Hassabis sees information as more fundamental than matter or energy

Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

1. 17:30

   Or a traditional classical Turing computer? Well, look, I think you can, of course, all the famous, you know, equals MC squared and all the stuff Einstein did and energy and matter are kind of equivalent. But I actually think information has a kind of equivalency in the same way. So you can think of, you know, the organization of matter and structure and especially things like biology that are resisting entropy as basically information processing systems at their heart.

2. 17:57

   So I think one can convert all of those three kind of quantities into each other. But I have this feeling information is most fundamental. So it's a little bit the opposite way around to the classic physicist thought in the 1920s and things where, you know, it's sort of energy and matter primary. I actually think it's a better way to understand the world, the universe, is to think about it as information first.

3. 18:19

   And if that's true, and I think there's quite a lot of evidence for that, then of course AI is even more sort of profound in a sense than we think. And it's already pretty profound because it's also about organizing information and understanding information and constructing informational objects. So AI, in my opinion, is all about information processing. So I think there's something sort of very deeply connected with these different areas.

4. 18:49

   if you think of it through the lens of information processing as the primary way to think about it. And do you think a classical Turing machine will be able to compute everything? Well, I sometimes think, you know, I sometimes sort of think about what we're doing and refer to ourselves as Turing's champion because Turing machines, I think Alan Turing is one of my all-time, you know, favorite scientific heroes.

5. 19:11

   I think what he did obviously laid the foundations for the computers, for computer science, but also AI. and I think it's one of the most profound results ever is the Turing machine result. You know, everything that is computable can be computed by a relatively simple description of a machine. So I think our brains are likely to be approximate Turing machines and I think it's interesting to think about the connection between Turing machines and quantum computers and quantum systems but I think at least what we've shown with things like AlphaGo and especially AlphaFold is that a classical turing machine obviously in the guise of a modern neural network it can model what was thought to be in the case of protein folding it's a quantum system you know in some senses It's very, you know, it's dealing with very small particles and one might think you'd have to take into account all the quantum effects of the water bonds and all sorts of things.

6. 20:11

   But it turns out you can get to an approximate optimal sort of solution on a classical system. So it may turn out that a lot of things that we think that would need a quantum system to model or run might be modelable on a classical system if thought about in the right way.