From its reference announcement on github:
- Research and experimentation with self-play training in Go. Contains a working implementation of AlphaZero-like training with a lot of modifications and enhancements. Due to these enhancements, early training is immensely faster than in other zero-style bots – with a only few strong GPUs for a few days, even a single person should be able to train to mid or even high amateur dan strength on the full 19x19 board on consumer hardware. Also contains a GTP engine and pre-trained neural nets competitive with other top open-source Go engines. KataGo is also capable of estimating score and territory, and due to this right-out-of-the-box plays handicap games somewhat better than many other zero trained bots, without any special hacks.
KataGo is one of the two engines usable in the analysis program Lizzie, which now (from version 0.7.1 on) displays a graph of and shifts in KataGo’s score estimates. The default engine remains Leela Zero, which, however, does not provide a score estimate.