The Princess of Asturias Foundation

Scientific experts in the field of artificial intelligence Geoffrey Hinton (Canadian and British), Yann LeCun (French and American), Yoshua Bengio (Canadian) and Demis Hassabis (British) have been bestowed with the 2022 Princess of Asturias Award for Technical and Scientific Research, as announced today by the Jury responsible for conferring said Award

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The Jury for the Award –convened by the Princess of Asturias Foundation– was chaired by Pedro Miguel Echenique Landiríbar and composed of Juan Luis Arsuaga Ferreras, César Cernuda Rego, Juan Ignacio Cirac Lascuráin, Avelino Corma Canós, Elena García Armada, Jerónimo López Martínez, Sir Salvador Moncada, Concepción Alicia Monje Micharet, Ginés Morata Pérez, Inés Rodríguez Hidalgo, María Teresa Telleria Jorge, María Paz Zorzano Mier and Manuel Toharia Cortés (acting as secretary).

This candidature was put forward by Bart Selman, President of the Association for the Advancement of Artificial Intelligence and Professor at Cornell University (USA).

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).

Geoffrey Hinton (London, UK, 6th December 1947) graduated in Experimental Psychology from the University of Cambridge in 1970 and received his PhD in Artificial Intelligence from the University of Edinburgh in 1975. He has worked at the University of Sussex (UK), the University of California, San Diego and Carnegie-Mellon University (USA), as well as at the University of Toronto (Canada), among others. Between 1998 and 2001, he set up the Gatsby Computational Neuroscience Unit at University College London. He subsequently returned to the University of Toronto, where he is currently Professor Emeritus in the Department of Computer Science. Since 2013, he has worked with Google as vice president for the development of deep learning applications and he is currently Chief Scientific Advisor at the Vector Institute of Canada. He is the author or co-author of more than three hundred publications, has been cited 572 982 times and has an h-index of 169, according to Google Scholar. Hinton is a Fellow of the Royal Society of the United Kingdom (2011 Prince of Asturias Award for Communication and Humanities), the Royal Society of Canada and the Association for the Advancement of Artificial Intelligence (of international scope). He is an honorary member of the American Academy of Arts and Sciences and the US National Academy of Engineering. Companion of the Order of Canada and holder of honorary degrees from the Universities of Edinburgh, Sussex and Sherbrooke, he has received, among other distinctions, the David E. Rumelhart Award (USA, 2001), the Award for Research Excellence from the International Joint Conferences on Artificial Intelligence Organization (2005), the Gerhard Herzberg Canada Gold Medal for Science and Engineering from the Natural Sciences and Engineering Research Council of Canada (2010), the NEC C&C Prize (Japan, 2016), the James Clerk Maxwell Medal awarded by the Institute of Electrical and Electronics Engineers (IEEE) and the Royal Society of Edinburgh (2016), the BBVA Frontiers of Knowledge Award (2017) and the aforementioned Turing Award.

Yann LeCun (Soisy-sous-Montmorency, France, 8th July 1960) graduated in Electrical Engineering from the ESIEE Paris in 1983 and received his PhD in Computer Science from the Pierre and Marie Curie University (Paris) in 1987. After postdoctoral research in Geoffrey Hinton’s group at the University of Toronto, he joined AT&T Bell Laboratories in 1988, where he became head of the Image Processing Research Department in 1996. After a brief tenure as a Fellow of the NEC Research Institute in Princeton, New Jersey, he joined New York University in 2003. He is director of AI Research at Facebook and maintains his academic activity at New York University, linked to the Center for Data Science (which he founded and headed from 2012 to 2014) and the Courant Institute of Mathematical Science. He is a member of the Advisory Board of the Institute of Pure and Applied Mathematics and of the Institute for Computational and Experimental Research in Mathematics (ICERM). LeCun is the author or co-author of more than three hundred publications, has been cited 248 571 times and has an h-index of 135, according to Google Scholar. He is a member of the US National Academy of Engineering and is the recipient of numerous awards, including the IEEE Neural Network Pioneer Award (2014), the IEEE PAMI Distinguished Researcher Award (2015) and the University of Pennsylvania Harold Pender Award (2018), in addition to the aforementioned Turing Award. He holds honorary degrees from the National Polytechnic Institute of Mexico (IPN) and the Federal Polytechnic School of Lausanne (EPFL). He was included in Wired magazine’s list of 100 Global Influencers in 2016.

Yoshua Bengio (Paris, France, 5th March 1964) received his Bachelor’s degree in Engineering in 1986 from McGill University (Canada), where he also earned his Master’s degree and PhD in Computer Science. He completed a postdoctoral fellowship at the Massachusetts Institute of Technology (MIT) and with LeCun’s group at AT&T Bell Laboratories. He has been a Professor in the Department of Computer Science and Operations Research at the University of Montreal since 1993. In addition to holding the Canada Research Chair in Statistical Learning Algorithms, he is the founder and scientific director of Mila, the Quebec Artificial Intelligence Institute, co-founder of the Element AI startup and advisor to several tech companies. He is also Scientific Director of the Institut de Valorisation des Données (IVADO) and co-chair, since 2019, of the Canadian Advisory Council on Artificial Intelligence. Bengio has published more than six hundred articles, which have been cited 532 373 times and has an h-index of 205, according to Google Scholar. Officer of the Order of Canada and Chevalier of the French Legion of Honour, he is a Fellow of the Royal Society of Canada (2017). He has received distinctions such as the Prix Marie-Victorin from the Government of Quebec (2017), the Medal of the 50th Anniversary of Quebec’s Ministry of International Relations and Francophonie (2018), the Lifetime Award from the Canadian AI Association (2018), the Killam Prize and the IEEE CIS Neural Network Pioneer Award (2019). He is the author of three renowned books on deep learning and was one of the promoters of the Montreal Declaration for a Responsible Advancement of Artificial Intelligence.

Demis Hassabis was born in London (UK) on 27th July 1976. A child prodigy in chess (he was already a renowned player at the age of thirteen) and passionate about programming, at seventeen he joined the Bullfrog Productions company as a video game designer, where he created hit games like Theme Park. He studied at the University of Cambridge, where he graduated in 1997 in Computer Science, and in 1998 founded the video game company Elixir Studios, with which he created projects for multinationals such as Microsoft and Vivendi. In 2009, he received his PhD in Cognitive Neuroscience from University College London and rounded out his studies at Harvard (USA) and MIT. In 2011, with the support of investors such as Elon Musk, he founded the AI company DeepMind Technologies, with which he began to create learning algorithms to master video games, such as AlphaGo (which in a short time managed to defeat Lee Sedol, world champion of Go, a game of Chinese origin), and to advance in the development of an artificial intelligence learning system, AlphaZero, considered by some experts to be revolutionary, as it combines human neuronal functioning and the connections between memory and imagination with machine learning mechanisms. With another of these variants, AlphaFold, he managed, as mentioned above, to transform the study of the 3D structure of proteins. Following Google’s acquisition of DeepMind in 2014, Hassabis continued to serve as its CEO. According to Google Scholar, he has been cited 79 960 times and has an h-index of 73. Commander of the Order of the British Empire, Hassabis is a Fellow of the Royal Society, the Royal Academy of Engineering and the Royal Society of Arts, all in the UK, and has received the Mullard Award from the Royal Society (2014), the Golden Plate Award from the American Academy of Achievement (USA, 2017) and the Dan David Prize (Israel, 2020).

As stated in their Regulations, the Princess of Asturias Awards are aimed at rewarding “the scientific, technical, cultural, social and humanitarian work carried out at an international level by individuals, institutions or groups of individuals or institutions”. In keeping with these principles, the Princess of Asturias Award for Technical and Scientific Research is to be granted for the “work of fostering and advancing research in the field of mathematics, astronomy and astrophysics, physics, chemistry, life sciences, medical sciences, earth and space sciences or technological sciences, including those disciplines corresponding to each of these fields as well as their related technologies.”

This year, a total of 47 candidatures comprising 16 nationalities were put forward for the Technical and Scientific Research Award.

This is the seventh of the eight Princess of Asturias Awards to be bestowed in what is now their forty-second year. Previously, the Princess of Asturias Award for the Arts was jointly granted to flamenco singer Carmen Linares and flamenco dancer and choreographer María Pagés; the Award for Communication and Humanities went to journalist Adam Michnik; the Award for Social Sciences was conferred on Mexican archaeologist Eduardo Matos Moctezuma; the Award for Sports went to the Olympic Refuge Foundation and the IOC Refugee Olympic Team; the Award for Literature was conferred on playwright Juan Mayorga; and the Award for International Cooperation was bestowed on British former-yachtswoman and social entrepreneur Ellen MacArthur. The Princess of Asturias Award for Concord will be conferred next week.

As is customary, the presentation of the Princess of Asturias Awards will take place in October in a solemn ceremony presided over by TM The King and Queen of Spain, accompanied by TRH Leonor, Princess of Asturias, and Infanta Sofía.

Each Princess of Asturias Award comprises a Joan Miró sculpture symbolizing the Award, a diploma, an insignia and a cash prize of €50 000.