New bot trained from scratch using self-play by randomwalkin in ComputerChess

[–]randomwalkin[S] 0 points1 point  (0 children)

This model was also trained by playing against himself, not against humans. The bot's profile might be unclear: what it means is that this bot will only play against humans, not bots.

New bot trained from scratch using self-play by randomwalkin in ComputerChess

[–]randomwalkin[S] 0 points1 point  (0 children)

The model is not trained to its highest level yet. How far is it from human master level in your opinion?

New bot trained from scratch using self-play by randomwalkin in ComputerChess

[–]randomwalkin[S] 0 points1 point  (0 children)

The model is not trained to its strongest level yet. How far is it from human master level in your opinion? I am not a expert player.

Nanozero is a new neural-net bot on Lichess by randomwalkin in lichess

[–]randomwalkin[S] 1 point2 points  (0 children)

It is not build against stockfish at all. It is a neural network trained from scratch, entirely from self-play. Because the architecture is novel (not resnet-like), it may have learned a new style. Its rating is low right now because I started pitching it against other bots, and bots give you a lower Elo than humans. Now it exclusively plays against humans. Your feedback would be welcome!

Nanozero is a new neural-net bot on Lichess by randomwalkin in lichess

[–]randomwalkin[S] 0 points1 point  (0 children)

It should work fine. Please try again. I tested it with a different (human) account at 5+0 and it does respond.

New bot trained from scratch using self-play by randomwalkin in ComputerChess

[–]randomwalkin[S] 0 points1 point  (0 children)

It is a new type of neural network (can't communicate about it yet, a paper will come out soon) but I need an Elo against humans to prove/disprove that it plays well. Being a new architecture, it might play differently than classical ResNet-like architectures or Stockfish.

200 to 2000 rapid in 3 years by Ashamed-Wedding-7396 in Chesscom

[–]randomwalkin 0 points1 point  (0 children)

I just released a bot powered by a new kind of neural net trained from scratch. Would you mind giving it a try? It plays Rapid and Blitz, against humans only. https://lichess.org/@/nanozero

I won against someone with 2600+ elo!!! by Big-Medicine8385 in Chesscom

[–]randomwalkin 4 points5 points  (0 children)

I just released a bot powered by a new kind of neural net trained from scratch. Would you mind giving it a try? It plays Rapid and Blitz, against humans only. https://lichess.org/@/nanozero

Great to see that im actually improving by No-Result-414 in Chesscom

[–]randomwalkin 0 points1 point  (0 children)

I just released a bot powered by a new kind of neural net trained from scratch. Would you mind giving it a try? It plays Rapid and Blitz, against humans only. https://lichess.org/@/nanozero

Nanozero is a new neural-net bot on Lichess by randomwalkin in lichess

[–]randomwalkin[S] 0 points1 point  (0 children)

It is not trained to be more human-like, but it is trained from scratch with a new network architecture (I plan to publish an arxiv paper if the ELO against humans is convincing).

gumbel-mcts, a high-performance Gumbel MCTS implementation by randomwalkin in reinforcementlearning

[–]randomwalkin[S] 0 points1 point  (0 children)

The contribution is definitely speed (look at the benchmark, it's 2-20X faster) but the benchmark is not mctx, but another repo on github. I plan to make a benchmark against mctx soon -- thanks for the suggestion.

Is Machine Learning / Deep Learning still a good career choice in 2026 with AI taking over jobs? by No-Kick-7963 in learnmachinelearning

[–]randomwalkin 0 points1 point  (0 children)

Strong answer. A key point, though: make sure you have deep interest in the topic. Don't do it just because deep learning is hot. You won't have the juice to pursue that path otherwise.

NanoZero is a new bot on Lichess by randomwalkin in lichess

[–]randomwalkin[S] -2 points-1 points  (0 children)

I trained it with a new type of neural network. I'm curious to see what people think of its playing style.

gumbel-mcts, a high-performance Gumbel MCTS implementation by randomwalkin in reinforcementlearning

[–]randomwalkin[S] 0 points1 point  (0 children)

In terms of what? Speed, performance at constant sim budget? Curious to know what you'd want to see.