#121 Meet The Neuroscientist Teaching Neuron's in a Dish to Play Video Games

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Brett Kagan is the Chief Scientific Officer at Cortical Labs, the
Australian startup that fuses living human neurons with silicon
chips to create a fundamentally new kind of intelligence. His
team's DishBrain paper showed that neurons in a dish learned to
play Pong in under five minutes — without any reward signal —
providing some of the strongest experimental evidence for Karl
Friston's Free Energy Principle.


Expect to learn how neurons on a chip actually play Pong and
Doom, why unpredictable stimulation drives learning better than
reward, what the Free Energy Principle really says and where
Brett disagrees with Friston, why 200,000 neurons outperform
800,000 on certain tasks, how Brett's baby daughter staring at
fractals led to a new theory of intelligence, why no AI system
can walk into your kitchen and make a cup of tea, what biological
data centres look like and why they already exist, and much more…


Timestamps:


00:00 Trailer


02:30 Brett Kagan — Neurons Playing Doom


03:04 The stepping stones from Pong to Doom


04:00 What is the CL1 and Cortical Cloud?


05:20 The moonshot goal of Cortical Labs


06:46 Giant buildings of neurons as computation hubs


07:13 The biocomputing data centre already running in Melbourne


07:38 Not building a brain in a dish


09:00 What does a biological computer actually look like?


09:29 Electricity as the shared language between biology and
silicon


10:49 How neurons on a chip play Pong


11:10 Topographic mapping inspired by the whisker barrel system


13:10 Why the neurons hit the ball — and what happens when they
miss


14:33 The Free Energy Principle explained simply


16:03 The trap door analogy for unpredictable stimulation


18:42 How the structure of neuron cultures shapes performance


19:19 Bees vs elephants: why bigger brains aren’t always better


21:37 Growing hippocampal place cells in a dish


24:12 Teaching neurons Morse code


28:27 The Free Energy Principle — cups, predictions and surprise


32:29 Where Brett disagrees with Friston


37:03 The dog treat problem — how do you reward a neuron?


39:40 Complexity as a hidden driver of intelligence


41:53 His baby daughter’s obsession with fractals


43:57 Defining agency — the three orders of information
processing


50:33 Change how you change over time


53:27 Why scientists are incentivised to be vague instead of
wrong


59:42 J.D. Bernal’s 1929 vision for brains beyond bodies


1:02:38 Standing on the shoulders of iPSC pioneers


1:03:14 Can neurons play chess? Moravec’s Paradox


1:04:12 No AI can walk into your kitchen and make tea


1:05:16 Augmenting what silicon is bad at


1:06:35 Is general intelligence even possible for silicon?


1:09:40 Why 200,000 neurons beat 800,000


1:11:16 Complexity and structure matter more than scale


1:11:58 Could biological neurons end up in your laptop?


1:13:36 Edge robotics and the future of biological computing


...


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