[qwertox]

Google DeepMind keeps publishing these things while having missed the AI-for-the-people train, that I'm getting more and more the feeling that they have such a huge arsenal of AI-tech piling up in their secret rooms, as if they're already simulating entire AI-based societies.

As if they're stuck in a loop of "let's improve this a bit more until it is even better", while AGI is already a solved problem for them.

Or they're just an uncoordinated, chaotic bunch of AI teams without a leader who unifies them. With leader I don't mean Demis Hassabis, but rather someone like Sundar Pichai.

[ks2048]

I don’t get the criticism. It seems like basic research and the kind of thing that would lead the way to “AGI” (combining llm-style prediction with logical reasoning). Unless you’re talking about what’s the point of publishing Nature papers - then it’s probably that the people involved want some concrete recognition in their work up to this point. And I supposed tech/investor press until they get something useful out from it.

[achierius]

I think Occam's razor would have something to say about the relative likelihood of those two options.

[hacketthfk]

They are optimizing for Nature papers, not general usability.

Not even one thing they did was without an associated Nature paper, and the paper was always first.

[extractionmech]

Maybe they have a secret client. I mean someone must be doing this for our side. If not them then who?

[generationP]

What they did here is one of the first steps towards an AI that generates nontrivial and correct mathematical proofs. (An alternative benchmark would be IMO-level inequalities. Other topics such as algebra, combinatorics and number theory are probably no easier than the rest of mathematics, thus less useful as stepping stones.)

And an AI that generates nontrivial and correct mathematical proofs would, in turn, be a good first step towards an AI that can "think logically" in the common-sense meaning of the word (i.e., not just mess around with words and sentences but actually have some logical theory behind what it is saying). It might be a dead end, but it might not be. Even if it is, it will be a boon to mathematics.

[nybsjytm]

This is at almost the polar opposite end of the spectrum from "AGI," it's centered on brute search.

[margorczynski]

Brute searching all possible mathematical constructs, theorems, etc. to see which one fits the problem would probably take you practiacally an infinite amount of time.

This works tbh, how I see it, very closely to how a human does - via "instinct" it gathers relevant knowledge based on the problem and then "brute searches" some combinations to see which one holds. But this "intuition" is the crucial part where brute search completely fails and you need very aggressive compression of the knowledge space.

[nybsjytm]

> Brute searching all possible mathematical constructs, theorems, etc. to see which one fits the problem would probably take you practiacally an infinite amount of time.

That's not the kind of search which is being done. Read this paper: https://doi.org/10.1023/A:1006171315513

[danielmarkbruce]

They are not polar opposites.

[senseiV]

> simulating entire AI-based societies.

Didnt they already have scaled down simulations of this?