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Adam Marblestone – AI is missing something fundamental about the brain

Adam Marblestone has worked on brain-computer interfaces, quantum computing, formal mathematics, nanotech, and AI research. And he thinks AI is missing something fundamental about the brain.

Why are humans so much more sample efficient than AIs? How is the brain able to encode desires for things evolution has never seen before (and therefore could not have hard-wired into the genome)? What do human loss functions actually look like?

Adam walks me through some potential answers to these questions as we discuss what human learning can tell us about the future of AI.

Watch on YouTube; read the transcript.

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Timestamps

(00:00:00) – The brain’s secret sauce is the reward functions, not the architecture

(00:22:20) – Amortized inference and what the genome actually stores

(00:42:42) – Model-based vs model-free RL in the brain

(00:50:31) – Is biological hardware a limitation or an advantage?

(01:03:59) – Why a map of the human brain is important

(01:23:28) – What value will automating math have?

(01:38:18) – Architecture of the brain

Further reading

Intro to Brain-Like-AGI Safety - Steven Byrnes’s theory of the learning vs steering subsystem; referenced throughout the episode.

A Brief History of Intelligence - Great book by Max Bennett on connections between neuroscience and AI