ELF OpenGo: An Analysis and Open Reimplementation of AlphaZero · HackerPapers discussions

ELF OpenGo: An Analysis and Open Reimplementation of AlphaZero — mentioned by espadrine

Sat, 18 Feb 2023 13:19:26 GMT

100K visits is a reasonably large amount. ELF OpenGo beat professional players 20:0 with 80K visits per move[0]. The AlphaGo version that beat Ke Jie likely did 200K visits per move, since the paper indicated that their 1600 simulations per move during training corresponds to 0.4s of think time (with 4 TPUs). On a good consumer GPU (RTX 3060), I get 1.6K visits per second, so 100K takes about a minute. That makes a game last three to five hours typically. But the paper emphasizes that even with 10M visits per move (>1h per move), KataGo loses 72% of games against this exploit[1]. [0]…

Paper and discussion history. A mention is not an endorsement.

ELF OpenGo: An Analysis and Open Reimplementation of AlphaZero — mentioned by newswasboring

Mon, 22 Jun 2020 17:59:29 GMT

From an offline chat with the original author, The ELF OpenGo paper[1], which is an open implementation of AlphaGo Zero developed by Facebook AI: "First, we train a superhuman model for ELF OpenGo. Af-ter running our AlphaZero-style training software on 2,000GPUs for 9 days, our 20-block model has achieved super-human performance that is arguably comparable to the 20-block models described in Silver et al. (2017) and Silveret al. (2018)." [1]: https://arxiv.org/pdf/1902.04522.pdf

Paper and discussion history. A mention is not an endorsement.

ELF OpenGo: An Analysis and Open Reimplementation of AlphaZero — HN submission

Wed, 13 Feb 2019 11:20:02 GMT

ELF OpenGo: An Analysis and Open Reimplementation of AlphaZero

6 points; 0 discussion replies on HN. Paper and source history. A submission is not an endorsement.