EPISODE · Oct 29, 2020 · 43 MIN
The Computational Limits of Deep Learning
from The Data Exchange with Ben Lorica · host Ben Lorica
Subscribe: Apple, Android, Spotify, Stitcher, Google, and RSS.In this episode of the Data Exchange I speak with Neil Thompson, Research Scientist at Computer Science and Artificial Intelligence Lab (CSAIL) and the Initiative on the Digital Economy, both at MIT. I wanted Neil on the podcast to discuss a recent paper he co-wrote entitled “The Computational Limits of Deep Learning” (summary version here). This paper provides estimates of the amount of computation, economic costs, and environmental impact that come with increasingly large and more accurate deep learning models. Download the 2020 NLP Survey Report and learn how companies are using and implementing natural language technologies.Detailed show notes can be found on The Data Exchange web site.Subscribe to The Gradient Flow Newsletter.
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Subscribe: Apple, Android, Spotify, Stitcher, Google, and RSS. In this episode of the Data Exchange I speak with Neil Thompson, Research Scientist at Computer Science and Artificial Intelligence Lab (CSAIL) and the Initiative on the Digital Economy, both at MIT. I wanted Neil on the podcast to discuss a recent paper he co-wrote entitled “The Computational Limits of Deep Learning” (summary version here). This paper provides estimates of the amount of computation, economic costs, and env...
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The Computational Limits of Deep Learning
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