Adam Marblestone — AI is missing something fundamental about the brain

About this episode

Adam Marblestone discusses the insights AI can gain from neuroscience and the fundamental aspects of how the brain learns.

Adam Marblestone is CEO of Convergent Research . He’s had a very interesting past life: he was a research scientist at Google Deepmind on their neuroscience team and has worked on everything from brain-computer interfaces to quantum computing to nanotech and even formal mathematics. In this episode, we discuss how the brain learns so much from so little, what the AI field can learn from neuroscience, and the answer to Ilya’s question: how does the genome encode abstract reward functions? Turns out, they’re all the same question. Watch on YouTube ; read the transcript . Sponsors * Gemini 3 Pro recently helped me run an experiment to test multi-agent scaling: basically, if you have a fixed budget of compute, what is the optimal way to split it up across agents? Gemini was my colleague throughout the process — honestly, I couldn’t have investigated this question without it. Try Gemini 3 Pro today gemini.google.com * Labelbox helps you train agents to do economically-valuable, real-world tasks. Labelbox’s network of subject-matter experts ensures you get hyper-realistic RL environments, and their custom tooling lets you generate the highest-quality training data possible from those…

People in this episode

Host: Dwarkesh Patel

Guest: Adam Marblestone

Topics covered

• AI
• neuroscience
• brain-computer interfaces
• reward functions
• learning
• quantum computing

Keywords

• AI
• neuroscience
• brain
• reward functions
• learning
• quantum computing
• brain-computer interfaces

Sponsors

Gemini 3 Pro, Labelbox

Mentioned in this episode

Organizations: Convergent Research, Google Deepmind

Products: Gemini 3 Pro

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