Alex Krizhevsky

Last updated

Alex Krizhevsky (born 4 March 1986) is a Soviet-born Canadian computer scientist most noted for his work on artificial neural networks and deep learning. In 2012, Krizhevsky, Ilya Sutskever and their PhD advisor Geoffrey Hinton, at the University of Toronto, [1] developed a powerful visual-recognition network AlexNet using only two GeForce NVIDIA GPU cards. [2] 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. [2]

Contents

AlexNet

Motivated by Sutskever and inspired by Hinton, Krizhevsky developed AlexNet to expand the limits in image recognition and classification. Building on Convolutional Neural Networks and Sustkever’s Deep Neural Network approach of deepening the neural layers far beyond the convention of the time - as well as adding Dropout for training resilience - AlexNet won the ImageNet challenge in 2012. The team presented their paper for AlexNet [3] at NeurIPS (NIPS) 2012.

Shortly after AlexNet’s debut, Krizhevsky and Sutskever sold their startup, DNN Research Inc., to Google. 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. [1] Many of his numerous papers on machine learning and computer vision are frequently cited by other researchers. [4] He is also the main author of the CIFAR-10 and CIFAR-100 datasets. [5] [6]

Legacy

AlexNet is widely credited with igniting the deep learning revolution. Its success demonstrated the effectiveness of deep neural networks trained on GPUs, leading to rapid progress across multiple domains of artificial intelligence beyond computer vision. The techniques and momentum generated by AlexNet helped shape the development of modern natural language processing models, including large-scale transformer-based models such as BERT and GPT, which power tools like ChatGPT. [7]


References

  1. 1 2 Gershgorn, Dave (18 June 2018). "The inside story of how AI got good enough to dominate Silicon Valley". Quartz. Retrieved 23 February 2021.
  2. 1 2 Witt, Stephen (27 November 2023). "How Jensen Huang's Nvidia Is Powering the A.I. Revolution". The New Yorker. Retrieved 24 December 2023.
  3. ↑ Krizhevsky, Alex; Sutskever, Ilya; Hinton, Geoffrey E. (3 December 2012). "ImageNet classification with deep convolutional neural networks". In F. Pereira; C. J. C. Burges; L. Bottou; K. Q. Weinberger (eds.). NIPS'12: Proceedings of the 25th International Conference on Neural Information Processing Systems. Vol. 1. Curran Associates. pp. 1097–1105. Archived from the original on 20 December 2019. Retrieved 13 March 2018.
  4. ↑ "Alex Krizhevsky". Google Scholar Citations.
  5. ↑ "CIFAR-10 and CIFAR-100 datasets" . Retrieved 7 March 2021.
  6. ↑ Krizhevsky, Alex (2009), Learning multiple layers of features from tiny images (PDF), CiteSeerX   10.1.1.222.9220 , S2CID   18268744
  7. ↑ LeCun, Yann; Bengio, Yoshua; Hinton, Geoffrey (2015). "Deep learning". Nature. 521: 436–444. doi:10.1038/nature14539. PMID   26017442.
This page is based on this Wikipedia article
Text is available under the CC BY-SA 4.0 license; additional terms may apply.
Images, videos and audio are available under their respective licenses.