Alex Krizhevsky

Canadian computer scientist and principal author of AlexNetAlexNet, prop. n.: The neural network that won a major image-recognition contest by a huge margin in 2012, convincing researchers and companies that deep learning trained on graphics chips was the way forward.. As a graduate student of 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. at the University of Toronto he created the CIFAR-10 and CIFAR-100 image datasets (2009) and wrote cuda-convnet, fast code for training convolutional neural networksconvolutional neural network, n.: A kind of neural network built for images and other grid-like data. It slides small pattern detectors across the input, finding edges first, then shapes, then whole objects. on Nvidia GPUsGPU, abbr.: A computer chip first designed to draw video-game graphics that turned out to be ideal for AI, because it can do thousands of simple calculations at the same time.. With Ilya SutskeverIlya Sutskever, prop. n.: A Russian-born Israeli-Canadian computer scientist who co-built the AlexNet image recognizer, helped found OpenAI and lead its research until 2024, and now heads the startup Safe Superintelligence Inc. and Hinton he trained AlexNet, an eight-layer network using ReLUReLU, abbr.: The most common rule a neuron uses to produce its output: keep the number if it is positive, replace it with zero if it is negative. Simple, fast and surprisingly effective. activations, dropoutdropout, n.: A training trick that randomly switches off a fraction of a network's neurons at each step, so the network cannot lean too heavily on any one of them and learns sturdier patterns. and data augmentationdata augmentation, n.: Creating extra training examples by changing existing ones in ways that keep their meaning — a flipped, cropped or recolored photo of a cat still shows a cat — so the model learns more robustly., split across two consumer graphics cards, which won the 2012 ImageNetImageNet, prop. n.: A huge collection of more than 14 million labeled photos, sorted into object categories, whose yearly recognition contest from 2010 to 2017 sparked the deep learning boom. Large Scale Visual Recognition Challenge with a top-5 error of 15.3 percent against 26.2 percent for the runner-up. The result, published at NeurIPS 2012, persuaded much of computer visioncomputer vision, n.: The part of AI that lets computers make sense of images and video: recognizing faces, reading signs, spotting tumors on scans or judging how far away a car is. and the technology industry to adopt deep learningdeep learning, n.: Machine learning done with neural networks built from many stacked layers: raw data such as pixels, sound or text goes in at one end, and each layer turns what it receives into something more abstract.. He joined Google when it acquired the trio's company, DNNresearch, in 2013, and has since kept a low public profile.