Specialized microchips that manage signals at the cutting edge of wireless technology are astounding works of miniaturization and engineering. They're also difficult and expensive to design.
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.
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
Which is just stochastic optimisation.
Which yes is exactly what evolution does, big picture. Small picture the genome evolves a bit more intelligently, using not random generation and filtering but an algorithm employing randomness to generate, and then the usual survival filter because doing it that way is, well, fitter. Also what you can see under a microscope.