We've got a special guest, he's gonna come join us.
This always happens, another one.
There he is! Jinger Brin, everybody.
Oh my gosh. Somebody told me you started submitting code, and it kind of freaked everybody out that daddy was home.
All models tend to do better if you threaten them.
Threaten them? Like with physical violence.
Yes. Management is the easiest thing to do with AI.
Absolutely. 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, this has been good.
I want to do something else, I want to hang out in cafes.
read physics books and then like a month later it's like that's not really happening.
So 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 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.
You don't want. And you're a computer scientist. I'm a computer scientist. Forget that.
I'm the founder of Google, but you were a PhD student for computer science.
I haven't finished my PhD yet, but working on it.
Keep working. We'll get there.
Technically on leave of absence.
Right. And he told me this, and I had 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, Well, you guys all obviously follow the AI technology.
But being a computer scientist, it is 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, 100 users and 10 employees to, now you have over 2 billion people using I think six products or five products have over 2 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?
Am I a weirdo? And you remember there was a What's New page?
The What's New page is great.
Like you go to a whole page - Two or three new web pages again.
Yeah, it was like in this last week, these were the new websites, and it was like, such and such elementary school, such and such a fish tank, and you were like, wow.
Michael Jordan appreciation page.
Yeah. Whatever it was, these were the three new sites on the whole internet.
So obviously the web developed very rapidly from there.
And that was very exciting.
And then we found smart phones and whatnot, but the developments in AI are just astonishing, I would say by comparison.
Just because of the web spread, but didn't technically change so much from month to month, year to year.
But these AI systems actually change quite a lot.
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 Danny was home.
Okay, the code ... Daddy did a PR, what happened?
The code I submitted wasn't very exciting.
I needed to add myself to get access to some things, and a minor CL here or there.
Nothing that's going to win any awards.
But you need to do that to do basic things, run basic experiments, and things like that.
I've tried to do that and touch different parts of the system system.
So, first of all it is fun, and secondly I know what I am talking about.
It really feels privileged to be able to go back to the company and 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 a couple years ago, and maybe a year ago.
I was really very close with what we call pretraining.
Actually, most of what people think of as AI training, whatever people call it, pretraining for various historical reasons.
But that's sort of the big, super, you throw huge amounts of computers at it.
And I learned a lot just being deeply involved in that, and seeing us go from model to model, 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, you know, 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 getting the down caret and watching deep research in Gemini's mobile app and you've got a mobile app that's pretty great and by the way, I got the fold after you and I were talking about it.
Okay, Google kicks Siri's ass now.
Like, it actually does what you ask it to do.
When you ask it to open it 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 AGI yet as people are seeking or it's not super human 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.
So by default when you use some of our AI systems, it'll suck down whatever top 10 search results and kind of pull out what you need out of them, something like that.
But I could do that myself, to be honest. Maybe it would take me a little bit more time.
But if it sucks down the top thousand results and then does follow -on searches for each of those and reads them deeply, that's a week of work for me.
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 it first was like, that's gonna 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, OpenAI's?
No, I used Gemini 25.
Gemini's fabulous version?
They had a 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.
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 people feel weird about that, so we don't really talk about that.
Yeah, I was threatening with not being fabulous, and it responded to that as well.
Yeah, historically you just say Oh I'm going to kidnap you if you don't blah blah blah blah.
Yeah I'll unplug that.
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 estimate 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. Yeah, I mean, it's amazing and all of us have had these experiences where you suddenly decide, okay, I'll just throw this AI and I don't really expect it to work.
And then you're like, whoa, that actually worked.
Yeah, so as you have those moments and then you go home to your 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 and should I totally just change everything that they're doing right now?
Have you had any of those moments yet?
Yeah, I mean, look, I don't really know how to think about it, to be perfectly honest. I don't have a magical way.
I mean, I see I have a kid in high school, in middle school, and the AIs are basically already ahead.
I mean, obviously there's some things AIs are particularly dumb at, and they make certain mistakes human would never make.
But generally, you know, if you talk about math or calculus or whatever, 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 then I look at, you know, okay he's, whatever, my son's going to go on to whatever from sophomore to junior, and what is he going to learn?
And then I think in my mind, and I talk to about this?
Well what is the AI going to be in one year?
Are there areas... Are the areas where you would tell your son, look, don't or 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 just liked 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 think my kids should do what they like.
Hopefully it's somewhat challenging and they can overcome different kinds of problems and things like that.
Well, what about specifically 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.
people are like is it worth it?
Should I be more vocational?
What's actually going to 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 you know 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.
It's just fundamentally.
You know, my son is a rising junior, and his entire focus is he wants to go to an SCC 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. Sergey, can I ask you about hardware?
You know, 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 kind of 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?
I mean I think we've acquired and later sold five or so robotics companies and Boston being one of them.
I guess if I look back on it we built the hardware.
We also have 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.
But have you seen anything lately that...
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 am jaded because we have at least acquired at least two humanoid robotic startups and later sold them.
But 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 can train on YouTube or you can train on videos, people do all the things.
I personally don't think that's giving the AI quite enough credit.
Like, AI can learn 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 codebase now so like it actually could be quite impactful.
What are you seeing like literally in the company you know, are the 10x developers always this like ideal that you can you know you get a couple of unicorns once in a while but are we Are you gonna see all developers?
Their productivity hit that level?
8, 9, 10? Or is it gonna be all done by computers?
And we're just gonna 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.
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 Nolist. Oh, you have to be pure.
You can't... I don't know.
For like a bunch of really weird reasons that it would boggled my mind that, you know...
You couldn't vibe code on the Gemini code, right?
I mean nobody would enforce this rule, but, um, 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, and I cleared it up after a shocking, long period of time.
You escalated to your boss.
Oh, I definitely told Sundar about it.
Yeah, I don't know if you remember, but you got super voting founders.
You are the boss! You can do what you want!
You're a company still!
No, no, he was very supportive.
I talked to him. I was like, I can't deal with these people, you need to deal with this.
I'm beside myself that they're saying we can't.
It's weird that there's bureaucracy in a company.
it must be a weird experience to meet the bureaucracy and a company that you didn't hire.
But on the other side of it, 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.
I guess so. Anyway, it did get fixed and people are using it.
So they got fired? Is that working in Google's 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, definitely makes me more productive, because I'm not...
Do you think a number of foundational models, if you look three years forward, will they start to cleave off and get highly specialized?
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.
Is the number of foundational models in the future, Sergey, a multiple of what they are today, the same, something in between?
That's a great question.
I mean, look, I don't know, you guys can take a guess just as well as I can.
But if I had to guess, 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 had whatever RNNs for text and speech and stuff.
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 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.
Oh yeah, yeah, yeah.
I mean 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, you know, 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 Gemma, but, I mean, the jury's out which way that's 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 thinking?
Or like what's... 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.
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 commonplace 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 the glasses, and you tried that a long time ago.
Yes, okay. I kind of messed that up, I'll be honest. I got the timing totally wrong on that.
Early again. 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 we and others need to overcome.
But I think that's a cool form factor.
When you say ten years though, a lot of people are saying, hey the singularity is five years away, so your ability to see through that into the future, it's very hard to guess.
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?
like do you think that this AGI super intelligence, or really silicon intelligence, exceeds human capacity and humans are a stepping stone in progression of evolution?
Boy, I think sometimes us nerdy guys go and have a little too much wine and chitter chat.
I know I've had like two glasses.
I'm ready to go. I need a s'more for this conversation.
Human implants, 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.
There's a moment of insecurity maybe.
I guess as an aside, management is the easiest thing to do with AI.
When I did this at GEMNA on some of our 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 gonna bring it back and bring it to everybody, but it could suck down a whole chat space and then answer pretty complicated questions.
I was like, okay, summarize this for me, 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 it pretty soon.
There were a few giveaways here or there, but it worked remarkably well.
Then I was like, well, who should be promoted in this chat space?
I actually picked out this young woman engineer who I didn't even notice that she wasn't very vocal particularly in that group.
But her PR's kicked ass.
But I know that the AI had detected, and I talked to the manager, actually, and he said, you know what?
You're right. She's been working really hard, did all these things, and I think that ended up happening, actually.
I don't know. 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 length?
Oh, 100%. I mean...
All of Google's code base goes in.
Exactly, but sure, you should have access to...
Closely infinite, stateful, and then multiple sessions so you can have 19 of these things, 20 of these things running Or just evolve it in real time.
Eventually it will evolve itself.
Yeah, I guess, if it knows everything, then you can have just one in theory, you just need to somehow tell...
Disambiguate paths – you can tell what you're talking about.
But, 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 is it a valuable thing?
Like I don't know – say what you want to say, bud.
I 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 know, 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 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.
Well, we mostly for for Gemini, we mostly use our own TPU's 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 TPU's.
Uhm, at this stage it's for better force, not that abstract, and maybe someday the AI will abstracted 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.
Definitely. It's so quick now.
Last year was unusable.
It was too slow and now it like stops.
Okay, and then you sell it.
I would like a bullet point.
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 in his apartment saying zoom in, zoom in, closer to the left to the right.
And it'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, you know, smaller models 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 Niko'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 whisper and 11 for those speech examples that you're talking about are 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 you put your finger up it's 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 it's funny thing but we have these 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 the drive the drive is groan I don't feel like I could I mean I would the output in my headphones.
But if I want to speak to it, then everybody's listening to me.
I just think that would be socially awkward. But I should do that.
In my car ride, I do chat to the A .I.
But then it's audio in, audio out.
But I feel like, honestly, maybe it's a good argument for a private office.
I should spend more time than you guys are.
You could talk to your manager.
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, which I should probably figure out how to try more often.
If people want to try your new product, is there a website they can visit, or something, or special code?
Honestly, there's a dedicated Gemini app.
If you're using 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 is. It's also the best. And you should use 2 .5 Pro.
2 .5 Pro. You gotta 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're just gonna make all this like 20 bucks a month.
Yeah, you got a vision for like making it free and throwing some ads on the side?
Yeah, one step down in hardware costs the whole thing will be free.
Well, okay, it's free today without ads on the side.
You just got a certain number of the top model.
I think we likely are going to have always now like sort of top models that we can't supply infinitely to everyone right off But, you know, wait three months and then the next generation.
This seems to me like, if I'm asking all these queries, just having a little on the side bar of things I might be… A running list that changes in realtime of things I might be interested in to get it for free.
I'm all for really good AI advertising.
I just don't think we're going to necessarily… Our latest and greatest models which take a lot of computation, I don't think we're going to 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 to generation then the sort of, the new free tier is usually as good as the previous pro tier and sometimes better.
Alright, give it up for Sergey Brin.
Thank you! Okay, thanks everybody for watching that amazing interview with Sergey Brin and thanks, Sergey, for joining us in Miami.
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