Consider this 'KQNNPP vs kqbp' mate in 3 chess puzzle created by the program, Chesthetica, using the Digital Synaptic Neural Substrate (DSNS) computational creativity approach. It doesn't use endgame tablebases, deep learning or any kind of traditional AI. Depending on the type and complexity of the problem desired, a single instance of Chesthetica running on a desktop computer can probably generate anywhere between one and ten problems per hour. Any chess position over 7 pieces could not possibly have been derived from an endgame tablebase which today is limited to 7 pieces.
Chesthetica v10.57 : Selangor, Malaysia
White to Play and Mate in 3 : 2017.12.31 4:11:05 PM
Chesthetica, especially if running on multiple computers or operating system user accounts, is capable of generating far too many compositions than can be published in a timely fashion here. The newer ones will therefore only be published some time later. This is why the composition date above does not match today's date. White is significantly ahead in material. Try to solve this puzzle in time or just pause the video. At the end of the video, you will see the solution played out. This is followed by some analysis. Do try some of the others in the series as well before you go. Solving chess puzzles like this is probably good for your health as it keeps your brain active. Nobody wants something like early-onset Alzheimer's. If you're bored of standard chess, though, why not try this?
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