godfathers of AI
In plain wordsA media nickname for three scientists — Geoffrey Hinton, Yoshua Bengio and Yann LeCun — whose decades of work on neural networks underpins modern AI. They shared computing's top prize in 2019.
A journalistic epithet for 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., Yoshua BengioYoshua Bengio, prop. n.: A Canadian computer scientist who helped found deep learning, including ideas behind today's language models, and who has become a leading voice on the risks of advanced AI. and Yann LeCunYann LeCun, prop. n.: A French-American computer scientist who pioneered the neural networks that recognize images, led Meta's AI research for over a decade, and argues that chatbots alone will not reach human-level AI., who kept research on neural networksneural network, n.: A kind of computer program that learns a task from examples by tuning thousands to billions of connections between simple number-crunching units, an arrangement loosely inspired by nerve cells in the brain. alive through the 1990s and early 2000s, when most of the field had turned to other methods, and whose work on backpropagationbackpropagation, n.: The method neural networks use to learn from mistakes: it works backward from the error to figure out how much each internal connection contributed, so every connection can be adjusted in the right direction., convolutional 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., deep belief networksdeep belief network, n.: A many-layered neural network trained one layer at a time, introduced in 2006. It showed that deep networks could be trained after all and helped launch the deep learning boom, before simpler methods replaced it., neural language models and attention laid the foundations of 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.. The three shared the 2018 Turing AwardTuring Award, prop. n.: Nicknamed the 'Nobel Prize of computing', the top honor in computer science, awarded each year since 1966 by the Association for Computing Machinery. Several AI pioneers have received it., announced in March 2019. The label gained new prominence from 2023, when Hinton, who left Google that May, and Bengio warned publicly of catastrophic and existential risksexistential risk, n.: A danger that could end humanity, or shut it out of a good future forever. Some experts count advanced AI among the largest such risks; others think this worry is overblown. from AI while LeCun dismissed such fears, so that the 'godfathers' came to personify opposing sides of the AI safetyAI safety, n.: The effort to keep AI from doing serious harm, whether because it pursues aims its makers never intended, is turned to bad uses or simply malfunctions — a concern that grows as systems become more capable. debate. In the singular, 'godfather of AI' most often means Hinton.
Two of the three godfathers of AI now spend much of their time warning about it.
Origin
Hinton was being called the 'godfather of deep learning' in the press by the mid-2010s; the plural became standard after the three shared the Turing Award in 2019. They had worked together since 2004 in the Canadian Institute for Advanced Research's program on neural computation.
Usage note
Critics say the label slights other pioneers — Jürgen SchmidhuberJürgen Schmidhuber, prop. n.: A German computer scientist who co-invented the LSTM, a neural network with memory that powered much of speech recognition and translation in the 2010s, and who argues that early pioneers go under-credited. has publicly disputed the credit — and the many collaborators behind the work. Fei-Fei LiFei-Fei Li, prop. n.: A Chinese-American computer scientist whose ImageNet project, millions of hand-labeled photos, gave deep learning the proving ground that launched its boom; she now champions 'human-centered' AI. is sometimes called the 'godmother of AI' for 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..
Related
- 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.
- Yoshua BengioYoshua Bengio, prop. n.: A Canadian computer scientist who helped found deep learning, including ideas behind today's language models, and who has become a leading voice on the risks of advanced AI.
- Yann LeCunYann LeCun, prop. n.: A French-American computer scientist who pioneered the neural networks that recognize images, led Meta's AI research for over a decade, and argues that chatbots alone will not reach human-level AI.
- Turing AwardTuring Award, prop. n.: Nicknamed the 'Nobel Prize of computing', the top honor in computer science, awarded each year since 1966 by the Association for Computing Machinery. Several AI pioneers have received it.
- deep learning revolutiondeep learning revolution, n.: The rapid takeover of AI by many-layered neural networks from about 2012, when they suddenly began beating older methods at recognizing images and speech, leading to today's AI systems.
- Nobel Prizes for AINobel Prizes for AI, phr.: The two 2024 Nobel Prizes, in physics and chemistry, that honored artificial intelligence research for the first time, recognizing neural-network pioneers and the protein-structure system AlphaFold.
Mentioned in
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., 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., Yann LeCunYann LeCun, prop. n.: A French-American computer scientist who pioneered the neural networks that recognize images, led Meta's AI research for over a decade, and argues that chatbots alone will not reach human-level AI., deep learning revolutiondeep learning revolution, n.: The rapid takeover of AI by many-layered neural networks from about 2012, when they suddenly began beating older methods at recognizing images and speech, leading to today's AI systems., Nobel Prizes for AINobel Prizes for AI, phr.: The two 2024 Nobel Prizes, in physics and chemistry, that honored artificial intelligence research for the first time, recognizing neural-network pioneers and the protein-structure system AlphaFold., Statement on AI RiskStatement on AI Risk, prop. n.: A one-sentence public statement from May 2023, signed by hundreds of leading AI scientists and company heads, declaring that guarding against the chance of AI wiping out humanity should rank as a priority for the whole world., Turing AwardTuring Award, prop. n.: Nicknamed the 'Nobel Prize of computing', the top honor in computer science, awarded each year since 1966 by the Association for Computing Machinery. Several AI pioneers have received it., Yoshua BengioYoshua Bengio, prop. n.: A Canadian computer scientist who helped found deep learning, including ideas behind today's language models, and who has become a leading voice on the risks of advanced AI., capsule networkcapsule network, n.: A network design championed by Geoffrey Hinton in which groups of neurons, called capsules, each describe a part of an object and its position, so the network can check whether the parts fit together.