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mooreatyesterday at 8:31 PM2 repliesview on HN

I think one interesting thing to point out is that the proof (disproof) was done by finding a counterexample of Erdős' original conjecture.

I agree with one of the mathematician's responses in the linked PDF that this is somewhat less interesting than proving the actual conjecture was true.

In my eyes proving the conjecture true requires a bit more theory crafting. You have to explain why the conjecture is correct by grounding it in a larger theory while with the counterexample the model has to just perform a more advanced form of search to find the correct construction.

Obviously this search is impressive not naive and requires many steps along the way to prove connections to the counterexample, but instead of developing new deep mathematics the model is still just connecting existing ideas.

Not to discount this monumental achievement. I think we're really getting somewhere! To me, and this is just vibes based, I think the models aren't far from being able to theory craft in such a way that they could prove more complicated conjectures that require developing new mathematics. I think that's just a matter of having them able to work on longer and longer time horizons.


Replies

gus_massayesterday at 10:05 PM

Searching for a proof and disproof are sometimes not so different. In most cases, you nibble the borders to simplify the problem.

For example, to prove something is impossible let's say you first prove that there are only 5 families, and 4 of them are impossible. So now 80% of the problem is solved! :) If you are looking for counterexamples, the search is reduced 80% too. In both cases it may be useful

In counterexamples you can make guess and leaps and if it works it's fine. This is not possible for a proof.

On the other hand, once you have found a counterexample it's usual to hide the dead ends you discarded.

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davebrenyesterday at 10:02 PM

> I think that's just a matter of having them able to work on longer and longer time horizons.

No this will never do the kind of math that humans did when coming up with complex numbers, or hell just regular numbers ex nihilo. No matter how long it's given to combine things in its training data.

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