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a commercial chess entity by [[ChessBase]] featuring a set of custom made [[Neural Networks|neural network]] weights that work in the open source project [[Leela Chess Zero]] within its [[Leela Chess Zero#Lc0|Lc0]] executable. Initially announced introduced as a cloud project in August 2019, inspired by [[DeepMind|DeepMind's]] ground breaking [[AlphaZero]] approach combining [[Deep Learning|Deep learning]] with [[Monte-Carlo Tree Search]] (MCTS) <ref>[[David Silver]], [[Thomas Hubert]], [[Julian Schrittwieser]], [[Ioannis Antonoglou]], [[Matthew Lai]], [[Arthur Guez]], [[Marc Lanctot]], [[Laurent Sifre]], [[Dharshan Kumaran]], [[Thore Graepel]], [[Timothy Lillicrap]], [[Karen Simonyan]], [[Demis Hassabis]] ('''2017'''). ''Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm''. [https://arxiv.org/abs/1712.01815 arXiv:1712.01815]</ref>,further motivated by and [[Albert Silver|Albert Silver's]] [[Deus X]] experience, relaxing the Leela Chess' "Zero" paradigm of pure [[Reinforcement Learning|reinforcement learning]] due to [[Supervised KearningLearning|supervised learning]], Fat Fritz was released in November 2019 as part the [[Fritz|Fritz 17]] package,

The project was further discussed and supported its underlying techniques were emphasized by a talk of [[AlphaZero]] co-author [[Thore Graepel]] at [[ChessBase]], attended by German computer chess icon [[Thomas Nitsche]] along with his sons and [https://de.wikipedia.org/wiki/Math42 Math42] authors Raphael Nitsche and Maxim Nitsche <ref>[https://en.chessbase.com/post/fat-fritz-what-on-earth-is-that Fat Fritz – What on Earth is that?] by [[Albert Silver]], [[ChessBase|ChessBase News]], August 13, 2019</ref>, and . Fat Fritz was further supported by [[Daniel Uranga]] <ref>[https://en.chessbase.com/post/standing-on-the-shoulders-of-giants Standing on the shoulders of giants] by [[Albert Silver]], [[ChessBase|ChessBase News]], September 18, 2019</ref> <ref>[https://github.com/DanielUranga/lc0/tree/uci-wdl-reporting GitHub - DanielUranga/lc0 at uci-wdl-reporting]</ref>.