@whitequark @0xabad1dea I was at the University of Reading. Can't remember where this system was though, certainly wasn't one of ours; just something one of the PhD students knew about, and used as an example to explain how machine learning (and optimisation systems) can find the weirdest loopholes.
@dijumx @whitequark @0xabad1dea Any of these links help?: https://news.ycombinator.com/item?id=18461565
@dragonfi @dijumx @0xabad1dea it's really not hard at all to induce FPGA LUTs to interact via parasitic oscillator lock-in, by the way: https://lab.whitequark.org/notes/2016-08-05/parasitic-interaction-between-oscillating-luts-on-silego-greenpak-4/
people treat it as some magic miracle when an evolved circuit does that. it's not. doing weird nasal demon things is literally the default. and leveraging weird nasal demon things to manipulate a fitness function is the entire purpose of an ML algorithm anyway
@whitequark @dijumx @0xabad1dea
I agree, but it still feels like a "magic miracle" when statistics predicts the most likely outcome and it indeed comes true, but following the exact chain of causality is an exercise in frustration. Physics is full of phenomena like that.