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.
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.
We need some baseline to call it "brute force".
“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.
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?
<rant> DeepMind "superhuman" hype machine strikes again.
I mean, it's cool that computers are getting even better at chess and all (and other perfectly constrained game environments), but come on. "Superhuman" chess performance hasn't been particularly interesting since Deep Blue vs Kasparov in 1997.
The fact that the new algorithms have "no knowledge of underlying dynamics" makes it sound like an entirely new approach, and on one level it is. ML vs non-statistical methods. But on a deeper level, it's the same shit.
Unless I'm grossly mistaken, (someone please correct me if this is inaccurate), the superhuman performance is only made possible by massive compute. In other words, brute force.
But it uses less training cycles, you say! AlphaZero et all mastered the game in only 3 days! etc etc. This conveniently ignores the fact that this was 3 days of training on an array of GPUs that is way more powerful than the supercomputers of old.
Don't get me wrong. These ML algorithms have value and can solve real problems. I just really wish DeepMind's marketing department would stop beating us over the head with all of this "superhuman" marketing.
For those just tuning in, this is the same company that got the term "digital prodigy" on the cover of Science [0]. Which is again a form of cheating, because the whole prodigy aspect conveniently ignores the compute power required to achieve AlphaZero. For the record, if you took A0 and ran it on hardware from a few years ago, you would have a computer that achieves superhuman performance after a very long time, which wouldn't be making headlines.
</rant>
0. https://science.sciencemag.org/content/362/6419