
#320 — Constructing Self and World
Making Sense with Sam Harris
00:00
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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