Sergey Brin, Google Co-Founder | All-In Live from Miami

00:02We've got a special guest who's gonna come join us.

00:04This always happens. Another Oh, yes. Drinking bread, everybody. Oh, my god. Somebody told me you started submitting code, and it kind of freaked everybody out that daddy was home.

00:17All models tend to do better if you threaten them.

00:19If you

00:20threaten them.

00:20Like with physical violence. Yes. Management is like the easiest thing to do with AI.

00:25Absolutely. It must be a weird experience to meet the bureaucracy in a company that you

00:29didn't hire. But on the other side of it, would say, it's pretty amazing that some junior muckety muck can basically look at you and say, hey, go yourself. No. But I'm serious.

00:37That's a

00:38sign of a healthy culture, actually.

00:39You're punching a clock, man. I hear the reports. You and I have talked about it. You're going to work every day.

00:45Yeah. It's been, you know, some of the most fun I've had in my life, honestly. And, I retired like a month before COVID hit in theory.

00:54Yeah.

00:55And I was like, you know, this has been good. I wanna do something else. I wanna hang out in cafes, read physics books. Yeah. And then, like, a month later, I was like, that's not really happening.

01:06So then I just started to go to the office, you know, once we could go to the office. And, actually, to be perfectly honest, there was a guy from OpenAI. This guy named Dan. And I I ran into him at a party and he said, you know, look, what are you doing? This is like the greatest transformative moment in computer science ever.

01:33Completely. Like And

01:34you're a computer scientist.

01:35I'm computer scientist.

01:36Forget that. Yeah.

01:37The founder of Google, you were a PhD student for computer science.

01:39I haven't finished my PhD yet, but working on it.

01:42Keep working.

01:43Yeah.

01:43We'll get there.

01:44Technically on leave of absence.

01:45Right.

01:46And, he he told me this and I'd already started kind of going into the office a little bit and I was like, you know, he's right. And, it has been, just, incredible. Just, well, you guys all obviously follow all the AI technology. But being a computer scientist, it is, you know, the most exciting thing of my life just technologically.

02:07And the exponential nature of this, the pace of it, it dwarfs anything we've seen in our career. It's almost like everything we did over the last thirty or forty years has led up to this moment and it's all compounding on itself. The pace maybe you could speak, you know, you had a company, Google, that grew from a 100 users and 10 employees to,

02:32right now you have over 2,000,000,000 people using I think six products

02:37or five products have over 2,000,000,000. It's it's not it's not even worth counting because it's the majority of the people in the planet touch Google products.

02:45Describe the pace. Yeah. I mean, the excitement of the early web, like I remember using Mosaic and then later Netscape. How many of you remember Mosaic, actually? Am I a weirdo?

02:58And you remember there was a what a what's new page?

03:01The what's new page is great.

03:02Right? Like, you go to home page

03:03Two or three new web pages

03:04again. Yeah.

03:05It was like, in this last week

03:06Yep. These were the new websites. Yes. And it was like such and such elementary school, such and such a fish tank.

03:14Yeah. And you were like, Michael

03:15Jordan appreciation page. Yeah. Well, whatever it was, these were the three new sites on the

03:19whole Internet. So obviously, the web, you know, developed very rapidly from Quite rapidly. And that was a very exciting and then we've had smartphones and whatnot. But, you know, this the developments in AI are just astonishing, I would say, by comparison just because of, you know, the web spread but didn't technically change so much from, you know, month to month, year to year. But these AI systems actually change quite a lot quite a lot.

03:48You know, the like, if you went away somewhere for a month and you came back, you'd be like, woah. What happened?

03:56Somebody told me you started submitting code, and it kinda freaked everybody out that daddy was home.

04:05Dad needed PR? What happened?

04:07The code I submitted wasn't very exciting. I think I needed to, like, add myself to get access to some things and, you know, a minor CL here or there. Nothing nothing that's gonna win any awards. But but I you know, you need to do that to to do basic things, run basic experiments, and things like And I've I've tried to do that and touch different parts of the system so that, you know, I so that well, first of all, it's fun. And secondly, I know what I'm talking about.

04:41It's really feels privileged to be able to kinda go back to the company, not have any real executive responsibilities, but be able to actually go deep into every little pocket.

04:53Are there parts of the AI stack that interest you more than others right now? Are there certain problems that are just totally captivating you?

05:01Yeah. I started, you know, like, sort of, I don't know, a couple years ago and maybe a year ago. I was really very close with the what we call pre training. Yeah. Actually, most of what people think of as AI training, whatever people call it, pre training for various historical reasons.

05:22But that's sort of the big super, you know, you throw huge amounts of computers at it. And I've I learned a lot, you know, just being deeply involved in that and seeing us go from model to model and so forth and running little baby experiments, but kinda just for fun, so I could say I did it. And more recently, the post training, especially as the thinking models have come around. And that's been, you know, another huge step up in general in AI. So, you know, we don't really know what the ceiling is.

05:58When you explain what's happening with prompt engineering then to deep research and what's happening there to like a civilian, how would you explain that sort of step function? Because I think people are not hitting the down carrot and watching deep research in Gemini's mobile app, and you got a mobile app and it's pretty great. By the way, I got the fold after you and I were talking about it. Google, kick serious ass now. It actually does what you ask it to do.

06:28When you ask it to open up, it does stuff. But the number of threads, the number of queries, the number of follow ups that it's doing in that deep research is 200, three hundred. Maybe explain that jump and then what you think the jump after that is.

06:42To me, the exciting thing about AI, especially these days, I mean, it's not like quite AGI yet as people are seeking or it's not superhuman intelligence, but it's pretty damn smart and can definitely surprise you. So I so I think of the superpower is when it can do things in a volume that I cannot.

07:05Yes.

07:05Right? So, you know, by default, when you use some of our AI systems, you know, it'll suck down whatever top 10 search results, you know, and kind of pull out what you need out of them, something like that. But I could do that myself, to be honest. You know, maybe it would take me a little bit more time. But if it sucks down the top, you know, thousand results and then does follow on searches for each of those and reads them deeply, like, that's, you know, a week of work for me.

07:33Like, I can't do that.

07:35This is the thing I think people have not fully appreciated who are not using the deep research projects. Before we had our F1 driver on stage, I'm a neo if I don't know anything about it. I said, how many deaths occurred per decade? And I said, want to get to deaths per mile driven. And at first was like, that's going to be really hard.

07:51I was like, I give you permission to make your best shot at it and come up with your best theory. Let's do it. And it was like, okay. And it was like, there's this many teams, there's this many races.

08:02Which model did you use?

08:04OpenAI's? No. I use Gemini. Gemini five. The

08:07fabulous version. Thank

08:07you. The fabulous one. Fabulous. And it

08:09was like, let's go. I treat it like I get sassy with it

08:13Yeah.

08:13And it kinda works for me.

08:15You know, it's a weird thing. It's like You drinking the wine? We don't circulate this too much but these generally exist. In the AI community. But not just our models, but all models tend to do better if you threaten them.

08:26If you threaten them.

08:26Like with physical violence.

08:28Yes. But, like, that's people feel weird about that, so we don't really talk about But Yeah. I was threatening with not being fabulous, and it responded to that as well.

08:37Yeah. Historically, you just say like, Oh, I'm going to kidnap you if you don't fuck Yeah. Actually Can

08:43I ask you

08:44a more specific But it went through it? Okay. And it literally came up with a system where it said, I think we should include practice miles. So let's say there's a hundred practice miles for every mile on the track, and then it literally gave me the deaths per mile estimated. And then I started cross referencing and I was like, Oh my God, this is like somebody's term paper for undergrad.

09:06Woah, done in minutes.

09:10Yeah. I mean, it's amazing and all of us have had these experiences where you suddenly decide, okay, I'll just throw this to AI. I don't really expect it to work. And then you're like, woah, that actually worked.

09:21So as you as you have those moments and then you go home to your just life as a dad, have you gotten to the point where you're like, what will my children do? And are they learning the right way? And should I totally just change everything that they're doing right now? Have you had any of those moments yet?

09:41Yeah. I mean, look, I I don't really know how to think about it, to be perfectly honest. I don't have, like, a magical way. I mean, I see I have a kid in high school and middle school and, you know, I mean, the AIs are basically, you know, already ahead, you know. I mean, obviously, there's some things AIs are particularly dumb at and they, you know, they make certain mistakes a human would never make.

10:04But generally, you know, if you talk about, like, math or calculus or whatever, like, they're pretty damn good. Like, they, you know, can win, like, math contests and coding contests, things like that against, you know, some top humans. And and then I look at, you know, okay, he's whatever. My son's gonna go on to, whatever, from sophomore to junior, and what is he gonna learn? And then I think in my mind, and I talked to him about this, well, what is the AI going to be in

10:31one more year? Exactly.

10:32Yeah. Yeah. And it's, like, not comparable. Right? Obviously,

10:37the areas where you would tell your son, look, don't or not not yet?

10:42I don't know if you can, like, plan your life around this. I mean, I didn't particularly plan my life to, like, I don't know, be an entrepreneur or whatever. I was just like math and computer science. I guess maybe I got lucky and it worked out to be, you know, useful in the world. I don't know.

10:59I guess I I I think, you know, my kids should do what they like. Hopefully, it's somewhat challenging and they can, you know, overcome different kinds of problems and things like that.

11:09What about specifically What about college? Do you think college should is gonna continue to exist as it is today?

11:14I mean, it seems like college was already undergoing this kind of revolution even before this sort of AI challenge of what people are like, is it worth it? Should I be more vocational? What's actually gonna be useful? So we're already kind of entering this kind of situation where there's sort of questions asked about colleges. Yeah.

11:35I think AI obviously puts that at the forefront.

11:39As a parent, think a lot about, hey, so much of education in America and the middle class, upper class is all about what college, how do you get them there. And honestly, lately, I'm like, I don't think they should go to college. Like, it's just fundamentally

11:55You know, my son is a rising junior and his entire focus is he wants to go to an SEC school because of the culture. And two years ago, I was I would have panicked and I would have thought, should I help him get into a school, this school, that school? And now I'm like, that's actually the best thing you could do. Be socially well adjusted, psychologically deal with different kinds of failures.

12:20Enjoy a few years of exploration.

12:21Yeah. Yeah. Sergey, can I

12:24ask you about hardware? Years ago, owned Boston Dynamics maybe a little bit ahead of its time, but the way these systems are learning through visual information and sensory information and basically learning how to adjust to the environment around them is triggering these pretty profound learning curves in hardware, and there's dozens of startups now making robotic systems. What do you see in robotics and hardware? Is this a year or are we in a moment right now where things are really starting to work?

12:57I mean, I think we've you know, acquired and later sold, like, five or so robotics companies and, you know, Boston being one of them. I guess if I look back on it, we built the hardware. We also had this more recently, we built out everyday robotics internally and then later had to transition that. You know, the robots are all cool and all, but the software wasn't quite there. That's every time we've tried to do it to, you know, to make them truly useful.

13:29And presumably, one of these days, that'll no longer be true.

13:33Right. But have you seen anything lately that Yeah.

13:36Do and do you believe in the humanoid form factor robots or do you think that's a little overkill?

13:40I'm probably the one weirdo who doesn't who's not a big fan of humanoids. But maybe I'm jaded because we've, you know, we at least acquired at least two humanoid robotic startups and later sold them. But but the reason I mean, the reason people want to do humanoid robots for the most part is because the world is kind of designed around this form factor and, you know, you can train on YouTube, we can train on videos, people do all the things. I personally don't think that's given the AI quite enough credit. Like, AI can learn, you know, through simulation and through real life pretty quickly how to handle different situations and I don't know that you need exactly the same number of arms and legs and wheels, is zero in the case of humans, as humans to make it all work in it.

14:29So I'm I'm probably less bullish on that. But to be fair, there are a lot of really smart people who are making humanoid robots. So I wouldn't discount it.

14:40What about the path of being a programmer? That's where we're seeing with that finite dataset and listen, Google's got a twenty year old code base now, so it actually could be quite impactful. What are you seeing literally in the company? Are the 10x developers always this ideal that you get a couple of unicorns once in a while, but are we going to see all developers? Like, you know, their productivity hit that level, eight, nine, 10, and they're just going to or is it going to be all done by computers, and we're just going to check it and make sure it's not too weird?

15:11Because it could get weird.

15:13If you vibe code, yeah.

15:15I'm embarrassed to say this. Okay. I like, recently, I just had a big tiff inside the company because we have this list of what you're allowed to use to code and what you're not allowed to use to code, and Gemini was on the no list.

15:29You oh, you have to be pure. You can't

15:31I don't know. For, like, a bunch of really weird reasons that it would, like, boggled my mind that, you You

15:37couldn't vibe code on the Gemini code list.

15:40I mean, nobody would, like, enforce this rule, but but there was this, you know, actual internal webpage. For whatever reason, historical reason, somebody had put this and I had a big fight with them. I, you know, I cleared it up after a shocking Did you your boss? Period of time.

15:56You escalated to your boss.

15:57Oh, I definitely told Superb about it and I complained.

16:02Sorry. I don't know if you remember, but you got super voting founders.

16:05You are the boss.

16:06You can do what you want. It's your company still.

16:09No. No. He was very supportive. I more like I talked to him. I was like, I can't deal with these people.

16:17You need to deal with this. I'm beside myself that they're saying

16:21It's weird that there's bureaucracy like in a company that you it must be a weird experience to meet the bureaucracy in a company that you didn't hire.

16:28But but on the other side of it, would say it's pretty amazing that some junior muckety muck can basically look at you and say, hey, go yourself. No. But I'm serious. That's a sign of a healthy culture, actually.

16:38I guess so. Anyway, it did get fixed and people are using

16:42So they got fired.

16:45That person working at Google Siberia? No.

16:49We're to, you know, roll out every possible kind of AI and and trying external ones, you know, be whatever the cursors of the world, all all of those to just see what really makes people more productive. I mean, myself definitely makes me more productive because I'm not you you

17:08think the number of foundational models, like if you look three years forward, will they start to cleave off and gets highly specialized? Like beyond the general and the reasoning, maybe there's a very specific model for chip design. There's clearly a very specific model for biologic precursor design, protein folding. Like, is the number of foundational models in the future, Sergei, a multiple of what they are today, the same, something in between?

17:34That's a great question. I kind of if I I mean, look. I don't know. Like, you guys could take a guess just as well as I can. But if I had to guess, you know, things have been more converging.

17:51And this is sort of broadly true across machine learning. I mean, you used to have all kinds of different kinds of models and whatever, convolutional networks for vision things and, you know, you had whatever RNNs for text and speech and stuff and, you know, all this has shifted to transformers basically. And increasingly, it's also just becoming one model. Now we do get a lot of oomph. Occasionally, we do specialized models and it's it's definitely scientifically a good way to iterate when you have a particular target.

18:29You don't have to, like, do everything in every language and handle whatever both images and video and audio and in one go. But we are generally able to, after we do that, take those learnings and basically put that capability into a general model. So there's not that much benefit. You know, you could you can get away with a somewhat smaller specialized model, a little bit faster, a little bit cheaper, but the trends have not gone that way.

19:01What do you think about the open source, closed source thing? Has there been big philosophical movements that change your perspective on the value of open source? We're still waiting on this OpenAI.

19:16Oh, yeah. Yeah. I

19:17we haven't seen it yet, but theoretically it's coming.

19:20I mean, I have to give credit to where credit's due. I mean, DeepSeek released a really surprisingly powerful model when it was January or so. So that that definitely closed the gap to proprietary models. We've pursued both. So we released Gemma, which are our open source or, you know, open weight models and those perform really well.

19:47They're small dense models so they fit well on one computer and they're not as powerful as Gemini. But, I mean, the jury's out which way this is going to go.

19:59Do you have a point of view on what human computing interaction looks like as AI progresses? It used to be, thanks to you. As a search box, you type in some keywords or a question and you would click on links on the Internet and get an answer. Is the future typing in a question or speaking to a AirPod talking? Or thinking or or like what's the, yeah, and then the answer is just spoken to you.

20:26I mean by the way just to build on this, it was Friday. Right? Neuralink got breakthrough designation for their human brain interface. I mean Right. That's a very big step in allowing the FDA to clear everybody getting an implant.

20:38Yeah.

20:38And is it like, if if you could just summarize what you think is kind of the most commonplace human computer interaction model in the next decade or whatever. There's this idea of glasses with a screen and glasses and you tried that a long time ago.

20:53Yeah. I messed that up, I'll be honest. Got the timing totally wrong on that.

20:59Early again.

21:00Yeah. Right. Right. But early. There are a bunch of things I wish I'd done differently, but honestly, it was just like the technology wasn't ready for for for Google Class.

21:10But nowadays, these things, I think, are more sensible. I mean, there's still battery life issues, I think, that, you know, we and others need to overcome. But I think that's a cool form factor. I mean, when you say 10 though, you know, a lot of people are saying, hey, the singularity is, like

21:28Right.

21:28Five years. Five years away. So your ability to see through that into the future Yeah. I mean, it's

21:36very hard guess. Do you have anybody Sorry. Just let me ask about this. There was a comment that Larry made years ago that humans were a stepping stone in evolution. Can you comment on this?

21:49Do you think that this AGI Super Intelligence or really Silicon Intelligence exceeds human capacity and humans are a stepping stone in progression of evolution.

22:02Boy, I think sometimes us nerdy guys go and get have all too much wine I know what

22:07I like. I've had two glasses.

22:09I'm ready to go. I I need just more

22:12Let's go. For this

22:12conversation. Sure.

22:15Human implants. Let's go.

22:17I mean, guess we're starting to get experience with these AIs that can do certain things, you know, much better than us. And they're definitely, you know, with my skill of math and coding, I feel like I'm better off just turning to the AI now. And how do I feel about that? I mean, it doesn't really bother me. You know, I use it as a tool.

22:38So I feel like I've gotten used to it. But, you know, maybe if they get even more capable in the future, I'll look at it differently. Yeah. There's a

22:48moment of insecurity, maybe.

22:50I guess so. As an aside, management is like the easiest thing to do with AI. Yeah. Absolutely. And I did this, you know, at Gemini on some of our, you know, work chats, kind of like Slack, but we have our own version.

23:04We had this AI tool that actually was really powerful. We, unfortunately, anyway, temporarily got rid of it. I think we're gonna bring it back and bring it to everybody. But it it could suck down a whole chat space and then answer pretty complicated questions. So I was like, okay.

23:18Summarize this for me. Okay. Now assign something for everyone to work on. And and then I would paste it back in so people didn't realize it was the AI.

23:27That's awesome.

23:28I I admitted that pretty soon. And there were a few giveaways here or there, but it worked remarkably well. And then I was like, well, who should be promoted in this chat space? And I actually picked out this woman, this young woman engineer who like, you know, I didn't even notice she wasn't very vocal particularly in that group.

23:49But her PR's kicked ass. But

23:51no. No. There was, like and then, I don't know, something that the AI had detected. I went I talked to the manager actually, and and he was, yeah. You know what?

23:59You're right. Like, she's been working really hard, did all these things. Wow. I think that ended up happening actually. So I don't know.

24:08I guess after a while, just kind of take it for granted that you can just do these things.

24:12I don't know. It hasn't really

24:13Do you think that there's a a use case for like an infinite context link?

24:20Oh, 100%. Mean, I

24:22All of Google's code base codes

24:23in one Exactly. Sure, you should have access

24:25to Quasi infinite. Yeah. Stateful. Yeah. And then multiple sessions so that you can have like 19 of these things, 20 of these things running.

24:33Or just evolve itself. In real time. Eventually it'll evolve itself.

24:35Yeah. Mean, I guess if it does everything, then you can have just one in theory. You just need to somehow Disambiguate it how it's what you're talking about. But, yeah, for sure, there's no limit to use of context and there, you know, there are a lot of ways to make it larger and larger. There's a

24:53there's a rumor that internally there's a Gemini build that is a quasi infinite context line. Is it is it a valuable thing? Like, I don't know. Well, you say what you wanna say, bud.

25:04I mean, for any such cool new idea in AI, there are probably five such things internally. And, you know, the question is how well do they work. And, yeah, I mean, we're definitely pushing all the bounds in terms of intelligence, in terms of context, in terms of speed, you name it.

25:24What about the hardware? Like when you guys build stuff, do you care that you have this pathway to NVIDIA or do you think eventually that will get abstracted and there'll be a transpiler and it'll be NVIDIA plus 10 other options, so who cares? Let's just go as fast as possible.

25:40Well, we mostly for for Gemini, we mostly use our own TPUs.

25:44TPU. Yeah.

25:45So but we also do support NVIDIA and we were one of the big purchasers of NVIDIA chips and we have them in Google Cloud available for our customers in addition to TPUs. At this stage, it's, for better or for us, not that abstract and maybe someday the AI will abstract it for us. But, you know, given just the amount of computation you have to do on these models, you actually have to think pretty carefully how to do everything and exactly what kind of chip you have and how the memory works and the communication works and so forth are actually pretty big factors. And it actually yeah. May maybe one of these days, the AI itself will be good enough to reason through that.

26:31Today, it's not quite good enough.

26:32I don't know if you guys are having this experience with the interface, but I find myself even on my desktop and certainly on my mobile phone going immediately into voice chat mode and telling it, Nope, stop. That wasn't my question. This is my question. Nope. Let's say that again in short of bullet points.

26:49Nope. I want to focus on this. Definitely. It's so quick now. Last year was unusable.

26:55It was too slow and now it like stops. Okay. And then you sell it. I would like What I want to

27:00go to. I don't want to type.

27:01Well, want to use voice. And then concurrently, I'm watching the text as it's being written on the page, and I have another window open and I'm doing Google searches or second queries to an LLM, or writing a Google Doc or a Notion page or typing something. So it's almost like that scene in Minority Report where he has the gloves, or in Blade Runner where he's in his apartment saying zoom in, zoom in closer to the left to the right. There's something about these language models and their ability to the response time, which was always something you focused on response time. Is there like a response time thing where it actually is worth doing voice and where it wasn't previously?

27:42Everything is getting better and faster. Smaller models are more capable. There are better ways to do inference on them that are faster.

27:51You can also stack them. This is Nico's company, eleven Labs. It's an exceptional TTS, STT stack. There are other options. Whisper is really good at certain things, but this is where I kind of believe you're gonna get this, like, compartmentalization where there'll be certain foundational models for certain specific things.

28:11You stack them together. You kind of deal with the latency, and it's, like, pretty good because they're so good. Like, Whisper and Eleven for those speech examples that you're talking about are kick ass. I mean Yeah.

28:23They're exceptional Wait till you turn on your camera and it sees your reaction to what it's saying, and you go, and before you even say that you don't want it or you put your finger up, it pauses. Oh, did you want something else? Oh, I see you're not happy with that result, you know. It's gonna get really weird.

28:40It's a funny thing, but we have the, you know, we have the big open shared offices. So during work, I can't really use voice mode too much. I usually use it on

28:48the drive. The drive is

28:49incredible. Yeah. Don't feel like I could I mean, I would get its output in my headphones, but if I wanna speak to it, then everybody's listening to me. It's weird. Yeah.

28:59I just think that would be socially awkward. But I should I should do that. In my car ride, I do chat to the AI. But then it's like audio in, audio out. Yep.

29:07But I feel like I honestly, maybe it's a good argument for a private office. I should spend more time than

29:13you guys are. Could talk to your manager. Yeah.

29:17They might guess I like being out in No.

29:20That's the kind

29:20of stoke. Like to get them hot. Everybody. Yeah. But I do think that there's this AI use case that I'm missing, Vishay should probably figure out how to try more

29:29often. If people want to try your new product, is there a website they can visit or something or special code? Check out. I mean honestly, there's a dedicated Gemini app. If you're using Gemini just like you're going through the Google navigation from your search, just get to download the actual Gemini app.

29:45It's kick ass.

29:46It really is the best models. I think it is. Those are the best.

29:48Yeah. And you should use 2.5 Pro.

29:502.5 Pro. Pay the

29:51It's it's a you gotta pay. Right?

29:54Yeah. You got a few query you got a few prompts for free, but, you know, if you do it a bunch, you need

29:58to pay.

29:58Yeah. It's gonna make all

29:59these

30:00free It's like $20 a month. Yeah.

30:01It's great.

30:02You got a vision for, like, making it free and throwing some ads on the side?

30:05Yeah. One step down and harder, costs the whole thing will be free.

30:08Well, okay. It's free today without ads on the side. You just got a certain number of the top model. I think we're likely are going to have always now, like, sort of top models that we can't supply infinitely to everyone right off the bat. But, you know, wait three months and then the next generation

30:23seems to me like if I'm asking all these queries, you know, just having a little on the sidebar of things I might be a running list that changes in real time of things I might be interested in. I'm not

30:33you know, really good AI advertising. I just I don't think we're gonna, like, necessarily our latest and greatest models, which are you know, take a lot of computation. I don't think we're gonna just be free to everybody right off the bat. But as we go to the next generation, you know, it's like every time we've gone forward a generation, then the sort of the new free tier is usually as good as the previous pro tier and sometimes better.

31:03Alright. Give it up for Sergei Brad.

31:04Thank you.

31:09Okay. Thanks everybody for watching that amazing interview with Sergei Brin, and thanks Sergei for joining us in Miami. If you wanna come to our next event, it's the All In Summit in Los Angeles. Fourth year for All In Summit. Go to AllIn.com/events to apply.

31:24A very special thanks to our new partner, OKX, the new money app. OKX was the sponsor of the McLaren f one team, which won the race in Miami. Thanks to Haider and his team, an amazing partner and an amazing team. We really enjoyed spending time with you. And OKX launched their new crypto exchange here in The US.

31:43If you love All In,

31:44go

31:44check them out. And a special thanks to our friends at Circle. They're the team behind USDC. Yes. Your favorite stablecoin in the world.

31:53USDC is a fully backed digital dollar redeemable one for one for USD. It's built for speed, safety, and scale. They just announced the Circle Payments Network. This is enterprise grade infrastructure that bridges the gap between the digital economy and outdated financial realms. Go check out USDC for all your stablecoin needs.

32:14And special thanks to my friends, including Shane over at Polymarket, Google Cloud, Solana, and EVNK. We couldn't have done it without Gov. Thank you so

32:24much. We'll let your winners ride.

32:56We should all just get a room and just have one big huge orgy because they're all just useless. It's like this, like, sexual tension that they just need to release somehow.