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we have great partnerships with Eli Lilly. I think you had the CEO speaking earlier, and Novartis, which are fantastic, and our own internal drug programs.
I think you're going to see two things, which is the sort of democratization of these tools for everybody to just use and create with without having to learn incredibly complex UXs and UIs like we had to do in the past. But on the other hand, I think we're also collaborating with filmmakers and top creators and artists. So, they're helping us design what these new tools should be. What features would they want? People like the director, Darren Aronofsky, who's a good friend of mine, an amazing d
with Nano Banana, what's amazing about it is that it's an image generator. It's state-of-the-art and best-in-class.
No, I mean, we're not seeing that internally. And we're still seeing a huge rate of progress.
So I think that we are maybe, you know, I would say sort of five to 10 years away from having an AGI system that's capable of doing those things.
we have great partnerships with Eli Lilly. I think you had the CEO speaking earlier, and Novartis, which are fantastic, and I think we'll be entering sort of preclinical phase sometime next year.
especially us at Google and at DeepMind, we focus a lot on very efficient models that are powerful because we have our own internal use cases, like serving AI overviews to billions of users every day. It has to be extremely efficient, extremely low latency and very cheap to serve. And so we've kind of pioneered many techniques that allow us to do that, like distillation... And over time, if you look at the progress of the last two years, the model efficiencies are like 10x, you know, even 100x b
I think we'll be entering sort of preclinical phase sometime next year.
we have great partnerships with Eli Lilly. I think you had the CEO speaking earlier, and Novartis, which are fantastic, and our own internal drug programs.
I think we could reduce down drug discovery from taking years, sometimes a decade to do, down to maybe weeks or even days over the next 10 years.
I actually foresee a world, and I think a lot about this, having started in the games industry as a game designer and programmer in the 90s, is that, you know, I think the future of entertainment, this is what we're seeing is the beginning of the future of entertainment. Maybe some new genre or new art form, and where there's a bit of co-creation. I still think that you'll have the top creative visionaries. They will be creating these compelling experiences and dynamic storylines, and they'll be
I think you're going to see two things, which is the sort of democratization of these tools for everybody to just use and create with without having to learn incredibly complex UX and UIs like we had to do in the past. But on the other hand, I think we're also collaborating with filmmakers and top creators and artists. So, they're helping us design what these new tools should be. What features would they want? People like the director, Darren Aronofsky, who's a good friend of mine, an amazing di
what's amazing about it is that it's an image generator. It's state-of-the-art and best-in-class. But one of the things that makes it so great is consistency. It's able to, under instruction, follow what you want changed and keep everything else the same. And so, you can iterate with it and eventually get the kind of output that you want. And that's, I think, what the future of a lot of these creative tools is going to be and sort of signals the direction. And people love it. And they love creat
No, I mean, we're not seeing that internally. And we're still seeing a huge rate of progress.
I think that we are maybe, I would say sort of five to 10 years away from having an AGI system that's capable of doing those things.
we've applied our AI systems to many branches of science, whether it's material design, helping with controlling plasma and fusion reactors, predicting the weather, solving, you know, maths Olympiad, maths problems. And the same types of systems with some extra fine tuning can basically solve a lot of these complex problems.
AI today, I would say, doesn't have true creativity in the sense that it can't come up with a new conjecture yet or a new hypothesis. It can maybe prove something that you give it, but it's not able to come up with a sort of new idea or new theory itself. So I think that would be one of the tests actually for AGI.
I think eventually we will have millions of robots helping society and increasing productivity. But the key there is when you talk to hardware experts is, at what point do you have the right level of hardware to go for the scaling option? Because effectively, when you start building factories around trying to make tens of thousands, hundreds of thousands of a particular robot type, you know, it's harder for you to update, quickly iterate the robot design. So it's one of those kind of questions w
I think we're still a little bit early on robotics. I think in the next couple of years, there'll be a sort of real wow moment with robotics. But I think the algorithms need a bit more development. The general purpose models that these robotics models are built on still need to be better and more reliable and better understanding the world around it. And I think that will come in the next couple of years.
Exactly. That's certainly one strategy we're pursuing is a kind of Android play, if you like, as a kind of robotics, almost an OS layer, cross-robotics. But there's also some quite interesting things about vertically integrating our latest models with specific robot types and robot designs, and some kind of end-to-end learning of that too. So both are pretty interesting, and we're pursuing both strategies.
And then with robotics, we've built something called Gemini Robotics Models, which are sort of fine-tuned Gemini with extra robotics data. And what's really cool about that is, and we released some demos of this over the summer, was we've got these tabletop setups of two hands interacting with objects on a table, two robotic hands. And you can just talk to the robot. So you can say, put the yellow object into the red bucket or whatever it is. And it will interpret that instruction, that language
So the reason we're building these kind of models is we feel, and we've always felt, we're obviously progressing on the normal language models like with our Gemini model. But from the beginning with Gemini, we wanted it to be multimodal. So we wanted it to input and take any kind of input, images, audio, video, and it can output anything. And so we've been very interested in this because for an AI to be truly general, to build AGI, we feel that the AGI system needs to understand the world around
This model is reverse engineering intuitive physics. So, you know, it's watched many millions of videos and YouTube videos and other things about the world. And just from that, it's kind of reverse engineered how a lot of the world works. It's not perfect yet, but it can generate a consistent minute or two of interaction as you as the user in many, many different worlds. There are some videos later on where you can control, you know, a dog on a beach or a jellyfish. That's not limited to just hu
all of these videos, all these interactive worlds that you're seeing, so you're seeing someone actually can control the video. It's not a static video. It's just being generated by a text prompt, and then people are able to control the 3D environment using the arrow keys and the space bar. So everything you're seeing here is being fully, all these pixels are being generated on the fly. They don't exist until the player or the person interacting with it goes to that part of the world. So all of t
there's around 5,000 people in my org, in Google DeepMind. And it's predominantly, I guess, 80% plus engineers and PhD researchers. So, yeah, about 3,000 or 4,000.
the way I describe it now is that we're the engine room of the whole of Google and the whole of Alphabet. So Gemini, our main model that we're building, but also many of the other models that we also build, the video models and interactive world models, we plug them in all across Google now. So pretty much every product, every surface area has one of our AI models in it. So billions of people now interact with Gemini models, whether that's through AI overview, AI mode, or the Gemini app. And tha