Entropic perspective on AI resilience, data-minimal learning and optimal control
The research formulates mathematical conditions for finding minimal adversarial paths and distances in AI classifiers. It develops methods like entropic AI to find optimal, small perturbations for attacks and uses self-attacking learning algorithms to train simpler, cheaper models with superior performance on complex problems like hydrodynamics and biomedicine.