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Tom Mitchell: The History of Machine Learning

In anticipation of the release of his new podcast Machine Learning: How Did We Get Here? Tom Mitchell, Founders University Professor at Carnegie Mellon University, stopped by the Lab for his talk, "The History of Machine Learning." He takes us from the writings of early philosophers about whether it is even possible to form correct general laws given only specific examples, to today’s machine learning algorithms that underlie a trillion dollar AI economy. Along the way we see the thoughts and recollections of many of the pioneers in the field, in the form of excerpts from upcoming podcast episodes featuring full interviews with each. Tom discusses the wonderful creativity and diversity of approaches explored during the 1980s, the integration of statistics and probability into the field in the 1990s and early 2000s, and the amazing progress over the past decade that has brought us today’s AI systems. He reflects in the end on what we should learn from this history. Visit digitaleconomy.stanford.edu to sign up for our newsletter and for more information on future Lab events. Machine Learning: How Did We Get Here? is available on most podcast platforms, as well as just a few clicks away on the Stanford Digital Economy Lab YouTube channel.