The History of Machine Learning from the Inside Out — Talking Machines

In episode five of Talking Machines, we hear the first part of our conversation with Geoffrey Hinton (Google and University of Toronto), Yoshua Bengio (University of Montreal) and Yann LeCun (Facebook and NYU). Ryan introduces us to the ideas in tensor factorization methods for learning latent variable models (which is both a tongue twister and and one of the new tools in ML). To find out more on the topic, the paper Tensor decompositions for learning latent variable models is a good place to start. You can also take a look at the work of Daniel Hsu, Animashree Anandkumar and Sham M. Kakade Plus we take a listener question about just where statistics stops and machine learning begins.