There's an interesting bias I've noticed on HN where a lot of people still believe AlphaZero is the state of the art in computer chess, when that hasn't been true except for a short while after the release. AZ still gets posted and upvoted today while newer improvements in other engines are discussed far less.
AZ revolutionized chess engine architecture and then moved on to other fields. Fast followers who incrementally improve upon the breakthroughs are very rarely recognized.
E.g. inventor of the blue LED versus those who improve the efficiency by .1%
It changed engine analysis of games because it doesn’t generate a series of “lines” that each has a centipawn value. It just gives you the move.
Subjectively, the Monte Carlo moves seem so human-like in comparison to minimax. Minimax can suggest a move that no human would play because the depth of calculation at which that move is good is just impossible for people.
The link you linked confirms what I already pointed out in another subthread. NNUE was invented by Yu Nasu for the game of Shogi. It bears very little resemblance to the AZ neural net. It's much more shallow, and inspired by work that pre-exists AZ, from the computer Shogi community. The way it trains is different, inference is different. The only commonality is the fact it's a neural net. But neural nets have been used for chess before in various capacities; Deepmind didn't invent this. All they did was throw a bunch of compute at it and do a big PR stunt then walk away.
I'm not sure where you get the LCZero connection from.
Well, AZ could perform above Stockfish by using much simpler principles. A lot of tinkering was required to get Stockfish to where it was, and AZ pretty much rediscovered and improved on some of these refined fine-tuned principles, such as board evaluation, opening books or endgames, from its own training. I think that's very impressive.
I guess it's because AZ came out of Google?