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HBO and The Ringer's Bill Simmons hosts the most downloaded sports podcast of all time, with a rotating crew of celebrities, athletes, and media staples, as well as mainstays like Cousin Sal, Joe House, and a slew of other friends and family members who always happen to be suspiciously available.
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Darryl and I discuss his background, how he became interested in machine learning, and a project we are currently working on investigating the penalization of polysemanticity during the training of neural networks.
Check out a diagram of the decoder task used for our research!
01:46 - Interview begins
02:14 - Supernovae classification
08:58 - Penalizing polysemanticity
20:58 - Our "toy model"
30:06 - Task description
32:47 - Addressing hurdles
39:20 - Lessons learned
Links to all articles/papers which are mentioned throughout the episode can be found below, in order of their appearance.
24 episodes
