Glossary · Term

Bayesian inference

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Definition

Plain language

Updating what you believe as new evidence comes in, by combining your starting guess with how well each option fits the data.

As stated in the literature

Computing a posterior distribution from a prior and a likelihood via Bayes' rule; invoked in the RL-as-inference equivalence, where the optimal KL-regularized policy is exactly a reward-tilted posterior over the base model's outputs.

Also called: Bayes' rule, Bayesian update

Why it matters: It gives a principled way to combine prior knowledge with fresh evidence, which is the backbone of reasoning under uncertainty.

For example, if you think a coin is probably fair but then see it land heads ten times in a row, Bayesian inference tells you how to shift your belief toward it being biased.

Heard on the show

“Through Bayes' rule, and the intuition is the only thing you need.”
Episode 170 — When a One-Liner Beats Your Agent's Clever Verification Logic

Mentioned in 4 episodes

  1. 170
    When a One-Liner Beats Your Agent's Clever Verification Logic
  2. 119
    Beating Reinforcement Learning Without Ever Touching the Model's Weights
  3. 118
    Why the Best-Aligned AI Models Are the Easiest to Trick Into Producing Harm
  4. 091
    When Better Fine-Tuning Can't Help: A Geometric Impossibility in LLM Causal Reasoning

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