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Thomas Bayes
mathematician · 10 mentions across 4 readings
In this course
Bayes is invoked here as the namesake for a fundamental epistemological problem in perception and machine learning: the circularity that arises when we use measurements filtered through our existing beliefs (posteriors) to justify those same beliefs. The readings use Bayes' theorem on conditional probability as the mathematical foundation for contemporary approaches to perception in AI systems, while simultaneously grappling with the philosophical trap—"Bayes' circle"—that threatens any naive application of Bayesian inference to understanding how minds or algorithms can access reality beyond their own representational systems.
Mentioned in 4 readings
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