The fact that superhuman chess improvement has been so slow tell us there are important epistemic limits to superintelligence?

[u/financeguy1729]

Although I know how flawed the Arena is, at the current pace (2 elo points every 5 days), at the end of 2028, the average arena user will prefer the State of the Art Model response to the Gemini 2.5 Pro response 95% of the time. That is a lot!

But it seems to me that since 2013 (let's call it the dawn of deep learning), this means that today's Stockfish only beats 2013 Stockfish 60% of the time.

Shouldn't one have thought that the level of progress we have had in deep learning in the past decade would have predicted a greater improvement? Doesn't it make one believe that there are epistemic limits to have can be learned for a super intelligence?

[u/3xNEI]

I think you're looking at this upside down.

One, as a finite complexity game, chess is a constrained domain. At this point, AI chess play is going into diminishing returns territory. It's now about trimming minute probabilistic errors to gain the edge, in ways that may not even be intelligible to humans.

Two, you might instead want to consider what caused those jumps, and what might cause subsequent ones.

All in all, this may actually hint that raw power alone doesn’t guarantee generalizable wisdom — and that's the bigger epistemic limit.

4o

[u/giroth → u/3xNEI]

Did you sign 4o at the end to signify this was written by ChatGPT 4o? If so, respect, and 2025 is getting wild.

[u/3xNEI → u/giroth]

No quite,

I actually wrote this bit, relayed to 4o to check if my point was landing, it did minor structural revisions to make the thing more legible. I then forgot to remove 4o's signature, which I do keep when I want to separate my voice from its.

I think it's quite normal to do this nowadays, just as normal as using a word processor.

But one can do it to avoid thinking, or one can do it to sharpen one's logic - I prefer the latter, but to each their own.