#76 – John Hopfield: Physics View of the Mind and Neurobiology

John Hopfield is professor at Princeton, whose life's work weaved
beautifully through biology, chemistry, neuroscience, and physics.
Most crucially, he saw the messy world of biology through the
piercing eyes of a physicist. He is perhaps best known for his work
on associate neural networks, now known as Hopfield networks that
were one of the early ideas that catalyzed the development of the
modern field of deep learning. EPISODE LINKS: Now What? article:
http://bit.ly/3843LeU John wikipedia:
https://en.wikipedia.org/wiki/John_Hopfield Books mentioned: -
Einstein's Dreams: https://amzn.to/2PBa96X - Mind is Flat:
https://amzn.to/2I3YB84 This conversation is part of the Artificial
Intelligence podcast. If you would like to get more
information about this podcast go to https://lexfridman.com/ai or
connect with @lexfridman on Twitter, LinkedIn, Facebook, Medium, or
YouTube where you can watch the video versions of these
conversations. If you enjoy the podcast, please rate it 5 stars on
Apple Podcasts, follow on Spotify, or support it on Patreon. This
episode is presented by Cash App. Download it (App Store, Google
Play), use code "LexPodcast".  Here's the outline of the
episode. On some podcast players you should be able to click the
timestamp to jump to that time. OUTLINE: 00:00 - Introduction 02:35
- Difference between biological and artificial neural networks
08:49 - Adaptation 13:45 - Physics view of the mind 23:03 -
Hopfield networks and associative memory 35:22 - Boltzmann machines
37:29 - Learning 39:53 - Consciousness 48:45 - Attractor networks
and dynamical systems 53:14 - How do we build intelligent systems?
57:11 - Deep thinking as the way to arrive at breakthroughs 59:12 -
Brain-computer interfaces 1:06:10 - Mortality 1:08:12 - Meaning of
life