Sure, but both of them are more brute force than Deep Blue (unless anybody has a compelling counter argument), so we’re actually heading in the wrong direction.

AlphaZero evaluates comparably less positions per second than Deep Blue. It doesn't even reach 100k nodes per seconds of I remember correctly, while Deep Blue was in the millions[1]. Therefore, even though the training is done by brute force, the evaluation is way less "brute forcing" in AlphaZero than in Deep Blue.

Not just Stockfish on modern hardware can evaluate fewer nodes than Deep Blue and still beat it left and right; in 1995 Fritz on a Pentium was able to beat Deep Thought II at the world chess championship. Deep Blue and its ancestors, with their custom hardware, were perhaps the "most brute force" of all chess engines.

[1] https://www.stmintz.com/ccc/index.php?id=91692

As you yourself point out, the brute force here refers to solving a problem by throwing more hardware at it.

Number of nodes searched is not the key metric for gauging how “smart” the algorithm is. You have less nodes searched but you only got there by having way more upfront processing.

But that processing happens just once, and then you amortize it over the software's lifetime. Play a million games and you probably come out ahead.

And what is an estimation of the minimal hardware/time requirements for learning to beat humans at chess?

We need some baseline to call it "brute force".

Seems like ML/AI is still looking for its quantum supremacy moment.

It should be pointed out AlphaZero plays better than Deep Blue. I think comparing computational resource usage is important, but direct comparison only makes sense with equivalent performance level.

I did point this out at the top of my original comment.

“I mean, it's cool that computers are getting even better at chess and all“

> direct comparison only makes sense with equivalent performance level

This makes no sense to me. 50% increase in performance can be compared to 50% increase in processing power to evaluate level of brute force-ness.

> This makes no sense to me. 50% increase in performance can be compared to 50% increase in processing power to evaluate level of brute force-ness.

Computational complexity theory taught us that fundamental difficulty of solving specific types of problems does not always linearly scale with the size of the problems. I guess the same logic applies to the quality of the output?

Yes, but how is "50% better" measured? On what scale?

Easy. Chess uses the Elo rating system.

https://en.m.wikipedia.org/wiki/Elo_rating_system

I mean that ELO is not linear and there is no obvious ratio operation for ELO scores. How much is better than 2,600? Is it 5,200? Is it the rating at which you'd have 2:1 odds of winning a match? (Wikipedia says 200 points represent 74% chance of winning, so somewhere below 2,800) There's just no commonly agreed meaning of "50% better Chess player".