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Mathematics

Mathematics in AI History

The mathematical foundations of AI - probability, statistics, and optimisation results that made machine learning possible.

6 stories

1763Mathematics

Bayes' Theorem: The Equation That Came Back from the Dead

Thomas Bayes never published his most famous result. A friend found it among his papers after he died.

1805Mathematics

Least Squares: The Statistical War That Shaped Every Regression

Gauss claimed he invented it. Legendre published it first. The dispute never fully resolved, and it's still the most widely used statistical technique in history.

1906Mathematics

Markov Chains: From a Poetry Dispute to Language Models

Markov Chains were invented to prove free will doesn't exist in Russian poetry.

1953Mathematics

SHAP: From Game Theory Tables to Model Explainability

SHAP values come from a 1953 paper on dividing poker winnings fairly.

1997Mathematics

No Free Lunch: Why There's No Best Algorithm

The No Free Lunch theorem proved that no algorithm is universally better than any other, averaged over all possible problems.

2020Mathematics

Scaling Laws: The Equation That Predicted the Future of AI

A 2020 OpenAI paper proved that AI capability scales predictably with compute, and that most teams were training their models wrong.

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