Bayesian inference

Dec 31, 2025

The Algorithm That IS The Scientific Method [Dr. Jeff Beck]

Dr. Jeff Beck argues that the future of AI lies not in scaling up large language models, but in building systems that mirror the brain's approach to understanding the world. He posits that true intelligence is grounded in physics and object-centered models, not language. Beck's vision involves creating AI composed of numerous small, modular models—much like a video game engine—that can be dynamically combined, updated through continual learning, and understand the world through causal relationships and forces. This approach, he claims, will solve key challenges in generalization, robotics, and alignment by enabling machines to 'know what they don't know' and reason about the physical world in a way that is fundamentally similar to humans.

Oct 13, 2025

Columbia CS Professor: Why LLMs Can’t Discover New Science

Professor Vishal Misra of Columbia University introduces a formal model for understanding Large Language Models (LLMs) based on information theory. He explains how LLMs reason by navigating "Bayesian manifolds", using concepts like token entropy to explain the mechanics of chain-of-thought, and defines true AGI as the ability to create new manifolds rather than just exploring existing ones.