Is AlphaZero really a breakthrough in AI?

Post by forgot-my-pw » Thu, Dec 14, 2017, 7:41 PM UTC

roganp wrote: post #63

super_mario wrote: post #61

I would like to see a rematch with Stockfish configured correctly. I give Stockfish at least 1 GB of hash per thread. In AlphaZero match they had 64 threads and only 1 GB of hash for all of them. No one knows how Stockfish behaves with that many search threads, since no one tested it. I don't know if there is any data on how Stockfish scales with number of CPUs but I seem to remember that being one of the weaknesses…

It seems to me that that someone can prove that the configuration mattered by pitting a correctly configured Stockfish against the configuration used by AlphaZero, and see what the outcome is for 100 games. I haven't read the paper, but some of the constraint choices seem odd to me (1 minute max per move?).

Post by forgot-my-pw » Thu, Dec 14, 2017, 7:51 PM UTC

seanwilson wrote: post #47

Given their track history, I don't think it's likely the DeepMind team are trying to be sneaky here. They'd be found out eventually given how big their claim is. When working in academia, I found it very common for research papers to not come with source code or enough information to allow you to replicate experiments yourself. You usually have to pester the author. I don't find the (valid) criticisms here that unusu…

Post by amarkov » Thu, Dec 14, 2017, 10:26 PM UTC

YeGoblynQueenne wrote: post #40

rstuart4133 wrote: post #4

The article glosses over why the 4 hours was possible. Firstly, a major challenge in training an AI of this sort is getting enough labelled data. They played 300,000 games from memory. Under normal circumstances, that requires access to 300,000 games played by experts so the AI can learn to copy what the export does. That is how Alpha Go did it. AlphaZero neatly side steps this by generating it's own training data by…

>> Finally, he overstates how hard it is to customise the engine (Markov algorithm + AI) to a game. I think you're imagining some setup in which a neural net is directly communicating with an external rule engine that generates a set of legal moves for each piece in each board configuration. That's not how it works. You know how people say that Neural Nets are "black boxes"? That's what they mean. You can't just plug…

Post by vatueil » Fri, Dec 15, 2017, 12:52 AM UTC

forgot-my-pw wrote: post #73

seanwilson wrote: post #47

Given their track history, I don't think it's likely the DeepMind team are trying to be sneaky here. They'd be found out eventually given how big their claim is. When working in academia, I found it very common for research papers to not come with source code or enough information to allow you to replicate experiments yourself. You usually have to pester the author. I don't find the (valid) criticisms here that unusu…

They hinted that a full paper will be released in the future.

Post by seanwilson » Fri, Dec 15, 2017, 2:43 AM UTC

pdpi wrote: post #53

seanwilson wrote: post #47

Given their track history, I don't think it's likely the DeepMind team are trying to be sneaky here. They'd be found out eventually given how big their claim is. When working in academia, I found it very common for research papers to not come with source code or enough information to allow you to replicate experiments yourself. You usually have to pester the author. I don't find the (valid) criticisms here that unusu…

More hardware still means better results — or there would be no need to cap the time per move. It’s always been a trade off between using more expensive heuristics on fewer moves or cheaper heuristics on more moves. The “number of moves” thing only says that they went all-in on the better heuristics angle. In fact, there was something posted recently about test games where they played go by just using the first move…