Striking finding: Lab-grown neurons in petri dishes learn simple tasks faster than our most sophisticated deep learning models, with dramatically better sample efficiency.
Why? The biological substrate has computational advantages we haven't figured out how to engineer.

#CognitiveScience #AI

Your brain uses 20% of your body's energy while comprising only 2% of its mass.

This metabolic crisis forced evolution to develop:
• Hybrid continuous-discrete computation
Multi-scale integration
Electrochemical dynamics
• Real physical time coupling

Digital systems face none of these constraints.

Mathematical twist: Gödel proved discrete arithmetic (computer logic) is incomplete—it has blind spots.

But Tarski proved continuous arithmetic (brain physics) is complete and decidable.

The logic of continuous processes is, in a deep sense, more powerful than the logic of discrete steps.

Central question: Can you simulate a river by photographing it fast enough?

Maybe technically. But have you captured what it IS to be the river—the continuous, unbroken flow through physical time?