Terry Sejnowski

American computational neuroscientist at the Salk Institute and the University of California, San Diego, and a founder of modern neural-network research. A physics doctoral student of John HopfieldJohn Hopfield, prop. n.: An American physicist who showed in 1982 how a network of simple units can store and recall memories, and who shared the 2024 Nobel Prize in Physics for work that enabled machine learning. at Princeton, he devised the Boltzmann machineBoltzmann machine, n.: A network of randomly flipping on–off units, including hidden ones, that learns the statistical patterns in its training data and can then produce new examples like them. with Geoffrey HintonGeoffrey Hinton, prop. n.: A British-Canadian scientist whose decades of persistent work on brain-inspired neural networks laid the foundations of modern AI; often called a 'godfather of AI', he now warns publicly about its dangers. (1983–85), a stochastic network that learns a probability distribution over its inputs, and with Charles Rosenberg built NETtalk (1987), a network that learned to pronounce English text and became a widely publicized demonstration of connectionismconnectionism, n.: The view that minds and intelligent machines are best built from huge networks of simple, neuron-like units whose connection strengths are learned, rather than from explicit rules and symbols.. With Tony Bell he developed the infomax algorithm for independent component analysis (1995). He founded the journal Neural Computation (1989), has long presided over the foundation that runs the NeurIPSNeurIPS, prop. n.: The largest yearly scientific conference on artificial intelligence and machine learning, held each December, where many of the field's landmark papers were first presented. conference, and wrote 'The Deep Learning Revolution' (2018). He is a member of all three US national academies, of sciences, engineering and medicine, and shared the 2024 Brain Prize for computational and theoretical neuroscience.