Contemplate this 'KQQ vs krrbnn' mate in 5 chess problem generated by the prototype computer program, Chesthetica, using the Digital Synaptic Neural Substrate (DSNS) computational creativity approach. It doesn't use endgame tablebases, neural networks or any kind of machine learning found in 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.
White to Play and Mate in 5
Chesthetica v11.62 (Selangor, Malaysia)
Generated on 3 Mar 2020 at 10:55:51 PM
Chess puzzles are ancient. Some are over a thousand years old but only in the 21st century have computers been able to compose original ones on their own like humans can. What was the machine 'thinking' when it came up with this? If this one is too easy or too difficult for you, try out some of the others. 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.
Solution
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