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Humans have been creating artistic images of their environment for tens of thousands of years, but weirdly missing from all their cave art and carvings is a pretty obvious omission – the human face. Today we look at the mystery of why Paleolithic humans never drew human faces, and search for the first confirmed image ever created of a human face.
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Are we all living in a simulation inside our brains? Neil deGrasse Tyson and co-hosts Chuck Nice and Gary O’Reilly learn about the root of perception, if AI really is intelligent, and The Free Energy Principle with theoretical neuroscientist Karl Friston.
Discover the Free Energy Principle as a framework for understanding how the brain self-organizes and minimizes uncertainty about the world. Does the brain keep an internal model of the world that it continues to update? How does this principle relate to perception, decision-making, and the human experience? How does our brain, a blob of neurons locked inside a skull, make sense of the chaotic data it receives from the world?
Friston introduces us to “Active Inference,” the application of this principle, explaining how the brain samples the environment and updates its beliefs to create a cohesive understanding of reality. He discusses how psychiatric disorders, like schizophrenia, can arise when there’s a mismatch between the brain’s internal model and external reality, and how this theory could one day help explain and treat these conditions.
We explore how these ideas from neuroscience can be used in artificial intelligence and large language models, discussing the limits of machine learning. Can AI truly possess intelligence? Or is it merely following pre-programmed paths, unable to build the complex internal models humans use to navigate the world? Can AGI– artificial general intelligence– ever be achieved in a machine? What do we even mean when we say AGI? Does an objective reality even exist?
Timestamps:
00:00 – Introduction: Karl Friston
03:32 – What is The Free Energy Principle?
11:10 – Breaking Down Active Inference & Perception
16:04 – Perception vs. Imagination
19:15 – What It Means to Predict
21:27 – Einstein’s Brain, Embodiment, & Large Language Models
25:48 – The Matrix, Deja Vu, & Missing Reality
32:28 – The Intelligence in Large Language Models
37:10 – Mechanical vs. Biological AGI
43:10 – Discussing Consciousness
45:00 – Why Studying the Brain Helps
50:40 – Bayesian Inference
52:58 – Hallucinations
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