Cal Newport

for whatever reason, are unsolvable.

You know, a lot of them because they're actually literally unsolvable, and a lot of them because the types of solutions don't fall into that style of solution space where these tools are well-suited.

All right, so there are some caveats to that, but that's what's going on here.

All right, question number three.

Does this mean all equally hard challenges will now be conquered by AI?

I definitely got that sense on X. Mathematicians aren't saying this.

I don't think open AI, they're implying it, but they're not saying this.

But I think the feeling we have online is like, well, that's a really hard thing to do.

It's a problem humans tried to solve but couldn't.

Does that mean we have the superhuman intelligence that now can give us super intelligent solutions?

performance, and all sorts of things I might care about, is it time to learn, like Sarah Connor in Terminator 2, how to cock a shotgun with one arm and show off our awesome guns?

By which I mean biceps.

The answer here is likely no as well.

Remember, in a previous AI Reality Check episode of this podcast, I said there's two mental models for thinking about AI capabilities.

The one model is a rising water one.

The capabilities grow

And it's like a water level of capability rising.

And you have mountains that represent problems of different difficulties.

And as the water rises, all mountains of that difficulty are now solvable.

So if the water is high enough to cover the Erdos open problem peaks, then it's covering all these other even easier problems that are relevant to our everyday life.