Alex Krizhevsky is a Ukrainian-born Canadian computer scientist most noted for his work on artificial neural networks and deep learning. In 2012, Krizhevsky and Ilya Sutskever developed a powerful visual-recongition network AlexNet using only two GeForce NVIDIA GPU cards. This revolutionized research in neural networks. Previously neural networks were trained on CPUs. The transition to GPUs opened the way to the development of advanced AI models.[1] AlexNet won the ImageNet challenge in 2012. Krizhevsky and Sutskever sold their startup, DNN Research Inc., to Google, shortly after winning the contest. Krizhevsky left Google in September 2017 after losing interest in the work, to work at the company Dessa in support of new deep-learning techniques.[2] Many of his numerous papers on machine learning and computer vision are frequently cited by other researchers.[3] He is the creator of the CIFAR-10 and CIFAR-100 datasets.[4][5]

Alex was a PhD student at University of Toronto under Geoffrey Hinton.[6]

References

  1. ↑ Witt, Stephen (27 November 2023). "How Jensen Huang's Nvidia Is Powering the A.I. Revolution". The New Yorker. Retrieved 24 December 2023.
  2. ↑ Gershgorn, Dave (18 June 2018). "The inside story of how AI got good enough to dominate Silicon Valley". Quartz. Retrieved 23 February 2021.
  3. ↑ "Alex Krizhevsky". Google Scholar Citations.
  4. ↑ "CIFAR-10 and CIFAR-100 datasets". Retrieved 7 March 2021.
  5. ↑ Krizhevsky, Alex (2009), Learning multiple layers of features from tiny images (PDF), CiteSeerX 10.1.1.222.9220, S2CID 18268744
  6. ↑ Goldenfein, Jake (31 October 2019), Monitoring Laws: Profiling and Identity in the World State, doi:10.1017/9781108637657.008, S2CID 243673378
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