Aria Finger

And I remember, you know, when I was in middle school, it was obviously the deep blue versus Garry Kasparov. And this was like a man versus machine moment. And one thing that you've gestured at about this moment is that it illustrated, like in this case, based on Grandmaster Data, it was like brute force versus like a self-learning system. Can you say more about that dichotomy?

I think so many people outside of sort of the AI realm would sort of be surprised that sort of it all starts with gaming, but that's sort of gospel for what we're doing. It's like, that's how we created these systems.

I think so many people outside of sort of the AI realm would sort of be surprised that sort of it all starts with gaming, but that's sort of gospel for what we're doing. It's like, that's how we created these systems.

I think so many people outside of sort of the AI realm would sort of be surprised that sort of it all starts with gaming, but that's sort of gospel for what we're doing. It's like, that's how we created these systems.

And so switching gears from board games to video games, can you give us just like the elevator pitch explanation for what exactly makes an AI that can play StarCraft II like AlphaStar so much more advanced and fascinating than the one that can play chess or go?

And so switching gears from board games to video games, can you give us just like the elevator pitch explanation for what exactly makes an AI that can play StarCraft II like AlphaStar so much more advanced and fascinating than the one that can play chess or go?

And so switching gears from board games to video games, can you give us just like the elevator pitch explanation for what exactly makes an AI that can play StarCraft II like AlphaStar so much more advanced and fascinating than the one that can play chess or go?

Can you double click on that for a moment? Like you said, it is in vogue to talk about, are we running out of data? Do we need synthetic data? Like, where do you stand on that issue?

Can you double click on that for a moment? Like you said, it is in vogue to talk about, are we running out of data? Do we need synthetic data? Like, where do you stand on that issue?

Can you double click on that for a moment? Like you said, it is in vogue to talk about, are we running out of data? Do we need synthetic data? Like, where do you stand on that issue?

I mean, that's wild. And thinking about benchmarks and what we're going to need these digital assistants to do, when we look under the hood of these big AI models, well, some people would say it's attention. So the trade-offs is thinking time versus output quality. We need them to be fast, but of course, we need them to be accurate.

I mean, that's wild. And thinking about benchmarks and what we're going to need these digital assistants to do, when we look under the hood of these big AI models, well, some people would say it's attention. So the trade-offs is thinking time versus output quality. We need them to be fast, but of course, we need them to be accurate.

I mean, that's wild. And thinking about benchmarks and what we're going to need these digital assistants to do, when we look under the hood of these big AI models, well, some people would say it's attention. So the trade-offs is thinking time versus output quality. We need them to be fast, but of course, we need them to be accurate.

And so talk about what is that trade-off and how is that going in the world right now?

And so talk about what is that trade-off and how is that going in the world right now?

And so talk about what is that trade-off and how is that going in the world right now?

So I want to go back to the world of multimodal that we were talking about before with sort of robots in the real world. And so right now, most AI doesn't need to be multimodal in real time because the internet is not multimodal. And for our listeners, that means absorbing many types of input, voice, text, vision at once.

So I want to go back to the world of multimodal that we were talking about before with sort of robots in the real world. And so right now, most AI doesn't need to be multimodal in real time because the internet is not multimodal. And for our listeners, that means absorbing many types of input, voice, text, vision at once.

So I want to go back to the world of multimodal that we were talking about before with sort of robots in the real world. And so right now, most AI doesn't need to be multimodal in real time because the internet is not multimodal. And for our listeners, that means absorbing many types of input, voice, text, vision at once.

And so can you go deeper in what you think the benefits of truly real-time multimodal AI will be? And like, what are the challenges to get to that point?