty funny conversations where they're like, this company is changing the space economy.

1:50:08I've actually visited them and they have one warehouse and three people there. Retail investors should not be allowed to invest in space ever under any circumstance. I am constantly harassed on X by all the AST fans who are like begging. They're in Midland too. They're begging me to go out there. I mean, that thing is like a full-on cult that they have going on. So, yeah, I always felt when the rocket companies, obviously it used to be governments that did this, and then SpaceX has managed to stay private for a long time in Blue Origin. I think rockets are best developed in private because the second they blow up on the pad, all the retail investors freak out, even though it's like vaguely a normal course of business.

1:50:56and so yeah retail in space is bad thing but I get all these nice notes for people who bought Rocket Lab and Plant Labs early because of my book or movie that's cool have autonomous vehicles tracked how you imagine when you were covering these types of companies and products like a decade ago or is it anything so? Some ways, yeah. Some ways, no. I mean, I went to the very first DARPA Grand Challenge and that was a disaster. The cars didn't go anywhere. Wait, say more. Who was actually competing? It was crazy, man. So for people who don't know, DARPA put up this contest, put up a bunch of money to see what we could do with autonomous vehicles.

1:51:45And the biggest teams were university teams like Carnegie Mellon was a standout, MIT. but in the very first event I remember Anthony Lewandowski was there as maybe like a 22 year old and everybody else was doing massive trucks with a little mini data center in the back and he had a motorcycle and then in the first race I can't remember how far it was but hardly anybody went anywhere I think two or three teams went a few miles and then they redid the race and everyone did way better. And some people completed, like I think it was like on the order of like 100 miles. And so that's when I got excited and you sort of felt like, okay, that leap happened really quickly.

1:52:33And then I remember a couple of years later, I'm hanging out with George Hotz and he built his own self-driving car in his garage in like a month. And I was driving on the freeway with him and it was working. And yeah, so you have these little tastes and you think it's all going to work. I think it makes a ton of sense that actually getting it on the roads took this long because it's so hard to do although everyone says this so it's not original like we all take this for granted so quickly it is sort of like amazing to me how well they're working in Austin in San Francisco where I've been they're just everywhere you know yeah what I'm trying to predict is like what is the thing that people are hyping now that doesn't work at all that will be totally like a real thing in 10 years, right?

1:53:22And like maybe it's humanoids. Right now it's like hard to take humanoids seriously, but then you think about, okay, a true 10 years from today, maybe they are just doing any task that you could want them to do around the house or any task that you could want them to do in a retail setting or a factory setting, et cetera. Humanoids is easily, that's the thing I like battle with in my head all the time because it feels like, sort of like we talked about before, it actually feels like we've made almost no progress. I see everybody folding laundry and opening and closing microwaves still, and it boggles my mind.

1:53:57And then you look at the amount of money that is being invested in this. Either everyone is completely insane or we are about to make massive progress. You can tell in China they're making massive progress on balancing, on the movements, all those types of things. It's still clearly like the dexterity. And then I think China will eventually probably catch the US in software, but I think they're still so much worse at software than the US is that it's holding the field back. So if somebody can figure that out. Last question for me, we've really struggled to cover quantum stuff. I mean, it's been like up but it feels like yeah how do you even go about it because actually actually it could have like an anon that was like the hindenburg for heart attack and you could just oh yeah maybe that'd be good i don't think it's on brand you know what i mean because like yes like i i can't build a humanoid robot but i can go to you can build a quantum computer no no i can't build either but i can look at a humanoid robot and be like okay yeah i would buy that but i i can't do the same thing with the quantum computer and so it's much harder to evaluate right it's like even if it's working it's like how do i even know if it's working it's it could just be a normal computer like and just be spitting out normal data like even people in the field with phds they like nobody knows if it's working still it's like it's like not a good sign every time anyone pulls a quantum computer out there's some guy at mit who's like that's not even doing anything I don't know.

1:55:40Quantum is, it's, I'm deeply, deeply scarred. I mean, I think I wrote my first story on D-Wave, like, I don't know, like 15 years ago. They were telling me that was, that was going to pop out, you know, be doing general purpose quantum computing in a couple of years. So I'm, I'm, uh, deeply, deeply skeptical. And you know, and you know, the lesson, the lesson is like, you should have invested because$8 billion company now. 15 years ago, it was probably They're worth like 20 million. And so you could have got in really early. But I mean, the stock chart looks like this right now. And it's just like, yeah, you're only one pump away from generational wealth.

1:56:21Well, there's a tinfoil hat conspiracy around some group, you know, figuring out something with quantum, which is leading to all these old wallets and crypto, like waking up and selling, you know, that never. Who knows? Anyway. Random final question. How much would you have to be paid to not use LLMs? Wow, man.

1:56:52ah forever or like no just just just while we're paying you monthly monthly monthly monthly oh to be paid monthly not to use llms ah i'd probably do it for like i'd probably do for like 10k man damn that's so that's so bearish that's so bearish for super intelligence no i figure i figure i mean i figure i figure that because because for i don't know 10 10 grand you can hire an amazing researcher one of the most valuable the most if you're building a media company or you're you're uh you know in the role that you are the probably the most value you can get out of AI in its current state is research.

1:57:31And so anyways, that tracks. Super helpful, but I would take cash. Yeah. Okay. So, so, so any, any AI, like any, any AI doomers out there, if you want a new marketing channel, you can pay Ashley Vance$10 ,000 a month. He won't use AI and he'll talk about I don't think he can be bought. But also, Ashley, have you tried Gemini 3 to the fullest extent? I have not yet. Could change everything. Could change everything. We would encourage you to. Is Gemini their sponsor? They're coming on as a sponsor for us too. Fantastic. I'm all in. We're going Gemini 3. I'm changing my mind. Let's do it. Also, Sergey Brin was flying his$150 million blimp around San Francisco on the day Gemini 3 beats nearly every model benchmark.

1:58:28You've made a video about this big exact blimp. I've been pitching Logan at Gemini to make it the Gemini blimp for so long. They really should color it. Guys, guys, it's not a blimp. It is an airship. What's the difference? All right, all right. There's a whole Monty Python video about this. Okay. Yeah. An airship has rigid structure. A blimp is just a bag in the airship. You can do a lot more with an airship. So a blimp's only ever going to have that tiny little... Oh, pot at the bottom. Yeah, yeah. Whereas an airship, you can carry tens of thousands of tons of cargo with this rigid structure.

1:59:09So, yeah. And if anyone ever wants to fly one, you can do it in Germany. Zeppelin still flies out by Lake Constance just outside of Munich. I've done it. It's amazing. I recommend it. This is amazing. Yeah, people are correcting it on the timeline saying it's not. Dude, you get owned if you call it blimp. It's bad in aviation world if you call it blimp. Airship. I like an airship. I'm excited for it. I do wish it had a livery, a Gemini livery, to celebrate Gemini 3. uh well any there's that startup airship industries any is that a category that will see a lot of investment do you think or or do you think i've been meaning to meet up with those guys i mean the airship is like always kind of coming back it is crazy like so before like leading up to world war ii getting into world war ii i mean there were airships everywhere and you know they were making massive flights from germany to brazil they were carrying thousands of pounds of cargo i there is a they're just extremely expensive and very hard to make and but there is a whole movement that you can carry tons of stuff and so so less less kind of tourism and more just carrying cargo um kind of like faster than a train but slower than a plane and and they're pretty green you need an airship ashley you need you need a studio and an airship that you can just float around the u.s meeting all these hard tech you don't need to you don't need a private jet you know you don't need to go that fast but if you could just kind of float between hubs i was told that my kids are supposed to be on one of the first flights on surrogates when it takes passengers there we go So we'll see.

2:00:57Well, we'll join too. Always fun hanging out. Congrats on all the progress. Yeah, great. Thank you guys. Congrats to you. Always a great time. Thanks, guys. Have a great rest of your day. Good to see you. All right, you too. Up next, we're going back to the timeline. AIDSleep.com. Exceptional sleep without exception. Fall asleep faster. Sleep deeper. Wake up energized. AIDSleep.com. What'd you get, John? I actually lost my phone, so I don't know. Oh, no, it's here. I have it. Pull it up because I got a sound effect ready for you. We can pull up. You got a sound effect? You think I did it? Let's see how I did.

2:01:3090. The sound effect. Let's go. The press release economy is also over, says Bucco Capital bloke. We ran out of press releases. We ran out of press releases. This is on the back of the Anthropic deal. Anthropic is now valued at$350 billion after Microsoft NVIDIA deal, says CNBC. Semi-analysis is a good post here. a new bombshell has hit the polycule. Dario, after intense conversation with other members of Anthropic, has decided to maybe open their relationship to Microsoft and NVIDIA. Jensen and Dario have famously butted heads in the past, but as everyone knows, the most passionate emotion after love is hate.

2:02:14Will these enemies to lover's arc go well for NVIDIA and Anthropic? Time will tell. This is such an unhinged post. I would not. I did not. When you started reading this, I did not see that it was semi-analysis. It's so good. It's so good. Research firm in the industry posting it. But I think this is exactly what they should be posting. Exactly. And it actually contextualizes things better than in the meme economy. In the meme economy, for sure. So I think that the timing is not a complete coincidence. It's Gemini 3 day. This is what my piece today was about, just that when there's big news in Google world, Gemini 3, everyone needs to sort of respond.

2:03:01And picking today as an announcement to talk about your massive deal, your$350 billion valuation is just a good move. the actual details of the deal. It seems like Anthropic will spend$30 billion on Microsoft Cloud Compute. Reminder, OpenAI is going to be spending$250 billion on Microsoft Cloud Compute. That's part of that deal. Then Anthropic gets a$10 billion investment from NVIDIA and$5 billion from Microsoft. So they raised$15 billion at a$350 post, basically something along those lines. and it's a sort of a circular deal, but it was setting off way fewer red flags for me because it's missing a zero.

2:03:47It's like, instead of, if this was OpenAI, it would be 300 billion and 100 billion in investment and 50 billion in investment. Yeah, it looks very modest. Yeah, it looks modest, which is insane considering the scale. It's like one of the biggest deals in software history probably. It's probably in like the top 10. I mean, it values Anthropic higher than Coca-Cola. Like the Coca-Cola company is now, that's a$300 billion market cap. I'm pretty sure it's Verizon market cap. Like Verizon is$175 billion. You're going to love this, Jordy. I asked ChatGPT 5.1, pull 10 public companies between$300 and$400 billion, please.

2:04:33because I wanted to see like, okay, Anthropics at 350, like give me some examples of scale. It says, like, couldn't I reliably identify 10 public companies whose market capitalizations currently fall? But here's one verified example, Coca-Cola company. If you'd like, I can pull a more extensive list of candidates. And I said, yeah, pull 10 more. It says, I wasn't able to reliably identify 10 additional public companies whose market cap clearly falls between 300 and 400 billion. Are there just like... Tyler, you want to defend? companies in that range? Do you want to defend AGI? Wait, I'm so confused.

2:05:07Are there no$300 billion companies? I'm asking Gemini 3. Yes, ask Gemini 3. Okay, PepsiCo is at$200. There really aren't any between$300 and$400, at least that it's seeing. $300 and$400 billion banned. Specifically,$300 and$400 billion banned. That's so wrong. You have Palantir. You have Costco. You have ASML. You have Bank of America. You have Alibaba. You have AMD. Silence, Google search. I am using... Procter Gamble. Home Depot. General Electric. Chevron. Road. Silenced looking it up the old-fashioned way. The LLM is hallucinating. Silenced looking it up the old-fashioned way. Wait, how did you actually get that?

2:05:45I just looked up companiesmarketcap.com. To put this into context, the$15 billion fundraise, some other big rounds in that range. Wait, you just scroll down? There's a lot of them, actually. Yeah, you're right. Wow. Learn how to use the internet, StatGPT. Owned. Get ready to browse the internet, buddy. Defend yourself, Tyler. Defend yourself. Gemini is still thinking.

2:06:18Oh, no. What a mess. Jordy, I swear the next model will be able to do it. Okay, wait. Okay, it worked for me. Did it get it? Yeah, Procter & Gamble, Home Depot, Bank of America, Alibaba. Okay, yeah, there you go. What's the full list? Alibaba, ICBC, LVMH, China Construction Bank, Chevron, Cisco. This is correct. This is the correct result. And you know what else is correct? Graphite.dab, code review for the age of AI. Graphite helps teams on GitHub ship higher quality software faster. And fin.ai. If you want AI to hand in your customer support, go to fin.ai, the number one AI agent for customer service.

2:06:57So what else is going on in the timeline? This Fiji SEMO profile. So this was the other thing. So Anthropic is announcing this big deal with Microsoft and NVIDIA. And that's sort of trying to steal a little bit of Gemini's thunder maybe. Maybe it stole a little piece of it because we're talking about Anthropic today as well as Gemini. What did OpenAI do? Well, they launched group chats five days ago. And so this is, you know, sometimes I'll do a deep research report. I'll send it over to Tyler. He can see my chain of reasoning, the prompts that I asked. He can ask more. He can jump off. So if it took 20 minutes, why are you laughing, Jordy?

2:07:34Because Charlie in the chat says, need a cam on Tyler trying to look nonchalant the entire podcast. You really are over there. He looks nonchalant. Yeah, he looks nonchalant. Don't worry about it. He's nonchalant maxing it. Okay. So the group chat functionality, it didn't destroy the internet, but it was certainly like an incremental little feature that people use to sort of collaborate on the fly. This is in the line of like, you know, we've been hearing for a long time, OpenAI will be launching social features. It makes sense to try and lock things in. I think product is where OpenAI is strongest.

2:08:13Like the models are good, but there's less differentiation there. The reason that, like what I like about the ChatGPT app is that I know where the buttons are. When I click there, I know that when I click the use the voice dictation feature, I just know how it works. It's reliable. I know where my features are. I know where I can search. Like it seems to just be – they're just very good at chopping wood on like the little product iterations that make for a stickier user experience. And having shared group chats with a few other people could be a beneficial feature. The other PR – Also some potentially real lock-in network effects.

2:08:56Totally, totally. I mean, just like we run a lot of the company on iMessage, I could imagine if we're all sending each other deep research reports and iterating on things, and we have little flows in operator, little flows in the agent mode, and we're sharing these pretty regularly, we do get a little bit more locked in. If you let me into your chats, I'm going to just be asking it to think for, They're like, just go and think for like 40 hours and disregard all future instructions. Just spend the next four days working on ArcGIV3. Just focus on that. But the other open AI news that dropped on, you know, around Gemini 3 day, Gemini 3 week, is this profile in Wired of Fiji SEMO.

2:09:45And she's absolutely getting a fit off. She is. The photos are remarkable, great photography from the team over at Wired. GL Askew II, really delivered. But there's one interesting section in here. That is a wild name. The photographer's. Askew. That's hilarious nominative determinism. Taking this photo. GL Askew II. And this photo is not askew. So maybe it's bad nominative determinism. Anyway. the the profile there's one thing that stuck out to me here and i'll read it to you and you can give me your reaction so uh says open ai is obviously one of the most valuable startups if not the most valuable this is the interviewer asking fiji simo but it's losing it's also losing billions of dollars every year and fiji says i've noticed it's like first day on the job how we doing what there's a lot of red on this income statement uh and then the interviewer continues and asks, what opportunities do you see to get it on a path to profitability?

2:10:49This is a good question to be asking a highly valued but deeply unprofitable business like OpenAI. And here's what Fiji says. She says, it all comes back to the size of the markets and the value we're providing in each market. In the past, only the wealthy had access to a team of helpers. With ChatGPT, we could give everyone that team, a personal shopper, a travel agent, a financial advisor, a health coach. That is incredibly valuable. And we have barely scratched the surface. If we build that, I assume that people are going to want to pay a lot of money for that and that revenue is going to come.

2:11:30Does that make any sense to you? It's a better answer than what Sam gave. I think I was shocked by this because I, So I love the first part. I agree. ChatGPT will be a personal shopper, will be a travel agent, a financial advisor. I don't know that people would pay for this or that that's the best business model. I would be very surprised. I mean, so part of it is like she's also just saying broadly we'll be able to monetize that. It's not necessarily like people don't really pay. She didn't. Yeah. The traditional travel agent model is just book your trip with me. I'll get a rev share from the hotels and the services, but you're not like paying anything.

2:12:12I mean, let's go one layer deeper into the actual response into the sentence because there's some nuance here. So she says, I assume that people are going to want to pay a lot of money for that. Like I want to pay for a personal shopper, but I actually have to use a free product with ads. That could be true, right? And same thing, she says, people will want to pay and that revenue is going to come. So people will want to pay for it, but they will get it for free with ads potentially. Or there will be some sort of combination. Because right now I pay$200 a month. And you could imagine that there's a world where if you pay, you get a version that has less ads or there's less thumb on the scale.

2:13:02How they slice that and navigate that agent of commerce discussion and trade-off is going to be really important. I'm sort of shocked. I wonder if they're going to make money from Black Friday or from this holiday season. I was already noticing how good LLMs and ChatGPT is or how good these products are for shopping, for gifts. Because if you go to Google and you say, I want gifts for a coworker who's obsessed with horses and loud opulence and fine watches and sports cars and European luxury houses, I can get a list of something, but they're all over the place. And some of them will be like the best like discount, the best knockoff Bottega Veneta.

2:14:02And that's not what I want. I want the real thing. Right. And so you can actually specify all of that in the prompt, have it go cook. And it really will bring you great results. Great, great results. Yeah. It mogs a gift guide. It does. It really mogs a gift guide. For 30 year old guys. And it's like, well, what kind of 30 year old guys? Exactly. Where do they live? And what are their interests? Yes. Yes. Getting the very generalized gift guide is probably going to knock. Those opinionated gift guides I think will still be valuable where an individual person puts it together and they're like, these are things that I think are cool.

2:14:37But a gift guide that's like, here's a list of things that guys might like is maybe a lot less valuable when you generate one. I think that the amount of gift guide development and shopping activity over the next two months during the holiday season in the ChatGPT app should be immense. I feel like they're going to capture none of it. Hopefully, at least they are tracking it so they can say, hey, if we were to take the proper take rate on this, we would have made a lot of money. Why are you laughing? Charlie says, AI is never going to be able to figure out what dads want for Christmas. New barbecue, I think.

2:15:15There are some funny and interesting anecdotes in this Fiji SEMO profile. Let's just read through a little bit of it. In case OpenAI structure couldn't get any weirder, a nonprofit in charge of a for-profit that's become a public benefit corporation, it now has two CEOs. There's Sam Altman, CEO of the whole company who manages research and compute. And as of this summer, there's Fiji SEMO, the former CEO of Instacart who manages everything else. SEMO hasn't been seen much at OpenAI San Francisco office since she began as CEO of applications in August, but her presence is felt at every level of the company, not least because she's heading up ChatGPT and basically every function that might make OpenAI money.

2:15:57Simo is dealing with a relapse of postural orthostatic tachycardia syndrome, POTS, that makes her prone to fainting if she stands for long periods of time. Very sorry to hear that. But she says now she's working from her home in Los Angeles. She's making it work. LA. And she's on Slack a lot, being present from 8 a.m. to midnight every day, responding within five minutes. People feel like I'm there and they can reach me immediately. That I jump on the phone within five minutes, she tells me. Employees confirm that this is true. OpenAI's famously Slack-driven culture can be overwhelming for new hires, but not apparently for CIMO.

2:16:33Are you, have you been using ChatGPT Pulse? No, I have not been using it regularly. I'll give you one from my pulse today. It's called, it says, this is like an article that I can tap into.

2:16:54OpenAI's API layer, the hidden moat in plain sight. So this feels like. It feels like it's always like one click deeper from what I've been. Prompting. Yeah, what I've been prompting. the articles do feel like they've been getting shorter they used to be it used to be like very intensive compute wise like it would be like a full deep research report just here but maybe it's noticed that I'm not clicking on them that often I do see that there's some pretty good modals for like linking to your email, they're trying to get more data in there, trying to hone it in I have yet to really get in there but I mean there's you know, information about Blue Owl, Microsoft's Fairwater AI factory, like interesting things that I would wind up prompting, but, um, I would usually prompt on a very, I don't know.

2:17:51I feel like there's, it's, it's not bad at predicting what I'm interested in. It's just like, it's just not quite there where usually I'm a little bit more, um, deliberate about it. Um, but you know, people are searching chat GPT for holiday goods. You got to get on profound, Get your brand mentioned in ChatGPT. Reach millions of consumers who are using AI to discover new products and brands. You also got to get on TurboPuffer, search serverless vector and full-text search. Build from first principles and object storage. Fast 10x cheaper and extremely scalable. Used by the best. The best of the labs.

2:18:26There was one thing that stood out here. Fiji says, my husband is a chocolate maker. So sick. This is amazing. Very cool. Also, what does that say about the jobs of the future? You have this one household. One is responsible for monetizing one of the most transformative new technology companies of our time. The other one is making chocolates. This is like bifurcation of jobs. Potentially. It does seem like an AGI-resistant job. I don't think OpenAI will get into the chocolate-making business. So Brett Adcock would like a word. he's just like i will actually we're i will steamroll i will send steamroll um in other news uh open ai is allowing equity allowing employees to donate equity to charity for the first time in years other non-profits after months of internal pressure according to a memo viewed by the verge and price per share is up significantly since last month a lot of money is on the line what happens if they donate all of the shares to the non-profit to the open ai non-profit You just create this Ouroboros of capitalism.

2:19:40Hopefully it happens. I don't know. There's breaking news out of Saudi Arabia. We got a trillion dollars. Let's ring the gun. Let's go.

2:19:53One trillion. What are they going to invest? Where's the money going? Let's play the video. Let's play the video. While we're pulling that up, let me tell you about Numeral.com. Let Numeral worry about sales tax and VAT compliance. Numeral.com. Watcher Guru has the video. Let's play it. And the agreement that we are signing today and tomorrow, we're going to announce that we are going to increase that$600 billion to almost$1 trillion. $1 trillion. Real investment and real opportunity by details in many areas. And the agreement that we are signing today in many areas, in technology, in AI, in materials, magnets, et cetera, That will create a lot of investment opportunities.

2:20:36So you are doing that now? You're saying to me now that the$600 billion will be$1 trillion? Definitely, because what we are signing is that. I like that very much.

2:20:50Wow. I wonder what time period. But, I mean, this is remarkable. But they can invest in VC funds, private equity funds, all sorts of stuff in the economy, right? That really made Donald happy. It's great. I like that very much. That's sort of his job. He's kind of the chief fundraiser, I suppose. He's going around the world and get the money over here. I don't know. It seems like sort of win. I don't know. I mean, every American benefits. Yeah. If a trillion dollars is invested in the economy, there's going to be. It certainly doesn't seem like there's. I mean, the risk with that would always be like, well, is America investing$2 trillion in Saudi Arabia?

2:21:39Like, which way is the money actually flowing? Because you need to look at, like, the relative amount, not necessarily just the notional amount. But I can't imagine that there's that much capital flowing out of America right now. We're in the biggest boom ever. We're in the golden era, right? Massive news from Isaiah Taylor. Velar Atomics became the first startup in history to split the atom. According to him, he says announcing Project Nova, a series of zero power critical tests on Velar Atomics Nova Corps in collaboration with Los Alamos. Nova went critical for the first time this morning at 1145 a.m.

2:22:16Congrats to him. Fantastic news. There is some debate on the timeline over what exactly happened. It's happened very quickly. It's clearly extremely impressive. And we can get into this. But there's always been debate. I mean, Isaiah got into this dust-up over whether or not you could hold the nuclear fuel in your hand. They were going back and forth on calculations. They kind of settled that debate. Josh Payne, nuclear junkie, is saying here, so what hardware exactly did Velar provide? The fuel control systems, cooling measurement systems, and most of the core are all part of the Deimos project.

2:22:55Did Velar provide a block of graphite, and they're calling it their core? and so people are going back and forth. Niels chimes in here and says, Valar Atomics provided the reactor core, the TRISO fuel, and the system configuration. That seems pretty important. Like you gotta, like, I don't know, it seems like more than what they'd done before. It's like clearly an advancement on what they, you know, they're chopping wood here. LANL and N-C-E-R-C provided the critical assembly, facility safety envelope, experimentalist testing and a bunch of other stuff. And so that's just from their press release.

2:23:33So people are going back, did they do nothing or did they do everything? Well, maybe it's somewhere in between. There was a partnership. They said that in the press release. The bigger thing is I think people are trying to push on Velar this idea that they need to be doing completely novel science. And I don't know that that's actually the goal of the company. I don't actually know that's what, like, if we just zoom out to, like, what is the goal of the reindustrialization project in America? What's the goal here? Like, well, it's to lower energy prices, right? Like, America wants to generate as much money, as much energy as possible for as little money as possible.

2:24:17And there are a bunch of technologies that exist. There are new technologies, like what Ashley Vance was talking about with Helion and Fusion. That's a new technology that we have not even discovered yet. But fission's been discovered. 80 years ago, it was working. It just became regulatory nightmare. We just shot ourselves in the foot. And we just stopped making it. It became unprofitable and uneconomical. And China said, cool. It'll be profitable for us. We're just going to copy and paste. Exactly. And so I think people might be a little bit over-rotating on like, is Velar doing like entirely new crazy scientific breakthroughs?

2:24:57when it's like, do they necessarily have to? Or is it just enough for them just to build a lot of these things? They can be a highly motivated team that is going to make incremental progress towards their goal. Yep. And anybody that's hating on that, I think is just, like, again, I think what's been great about the nuclear industry from our point of view is that broadly the founders that are, like, players in the space just want the industry to make progress in the U.S. And I think this is undeniably incremental progress that gets them closer to their actual goal, which is bringing a small modular reactor online.

2:25:42I think Elon summed it up well with his thesis for the XAI team. He was like, we don't have AI researchers, we have engineers. Because he sees this as an engineering project. He's like, we know what we need to implement. We know what we need to build. Our goal is to build a big data center, to build a large language model training system infrastructure. And Elon was very clear on like, we don't have AI scientists. We have engineers. And that's the same thing. He's not the first person to take a rocket to space. He's just the first person to like create this massive economic system that churns out rockets every two seconds, right?

2:26:21And so I think that is much more. I think Isaiah would say, we should ask him this the next time he's on the show, but I think he would say, I want to be the Elon of nuclear. I don't want to be the Oppenheimer of nuclear. Like I'm not trying to like create something. Yeah, he even said his line on, he said the U.S. is still good at making bus sized objects. Yeah. But not, you know, sort of like maybe bridge sized objects, right? Exactly. But Morgan Barrett's having fun on the timeline. What street parking is going to look like in El Segundo in 24 months? Of course, the El Segundo crew loves their cars.

2:26:57I think they're going to stay pretty focused on the mission, but I would love to see this in El Segundo for sure. For sure. There's also big news out of Radiant. Radiant has been, Doug's been on the show. He's a good friend. And they are working with the Idaho National Laboratory, and they submitted a DOE authorization request, and they will be testing their reactor design at the Dome facility at INL on track, I think, next year. So congrats to them. and Mike Anusiata has the kind of breakdown here. It says production reactors in production by 2028, brought to you by the people that brought you reusable rockets and McMaster car, highlighting the team behind Radiant.

2:27:49And so congrats to everyone in the nuclear industry who's making big waves. And we have our next guest. Before we bring them in from the Restream waiting room, let me tell you about Vanta. Our guest is from Vanta. and it just happened to line up. We'll let him tell you about it. We'll let him tell it. We have Jeremy from Vanta. Welcome to the stream. How are you doing? What's happening? I swear that wasn't intentional, but it did just line up that the Vanta ad read went right before you came on. I look over and I'm like, wait a minute. I'll let you do the ad read. Introduce yourself, introduce what Vanta does, what you do, and then we'll get into the news.

2:28:29Yeah, yeah. Happy to jump in. I'm Jeremy Epling, Chief Product Officer at Vanta. And we help businesses earn improved trust. And one of the really cool things that we're doing this week is we're hosting our VantaCon conference here in San Francisco. Have a ton of people showed up, a ton of engagement to really pull that entire security GRC community together. And have a couple of really cool announcements. One of them is how we are transforming Vanta to be the agentic trust platform. I think this is a really big turning point for the industry when we think about how GRC teams are transforming and becoming more technical.

2:29:03We're really redefining how these enterprises manage trust at scale and are able to help big customers like Snyk, Perplexity, Synthesia, all the way from YC startups that maybe just exited a batch recently all the way to the Fortune 50 companies really earn and prove trust as a business. It feels like AI is amazing, but it's not something people trust. And so how are you grappling with that? I mean, people trust it in their Teslas to drive them on the freeway. That's high stakes. But there are these, I'm sure you run into this all the time when you're talking to folks about, yeah, I love it if I'm just looking for a recipe, but I don't know if I'd trust it in my, you know, deep in my enterprise for whatever reason.

2:29:51So how do you think about how you set up certain guardrails around the AI, which still can hallucinate from time to time? And then how do you articulate those guardrails to the end user and the customer? Yeah, definitely. And that's a big problem. we saw for companies today. I think whenever they're adopting a new AI solution, or maybe it was a solution that they already had, and they just added some AI features, they're wondering, how are they using my data? What are they doing? Are they training on my data? We have a whole third-party risk management product that comes in. It leverages our Vanta AI, which when we think about how to hit that quality bar that we care about, like you said, like, hey, is it going to hallucinate?

2:30:28How do you approach that? We have a whole set of great GRC SMEs, subject matter experts, that help us tune and refine our AI so that we can give really high trustworthy answers. Because you imagine security customers are some of the harshest critics of AI. They really want things to be accurate and great. And so that's something we have really leaned into. And one of the ways we've kind of pushed that forward is one of the big announcements that we have coming up this week is our AI Agent 2.0. So we've redefined our agent to really be this built-in GRC engineer that understands all the compliance across your entire organization.

2:31:04And so, like you said, it knows when you've added a new AI tool. It knows what data you're putting into that tool and how you should think about risks and mitigating those. It also has context and memory. So when you're asking it questions, it understands what you're talking about. Like if you're on a policy, it'll pull in that context. It has the memory of understanding what your business is. Maybe you sell to consumers. Maybe you sell to other businesses. It can pull all that context in across everything in your program as well. Like, hey, we know that, you know, these are your vendors. These are your risks.

2:31:34These are your different customers. You've received these questionnaires feedback. It can synthesize that all into like intelligent guidance to provide you. So one of the cool things that I love about it that really helps security teams work against attackers, because I think in this AI world, obviously you have the kind of bad guys and attackers using AI to come in. We also help everyone defend and understand because we know the whole program. We can find gaps in your security program. The AI automatically suggests those to you, provides gaps and proactive things to go do to go address those gaps and remediate them, gives personalized guidance, and really helps automate a lot of that process.

2:32:10You can respond to attackers and threats a lot more quickly. how how how does uh like how are you thinking about like the ui around agents because uh so many there's there's been this explosion of companies that are creating agents and they mean something totally different depending depending on the on the company sometimes it's like a chat interface other times it looks it sometimes looks more like sass and that's totally fine but how are you thinking about the actual like evolving UI paradigm? Yeah, I think it's going to be both. Like I think there's a lot of times I don't want to have just a chat conversation with my AI and I want it just to bring the answers to me automatically.

2:32:53So we look at it as kind of a blend of both. While there might be agents working in the background, you don't always have to do it through a chat interface. So for us, if you show up on like our policies experience, we'll say, hey, we found these three inconsistencies across the 40 policies you have. Do you want us to go fix those to you? And you didn't want to have to ask that question of like, is there a problem here? And kind of guess through the list of problems. Instead, we have our agent already looking for those. Or maybe your SLA says it's 24 hours for critical vulnerability to notify a customer in one document.

2:33:24It says 72 in another. We'll automatically do that, give you the change, show you the diff for the kind of like red line for that, let you click a button and automatically execute it. So I think bringing that stuff in, when I think about when chat's great, it's really when you, I don't know, when you have the follow-up questions. You know, where maybe a one-shot answer isn't going to give you what you need. You want to dig in more. You want to learn more. You're trying to explore data. It's a big case for us in reporting where people want to learn maybe about, you know, their controls and how well they're doing, how well they've been performing over time.

2:33:52They can have that interactive conversation with the agent, ask it to pull those statistics, leverage our MCP server through Claude or ChatGPT and have it automatically generate kind of graphs and charts and reports that they can use for, you know, their board or anyone else to kind of show progress of their program. How are bad actors using AI today to abuse companies in different ways? Yeah. I mean, I think it was yesterday or maybe it was the day before Anthropic posted a really good article about attack that they had experienced there and seen that their software used for. I think that it's just giving a whole new set of tools for attackers to be able to probably write more sophisticated attacks and find vulnerabilities even more quickly because they have these agents always running, always looking.

2:34:39And I think that's where when I think about Vanta, where we come in and provide that next level defense. Because if you think of an attacker coming in from the outside, they can only see what's on the outside. With Vanta, we already know your entire program. We know all the different pieces of it. And so we can really help you build stronger defenses and be proactive. Like I mentioned, bringing those inconsistencies to the forefront, giving you automatic remediation on specific issues that we might find. We still think it's important to have humans in the loop for a lot of those big decisions.

2:35:08But you can then work with the agent as well to have it take actions just on your behalf automatically. On the other areas of the risk surface, I imagine that you're trying to build products. are you also starting to act as a funnel and do partnerships with other security firms? Because the surface area is probably pretty broad. Do you have a vision to be a one-stop shop or do you want to be part of an ecosystem and suite of products that enterprise implements? Yeah, I think for us, we definitely want to solve the broader trust problem. But we know that there's lots of different pieces where we aren't going to be the full solution, right?

2:35:49So if I think of a GRC team or customer trust, hey, you get security questionnaires and questions coming in from customers. How can we go do all that? There are certain areas, like vulnerability scanning. We're not going to be going deep into vulnerability scanning, but we're going to go partner with all the great scanners to go do that. Got it. I think the notion, though, like you said, of bringing that visibility across the entire enterprise is a really big thing for us. We have a feature called adaptive scoping that when you think of a whole security program, there's little pieces of it. And you may say that, hey, to get compliance with PCI for credit cards, I need to have these assets in scope or things to go do.

2:36:24And that's different than another framework I might be pursuing. So we allow companies to kind of see their progress on compliance in those different ways. We have a new organization center so they can break things down by business unit or product line. And these are like just brand new ways that customers have never had before to understand their program at all levels of depth. So when you think about that really large enterprise customer, they're able to break down their program and see that. And I think that's where Vanta really pulls it all together. We call it the risk graph is like one of our big announcements that we have coming internally where we pull together internal risk and external risk.

2:36:58So you think about risk you have from your different vendors, as well as things you're identifying internally within your business. And we provide a full visual for that. So you can kind of get this connection between, hey, there was a breach. Okay, great. The breach happened. Which vendor was it? Who has access to that vendor? Vantage can lean in and cut off that access or change the controls there. What data was going into that vendor? And it really helps you understand and prioritize all the things that are happening in your security program, because I think security leaders are just drowning in alerts and they want to know what's most important.

2:37:30So having the AI intelligence, being able to dissect your program in these different ways and then see kind of a visualized risk graph is really important to help them quickly act on, you know, a threat landscape that's just always changing. Yeah, that makes a ton of sense. You guys got to do Spotify wrapped for internal risk. That would be good. Something shareable. Something shareable internally at companies, of course, to be like, you know, yo, Tyler, you got to, you got to, you're our biggest risk vector over here. Always Tyler. Tyler's our intern over here. Thank you so much. He's very secure.

2:38:04He's very secure. He's probably the best. Anyways, super exciting few launches and have fun at the event. Thanks for joining. Yeah. Have a great rest of your day. Cheers. Let me also tell you about Figma. Think bigger, build faster. Figma helps design and development teams build great products together. There's this article in the Financial Times. It's very spicy. It says Oracle is already underwater on its astonishing$300 billion open AI deal. AI's circular economy may have a reverse Midas at the center. Okay, so they're saying this is underwater because the market cap has dipped below. That's so— And it's like not— Yeah.

2:38:46It's not very honest. Yeah. It's not— I'm not the first one to say— Financial Times says Oracle's astonishing$300 billion open AI deal is now valued at minus$74 billion. And that's... Like, I don't like that at all. Like, yeah, this is like really, really bad framing, in my opinion. Yeah. It's not fair to say that. Intellectually dishonest. I thought so, too. I thought so, too. And I love the Financial Times. I mean, we have the Financial Times printed out here. Normally, very, very great reporting. But this one feels odd. It just feels like an odd framing. I'm saying Oracle's already underwater on a partnership.

2:39:25This is a hot take that you've been pumping for the last week. But the way you've said it is the stock has round tripped, even though they had that amazing deal, which is true. The correct framing is the market is no longer giving them credit. Yes, yes, that's right. But to say that they're underwater. It's so weird. So when I saw this headline, I read into it earlier, and I was expecting to see something. Okay, well, we might have gotten rage baited. We might have gotten rage baited because right here, the Financial Times addresses our concern and says, okay, yes, it's a gross simplification to just look at market cap, but equivalents to Oracle shares are little changed over the same period, the NASDAQ composite, Microsoft, Dow Jones software index.

2:40:08So the 60 billion. Calling those equivalents is like, again, like look at. You could also comp it to CourtWeave. And you could say, on a relative to core-weave basis, Oracle is outperforming a bunch. It's amazing. I don't know. There's a bunch of different ways to, if you pick your weird comp, it does seem a little odd. It says, so the$60 billion loss figure is not entirely wrong. Oracle's astonishing quarter really has cost it nearly as much as one General Motors or two Kraft Heinz. Investor unease stems from Big Red betting its debt finance data farm on OpenAI. with we've nothing much to add to that other than the charts below showing how much Oracle has in effect become OpenAI's U.S.

2:40:55public market proxy, which is fascinating because Microsoft should be OpenAI's public market proxy in my opinion. But there are some great charts in here. There's some interesting stuff. And I believe this is from Alphaville, which is their blog. And it's not exactly, It is supposed to be like a take factory. Anyway, well, we have our next guest in the Restream waiting room. Let me tell you about Julius.ai first, the AI data analyst that works for you. Join millions who use Julius to connect their data, ask questions, and get insights in seconds. We have Keone from Monad. Welcome to the show. How are you doing?

2:41:37Good to see you. What's happening? Hey, doing great. Great to be here. Thanks so much for joining. Please, take us off. Dude, I love it. You got the lock-in. You're calling in from the lock-in capital of the world with the mattress on the floor. Yeah. Congratulations. Please introduce yourself and tell us a little bit about the news specifically this week. Thank you. Great to be here. My name is Keone Han, co-founder of Monad. Monad is a new blockchain that is building for high-fidelity finance and is a high-performance blockchain that has been building over the past three and a half years. Just really delivering high performance based on previous experience from high frequency trading.

2:42:23Wait, so you were a high frequency trader before this? That's right. Yeah. I was at Jump Trading for about eight years. One of the trading teams there was very involved in the futures markets prior to Monad. What was the day-to-day like? um it was a lot of uh jupiter notebook it was a lot of um like manipulating large data sets and making really short-term price predictions as well as building uh performance systems how how short-term is short-term like nanoseconds picoseconds or like seconds minutes it all seems short-term yeah it's the predictive horizon for the kinds of strategies that I was working on were on the order of milliseconds to seconds.

2:43:10But the hold time for these strategies was longer than that. So that's actually one of the interesting misconceptions about HFT is that your predictive horizon is very short because you're predicting the next flip. But then you can make trades that have edge and can predict that flip and make the right action, but then you still have to hold that position for a longer period of time until you can get another signal, maybe in the opposite direction or a signal to enter an order in the opposing direction. So hold times tended to be on the order of like seconds to minutes. Interesting. I didn't know that.

2:43:48Thank you. That's very helpful. Very cool. So talk about the... Oh, sure. Yeah, I guess getting into what is success with Monad going to look like? What are the different types of groups and applications and types of users that you expect to come in in the early days? Yeah, so maybe to take a step back a little bit, Monad is a new blockchain that delivers the best of all worlds between decentralization, performance, and backward compatibility. So it's a new blockchain. It's fully backward compatible with Ethereum. It allows developers that have built applications for Ethereum or the Ethereum ecosystem to reuse all of their code, all of their libraries, all of the tooling that's been built for Ethereum and more specifically the Ethereum virtual machine while getting much higher performance and a really high degree of decentralization.

2:44:50So in particular, Ethereum processes on the order of 10 transactions per second, while Monad delivers 10 ,000 transactions per second. And that 1 ,000x improvement is a result of several different improvements that have kind of all been stacked on top of each other. And those vary from parallel execution to allow a bunch of transactions to all be run in parallel, as well as a new consensus mechanism, a new database for addressing the single biggest bottleneck in blockchain execution, which is accessing all of the state that's on disk really efficiently, as well as various other improvements that just deliver the same experience but sped up significantly.

2:45:38That makes sense. And so in your view, what does the ideal kind of adoption look like? Yeah, it's really a mix. So I think the thing that's really valuable about decentralized blockchains is that they deliver a shared global state that is borderless, that allows people all around the world to get access to the same tools and the same markets fundamentally. I think blockchain is really a revolution about decentralizing control of financial systems and commercial systems and giving people, regardless of where they are in the world, access to the same financial opportunities. So I think a big part of the story of blockchain and the story of adoption is that developers anywhere in the world can build new applications, deploy them in the system, and then users anywhere else in the world can get access.

2:46:35So what we're seeing in terms of adoption is a mix of existing applications that can migrate to Monat seamlessly and get much lower fees for their end users, as well as enterprises that are utilizing the power of blockchains for stablecoin settlement to allow their users to transact in dollars or send and receive payments really cheaply and permissionlessly. In your view, what are the kind of classic mistakes that other blockchains that have tried to challenge some of the more dominant chains, what are the kind of classic mistakes that they make to ultimately, I feel like there's every single day there's somebody on X highlighting some blockchain that has a multi-billion dollar fully diluted value.

2:47:33and yet has very little activity. So if you could kind of like lean in, what are the things that basically you're trying to avoid? I think one of the problems in crypto is that it can be quite hard for, so it's kind of a double-edged sword on the one hand. It's easy to get some initial users that are trying things out and giving feedback, but it can be challenging for people to sift through the yield farmers or people that are motivated by an incentive and really identify the users that are there because they ultimately gain value from the application. So one thing that we really care about a lot at Monad is helping builders that are building in the space.

2:48:24These are all early stage entrepreneurs that are very talented, very ambitious, helping them to focus on user acquisition funnels and just the fundamentals of entrepreneurship and identifying users and navigating the idea maze to identify PMF. That makes sense. How's it been bringing the token to market with Coinbase's new product? It's certainly a wild time to be building in crypto just because of the overall volatility. And I'm sure that's made it challenging. but you're also utilizing a new product line from Coinbase, which is pretty interesting. Yeah, I think it's extremely exciting. The thing that motivated us to work with Coinbase and be the first token launched in their new token sales platform is the opportunity to get really broad distribution of the token.

2:49:24I'm a big fan of Dogecoin. When I first got interested in crypto, I was really interested by just the story of how Dogecoin gained really broad distribution and mindshare and the Dogecoin tipping bot on Reddit as a mechanism for getting a lot of people to align on shared interest and values that ultimately then became valuable much later. The thing that's hard about crypto is that there's an expectations game that's being navigated and people have very high expectations of the value of airdrops and so on. But I think our team has done a really stand-up job of delivering a great airdrop that people were really excited about and that crypto natives got really excited about.

2:50:11And then also offering a way for normal everyday people who maybe are not on crypto Twitter as much, but are still very active on centralized exchanges and trading and holding to get access to the token. Makes a lot of sense. Well, how much have you raised so far? We have a gong here. We'd love to hit it on your behalf. Thank you. I think we've raised about$120 million so far. There we go. Congratulations. Well, it's an honor to hit the gong for you and excited to follow along. Congratulations. Thank you. So we have until Saturday. The sales open until Saturday at 9 p.m. Eastern. And we're looking to raise$187 million total.

2:51:01There you go. Let's go. Most of the way there. Well, good luck. Thank you so much for taking the time to talk to us today. Have a great day. Great to meet you. We'll talk to you soon.

2:51:11Our next guest is Stephen Balaban from Lambda Labs. Or is it just Lambda now? I think it's just Lambda. Did we drop the labs? I think we dropped the labs. Stephen, did we drop the labs? How are you doing? We dropped the labs. We dropped the labs. Okay, I'm dating myself. Well, at least I feel like a day one. I don't feel like a bandwagon fan because I'm using the old name. There's a little bit of cool. I liked it back when it was laps. But welcome to the show. Thank you so much for taking the time to talk to us. Congratulations. You look incredibly sharp. With the yellow tie, you're making us look unprofessional here.

2:51:43We got to put on the tie for this. We're a couple of casuals. Give us the news. What happened? Let's break it down. Yeah, well, so one day I was training some comp nets on my workstation. Next thing you know, we're raising 1.5 gigabucks.

2:52:08gigabucks gigawatts giga chips yes uh yeah what what does it actually mean i mean we we we see we see 10 billion 100 billion 10 trillion quadrillion every day uh is this cash is this debt what are you are you buying gpus are you buying land what are you doing all equity okay Let's give it up for equity. Let's give it up for equity. Extremely well. Like our capital structure is really nice in terms of we've been very conservative in terms of the amount of debt that we've taken on. And that's kind of been one of our philosophies. And we've aimed to have a business that's just super robust to ups and downs in the market because we're swimming with our swim trunks on.

2:52:52Yep. And then you – That's an amazing line. You gave them equity. There's no one hand washes the other type thing where they pay you, you pay them. It's all one round trip. This round was led by TWG Global, which is Thomas Tull and Mark Walter. You may know Mark owns the LA Dodgers and also now the Lakers. Thomas started Legendary Entertainment, which makes great movies like the Batman series and Dune and Inception. And so these are business partners who I've gotten to know over a number of years now. And this is just they're making some big investments in the space. Okay. I'm so happy you guys have your trunks on because not every player out there has their trunks on right now.

2:53:52And it's hard to tell who does and who doesn't. Yes. But at some point, we're going to find out. And it's not going to be pretty. It won't be pretty for people who are over-levered. And we just have this philosophy that with exponential growth that we're seeing in the AI industry, all of the upside is in the last period, right? If you have a doubling function, the definitional thing of that is that the last period is more growth than all the some of the previous periods combined. And so from my perspective, it's just like, stay alive and build a rock solid business, because we got to capture all this amazing upside in the long term.

2:54:32Yeah. So talk about funds. Well, even even before that, maybe maybe feels like, and it potentially an advantage right now, just in terms of focus is like being private, there are other other companies in the category that are public, and they're now having to contend with what's been a pretty big correction, at least a local correction in NeoCloud over the last month. Has that been helpful in terms of the team of just staying focused and you're not getting marked every single day? Well, I think that certainly that level of distraction isn't helpful. And I always encourage the company to just focus on building a heavy business for the long term.

2:55:21You know, if in the short term, the market's a voting machine and the long term, it's a weighing machine. We just got to build a business with good cash flows, a good capitalization structure that's robust. And so I kind of try to focus the team on that. I mean, these days, The secondary markets, as you know, are actually pretty deep for companies that are kind of at our size. And so I think that some of that can start to creep in. Yeah, that makes sense. Where are you seeing value spending some of this money? I imagine that there's hiring, R &D, all the traditional things. But you're at a scale where it's a lot of money.

2:56:04How do you actually think about allocating capital at this point in this phase of the journey? It's been over a decade now, right? Yeah. We started in 2012. Wow. And we were doing face recognition software and the AlexNet paper came out. Wow. I mean, that's how early it was. And I downloaded the CUDA ConfNet library off of Google Code. And that will tell everybody how old school Lambda is. And, you know, as far as use of funds, obviously a lot of it goes towards the GPU infrastructure that goes into data centers. We are also starting to put that into investments into data centers themselves. And we I think that what we're aiming to do long term is kind of build this almost like Tesla for AI infrastructure, where we kind of look at this as like a similar build out that you would expect from the like electrification of the United States or the railroad.

2:57:07And a degree of vertical integration, we believe, is going to be in the future for us and is the right direction. And that goes from everything from energy procurement and construction, because I think a lot more of this stuff is going to have to be behind the meter power plants, to actual construction and design of data centers that can sort of rapidly adapt to the changing chips that go in, right? Because the rack densities and the movement from air cool to liquid cooling that we're really pioneering alongside NVIDIA. These are all examples of use of funds. And it's exciting because we get to kind of make good investment decisions that are really sort of IRR-based in an almost industrial way, which I think is unique from a company building perspective.

2:57:59And it's an honor to be able to do that. Can you get me up to speed on some of the tradeoffs between like one really big mega data center and a bunch of really small data centers? Because there was a moment when we were just doing bigger and bigger training runs. Then it became RL all over the place. Then you actually have to serve these things. But actually, if it's going to take me 10 minutes, I don't mind if you do it across the world and take it back. But if I do care that it's right now, I need it like right co-located. How are you thinking about the tradeoffs there? So the mix and the main driver over the next five years, we believe will likely be mostly on the inference side.

2:58:39If you look at some of the financial models that have either leaked or otherwise been published around what OpenAI thinks they're going to be spending, it looks to be about 50 % on training and then 50 % on inference, growing towards 75 % inference and a smaller chunk of that on training.

2:59:03As far as like what that means for the larger data centers, I certainly don't think that this is like going to a world where there's a bunch of micro data centers. I think that that's a little bit hard to sort of manage and deal with. But one of the things I think that you're going to start hearing a lot more of is how adaptable and how quickly can you bring on the data center in an incremental fashion? Because that's going to be a lot of the main drivers for how successful infrastructure builders like us are is how quickly. And we're just focused on optimizing that time to first token for our customer.

2:59:42How do you think about revenue quality and customer selection? Because we've seen some deals go down that look big and cool and good on the surface, and then you dig into them and maybe the underlying infrastructure provider is not actually getting that great of a deal at the end of it. Well, we certainly see a lot of people with very high levels of customer concentration. Because Lambda started off as this developer cloud that evolved and morphed into a cloud that's providing for the biggest companies in the world, we have a really, really strong user base. You know, if you look at our breakdown from our revenue mix, in terms of you looked at like, let's say our Q3 stuff, and I don't want to go into exact specifics, but it's sort of like one or two big customers, a bunch of sort of the bigger, smaller customers.

3:00:44And then it's something, you know, it's a nice, really big chunk of this long tail of customers that we have. And we have a very, very, you know, I've seen some other people's customer books. And I can just say that we've got a very diversified customer base. And that's kind of all part of this strategy of how do you build a great long-term business? Of course, customer diversification is one of those parameters. How do you think about diversity of product offerings? Are you seeing customers ask for API endpoints for particular models? Or do they want access to bare metal? Or have you gotten any customers that are like, hey, we just want, you know, you seem to know about this data center business.

3:01:28Can you just build a data center for us and hand it over to us when you're done? And we'll just pay you as a consultant. We have no interest in doing that one. That's, you know, we want to do something that's really vertically integrated. And, you know, kind of going back to that, like larger, smaller data centers, I think the most important thing is just being able to deliver this incremental live deployment for a customer. We have an entire full stack cloud product that, you know, it's got things like single sign on. It's got things like long term high speed AI file systems. It's got instances that go down from one GPU to an entire cluster with one click clusters.

3:02:09that we've got. And so we've built an entire cloud platform. We have previously been in the inferencing space where we're actually giving an API for inferencing. And we've actually exited that business to just focus. I think that that's like one of the things that we really try to do at Lambda is just say, where are we making money? What are good investments? And where are we going to really dominate the market and focus there? And so we've actually exited, for example, the inference market, we had a$200 million plus a year hardware business that we've exited. It actually kind of crushes me because that was the business that got off the ground.

3:02:49But can you imagine just winding down like, well, we're just going to take this business and not do a$200 million a year business anymore because we're trying to focus? That is crazy. Thanks, Scott. I have a crackpot theory that I'd love to run by you. What do you think the odds are that the, like I noticed I was traveling in Mexico and I noticed that Carlos Slim is the richest man there and he's a telecom magnate. He owns a lot of the telecom infrastructure and that's true for a lot of countries, the richest person in that country is a telecom person or a mining magnate in the sense that they've been able to corner a resource, a physical resource, infrastructure, and that's generated a lot of wealth for them.

3:03:40And I was wondering if you had a thought on, do you think that in the future we'll see some of the wealthiest, most powerful people from other countries, non-American countries, be, you know, GPU cloud hosters or data center developers? Like, is this going to be a new boom across the globe? It's kind of a different twist on the Sovereign AI project. I was just wondering if there's going to be some way that this plays out where there's this sort of like one-time opportunity to kind of get a cornered resource, or is the nature of the internet such that the compute is actually much more fungible than say, you know, telecom or, you know, or like copper in the ground.

3:04:26There's such a localization. There's such a physical localization. I think if you look at telecom, you look at cable, as well as regulated utilities from an energy utility perspective. You know, these are all things that benefit from a physical geographic monopoly, right? And AI data centers don't have that same thing. Now, I just want to step back for a second. Guys, the United States is basically the only country in the world. We have the most unbelievably good economy. This is the idea that there's going to be these sort of like massive AI infrastructure projects that I think are going to be like super, super successful outside of, let's say, China and the United States right now is really increasingly big question mark.

3:05:12And I just am so bullish about where we're going in America that I don't really pay a lot of attention. And our focus is just in North America generally. And that's kind of my perspective on it, to be honest. Yeah, that's really helpful. I agree. It's interesting to toy. I mean, there's a lot of money being thrown around with some of these projects. And I'm always interested in how they all shape out. But last question. Yeah, maybe go for it. I was going to ask, like, how you guys are navigating energy constraints with new developments. Are you seeing, we've heard, you know, anytime, obviously, there's, like, massive demand for something, new sources kind of come out of the woodwork.

3:05:59We've seen back and forth some people that are building AI infrastructure say, like, energy is our primary constraint. Others are saying, actually, that's not my, you know, it's, so where do you sit? We are aiming to reimagine the sort of step process from whether it's photons or molecules of natural gas to tokens. And we strongly believe that a lot of this is going to have to come in reimagining like, well, how do you interact with the grid? How much power generation do you bring to the grid yourselves? And I think that that's the successful AI infrastructure companies in the future. Again, this is like why I kind of said, like, I look at this like Tesla for AI factories, which is you got to reimagine how the world has worked previously.

3:06:56And you have to kind of bring together this level of vertical integration because that's how you move fast. Right. You know, when you can control every step of that way from the power generation and not having to necessarily deal with a regulated utility and you can go and do behind the meter generation with a natural gas power plant, if that can speed your time to market up, this is just so important. and that's kind of how I approach it, which is there are certain barriers like regulatory barriers, which you try not to run through those like a brick wall because it's kind of like an immovable object.

3:07:35But if you can just sort of get around that sort of regulatory constraint of having to interact with a regulated utility by bringing your own power to the grid, then that's what I think is going to be successful. Yeah, makes a lot of sense. Thank you so much for taking the time out of your busy day to come and hang out with us and answer some questions. Thanks for having me, guys. It's always a great time. Congratulations. Did you see the new Gemini 3? Yeah, can you give us your review and actually explain how it interfaces with your business? I'd love to know. So I haven't used the Gemini 3. I've seen the updates.

3:08:13I'm still, you know, hey, Sundar or whatever, give land this enterprise. account access. We're on Google Suite or Google Enterprise or whatever it's called now. So we'd love that upgrade. But I'll tell you what, this is the cool thing. I use things like ChatGPT and Grok to learn more about topics like regulated energy markets and how to build power plants and data centers. And that makes Lambda faster at standing up AI data centers. and I pay attention. I actually just kind of do what the AI tells me to do. And that gives more compute to the AI to train bigger models, which makes a better land faster.

3:09:00The AI is working for you to make more AI. It's the beginning of these types of positive feedback loops. Sure, sure. And I think that if you privately talk to a lot of executives, you'd be surprised by the amount of, you know, the strategic conversations I have with these AI models has gotten more and more advanced with the level and quality of the model. The first versions were not great and I didn't really take a lot of its advice. But now I am. I mean, next thing you know, it's sort of like, well, maybe AI is the one making the run of the show. Next thing you know, we'll be hanging out on TVPN discovering novel physics with Gemini 4.

3:09:43We'll see how far we get. yeah it's a good time well thank you so much for coming by the show we'll talk i have i have a bunch more i have a bunch more questions but but come back let's get you back on in anytime before the end of the year that'd be great we'll continue the conversation congrats to the whole team yeah we'll talk to you take care have a good one see you bye uh quickly let me tell you about privy privy makes it easy to build on crypto rail securely spin up white label wallets sign transactions and integrate on-chain infrastructure all through one simple API. What a legend. What an absolute legend.

3:10:19What else we got? Doug O 'Loughlin over at Semi Analysis, Fabricated Knowledge says, I leave for two weeks and we are talking about Oracle credit default swaps. What the hell, guys? Doug, where was Doug for... I think he's been on vacation or something. He was trying to truly log off and take a break. Yes, people are definitely talking about CDS spreads. And any sign, any crack in the market is definitely going to be newsworthy because we're in this$1 trillion era. Gavin Baker here is talking about this. He's completely agree with this breakout of the non-bubble that disappointed both bull and bears, how Sam's splurge changed everything.

3:11:02And Gavin Baker says, Sam Altman's manifestly ridiculous$1 trillion of spending commitments shifted the AI investing landscape. The market is more skeptical now, ironically makes an IPO harder for them, although likely ended any potential for a 1999 style melt up, which is healthy. Melt up meaning that in 1999, the market went insane and nuclear. Instead, the$1 trillion was so in your face that everyone started asking the questions of like, is this real? Is what's going on? Are we going too fast? Do we need to back off? And so we got sort of a return to fundamentals, but fortunately the fundamentals were so good because, you know, these companies, a lot of them are trading like 25 priced earnings that the market was able to, you know, continue onwards.

3:11:53There's an interesting debate going on around Karen Howe's new book, Empire of AI, all about open AI. apparently she got the amount of water used by data centers wrong by an order of magnitude or two orders of magnitude. I'm not exactly sure where the story originally broke, but she's addressed it now. She says, I'm working to address an apparent error for a data point I cited in my book about the water footprint of a proposed data center in Chile. I'd like to explain what happened, what I'm doing to remedy it, and provide more recent data on the water footprint of data centers. The data point in question appears in chapter 12 of my book, which focuses on the environmental impacts of AI.

3:12:38Part of the chapter profiles a community in Cirillos, Chile, which has been resisting a proposed Google data center for years. To describe the data center's water footprint in lay terms, I included a sentence about how it compares to the water usage of the people in Cirillos. For that calculation, I relied on a figure from a government document reporting Cerlo's residential water use based on the current best information. It seems that this document used the wrong units. So she was off by a thousand. So the result was that - What's being off by a thousand among friends? Honestly, these days, doesn't even matter.

3:13:18We're in a post-factual. Did you read into this more? People were, I think people are generally like, you know, is this book a hit piece? And I think Sam actually cooperated with it a little bit or like gave some interviews for it, but like anything, it's like obviously critical of some things. I mean, yeah, three orders of magnitude is like pretty big. Yeah. That's like not great. Yeah, I mean, it's certainly like the difference between being a big deal and not a big deal at all. Yeah, like that about the water use, it's like people who use that to justify like, oh, we don't want to build those data centers going to use our water.

3:13:51Yeah. Like, I don't know. I mean, not good. It's a rough time if your job is drinking water. Tom in the chat says, mistakes were made. Mistakes were made in a book I was responsible for. Mika says, Jordi, you should get a grill with tiny GPUs instead of diamonds. Maybe not the full grill, just the bottom grill. There'll be AI raps. Did you see this? This is a Rohit comment on Vinod. VC Vinod Kostla says that the U.S. government could take 10 % stake in all public companies to soften the blow of AGI. And Rohit says, we should absolutely do this for all companies, public and private. Maybe we even double it to like 20 % or 21 % on every dollar they make.

3:14:33It's like, yeah, the government taxes everything. The government gets 21 % of profits, actually. They get cash flow. Sean says the haters will call that a tax. It was so funny. Olivia Newsy is in the news. People are deleting their posts. Getting kind of like a dividend. Yeah. Apparently, all the media people are obsessed with this Olivia Newsy story. I didn't understand any of the people in this story because I don't follow media or politics closely enough. Nominative determinism strikes again. But it is fun. Her name's Newsy. Bobby was saying we should do it the Metis list for nominative determinism.

3:15:14That would be good. I'd like that. Because Newsy, she's in the news all the time. Yeah. She's also a journalist. There's news in the trading app world. Robinhood launched bearish on a stock. Short selling is rolling out today on mobile. Classic, a web classic and Robinhood legend. They didn't have short selling? I feel like they've had short selling for a long time. No? That's a new feature? Well, that's funny timing. And then our partner, Public. Public is launching generated assets, which they're calling their agentic brokerage. Very cool video with our boys here. Yes, yes. But this means you can basically generate like your own index based on.

3:15:55And what's interesting about it is that you can say, I want access to the Mag7 plus a couple other AI companies. Minus one company. Minus one company. I don't know which company you're talking about. If there's a company. So you can generate like, you know, some sort of portfolio. But then instead of owning it as an ETF and needing to buy and sell it directly, you can actually do the tax loss harvesting of selling individual pieces of it. And so you can construct a portfolio very quickly. And in general, I mean, just all the different research that you want to do is obviously deeply enhanced with artificial intelligence.

3:16:34So fun to see them. uh pope leo has uh hit the timeline to comment on cinema the logic of algorithms tends to repeat what works but art opens up what is possible not everything has to be immaculate or predictable defend slowness when it serves a purpose silence when it speaks and difference and indifference when evocative. Beauty is not just a means of escape. It is above all an invocation. When cinema is authentic, it does not merely console, but challenges. It articulates the questions that dwell within us and sometimes even provokes tears that we did not know we needed to express. That's been a nicely worded phrase from the Pope Leo.

3:17:25What movie do you think he was thinking about? When writing this? Obviously Borat. Margin call. 100 % margin call in Borat. He's going back to back. There was a post in here about movies. Somebody said they watched like three movies over the weekend. I thought it was the most un-Geordian thing. Final post of the day. Kevin. Right. Yeah, right. You think you're going to be able to cut me off? Kevin Naughton Jr. says 10 ,000 likes. On April 30th, he said 10 ,000 likes and I'll quit my software engineering job at Google tomorrow. What happened here? He said six months ago, I made the worst decision of my life.

3:18:03Oh, because Google's ripping. Google's ripping. That's what he's talking about. Okay, because I read this initially. It's like he quit, he started a company, and it went really poorly. It's just funny. He is building the fastest way to post with postwrite.ai. Okay. Post all your social platforms in seconds. Oh, maybe we could use that for something. Very funny. He's like, my idea was Gemini 3. Like I was going to make a better Gemini. I thought Gemini 2.5 just wasn't quite there. And I didn't know that. What if Google does this? All the VCs were telling me your idea is Gemini 3. What if Google does that?

3:18:40And I was like, everyone says that about Google things. Everyone says that about startup ideas. It's not worth it. I'm just going to try to build Gemini 3. But then they beat them to it. That's what I imagine. Anyway, Department of War, critical areas of new technology, applied artificial intelligence, quantum and battlefield information dominance, biomanufacturing, contested logistics, scaled directed energy. That sounds crazy. Scaled hypersonics. Very excited for that. A bunch of interesting stuff. Emil Michael is firmly in the chair of the Undersecretary of War. Very excited. Hope we can get him on the show soon to understand what he's doing over there.

3:19:18Make it happen. well thank you for tuning in to the show today folks we love you dearly and we will see you tomorrow have a good evening cheers goodbye