The Three Ages of AI – Figuring Out Where We Are

While our ability to utilize machine learning statistical algorithms like regression, SVMs, random forests, and neural nets expanded rapidly starting in roughly the 1990's the application of these handcrafted systems didn't entirely go away. There is very little in common among convolutional neural nets, recurrent neural nets, generative adversarial neural nets, evolutionary neural nets used in reinforcement learning, and all of their variants. They all also need massive parallel processing across extremely large computational arrays, many times requiring specialized chips like GPUs and FPGAs to get anything done on a human time scale. Models That Explain Their Reasoning: Although our deep neural nets are good at classifying things like images they are completely inscrutable in how they do so.