Uri and I discuss his recent perspective that conceives of brains as super-over-parameterized models that try to fit everything as exactly as possible rather than trying to abstract the world into usable models. He was inspired by the way artificial neural networks overfit data when they can, and how evolution works the same way on a much slower timescale. Show notes: Uri's lab website. Follow his lab on twitter: @HassonLab.The paper we discuss: Direct Fit to Nature: An EvolutionaryPerspective on Biological and Artificial Neural Networks. Here’s the BioRxiv version in case the above doesn’t work.  Uri mentioned his newest paper: Keep it real: rethinking the primacy of experimental control in cognitive neuroscience.

Uri and I discuss his recent perspective that conceives of brains as super-over-parameterized models that try to fit everything as exactly as possible rather than trying to abstract the world into usable models. He was inspired by the way artificial neural networks overfit data when they can, and how evolution works the same way on a much slower timescale.

Show notes:

• Uri's lab website.
• Follow his lab on twitter: @HassonLab.
• The paper we discuss:
  • 69fa-461c-8a44-239d3f2b4c80.filesusr.com/ugd/b75639_7ac844bc277c4f44ba7fb30e45ac3511.pdf">Direct Fit to Nature: An EvolutionaryPerspective on Biological and Artificial Neural Networks.
  • Here’s the BioRxiv version in case the above doesn’t work. 
  • Uri mentioned his newest paper: Keep it real: rethinking the primacy of experimental control in cognitive neuroscience.