#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


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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