About Geoffrey Hinton
Geoffrey Everest Hinton CC FRS FRSC is a British-Canadian computer scientist and cognitive psychologist, most noted for his work on artificial neural networks. He is widely regarded as the "Godfather of Deep Learning" and has been instrumental in making neural networks a central technology in modern artificial intelligence.
Hinton received his BA in Experimental Psychology from King's College, Cambridge in 1970, and his PhD in Artificial Intelligence from the University of Edinburgh in 1978. His doctoral thesis explored the use of relaxation in neural network models, laying the groundwork for decades of subsequent research.
In 2024, Hinton was awarded the Nobel Prize in Physics alongside John Hopfield for foundational discoveries and inventions that enable machine learning with artificial neural networks. He had previously received the ACM A.M. Turing Award in 2018, shared with Yann LeCun and Yoshua Bengio, for conceptual and engineering breakthroughs in deep neural networks.
Notable Quotes
“The key thing about deep learning is that these layers of features are not designed by human engineers. They are learned from data using a general-purpose learning procedure.”
— Turing Award Lecture, 2019
“I console myself with the normal excuse: if I hadn't done it, somebody else would have.”
— On his concerns about AI safety, New York Times, 2023
“It's hard to see how you can prevent the bad actors from using it for bad things.”
— Interview on AI risks, BBC, 2023
“These things will have learned from us by reading everything the human race has ever written. They'll understand us better than we understand ourselves.”
— MIT Technology Review, 2023
Contact Information
Geoffrey Hinton is best reached through academic channels. After retiring from Google in 2023, he remains affiliated with the University of Toronto as a Professor Emeritus. For media inquiries, his public statements on AI safety have been widely covered by major outlets.
For research collaboration inquiries, contacting through the Vector Institute in Toronto or through academic conference channels is recommended.
Use Lessie to find verified contact information, mutual connections, and the best outreach strategy for reaching Geoffrey Hinton and similar investors.
Contact via LessiePublications
Geoffrey Hinton has authored or co-authored over 300 peer-reviewed publications, many of which are among the most cited papers in computer science history. His most influential works include:
\"Learning representations by back-propagating errors\" (1986, Nature) — Co-authored with Rumelhart and Williams, this paper introduced backpropagation to a wide audience and remains one of the most cited papers in all of science with over 45,000 citations.
\"A Fast Learning Algorithm for Deep Belief Nets\" (2006) — This paper demonstrated effective pre-training of deep networks using restricted Boltzmann machines, sparking renewed interest in deep learning.
\"ImageNet Classification with Deep Convolutional Neural Networks\" (2012) — The AlexNet paper, co-authored with Alex Krizhevsky and Ilya Sutskever, which catalyzed the deep learning revolution in computer vision.
Podcast
Geoffrey Hinton has become one of the most sought-after voices in AI discourse, particularly since his departure from Google in 2023. His interviews and talks focus on both technical advances and AI safety concerns.
Notable appearances include his Turing Award Lecture (2019), extensive interviews with the New York Times, BBC, and 60 Minutes, and keynote addresses at major AI conferences including NeurIPS, ICML, and AAAI.
His 2023 public statements about the existential risks of AI received worldwide media coverage and significantly influenced the public discourse on AI safety and regulation.
Frequently Asked Questions
Who is Geoffrey Hinton?
Why did Geoffrey Hinton leave Google?
Hinton resigned from Google in May 2023 so he could speak freely about the potential dangers of artificial intelligence. He expressed concerns about AI systems becoming more intelligent than humans and the risks of misinformation, job displacement, and autonomous weapons.
What is Geoffrey Hinton known for?
Hinton is best known for his pioneering work on backpropagation, Boltzmann machines, deep belief networks, and dropout regularization. His supervision of the AlexNet project in 2012 triggered the modern deep learning revolution that transformed computer vision, natural language processing, and AI as a whole.
What awards has Geoffrey Hinton won?
Hinton has received numerous prestigious awards including the 2024 Nobel Prize in Physics, the 2018 ACM A.M. Turing Award, the NSERC Herzberg Gold Medal, the IEEE Frank Rosenblatt Award, and fellowship in the Royal Society. He is also a Companion of the Order of Canada.
What is Geoffrey Hinton's stance on AI safety?
Since leaving Google in 2023, Hinton has been vocal about AI safety risks. He has warned about the potential for AI systems to surpass human intelligence, the dangers of AI-generated misinformation, and the need for international regulation to prevent misuse of AI technology.
How can I contact Geoffrey Hinton?
Geoffrey Hinton can be reached through the University of Toronto where he remains a Professor Emeritus, or through the Vector Institute in Toronto. For media inquiries, he is frequently accessible through major technology and science journalists. Using a professional outreach tool like Lessie AI can help identify the best contact approach.