Princeton Scientist: We Don’t Understand AI – Tom Griffiths – #553

A Princeton cognitive scientist says AI can't think like a child — and giving it more data won't fix that.

If the field keeps scaling without solving what's actually missing, the gap between human and machine intelligence won't close. It'll just get more expensive.

Tom Griffiths is a professor of psychology and computer science at Princeton, and one of the leading researchers working at the intersection of human cognition and AI.

We cover:
-why a child learns language from breadcrumbs while AI needs continents of data
-the 250-year-old idea that quietly became the foundation of modern language models
-what sycophantic AI actually does to your beliefs over time
-why solving AGI might have less to do with scale and more to do with understanding what a child's mind really is.

The hallucinations don't bother him — it's the sycophancy that should worry you.

Key Takeaways:
00:00 The Math Behind How Minds Actually Work
00:30 Why Defining "Thought" Is Harder Than It Looks
04:30 What AI Gets Wrong About Consciousness
07:00 What ChatGPT Actually Revealed About the Field
08:10 Are Humans Really Irrational — Or Solving a Different Problem?
11:00 How Chomsky Turned Language Into a Math Problem
13:55 The Chessboard Analogy That Explains Generative Grammar
15:20 Why Aristotle Got Thought Right and Physics Wrong
19:45 The Man Who Tried to Build AI in the 1600s
22:40 What Everyone Gets Wrong About George Boole
25:25 From Boole to Turing: How Logic Became Computers
27:40 Why Your Brain Runs on Less Energy Than a Light Bulb
28:40 Jensen Huang Says AGI Is Here. Is He Right?
31:45 Why the "AI vs. Human Intelligence" Scale Is Misleading
33:50 Why a Child Still Outlearns Every AI Model
35:20 The Fuzzy Boundary Problem That Broke Rule-Based AI
37:20 How Semantic Networks Rewired the Theory of Memory
39:30 Rosenblatt Built a Brain — Then Minsky Killed It
43:15 The Plane Ride Where Backpropagation Was Solved
44:20 Hallucinations, Sycophancy, and What Should Actually Worry You
47:00 What Has to Change Before AI Can Truly Generalize
50:10 What a Layperson Should Actually Take Away From This
———

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