Last week, information reached my email that, at the national level, I observe has gone almost unnoticed, and that I would like to disseminate as it deserves, at least in this blog that tries to put the work that is being done in the spotlight, in all fields, in the field of artificial intelligence (AI). Yoshua Bengio, professor at the University of Montreal and Mila’s scientific director; Geoffrey Hinton, vice president and fellow of engineering at Google, and chief scientific advisor to The Vector Institute, as well as professor emeritus at the University of Toronto; and Yann LeCun, a professor at New York University and vice president and chief scientist for artificial intelligence at Facebook, received the ACM Turing Prize, considered by many to be the ‘Nobel’ in Informatics.
The award recognizes the work of the three scientists for their conceptual and engineering advances in the field of deep neural networks. According to the information that explains the Award, “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.”
While the use of artificial neural networks as a tool to help computers recognize patterns and simulate human intelligence was introduced in the 1980s, in the early 2000s, LeCun, Hinton, and Bengio were part of a small group. that he remained committed to this approach. Although his efforts to rekindle the interest of the artificial intelligence community in neural networks were initially met with skepticism, his ideas recently resulted in major technological advancements, and his methodology is now the dominant paradigm in this field.
The ACM AM Turing Prize awards a prize of € 1 million, with financial support provided by Google, and is named for Alan M. Turing, the British scientist who articulated the mathematical basis and limits of computing.
“Artificial intelligence is now one of the fastest growing areas in all of science and one of the most talked about topics in society,” says ACM President Cherri M. Pancake. “The growth and interest in AI is due, in large part, to the recent advancements in deep learning for which Bengio, Hinton and LeCun laid the foundation. These technologies are used by billions of people. Anyone with a smartphone in their pocket can tangibly experience advances in natural language processing and computer vision that weren’t possible just 10 years ago. In addition to the products we use every day, new advancements in deep learning have given scientists powerful new tools, in areas ranging from medicine, astronomy, to materials science. “
Geoffrey Hinton, who has advocated for 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 others proposed “artificial neural networks” as the cornerstone of their machine learning investigations.
Hinton, LeCun and Bengio recognized the importance of building deep networks using many layers, hence the term “deep learning”, and they have all worked together and independently in this realm of Deep Learning. For example, LeCun did postdoctoral work under Hinton’s supervision, and LeCun and Bengio worked together at Bell Labs in the early 1990s. Even when they don’t work together, there is a synergy and interconnectedness in their work, and they have influenced each other. Even today the three continue to explore the intersection of machine learning with neuroscience and cognitive science, especially through their joint participation in the machine learning and brains program, an initiative of CIFAR, formerly known as the Canadian Institute for Advanced Research.
Congratulations then to Bengio, Hinton and LeCun, the three musketeers and those responsible for the Depp Learning revolution.
