Letting neural networks be weird
It's interesting that so much neural net weirdness emerges from exploiting errors in physics simulators or floating point math.
I am now expecting the next generation of perpetual motion machines to include AI to try to take advantage of physics bugs in our own universe.<p>On a related note, does anyone know how you might go about fixing a simulator that allows collisions to generate more energy/momentum than was initially supplied?
Or otherwise violates known invariants?