Pedro Domingos is a professor of computer science at the University of Washington. He is a winner of the SIGKDD Innovation Award, the highest honor in data science. A fellow of the Association for the Advancement of Artificial Intelligence, he lives near Seattle.
Domingos’ core argument is that machine learning needs an unifying theorem, not unlike the Standard Model in physics or the Central Dogma in biology. He takes readers through a historical tour of artificial intelligence and machine learning and breaks down the five main schools of machine learning (below). But he argues that each has its limitations and the main goal for current researchers should be to discover/create “The Master Algorithm” that has the ability to learn any concept aka act as a general purpose learner.
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