hgm wrote:1GB hash seems pretty big. Have you actually measured if there is any advantage whatsoever of increasing the hash size?
And how much would AlphaZero gain by using a book, and not having to run at fixed time per move, in your estimate?
1GB hash is far too low. I have immense respect for the deepmind team, but this was a pretty serious error.
At 70 million positions/second, that 1GB of hash is being overwritten once every second (10 bytes per entry = 700MB overwritten/second). Even worse, it's being contended by all 64 threads on the same 1GB of RAM. To give some context, we usually play our 60 sec games with 64Mb of hash, with one thread!
In these games, at 1 minute/move, the hash table is all but useless. It should probably have been 32 or 64GB, and the machine certainly had that much RAM.
Yeah 100 elo above stockfish isn't like what they have accomplished with Go. However, I wonder how strong alphaZero could get given more training and optimizations specific to chess. Since AlphaZero was, basically, for any board game I think there might be a lot of improvements.
gladius wrote:1GB hash is far too low. I have immense respect for the deepmind team, but this was a pretty serious error.
At 70 million positions/second, that 1GB of hash is being overwritten once every second (10 bytes per entry = 700MB overwritten/second). Even worse, it's being contended by all 64 threads on the same 1GB of RAM. To give some context, we usually play our 60 sec games with 64Mb of hash, with one thread!
But normally you would only start to notice any effect if you overload the hash table more than a factor 10, and even then the speed only goes down as the 12th root of the hash size. That would mean 5-8 Elo/memory doubling. The factor 10 is reached in 14 sec, so you miss only 2 doublings, or 10-16 Elo. And at fixed time per move, the last 15sec of each move might often not be used at all.
Have you actually measured how much Elo you lose by overloading the hash table a factor 40 at fixed time per move?
mario carbonell wrote:One possible explanation it that chess engines are near the maximum strength possible, that may be around 3600 or 3700 elo.
We can see that in the game of go, AlphaZero was still learning, but at chess seemed to have arrived to a plateau. Maybe the maximum strength?
That also speaks about the very good work done in Stockfish, that is very near to A0.
The problem with chess is that the draw result exists, and even one or two pawns difference in material is not enough to win.
What if it just needs more steps than in go? Even in go it looks like it had already hit an early wall between 350K and 500k+ something, but in hindsight that assumption would have been wrong.
We would only know if it still tries to learn and we get more data.
Vinvin wrote:The results of the match AZ vs SF8 is translated in +100 Elo for AZ.
The weakened part of Stockfish for this match is already known :
1) Only 1 GB hashtable (64GB to 128GB would have been more way more suitable)
2) 1 minute by move fixed time control
3) No opening book for Stockfish (AZ saved his opening knowledge from its previous games)
4) Only version 8 (the current development version is already about 40 Elo above)
With this 4 points upgraded to a regular level, the current Stockfish version would been already 100 Elo stronger.
CheckersGuy wrote:Yeah 100 elo above stockfish isn't like what they have accomplished with Go. However, I wonder how strong alphaZero could get given more training and optimizations specific to chess. Since AlphaZero was, basically, for any board game I think there might be a lot of improvements.
Let's bet the improvements will be 0.0 in 5 years' time.
This is their peak.
You can not achieve an engine much stronger than 2800 with such algorithms.
mario carbonell wrote:One possible explanation it that chess engines are near the maximum strength possible, that may be around 3600 or 3700 elo.
We can see that in the game of go, AlphaZero was still learning, but at chess seemed to have arrived to a plateau. Maybe the maximum strength?
That also speaks about the very good work done in Stockfish, that is very near to A0.
The problem with chess is that the draw result exists, and even one or two pawns difference in material is not enough to win.
Did not we think the Kasparov level, 2850, was about the maximum one could achieve?
Chess will NOT be solved before 5500 elos are attained, I guess even 7000.
My proofs?
Well, I am able to get better positions than SF almost everywhere, in open and closed games alike, just that I am not able to win all. SF makes suboptimal moves quite often, maybe every second or even every 2 out of 3.
mario carbonell wrote:One possible explanation it that chess engines are near the maximum strength possible, that may be around 3600 or 3700 elo.
I think they reached "the maximum strength possible" of this configuration of the neural network. But it can be improved !!
In what way?
If it learns by itself?
Did not they say they are NOT touching the code at all?
And then what will they change?
I thought the assumption was you give the engine the raw rules of chess, and nothing else, and it starts learning.
Well, that is what it managed to learn.
