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Geoffrey Hinton, Yann LeCun, Yoshua Bengio and Demis Hassabis Princess of Asturias Award for Technical & Scientific Research 2022

Geoffrey Hinton, Yann LeCun, Yoshua Bengio and Demis Hassabis

Geoffrey Hinton, Yann LeCun and Yoshua Bengio are considered the ‘godfathers’ of an essential technique in artificial intelligence, called ‘deep learning’, which is based on the use of neural networks for voice recognition, computer vision and natural language processing, and has enabled advances in fields as diverse as object perception and machine translation. These neural networks aim to mimic the functioning of the human brain, using algorithms that convert the biological process of learning into mathematical sequences. The idea is for the machine to learn from its own experience. In 1986, Hinton invented backpropagation algorithms, fundamental for training neural networks. In 2012, these algorithms allowed him to create a convolutional neural network called AlexNet, made up of 650 000 neurons and trained with 1.2 million images, which registered an error rate in object recognition of only 26%, halving that of previous systems. He has made other contributions to artificial neural networks and their training, such as the co-invention of the Boltzmann machine, the Helmholtz machine and the so-called Product of Experts (PoE). In 2021, he published a document on the arXiv preprint platform in which he presented GLOM, an innovative project as yet theoretical which involves a new vector model for processing and representing visual information in a neural network, which is still in the development phase. Yann LeCun in turn made contributions to the development of the backpropagation algorithms that Hinton had invented and in 1989 created LeNet-5, a recognition system for characters written on bank checks, which represented a major advance for optical character recognition technology. He later contributed to the development of DjVu image compression technology, used by hundreds of websites and millions of users to access scanned documents on the Internet. He has also worked on deep learning methods for document recognition, human-computer interaction and speech recognition.

For his part, Bengio has made key contributions to probabilistic sequence models, used for speech and handwriting recognition and in unsupervised learning. He is currently studying more efficient algorithms in data representations, extracting pattern recognition and also enabling the understanding of more complex relationships and high-level concepts. Demis Hassabis is CEO and co-founder of DeepMind, one of the largest artificial intelligence research companies in the world, founded in 2011 and acquired in 2014 by Google (2008 Prince of Asturias Award for Communication and Humanities). At DeepMind, Hassabis has created a neural network model that combines the capabilities of an artificial neural network with the algorithmic power of a programmable computer. Hassabis’ company has combined the advances made in machine learning with deep learning processes and what is known as reinforcement learning to devise a new field of deep reinforcement learning, an artificial intelligence system that opens the door to multiple applications in the fields of many scientific disciplines. In 2021, the DeepMind team managed to predict the structure of more than 350 000 human proteins (44% of all known proteins) with a very high degree of accuracy. The data was made available to all laboratories in the world via the AlphaFold Protein Structure Database and the achievement was featured by Science magazine (2007 Prince of Asturias Award for Communication and Humanities) as Scientific Discovery of the Year. Edith Heard, director of the European Molecular Biology Laboratory, declared that the achievement “is truly a revolution for the life sciences, just as genomics was several decades ago.” Hinton, LeCun and Bengio were distinguished in 2018 with the Turing Award granted by the Association for Computing Machinery (ACM).

 Photographies:
Geoffrey Hinton: University of Toronto / Johnny Guatto
Yann LeCun: University of California
Yoshua Bengio: TEDxMontréal under license CC BY-NC-SA 2.0
Demis Hassabis: Royal Society under license CC BY-SA 4.0

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