DR. JEFF BECK - THE BAYESIAN BRAIN
Machine Learning Street Talk (MLST)
Understanding Bayesian Modeling and Its Implications
This chapter explores the principles and significance of Bayesian modeling in empirical inquiry, focusing on its role in managing uncertainty and decision-making. It discusses challenges in model selection and the idea of active inference, highlighting the dynamic relationship between models and real-world environments. The conversation further examines the complexities of understanding probabilistic knowledge, the nuances of reasoning in language models, and the essence of scientific inquiry beyond absolute truths.
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