Take a look at this 'KRRRN vs kbpp' four-move chess problem generated by a computer program, Chesthetica, using the Digital Synaptic Neural Substrate (DSNS) computational creativity approach. The DSNS does not use endgame tablebases, neural networks or any kind of machine learning found in traditional artificial intelligence (AI). It also has nothing to do with deep learning. The largest endgame tablebase in existence today is for 7 pieces (Lomonosov) which contains over 500 trillion positions, most of which have not and never will be seen by human eyes. This problem with 9 pieces goes even beyond that and was therefore composed without any such help whatsoever.
White to Play and Mate in 4
Chesthetica v11.20 (Selangor, Malaysia)
Generated on 22 Jun 2019 at 10:28:22 PM
Composing a chess puzzle or problem requires creativity and it's not easy even for most humans. White has a decisive material advantage in this position but the winning sequence may not be immediately clear. Try to solve this as quickly as you can. If you like it, please share with others. Solving chess puzzles like this can be good for your health as it keeps your brain active. It may even delay or prevent dementia.
Main Line of the Solution (Skip to 0:35)
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