Pierre-Simon Laplace
mathematician · 3 mentions across 3 readings
In this course
Laplace figures as a foundational reference for probabilistic reasoning and determinism—the classical framework that contemporary machine learning algorithms inherit and sometimes challenge. The excerpts invoke Laplacean logic implicitly through maximum-likelihood estimation and the problem of inference under uncertainty, where we calculate what model parameters best explain observed data. His philosophical legacy (deterministic causation paired with epistemic limits) shadows debates about simulation, prediction, and what can be known from limited information in the course's treatment of AI systems and their relationship to reality.
Mentioned in 3 readings
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