I respect what this team is doing, actually, all the ingredients to make bots like human are in place it’s a matter of time. Chess.com could have done this, but there is no such demand, what a difference such bot can make when you have millions of actual human playing.
I don’t know the team, who they are, professional data scientists, chess players, talented developers or a bit of all, but they should not have used AlphaZero in this context, as Zero (if you check name evolution) means a version without human data
“By playing games against itself, AlphaGo Zero surpassed the strength of AlphaGo Lee in three days by winning 100 games to 0” Google team introduced this zero approach on game Go, but logic stands for chess as well.
Bots with different elo = they train bots on games with different elo rating, but the fact that bot trained on 1500 games has 1700+ actual elo means something in their approach is wrong (revealing common chess engine performance on top of human-like NN).
I don’t know the team, who they are, professional data scientists, chess players, talented developers or a bit of all, but they should not have used AlphaZero in this context, as Zero (if you check name evolution) means a version without human data
“By playing games against itself, AlphaGo Zero surpassed the strength of AlphaGo Lee in three days by winning 100 games to 0” Google team introduced this zero approach on game Go, but logic stands for chess as well.
Bots with different elo = they train bots on games with different elo rating, but the fact that bot trained on 1500 games has 1700+ actual elo means something in their approach is wrong (revealing common chess engine performance on top of human-like NN).