Geoffrey Hinton, Yann LeCun, Yoshua Bengio and Demis Hassabis win the award, which last year recognized the creators of RNA vaccines
Yoshua Bengio (France, 1964), Geoffrey Hinton (United Kingdom, 1947) and Yann LeCun (France, 1960), three of the researchers known as the "godfathers of Artificial Intelligence", have just won the Princess of Asturias Award for Scientific and Technical Research 2022. And, to the three scientists, who were already recognized in 2018 with the Turing Prize, considered de facto as the 'Nobel of computer science', Demis Hassabis (United Kingdom, 1976) is added, who began to play to chess at the age of four, and soon became a child prodigy. Until, at the age of eight, success on the board led him to ask himself two questions that have haunted him ever since: first, how does the brain learn to master complex tasks? and second, could computers someday do the same?
This new award recognizes the work of the four scientists for their conceptual and engineering contributions made in the field of deep neural networks. Some works of capital importance, because, in recent years, deep learning methods have been responsible for amazing advances in computer vision, speech recognition, natural language processing and robotics, among other applications.
These technologies are used by billions of people every day around the planet. In fact, anyone with a smartphone in their pocket can tangibly experience advances in natural language processing and computer vision that weren't possible just a decade ago. But in addition to the products we use every day, new advances in deep learning have given scientists powerful new tools in areas ranging from medicine to materials science to astronomy.
Geoffrey Hinton, who has advocated a machine learning approach to Artificial Intelligence since the early 1980s, looked at how the human brain works to suggest ways to develop machine learning systems. Inspired by the brain, he and other researchers proposed "artificial neural networks" as a cornerstone of their machine learning research. Hinton, LeCun, and Bengio recognized the importance of building deep networks using many layers, hence the term "deep learning." And all of them have worked together and independently in this field of Deep Learning.
For his part, Demis Hassabis is well known for being the Co-Founder and CEO of Google DeepMind, a London-based machine learning startup specializing in building learning algorithms.
DeepMind was acquired in 2014 by Google for $527 million), where Hassabis is now vice president of engineering leading AI projects.
After developing several hugely successful computer games, Hassabis realized that his company's technology was ready to take on one of biology's most relevant and difficult puzzles, one that researchers had been trying to solve for half a century: predicting the structure of proteins.
And it is that the three-dimensional structure of proteins determines how they behave and interact in the body. But a lot of important proteins have structures that biologists don't yet know about. Using Artificial Intelligence to accurately predict them would offer an invaluable tool to help understand diseases, from cancer to covid. Proteins are a primary target for many drugs and a key ingredient in new therapies. Quickly unlocking their structures would speed up the development of new therapies and vaccines.
The jury for the Princess Prize for Research now recognizes that "his contributions to the development of deep learning (Deep Learning) represent a great advance in techniques as diverse as speech recognition, natural language processing, object perception, machine translation , strategy optimization, protein structure analysis, medical diagnostics, and many others.”
"Its current and future impact on the progress of society can be described as extraordinary," the minutes conclude.