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this post was submitted on 07 Jan 2025
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That was a different technique, using simulated evolution in an FPGA.
An algorithm would create a series of random circuit designs, program the FPGA with them, then evaluate how well each one accomplished a task. It would then take the best design, create a series of random variations on it, and select the best one. Rinse and repeat until the circuit is really good at performing the task.
I think this is what I am thinking of. Kind of a predecessor of modern machine learning.
It is a form of machine learning