August 1, 2017 (Vol. 37, No. 14)


Strong Points: Hot topic, content for both general audience and experts
Weak Points: Technical portion precedes general interviews (may lose people)


Created in 2015 by Katherine Gorman and Ryan Adams (and currently hosted by Gorman and Neil Lawrence of Amazon), the Talking Machines podcast takes listeners deep into the rapidly evolving world of machine learning, which is becoming ever more relevant to biology and biomedical research. Now in its third season, Talking Machines has just over 40 episodes thus far, each of which runs approximately 30 to 50 minutes long. A typical episode is comprised of three components: a technical explanation of a specific topic related to machine learning, a user-submitted question, and an interview with an expert in the field. The technical explanations are just that, geared toward an audience with some preexisting foundational knowledge. However, don’t let these dense introductory segments scare you off. The interviews in particular are accessible to a broader audience and explain—in easy-to-understand terms—many of the ways in which machine learning is being applied in academia and industry.

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