Demis Hassabis en el podcast Release Notes
- Podcast: Release Notes
- Enlace a YouTube
Descripción del episodio
Demis Hassabis, director ejecutivo de Google DeepMind, conversa con el presentador Logan Kilpatrick. En este episodio, conocerás la evolución desde la IA que juega a videojuegos hasta los modelos de pensamiento actuales, cómo proyectos como Genie 3 están construyendo modelos del mundo para ayudar a la IA a comprender la realidad y por qué se necesitan nuevos campos de pruebas, como Game Arena de Kaggle, para evaluar el progreso en el camino hacia la AGI (inteligencia artificial general).
Clips resaltados
Genie 3 genera modelos de mundos coherentes y persistentes al simular entornos:
But one great way is to just get it to reverse it and sort of generate something about the world. Like, you know, you turn on a tap and some liquid comes out of it, or there's a mirror and can you see yourself in the mirror, all of these things. And that's what Genie is sort of going towards is building that world model and then expressing it and actually be able to generate worlds that are consistent. And that's the surprising thing about Genie 3 is that, you know, you look away, you come back, and that part of the world is the same as you left it link
La planificación y razonamiento paralelos son claves para alcanzar AGI mediante deep thinking:
And then you need some thinking or planning or reasoning capability on top. And this is obviously the way to get to, you know, AGI. And then, of course, once you have thinking, you can do deep thinking or extremely deep thinking and then sort of have parallel planning. You know, you can do sort of planning and thoughts in parallel and then collapse on onto the best one and then make a decision and then move on to the next one. link
Auto-reflexión:
you want to sort of go back and refine your own thought processes which is in effect what the thinking systems link
Jagged intelligence y falta de consistencia como barrera para la AGI completa:
on the other hand, they can still make simple mistakes in high school maths or simple logic problems or simple games if they're posed in a certain way. So that must mean there's still something kind of missing. link
And in my opinion, this is one of the things that's missing from these systems being full AGI is the consistency. link
Se destaca la importancia de Game Arena para crear benchmarks más complejos y significativos:
I think there's actually really amazing work to be done in creating benchmarks that are really meaningful, that test slightly more complicated or subtle things than the sort of Brute force school exam type things that we have today. And that's why I'm so excited about Game Arena because, and it is going a little bit back to our roots, of course, which is why we came up with it. link
Cada partida es única; planean expandir el Game Arena de ajedrez a miles de juegos:
each game is unique because it's created by the two players. So there's a kind of uniqueness about that. So that's also nice for testing and then the final thing is just like we did with our own early games work as the systems get better and better you can introduce more and more complex games Into the game arena so we started with chess um for obvious reasons it's the classic one we test ai on um it's close to my heart of course but we the idea is we're going to expand it to potentially thousands of games link
La integración de herramientas externas en sistemas IA plantea límites difusos entre modelo y herramienta:
A lot of the thinking, the reason the thinking is part of the systems is very important is because you can use tools during the thinking, right? You can call search, you can, you know, use some math program, you can do some coding, come back, and then update your planning on what you're going to do. So I think that's still actually fairly nascent at the moment, but I think that's going to be incredibly powerful once that becomes really reliable and we work out, and the systems become Good enough, they can use pretty sophisticated tools very reliably. And then the interesting thing comes is, what do you leave as a tool versus put into the main system, the main brain, so to speak? Now, with humans, it's easy because we're physically constrained. So anything that's not in our body is a tool, right? So there's no question about what's a tool, what's our brain. But with a digital system, you can actually kind of, those things can get blurred. So should it be in the main model, the capability, for example, to play chess or something? Or do you just use Stockfish or AlphaZero as a tool? And that tool could also be an AI system. It doesn't have to be a piece of software. It could actually be something like AlphaFold or whatever. link
El diseño de productos exige prever avances tecnológicos y permitir reemplazo modular frecuente:
the hard part and we've talked about this before is in this new world is you've got I think it requires very interesting skills from a product manager or product designer type of you Know role because you've got to sort of design say your product's coming out in a year you've got to be really close and understand the technology well to kind of intercept where that Technology will be in a year's time and design for that right and um and i think uh i've also whatever polish product polish you put on top uh of your product it has to allow for the engine Under the hood to be unplugged and plugged back in with a more advanced uh system you know, that's coming out every three to six months link
El sueño post-AGI:
Logan Kilpatrick: I feel like Genie 3 is a good excuse for us to have a chance to make games and play them and then DeepMind's a video game.
Demis Hassabis Well, you know, that's always my secret plan is maybe like post-AGI, once that's done safely over the line, you know, go back with these tools and make the greatest game ever. That would be a real dream come true. link