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Kudos AI

Pioneers

The people behind the theory. Documented contributions from the founders of probability and statistical inference to the architects of modern machine learning.

1777–1855

Carl Friedrich Gauss

Classical mathematics

Developed least squares and the normal distribution that underpins regression.

MathematicsStatisticsProbability
1890–1962

Ronald A. Fisher

Modern statistics

Formalized maximum likelihood and the design of experiments.

StatisticsProbability
1903–1957

John von Neumann

Game theory and computing

Proved the minimax theorem and co-founded game theory.

Game TheoryMathematicsProgramming
1903–1987

Andrey Kolmogorov

Foundations of probability

Put probability theory on a rigorous axiomatic foundation.

ProbabilityMathematicsInformation Theory
1912–1954

Alan Turing

Foundations of computation

Defined computation formally and framed the question of machine intelligence.

Artificial IntelligenceMathematicsProgramming
1916–2001

Claude E. Shannon

Information theory

Founded information theory and defined entropy as a measure of uncertainty.

Information TheoryProbabilityArtificial Intelligence
1927–2011

John McCarthy

Founding of AI

Named the field of artificial intelligence and created the Lisp language.

Artificial IntelligenceKnowledge RepresentationProgramming
1927–2016

Marvin Minsky

Founding of AI

Co-founded the MIT AI Laboratory and analysed the limits of single-layer networks.

Artificial IntelligenceKnowledge Representation
1928–1971

Frank Rosenblatt

Early neural networks

Built the perceptron, the first trainable artificial neuron.

Machine LearningDeep LearningArtificial Intelligence
1928–2005

Leo Breiman

Statistical learning

Created bagging and random forests, and formalized decision trees.

Machine LearningStatistics
1928–2015

John Nash

Game theory

Proved that every finite game has an equilibrium, generalizing game theory beyond zero-sum.

Game TheoryMathematics
c. 1701–1761

Thomas Bayes

Foundations of probability

Gave the rule for revising a probability in the light of evidence.

ProbabilityStatistics
b. 1936Living

Vladimir Vapnik

Statistical learning theory

Co-developed the support vector machine and statistical learning theory.

Machine LearningStatisticsMathematics
b. 1936Living

Judea Pearl

Probabilistic reasoning

Made probabilistic reasoning tractable through Bayesian networks, then formalized causality.

ProbabilityArtificial IntelligenceKnowledge Representation
b. 1947Living

Geoffrey Hinton

Deep learning

Co-authored the paper that made backpropagation widely known, and led the deep learning revival.

Deep LearningMachine LearningComputer Vision
b. 1960Living

Yann LeCun

Deep learning

Developed convolutional networks and demonstrated them at scale on real recognition tasks.

Deep LearningComputer VisionMachine Learning
b. 1964Living

Yoshua Bengio

Deep learning

Advanced neural approaches to language, including distributed word representations.

Deep LearningNatural Language ProcessingMachine Learning

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