Dmitri Chklovskii believes all your neurons are smart controller agents. Understanding this will transform neuroscience and how we build artificial intelligence.
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Since the 1940s and 50s, back at the origins of what we now think of as artificial intelligence, there have been lots of ways of conceiving what it is that brains do, or what the function of the brain is. One of those conceptions, going to back to cybernetics, is that the brain is a controller that operates under the principles of feedback control. This view has been carried down in various forms to us in present day. Also since that same time period, when McCulloch and Pitts suggested that single neurons are logical devices, there have been lots of ways of conceiving what it is that single neurons do. Are they logical operators, do they each represent something special, are they trying to maximize efficiency, for example?
Dmitri Chklovskii - Mitya - runs the Neural Circuits and Algorithms lab at the Flatiron Institute. Mitya believes that single neurons themselves are each individual controllers. They're smart agents, each trying to predict their inputs, like in predictive processing, but also functioning as an optimal feedback controller. We talk about historical conceptions of the function of single neurons and how this differs, we talk about how to think of single neurons versus populations of neurons, some of the neuroscience findings that seem to support Mitya's account, the control algorithm that simplifies the neuron's otherwise impossible control task, and other various topics.
0:00 - Intro
7:34 - Physicists approach for neuroscience
12:39 - What's missing in AI and neuroscience?
16:36 - Connectomes
31:51 - Understanding complex systems
33:17 - Earliest models of neurons
39:08 - Smart neurons
42:56 - Neuron theories that influenced Mitya
46:50 - Neuron as a controller
55:03 - How to test the neuron as controller hypothesis
1:00:29 - Direct data-driven control
1:11:09 - Experimental evidence
1:22:25 - Single neuron doctrine and population doctrine
1:25:30 - Neurons as agents
1:28:52 - Implications for AI
1:30:02 - Limits to control perspective
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