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Gary Marcus is well known as a deep learning critic. A neuroscientist, entrepreneur, and the author of “Rebooting AI: Building Artificial Intelligence We Can Trust,” Marcus believes that researchers need to move past deep learning in order to make true advances in machine intelligence. Marcus and Azeem Azhar discuss why, how, and when we can expect progress.
In this podcast, they also discuss:
- What newborn ibexes can teach us about intelligence and learning.
- How deep learning widens the gap between big companies and startups.
- What we need for a breakthrough in AI.
Further reading:
- “How to Build Artificial Intelligence We Can Trust” (The New York Times, Gary Marcus and Ernest Davis, Sep. 6, 2019)
- “Deep Learning: A Critical Appraisal” (Cornell University, Gary Marcus, Jan. 2, 2018)
@garymarcus
@azeem
@exponentialview
HBR Presents is a network of podcasts curated by HBR editors, bringing you the best business ideas from the leading minds in management. The views and opinions expressed are solely those of the authors and do not necessarily reflect the official policy or position of Harvard Business Review or its affiliates.