All-In with Chamath, Jason, Sacks & Friedberg - Sergey Brin, Google Co-Founder | All-In Live from Miami
Episode Date: May 20, 2025(0:00) The Besties welcome Sergey Brin! (0:40) Sergey on his return to Google, and how an OpenAI employee played a role! (5:58) AI's true superpower and the next jump (12:23) AI robotics: humanoids an...d other form factors (17:07) Future of foundational models and open-source (19:59) Human-computer interaction in the age of AI (31:09) Partner shoutouts: Thanks to OKX, Circle, Polymarket, Solana, BVNK, and Google Cloud! Check out OKX:Â https://www.okx.com Check out Circle: https://www.circle.com Follow the besties: https://x.com/chamath https://x.com/Jason https://x.com/DavidSacks https://x.com/friedberg Follow on X: https://x.com/theallinpod Follow on Instagram: https://www.instagram.com/theallinpod Follow on TikTok: https://www.tiktok.com/@theallinpod Follow on LinkedIn: https://www.linkedin.com/company/allinpod Intro Music Credit: https://rb.gy/tppkzl https://x.com/yung_spielburg Intro Video Credit: https://x.com/TheZachEffec
Transcript
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We've got a special guest who's going to come join us.
This always happens.
Another guest.
There he is.
Sergey Brin, everybody.
Oh my God.
Somebody told me you started submitting code and it kind of freaked everybody out that
daddy was hungry.
All models tend to do better if you threaten them.
If you threaten them.
Like with physical violence.
Yes.
Management is like the easiest thing to do with AI.
Absolutely.
It must be a weird experience to meet the bureaucracy in a company that you didn't hire.
But on the other side of it I would say it's pretty amazing that some junior muckety muck
can basically look at you and say, hey go f*** yourself.
No, but I'm serious. That's a sign of a healthy culture actually.
You're punching a clock, man. I hear the reports. You and I have talked about it.
You're going to work every day
Yeah, 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. Yeah, and I was like, you know, it's been good I want to do something else. I want to hang out in cafes
Read physics books
And then like a month later, I was like, that's not really happening.
So then I just started to go to the office,
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 ran into him at a little party,
and he said, look, what are you doing?
This is like the greatest
transformative moment in computer science ever.
And you're a computer scientist.
Forget that.
You're a PhD student for computer science.
I haven't finished my PhD yet, but
working on it.
Technically on leave of absence.
Right.
And 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 while 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.
And 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 30 or 40 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, you know,
a hundred users and 10 employees to,
now you have over two billion people using,
I think six products or five products have over two billion.
It's not even worth counting because it's the majority
of the people on the planet touch Google products
Describe 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 my weirdo and you remember there was a what's new page the what's new page is homepage. Two or three new webpages. Yeah, it was like this last week,
these were the new websites.
Yes.
And it was like such and such elementary school,
such and such a fish tank.
Yeah.
And you were like, wow.
Michael Jordan appreciation page.
Yeah, well, whatever it was,
these were the three new sites on the whole internet.
So obviously the web, you know,
developed very rapidly from there.
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.
You know, like if you went away somewhere for a month
and you came back, you'd be like, whoa, what happened?
Somebody told me you started submitting code,
and it kind of freaked everybody out that daddy was home.
OK. Daddy did a PR? What happened? The code I submitted wasn't very exciting. and it kind of freaked everybody out that daddy was home.
Okay, the code... Daddy did a PR? What happened?
The 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 seal here or there.
Nothing that's going to win any awards.
But you know, you need to do that to do basic things, run basic experiments and things like that.
And I've tried to do that and touch different parts of the system so that, first of all, it's fun.
And secondly, I know what I'm talking about.
It really feels privileged to be able to kind of go back to the company,
not have any real executive responsibilities, but be able to actually go deep into every
little pocket.
Are there parts of the AI stack that interest you more than others right now? Are there
certain problems that are just totally captivating you?
Yeah, I started, you know, like sort of,
I don't know, a couple of years ago and maybe a year ago,
I was really very close with what we call pre-training.
Actually, most of what people think of as AI training,
whatever people call it, pre-training
for various historical reasons.
But that's sort of the big super, you know,
you throw huge amounts of computers at it.
And 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 kind of 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 another huge step up in general in AI.
So, we don't really know what the ceiling is.
When 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
and by the way, I got the fold after you and I
were talking about it.
Okay Google, kick Siri's ass now.
Like it actually does what you ask it to do.
When 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, 300?
Maybe explain that jump
and then what you think the jump after that is.
To me, the exciting thing about AI,
especially these days,
I mean, it's not like quite a GI yet as people are seeking
or it's not superhuman intelligence,
but it's pretty damn smart and can definitely surprise you.
So I think of the superpower is when it can do things
in a volume that I cannot.
Yes.
Right?
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. Like, I can't do that.
This 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 neophyte, I don't know anything about it.
I said, how many deaths occurred per decade?
And I said, I want to get to deaths per mile driven.
And at first was like, that's going to be really hard.
I 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.
Which model did you use?
Open AIs? No, I used Gemini. Gem there's this many races. Which model did you use? Open AIs?
No, I used Gemini's Fabulous version.
The Fabulous one.
Fabulous.
And it was like, let's go.
I treat it like I get sassy with it, and it kind of works for me.
You know, it's a weird thing.
It's like...
Is he drinking the wine?
We don't circulate this too much in the AI community, but not just our models, but all
models tend to do better if you threaten them.
If you threaten them.
Like with physical violence.
Yes.
But like that's, people feel weird about that,
so we don't really talk about that, but like.
Yeah, I was threatening with not being fabulous,
and it responded to that as well.
Yeah, historically you just say like,
oh, I'm going to kidnap you if you don't blah, blah, blah.
Yeah, I'll unplug the, yeah.
They actually.
Can I ask you a more,
pick as many questions? But it, hold on, but it went through it. Okay. And it literally came up with a system where it said, I could kidnap you if you don't blah blah blah. Yeah, they actually. Can I ask you a more specific question?
Hold on, but it went through it,
and it literally came up with a system where it said,
I think we should include practice miles.
So let's say there's 100 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.
You know, like, whoa, done in minutes.
It's, yeah, I mean, it's amazing.
And all of us have had these experiences
where you suddenly decide, okay, I'll just throw this day.
I don't really expect it to work.
And then you're like, whoa, that actually worked.
So 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?
Yeah, I mean, I look, 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've
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 human would never make. But generally, if you talk about math or calculus
or whatever, they're pretty damn good.
They can win math contests, coding contests,
things like that against some top humans.
And then I look at, okay, he's whatever.
My son's gonna go on to to whatever from sophomore to junior.
And what is he going to learn?
And then I think in my mind, and I talked to him about this.
Well, what is the AI going to be in one year?
Exactly. Yeah. Yeah.
And it's like not comparable, right?
Obviously, the AI is where you would tell your son, look, don't or not.
Not yet.
I don't know if you can plan your life around this.
I mean, I didn't particularly plan my life to 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 useful in the world.
I don't know.
I guess I think 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.
What about specifically the...
What about college? Do you think college is going to continue to exist as it is today?
I mean, it seems like college was already undergoing this kind of revolution,
even before this sort of AI challenge of 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, I think AI obviously puts that at the forefront.
As a parent, I think a lot about,
hey, so much of education in America,
in 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.
You 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 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.
Enjoy a few years of exploration.
Yeah.
Yeah.
Yeah.
Sergey, can I ask you about hardware?
Years ago, Google 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 like 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?
I mean, I think we've, you know, acquired and later sold like five or so
robotics companies and, you know and 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 make them truly useful.
And presumably one of these days that'll no longer be true.
Right. But have you seen anything lately that...
Yeah, and do you believe in the humanoid form factor robots
or do you think that's a little overkill?
I'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 the reason is, 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, which is zero in the case of humans,
as humans to make it all work.
So 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.
What about the path of being a programmer?
That's where we're seeing with that finite data set,
and listen, Google's got a 20 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?
Their productivity hit that level, 8, 9, 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. Because it could get weird. If you vibe code, yeah. I'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 what you're allowed to use to code and
what you're not allowed to use to code.
And the Gemini was on the no list.
Oh, you have to be pure.
You can't.
I don't know for like a bunch of really weird reasons that it would
like boggled my mind that.
You know, you couldn't vibe code on the Gemini code.
I mean, nobody would like enforce this rule, but, um, but there was this, you
know, actual internal webpage
for whatever historical reason,
somebody had put this and I had a big fight with them.
I cleared it up after a shocking long period of time.
You escalated to your boss.
Oh, I definitely told Sunder about it.
I want to remind you.
Sorry, I don't know if you remember,
but you got super voting founders.
You are the boss.
You can do what you want.
It's your company still.
No, no.
It was, he was very supportive.
I was more like, I was like, I talked to him.
I was like, I can't deal with these people.
You need to deal with this.
Like I just like, I'm beside myself.
That they're like saying.
It's weird that there's bureaucracy, like in a company.
It must be a weird experience to meet the bureaucracy
in a company that you didn't hire.
But on the other side of it I would say,
it's pretty amazing that some junior muckety muck
can basically look at you and say,
hey go fuck yourself.
No, but I'm serious, that's a sign of a healthy culture.
I guess so, anyway, it did get fixed
and people are using it.
So they got fired.
That person's working in Google Siberia.
No, we're trying to roll out every possible kind of AI.
And trying external ones, whatever
the cursors of the world, all of those,
to just see what really makes people more productive.
I mean, for myself, it definitely
makes me more productive. Because I for myself, definitely makes me more productive
because I'm not coding.
Do you think the number of foundational models,
like if you look three years forward,
will they start to cleave off and get 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?
That's a great question.
I kind of.
If 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. And 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 definitely
scientifically a good way to iterate when you have a particular target. You 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 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.
What 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 open AI open source drop.
We haven't seen it yet, but theoretically it's coming.
I mean, 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 definitely closed the gap to proprietary models.
We've pursued both. So we released Gemma, which are our open source or open-to-weight models.
And those perform really well.
They'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 is this gonna go?
Do 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 or talking?
Or thinking.
Or thinking, or like what's the,
yeah and then the answer is just spoken to you.
I mean by the way just to build on this,
it was Friday right?
Neuralink got breakthrough designation for their human brain interface.
I mean that's a very big step in allowing the FDA to clear everybody getting an implant.
Yeah and is it like if you could just summarize what you think is kind of the most common place
human computer interaction model in the next decade or whatever?
Is it a, you know, there's this idea of glasses with a screen and glasses and you tried that
a long time ago.
Yeah, I kind of messed that up, I'll be honest.
Got the timing totally wrong on that.
Early again.
Yeah.
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 Google class.
But 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 years though, though, a lot of people are saying,
hey, the singularity is like five years away.
So your ability to see through that into the future.
Yeah.
I mean, it's very hard to judge.
Sorry, just let me ask about this.
There was a comment that Larry made years ago
that humans were a stepping stone in evolution.
Okay. Can you comment on this?
Like, do you think that this AGI super intelligence,
or really silicon intelligence, exceeds human capacity
and humans are a stepping stone in, you know, progression of evolution?
Boy, I think like sometimes us nerdy guys go
and get too much wine and chitter chat.
I've had two glasses.
I'm ready to go.
I need some more for that conversation.
Cumin and plants, let's go.
I mean, I guess we're starting to get experience
with these AIs that can do certain things
much better than us.
And they're definitely, 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.
I use it as a tool.
So I feel like I've gotten used to it,
but maybe if they get even more capable in the future, I'll look
at it differently. Yeah, there's a moment of insecurity, maybe.
I 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. We had this AI tool that actually
was really powerful. We unfortunately, anyway, temporarily got rid of it. I think we're going
to bring it back and bring it to everybody. But it could suck down a whole chat space and then
answer pretty complicated questions. So I was like, okay, summarize this for me. Okay, now
assign something for everyone to work on. And then I would paste it back in
so people didn't realize it was the AI.
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 actually picked out this woman,
this young woman engineer who like,
I didn't even notice she wasn't very vocal, particularly in that group.
But her PR's kicked ass.
But no, no, it was like, and then, I don't know, something that the AI had detected, and I went and I talked to the manager actually, and he was like, yeah, you know what, you'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, I guess after a while,
you just kind of take it for granted that you can just do these things.
I don't know, it hasn't really...
Do you think that there's a use case for like an infinite context link?
Oh, 100%. I mean...
All of Google's code base goes in one day.
But sure, you should have access to...
Quasi-infinite, stateful, and then multiple sessions
so that you can have like 19 of these things, 20 of these things running in real time.
Or just evolve itself eventually.
Eventually it will evolve itself.
Yeah, I mean, I guess if those everything, then you can have just one in theory.
You just need to somehow...
Disambiguate the paths.
...tell it what you're talking about.
But yeah, for sure, there's no limit to use of context.
And there are a lot of ways to make it larger and larger.
There's a rumor that internally there's a Gemini build that is
a quasi-infinite context.
Is it a valuable thing?
Like, I don't know.
Well, you say what you want to say, but.
I mean, for any such cool new idea in AI,
there are probably five such things internally.
And 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.
And what 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'll 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.
Well, we mostly for Gemini, we mostly use our own TPUs.
Well, we mostly for Gemini, we mostly use our own TPUs. So, 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 for us, not that abstract.
And maybe someday the AI will abstract it for us.
But 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, maybe one of these days
the AI itself will be good enough to reason through that.
Today it's not quite good enough.
I 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,
nope, I want to focus on this.
It's so quick now, last year it was unusable,
it was too slow, and now it stops, okay,
and then you saw it, I would like bullet points.
It's what I want to go to, I don't want to type,
I 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, you know, in his apartment
saying zoom in, zoom in, closer to the left, to the right.
And 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?
Everything is getting better and faster.
And so for smaller models that are more capable,
there are better ways to do inference on them
that are faster.
You can also stack them.
Like, you know, this is like Nico's company, 11 Labs.
It's an exceptional TTS STT stack.
Like there's, I mean, there are other options.
Whisper is really good at certain things,
but this is where I kind of believe you're going to get this
like compartmentalization where there'll be certain
foundational models for certain specific things.
You stack them together. You kind of deal with the
latency and it's like pretty good because they're so good.
Like Whisperer and Eleven for those speech examples
that you're talking about are f***ing kick ass.
I mean they'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 going to get really weird.
It's a funny thing, but we have the big open shared offices.
So during work, I can't really use voice mode too much.
I usually use it on the drive.
The drive is incredible.
Well, I don't feel like I could.
I mean, I would get its output in my headphones,
but if I want to speak to it, then everybody's listening to me.
It's weird.
I just think that would be socially awkward.
But I should do that.
In my car ride, I do chat to the AI.
But then it's like audio in, audio out.
But I feel like I honestly,
maybe it's a good argument for a private office.
I should spend more time like you guys are.
You could talk to your manager.
They might get you one.
I like being out in the bullpen, so to speak.
I like being with everybody.
But I do think that there's this AI use case that I'm missing. Asha should probably figure out how to try more often. I like being with everybody.
But I do think that there's this AI use case that I'm missing.
If people want to try your new product, is there a website they can visit?
Special code? Go check it out.
Honestly, there's a dedicated Gemini just like you're going to the Google navigation from your search just get to download the actual Gemini app
It's kick-ass. It really is the best models. I think it was and you should use 2.5 Pro 2.5 Pro
Hey, it's a you got to pay right?
Yeah, you got a few query you got a few prompts for free
But you know if you do it a bunch you need it's gonna make all this like 20 bucks a month
Yeah, it's great. You got a vision for making it free and throwing some ads on the side?
Yeah, one step down in hardware costs,
the whole thing will be free.
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
sort of top models that we can't supply infinitely
to everyone right off the bat.
But wait three months and then the next generation.
It seems 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 to get it for free.
I'm all for, you know, really good AI advertising.
I just...
I don't think we're going to necessarily...
Our latest and greatest models, which are, you know, take a lot of computation.
I don't think we're going to just be free to everybody right off the bat. are 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.
All right, give it up for Sergey, Brian.
Thank you. Thank you.
Okay, thanks everybody for watching that amazing interview
with Sergey Brent and thanks Sergey for joining us in Miami.
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Besties are gone
That's my dog taking a notice in your driveway
Sex!
Oh man
My appetizer will meet me at Blitz
We should all just get a room and just have
one big huge orgy cause they're all just
like this sexual tension
but they just need to release it out
What? You're a bee! What? You're a bee! It's like this like sexual tension, but we just need to release it out