---
title: Geoffrey Hinton
tags: [researcher, deep-learning, neural-networks, biography]
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created: 2026-05-09
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---

# Geoffrey Hinton

Geoffrey Hinton is a British-Canadian cognitive scientist and computer scientist widely
regarded as one of the founding figures of modern deep learning. His work on
backpropagation, Boltzmann machines, and deep belief networks laid the groundwork for the
neural network revolution of the 2010s.

## Key Contributions

**Backpropagation (1986)**  
Hinton, Rumelhart, and Williams published the landmark paper demonstrating that
backpropagation could efficiently train multi-layer neural networks. This established
the practical training algorithm still used, in refined form, for all modern networks.

**Deep Belief Networks (2006)**  
With Salakhutdinov, Hinton showed that deep networks could be effectively pre-trained
layer by layer using restricted Boltzmann machines (RBMs), then fine-tuned. This was the
first demonstration that deep architectures were trainable and useful — reigniting
interest in neural networks after years of stagnation.

**AlexNet (2012)**  
Hinton's lab produced AlexNet (Krizhevsky, Sutskever, Hinton), which won the ImageNet
Large Scale Visual Recognition Challenge by a 10.8 percentage point margin using a deep
convolutional neural network trained on GPUs. This result ended a decade of feature
engineering and established deep learning as the dominant paradigm for vision.

**Capsule Networks**  
Hinton proposed capsule networks as an alternative to CNNs, arguing that pooling discards
spatial relationships that are important for viewpoint-invariant recognition. Capsule
networks have not achieved the widespread adoption of CNNs.

## Departure from Google

Hinton joined Google in 2013 following the acquisition of his startup DNNresearch. In
May 2023 he resigned from Google to speak freely about the risks of AI development,
stating that he had come to believe AI systems could surpass human intelligence sooner
than he had previously expected, with potentially serious consequences.

## See Also

- [[training-techniques]] — techniques Hinton's research helped establish
- [[large-language-models]] — modern systems built on the foundations he pioneered
- [[andrej-karpathy]] — researcher who studied under Hinton at Toronto
