After AI beat them, professional Go players got better and more creative

This page summarizes the projects mentioned and recommended in the original post on news.ycombinator.com

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  • KataGo

    GTP engine and self-play learning in Go

  • > KataGo was trained with more knowledge of the game (feature engineering and loss engineering), so it trained faster.

    Not really important to your point, but it's not really just that it uses more game knowledge. Mostly it's that a small but dedicated community (especially lightvector) worked hard to build on what AlphaGo and LeelaZero did. Lightvector is a genius and put a lot of effort into KataGo. It wasn't just add some game knowledge and that's it. https://github.com/lightvector/KataGo?tab=readme-ov-file#tra... has a bunch of info if you're interested.

  • online-go.com

    Source code for the Online-Go.com web interface

  • https://online-go.com/ is the easiest place to get started as a western beginner. The far more active go servers are Asian and have a higher barrier to entry in terms of registration, downloading the client, and dealing with poor localization. (Fox Weiqi, Tygem, etc.)

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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  • shinkgs

    A JavaScript client for the KGS Go Server

  • KGS is where I used to play, this is the web client:

    https://shin.gokgs.com/

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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