The Mathematical Foundations of Modern AI
rounak · x · 2026-07-19
Modern AI is built upon a series of historical mathematical concepts: - Bayes' Theorem (1763) - Cauchy's Gradient Descent (1847) - Markov Chains (1906) - Shannon's Information Theory (1948) - Bellman's Dynamic Programming (1950s) The author's core idea is that many of the critical AI concepts we use today actually originated a long time ago. This naturally leads to the question: what current concepts might only truly make an impact decades or even centuries from now?
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