Fat Fritz 2.0 SE
Fat Fritz 2.0 SE is the successor to the revolutionary Fat Fritz, which was based on the famous AlphaZero algorithms. Using a new Japanese AI technology that achieves optimal performance on regular computer processors (CPUs – no expensive graphic card required) it combines the best of both worlds: a massive new neural network, trained by Albert Silver with the original Fat Fritz, while learning from the surgical precision of Stockfish’s legendary search.
This new version takes chess analysis to the next level and is a must for players of all skill levels, whether beginner or professional, who won’t accept any compromises. Its understanding is unparalleled, as it learned by literally studying billions of chess positions.
Fat Fritz 2 comes with the latest version of the most advanced chess playing interface in the world, which provides coach functions, automatic game analysis, a database with 1 million games as well as a six-month subscription to ChessBase Premium Account.
- Fat Fritz 2 engine with a massive new neural network*
- 64-bit program interface
- Includes current Fritz 17 program interface
- ChessBase Premium Account (6 months) with access to training videos, Playchess, tactics training, and much much more!
- Database with 1 million games, etc.
Minimum: PC Core i3 oder i5 / AMD FX or Ryzen 3, 2 GB RAM, Windows 7/8/8.1 64Bit, DirectX9, , graphics card with 256 MB RAM, DVD-ROM drive, Windows Media Player 11 and Internet access.
Recommended: PC Core i7, i9 or AMD FX, Ryzen 7/9 and Windows 10 64-Bit, 4 GB RAM, Windows 10, DirectX10, graphics card with 512 MB RAM or more, Windows Media Player 11, DVD ROM drive and Internet access.
System requirements for ChessBase Account: Internet access and up-to-date browser, e.g. Chrome, Safari. Runs on Windows, OS X, iOS, Android and Linux.
*Fat Fritz 2 is an original neural network that is powered by a modied version of Stocksh. Stocksh is an open-source project licensed through the GPL v3 with all due rights. The source code of Stocksh and the modications for Fat Fritz 2 can be found on Github.