Consider this 'KQB vs kbnp' mate in 3 chess problem generated autonomously 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.
White to Play and Mate in 3
Chesthetica v10.67 : Selangor, Malaysia
2018.5.25 7:42:03 AM
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. Now, let's see what else there is to say. Give me a moment. If this one is too easy or too difficult for you, try out some of the others. Some of these problems may be trivial for you, especially if you're a club or master player but bear in mind that chess lovers can be found at all levels of play. So do check out some of the other problems. You can probably find something more to your taste.
Solution (Skip to 0:35)
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