Demis Hassabis谈AI未来：10年内或可治愈所有疾病

weak and easy [music] questions. Please try to answer in one sentence, sometimes one word.

Oh, wow. That's hard. Um,

Fineman or Newton.

Oh, wow. That's even harder. [laughter]

Dennis, I don't know if I told you, but my mother recently got some health scan results. It was a massive video file, and we had to wait for weeks for the evaluation, and we were really anxious.

And then I thought, wait, Gemini, long context, you know, why not give it a look? and it analyzed the scan and said don't worry it's it's fine and and later the doctor verified that fantastic that it's it nailed it

and I am really grateful for that

and I was about to say thank you.

Mhm.

Uh but in the meantime you also released Gemma 4

free local AI that can likely do the same with a little compassion.

Just wanted to say these are a gift to humanity and thank you so much for doing this for the little man.

Fantastic. Well, I'm I'm glad to hear that. It's it's it's and I'm glad to hear your mom's fine, but it's uh we've had a lot of anecdotes like that of people using Gemini for health reasons and actually in some cases life savings. So uh advice so I think it's an incredible use case. So I'm glad it helped.

Yeah. Yeah. Thank you very much. Now Jensen Hang of Nvidia says that he uses LLM as a confidant for decision- making.

What about you? Do you use Gemini for things beyond research?

Yes. Um, I don't use it quite as a confidant yet, although maybe at some point I will. I use it a lot for brainstorming. So, you know, project ideas, project names, uh, uh, you know, think creative ideas. I quite like it as a kind of sparring partner for that. Uh, and that's probably the main use. And then I also use uh uh for for and to you know look at summarize some new area of research some new body of research I'm not so expert in but I want to get a quick take on you know the main key points.

Do you use it to get your ideas criticized like like fire up deep think you know mathematical Olympia and now criticize my idea?

Yes. Uh I have a yes I I mostly use it for uh helping me kind of think through some of the steps I've been thinking of as well. I mean I guess you could call it critiquing it, but it's I try it in a more collaborative frame rather than maybe I should try it with more like be harsher come up with the the the the flaws in this. Um but I definitely use it as a kind of sparring partner.

Amazing. Now, when I heard you got the Nobel Prize, I thought finally some proper recognition for the theme park AI. [laughter]

Exactly. Exactly. Took a while.

Yes. And then I heard John Jumper say something that really stuck with me. He said that he's looking forward to seeing someone use your alpha technique to invent something to win the prize.

I thought,

let's call it the second order Nobel.

Yeah.

So, do you expect that to happen?

Second order Nobel. That's a really interesting idea. I I I am I think it's it's possible um given the number of researchers who are using Alphafold, you know, over 3 million at this point and they're all doing incredibly important work and impactful work. So, uh yeah, I guess that that that John's right that may happen at some point. That would be an amazing moment.

Amazing. Now, you have a system called co-scientist that can invent new things.

Can you tell me about it? Yeah, you can think of CO scientist as a sort of um fine-tuned version of Gemini that's specifically uh with extra tools and extra harnesses on top that uh is specific for helping with hypothesis generation, helping you analyze data, helping you uh summarize literature as well. So, it's the beginnings of a kind of almost like having a great research assistant that's helping you in your daily work.

It's incredible. By the way, the new hypothesis generator,

they also tried it.

Oh, great.

Gave it some ideas. Yes.

And then it was interesting interesting because it it it wants you to narrow down the idea because you just you just say something and then just the result was absolutely amazing like wait the eight hours and then I was like this this is incredible and I tried it on on on my original area ray tracing global illumination very little training data very few people do that. So that's I I think it's pretty cool to see it perform on that on that not just on

and it came back with some interesting sensible ideas helped you.

Okay.

I wish I wish I had more time. [laughter]

Me too. Me too. This is the problem is actually finding the time now to to do that. We almost need I feel like we almost need really good AI assistants to help deal with our admin work. We have to do all of that stuff. So we have more time for using co-scientist. Right. This is my dream too. on April 20th, 2025, you said, "I think one day maybe we can cure all disease with the help of AI, maybe within the next decade.

I don't see why not."

When I saw that,

I got so excited.

I made a website for that.

Oh, cool.

cure all disease.com.

Okay.

And I have some data in there and I wrote,

"Check back often because I will update it with new data."

Fantastic. and

never updated.

Yeah. Well, [laughter] we're working hard.

Uh, no. Yeah, but it won't be it won't be uh a gradual thing. It'll be more like Alpha Fold is the way I'm thinking about it. We're building isomeorphic labs and and also our spin out and also uh at Deep Mind as well in our science group um more and more tools. You can think of it as building a platform. you know alpha fold's one of the components of that the the you know um advanced versions of alpha fold but as you know protein structure is only one component it's an important component but it's only one step in the drug discovery process so we're building you can think another half dozen to a dozen alpha fold level models that are on different parts of the of the drug discovery process and then we got to put that all together and of course test it on um some uh some disease profiles which is what we're doing now in pre-clinical stage um and then once we've proven that out which I think will take a few more years then we may have a an engine that can be applied to you know a platform that can be applied to almost any disease area that's the hope so a bit like with alpha fold 2 you know you get it accurate enough and then suddenly you can fold all 200 million proteins in one year so it's going to be more like that so you may not have any updates on your website for a few years and then suddenly I hope there will be some big breakthrough cruise where then you'll have you know you won't be able to you have to update it every day. [clears throat]

Okay. I think I've heard something similar from from Watson's talk. He said that the process is going to be exponential.

Mhm.

And then at year year five they said that well you're only at I don't know 8%. What are you doing? And he said no that's fantastic. I mean if it's doubling every year we are way ahead.

Yes. He may he may have been by the genome project probably or or the human genome project. That's exactly right. And and we've already seen this once with Alphault. So, um, I we need to rep, you know, replicate that success. Obviously, it's much much more complex. Um, and I also meant by that as well that we would potentially have a a platform that could come up with those uh potential cures. You still would need to test them in the clinic and and and go through that process.

That could still take more time.

Speed that up.

I think actually AI could also help with that, too. Like stratify patients, maybe predict dosages better, all of those things. So I actually think AI could probably speed that up too. Um so there's two parts you know to drug. You got to do the drug discovery process and then you've got to do the clinical trials and right now we're focusing on the first part but I think AI could also help with the second part. That'

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