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University of Toronto

A public research university in Toronto where Geoffrey Hinton has been affiliated since 1987 and where AlexNet, the 2012 deep convolutional network, was developed.

Founded 1827Website utoronto.ca Era Prehistory

What it is

The University of Toronto, often called UofT, is a public research university in Toronto, Ontario, Canada.[1] Its importance in AI history comes largely from the people who worked there: Geoffrey Hinton, a central figure in deep learning, and the graduate students who built AlexNet in 2012.

Origins

The university was founded as King's College under a royal charter issued on 15 March 1827.[1] Hinton joined as a professor of computer science in 1987 and was named a University Professor, the university's highest academic appointment, in 2006. He is now University Professor Emeritus.[2] He was also one of the first researchers supported by the Canadian Institute for Advanced Research (CIFAR).[2]

Hinton's ties to Toronto were nearly continuous. Apart from 1998 to 2001, when he founded and directed the Gatsby Computational Neuroscience Unit at University College London, he was affiliated with Toronto from 1987 onward. From 2013 to 2023 he divided his time between Google Brain and the university.[9]

Known for

The best-known work from the university is AlexNet. It was developed at the university in 2012 by graduate students Alex Krizhevsky and Ilya Sutskever, with their faculty adviser Geoffrey Hinton.[3] The paper, “ImageNet Classification with Deep Convolutional Neural Networks”, was published at NIPS 2012 and lists all three authors at the University of Toronto. Training the network took five to six days on two NVIDIA GTX 580 GPUs.[4] A deep convolutional network is a neural network that processes images through stacked layers of learned filters, each layer picking out features from the one before.

The Computer History Museum released the 2012 AlexNet source code with Google in March 2025. The museum reports that the paper has been cited more than 172,000 times on Google Scholar.[3]

Ilya Sutskever's own training also took place in Toronto. He earned a BSc in mathematics (2005), an MSc (2007) and a PhD (2013) in computer science there, with Hinton as his doctoral adviser.[5] Yann LeCun spent a year as a postdoctoral researcher under Hinton at Toronto starting in 1987, before joining AT&T Bell Labs in 1988.[6]

In 2024 Hinton shared the Nobel Prize in Physics with John Hopfield. At the time of the award, his listed affiliation was the University of Toronto.[8]

Place in AI history

Toronto's role extends beyond the 2012 work to the institutions built around it. In 2017 the Vector Institute launched in Toronto in partnership with the university. Its founding scientists, including Hinton, were affiliated with the University of Toronto.[7]

In 2019 Gerry Schwartz and Heather Reisman donated $100 million, then a record, to create the Schwartz Reisman Innovation Campus, an innovation and artificial-intelligence centre.[1]

The university's history shows how a single research group, working on a specific result, can become connected to later research institutes, donors and a wider network of researchers that shapes the field.

CapabilitiesComputer vision

TechniquesDeep learning

ApplicationsEducation

HistoryResearch history

20241

  1. MilestoneHopfield and Hinton win the Nobel Prize in Physics for neural-network foundations

    On 8 October 2024 the Nobel Prize in Physics went to John J. Hopfield and Geoffrey Hinton for foundational work on artificial neural networks, the systems behind much of modern machine learning.

20121

  1. BenchmarkAlexNet wins the ImageNet ILSVRC 2012 challenge

    In October 2012 AlexNet, a deep neural network built by a University of Toronto team, won the ImageNet image-classification challenge by a wide margin. Its result showed that large neural networks trained on GPUs could outperform hand-designed vision methods.

Models and products over time

2
  1. 2009
    • Apr 8, 2009 CIFAR-10 Product

      CIFAR-10 is a labelled image dataset of 60000 32×32 colour images in 10 mutually exclusive classes, split into 50000 training and 10000 test images; it was created by Krizhevsky, Nair and Hinton for training and comparing image classifiers.

  2. 2012
    • 2012 AlexNet Model

      AlexNet is the eight-layer convolutional network that won the ILSVRC2012 image classification task by a wide margin, showing that a large network trained on a large labelled dataset with GPUs could beat hand-designed features.

Notes and sources

  1. University of Torontohttps://en.wikipedia.org/wiki/University_of_Toronto
  2. Geoffrey Hinton wins Nobel Prize in Physicshttps://www.utoronto.ca/news/geoffrey-hinton-wins-nobel-prize
  3. CHM Releases AlexNet Source Codehttps://computerhistory.org/blog/chm-releases-alexnet-source-code/
  4. ImageNet Classification with Deep Convolutional Neural Networkshttps://papers.nips.cc/paper_files/paper/2012/file/c399862d3b9d6b76c8436e924a68c45b-Paper.pdf
  5. Ilya Sutskeverhttps://en.wikipedia.org/wiki/Ilya_Sutskever
  6. Yann LeCunhttps://en.wikipedia.org/wiki/Yann_LeCun
  7. News release: New Artificial Intelligence Research Institute Launched in Torontohttps://vectorinstitute.ai/?p=484
  8. Geoffrey Hinton – Facts – 2024https://www.nobelprize.org/prizes/physics/2024/hinton/facts/
  9. Geoffrey Hintonhttps://en.wikipedia.org/wiki/Geoffrey_Hinton

Cite this page: University of Toronto. TellWorld, https://www.tellworld.net/companies/university-of-toronto. Updated 2026-11-08