The Master Algorithm

In 2015, a book by AI researcher Pedro Domingos came out called The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World . The author explored the "five tribes" of artificial intelligence (AI), and how each one might develop into the "Master Algorithm" of intelligence itself — the algorithm that could learn to do virtually anything humans and other animals can learn to do. The five tribes are: inductive reasoning connectionism (aka neural networks) evolutionary computation Bayesian networks analogical modelling This was ten years ago. It was very much not obvious, at that time, which of these — or what combination of them — or even whether something entirely different — might turn out to be the Master Algorithm. But it's clear now. I'm calling it. The Master Algorithm is neural networks. It turns out, the master algorithm is connectionism. A neural network, when it's big enough, structured appropriately, and trained on enough data, can do it all: lang