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#320 — Constructing Self and World

Making Sense with Sam Harris

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Approximate Bayesian Inference for Understanding Sensory Data

Understanding sensory data is crucial to comprehend the environment, locate food, and identify threats like tigers. The brain tackles this challenge by engaging in Bayesian inference, seeking to determine the probability of perceiving specific objects based on sensory input. However, the formal solution to Bayesian inference is highly complex and computationally intensive, leading to the utilization of approximate Bayesian inference. This approach involves learning to interpret sensory data by processing incoming information and attempting to discern the perceived objects effectively.

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