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huh? what could op mean by 'The "success of Alpha Zero" was largery a PR stunt and the field has moved on long since then.' The commenter is suggesting that t

by singularity2001 4y ago

huh? what could op mean by 'The "success of Alpha Zero" was largery a PR stunt and the field has moved on long since then.' The commenter is suggesting that the success of Alpha Zero was largely exaggerated for public relations purposes, and that advancements in the field have since progressed beyond it. This likely implies that the commenter considers Alpha Zero to be less significant than it was initially made out to be. I still don't get the phrasing "PR stunt" in this context

mtlmtlmtlmtl 4y ago
The match between alpha zero and stockfish was a PR stunt specifically because the match was partially fixed; Stockfish was run with unoptimal settings without an opening book. AlphaGo and AlphaZero Go were a significant achievement. AlphaZero was just applying the same training process to western chess with a huge amount of compute, running it against stockfish on a handful CPUs with suspicious settings and making a big fuzz about the result. There are good reasons to believe that the searching method and size of neural net employed in AlphaZero, while very strong for go, is just overkill for a game like chess, and that the conventional techniques are just a far better fit. The best reason is the almost total dominance of Stockfish since the PR stunt. Another is that chess is in a different complexity class than go, so it's only reasonable to expect that different algorithms will be superior in chess versus go.
- singularity2001 4y ago
  very insightful, thanks
  - mtlmtlmtlmtl 4y ago
    Also of note is Leela Chess Zero, which is essentially the open source, weights available reimplementation of AlphaZero, trained using decentralised training among other things, I believe. A lot of the work Deepmind did with AlphaZero had to be painstakingly redone by the community and it took years. I'd feel bad if I didn't mention them too, they've done a great job. I'm working on my own weird ideas within this space that are quite different from both stockfish and leela zero(but partially taking inspiration from both) but that's still very much under construction...

mtlmtlmtlmtl 4y ago

The match between alpha zero and stockfish was a PR stunt specifically because the match was partially fixed; Stockfish was run with unoptimal settings without an opening book. AlphaGo and AlphaZero Go were a significant achievement. AlphaZero was just applying the same training process to western chess with a huge amount of compute, running it against stockfish on a handful CPUs with suspicious settings and making a big fuzz about the result. There are good reasons to believe that the searching method and size of neural net employed in AlphaZero, while very strong for go, is just overkill for a game like chess, and that the conventional techniques are just a far better fit. The best reason is the almost total dominance of Stockfish since the PR stunt. Another is that chess is in a different complexity class than go, so it's only reasonable to expect that different algorithms will be superior in chess versus go.

singularity2001 4y ago
very insightful, thanks
- mtlmtlmtlmtl 4y ago
  Also of note is Leela Chess Zero, which is essentially the open source, weights available reimplementation of AlphaZero, trained using decentralised training among other things, I believe. A lot of the work Deepmind did with AlphaZero had to be painstakingly redone by the community and it took years. I'd feel bad if I didn't mention them too, they've done a great job. I'm working on my own weird ideas within this space that are quite different from both stockfish and leela zero(but partially taking inspiration from both) but that's still very much under construction...