Yann LeCun
In plain wordsA 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.
French-American computer scientist, professor at New York University since 2003. His 1987 Paris doctorate proposed an early form of 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., and at AT&T Bell Laboratories he used it to train 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. to read handwriting; the resulting LeNetLeNet, prop. n.: A family of early image-recognition neural networks built at Bell Labs from 1989 that learned to read handwritten digits. A version read huge numbers of bank checks, and its design underlies today's image models. systems read a large share of US bank checks by the late 1990s, and he co-created the MNISTMNIST, prop. n.: A famous collection of 70,000 small images of handwritten digits used to test image-recognition programs. Getting a model to read MNIST digits is the 'hello world' of machine learning. dataset. He was founding director of Facebook AI Research (FAIR) from 2013 and later Meta's chief AI scientist, championing open-weightopen-weight model, n.: An AI model whose trained internal numbers are published for anyone to download and run on their own computers, even if the data and code used to make it stay private. releases. A prominent skeptic of existential riskexistential 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. arguments and of large language modelslarge language model, n.: A computer program trained on enormous amounts of text to predict the words that come next. At vast scale, that simple skill lets it chat, answer questions, translate, summarize and write code. as a path to human-level AI, he advocates world modelsworld model, n.: An AI's internal simulation of how its world works, which lets it predict what will happen next — especially in response to its own actions — and so plan, imagine or practice without acting for real. trained with joint-embedding predictive architectures (JEPA). Leaving Meta at the end of 2025, he co-founded and chairs Advanced Machine Intelligence (AMI) Labs, a world-model startup that raised over US$1 billion in 2026. He 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. 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. and 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..
Related
- convolutional neural networkconvolutional 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.
- LeNetLeNet, prop. n.: A family of early image-recognition neural networks built at Bell Labs from 1989 that learned to read handwritten digits. A version read huge numbers of bank checks, and its design underlies today's image models.
- MNISTMNIST, prop. n.: A famous collection of 70,000 small images of handwritten digits used to test image-recognition programs. Getting a model to read MNIST digits is the 'hello world' of machine learning.
- godfathers of AIgodfathers of AI, phr.: A 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.
- world modelworld model, n.: An AI's internal simulation of how its world works, which lets it predict what will happen next — especially in response to its own actions — and so plan, imagine or practice without acting for real.
- Meta AIMeta AI, prop. n.: The artificial intelligence research group of Meta, the company behind Facebook and Instagram, known for the PyTorch software and the Llama models. It is also the name of Meta's chatbot.
- open-weight modelopen-weight model, n.: An AI model whose trained internal numbers are published for anyone to download and run on their own computers, even if the data and code used to make it stay private.
Sources
- LeCun, Y., Bottou, L., Bengio, Y. & Haffner, P. (1998). Gradient-Based Learning Applied to Document Recognition. Proceedings of the IEEE 86(11): 2278–2324.
- LeCun, Y. (2022). A Path Towards Autonomous Machine Intelligence. OpenReview preprint.
Mentioned in
artificial general intelligenceartificial general intelligence, n.: AI that could learn and do almost any mental task a capable adult can, rather than excelling at one narrow job. Experts disagree on the exact bar and on when, or whether, it will arrive., 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., Meta AIMeta AI, prop. n.: The artificial intelligence research group of Meta, the company behind Facebook and Instagram, known for the PyTorch software and the Llama models. It is also the name of Meta's chatbot., p(doom)p(doom), n.: Shorthand for someone's personal estimate of the chance that AI leads to catastrophe for humanity, such as extinction. People give it as a percentage, from nearly zero to nearly certain., godfathers of AIgodfathers of AI, phr.: A 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., human-level AIhuman-level AI, n.: AI that can match an ordinary adult across the whole range of thinking tasks, such as talking, learning, reasoning and planning. An older, more intuitive name for the goal now usually called general AI., ICLRICLR, prop. n.: A major deep-learning conference, held every spring since 2013, where the reviews of each submitted paper are posted online for anyone to read., instrumental convergenceinstrumental convergence, n.: The idea that almost any goal is easier to reach if you stay switched on, keep your goal and gain resources and power, so very different AIs might all seek those same things., LeNetLeNet, prop. n.: A family of early image-recognition neural networks built at Bell Labs from 1989 that learned to read handwritten digits. A version read huge numbers of bank checks, and its design underlies today's image models., Mark ZuckerbergMark Zuckerberg, prop. n.: The American co-founder and chief executive of Facebook's parent company Meta, who made it a major AI developer that released its Llama models for anyone to download., MNISTMNIST, prop. n.: A famous collection of 70,000 small images of handwritten digits used to test image-recognition programs. Getting a model to read MNIST digits is the 'hello world' of machine learning., 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., Bell LabsBell Labs, prop. n.: A famous American industrial research laboratory, long owned by the telephone company AT&T, where the transistor, information theory and key early machine-learning methods were invented., GalacticaGalactica, prop. n.: A science-focused AI language model released by Meta in November 2022 and pulled after three days because it confidently produced fake scientific papers and facts., Koray KavukcuogluKoray Kavukcuoglu, prop. n.: A Turkish-born computer scientist who co-authored many of DeepMind's landmark papers and in 2026 took charge of Google DeepMind as its senior vice president., Kunihiko FukushimaKunihiko Fukushima, prop. n.: A Japanese engineer who in 1979 invented the neocognitron, a brain-inspired image-recognition network that was the direct ancestor of today's convolutional neural networks.