I last sat in 2005,” Geoffrey Hinton often says, “and it was a mistake.” In the 17 years since, Hinton has never sat down; his severe back problems prevent him from doing so. He only trains or Travels by car, so he can stretch out on seats. He can’t fly commercial, because airlines insist on sitting for take-off or landing. He kneels on a table using foam cushions” eats like a monk at the altar”. With his trademark, he turns his back to what he calls “a long-standing problem.” For 17 years working at the University of Toronto, Hinton developed Artificial Intelligence (AI). He rescued neural networks back from the AI winter, ‘invented’ deep learning, taught a bevy of geniuses now on the bleeding edge of AI, and while he was at it, he called Turing won the award.
I first came across Hinton’s legend in a brilliant book by Cade Metz called Genius Makers, where he details the lives of those who shaped AI, the most prominent of them being Hinton. After studying psychology at Cambridge and AI at the University of Edinburgh, Hinton went back to something that had fascinated her even as a child: how the human brain stored memories, and how it worked. He was one of the first researchers to begin work on ‘mimicking’ the human brain with computer hardware and software, thus creating a new and purer form of AI, which we now call ‘deep learning’. He began doing this in the 1980s with a fearless group of students. His PhD thesis, titled Deep Neural Networks for Acoustic Modeling in Speech Recognition, showed how deep neural networks outperformed older machine learning models such as Hidden Markoves and Gaussian Mixtures in identifying speech patterns. He literally invented ‘backpropagation’, which was reportedly one of the concepts that inspired Google’s BackRub search algorithm, which is the core of its exemplary service.
“I get very excited when we discover a way to improve neural networks — and when it’s closely related to the way the brain works,” Hinton says. By mimicking the brain, he tried to get rid of traditional machine learning techniques, where humans label pictures, words, and objects; Instead, his work mimicked the brain’s self-learning techniques. He and his team “built artificial neurons out of interconnected layers of software modeled after columns of neurons in the brain’s cortex. These neural nets can collect information, respond to it, sense that something is going on.” what it looks like or how it sounds” (bit.ly/3LRJwWo ). The AI community did not trust this new approach; Hinton told Sky News that it was “an idea that almost no one on Earth believed at the time – it was largely a dead idea even among AI researchers”.
Well, that sentiment has changed. Deep learning has been used by Google, Meta, Microsoft, DeepMind, Baidu and almost every other tech firm to build driverless cars, predict protein folding, and beat humans in Go. Among Hinton’s students, Yan Lecan now leads Meta’s AI efforts, Yoshua Bengio is doing seminal work at the University of Montreal, Ilya Sutskever co-founded OpenAI, which is famous for GPT-3. Hinton himself works part-time for Google, the result of a frenzied bidding process between Google, Microsoft, and Baidu, where he auctioned his company (and its services) to Google for $44 million—a legend in itself. Goods of Deep learning is now considered one of the most exciting developments in AI. It is believed to be the surest bet that AI will achieve Artificial General Intelligence, or AGI. As Hinton put it: “We stopped being crazy fringe. Now we’re crazy core.”
Hinton comes from an intellectual and academic family. His mother used to tell him to “become academia or fail”. His great-grandfather was George Boole, who invented Boolean logic and algebra, the foundation of the modern computer. George’s wife Mary was a renowned teacher of algebra. and logic. Mary’s uncle was George Everest, and as Surveyor General of India, he had the world’s highest peak named after him. Geoffrey’s great-grandfather, a renowned mathematician, conceptualized the ‘fourth dimension’, and was the first to create the Tesseract, and his cousin, Joan, a nuclear physicist, was one of the few women to work on the Manhattan Project. His father, Howard Hinton, a formidable entomologist and a fellow of the Royal Society, would often tell him, “Work really hard and maybe when you’re twice as old as me, you’ll be half as good.” Geoffrey worked hard, becoming the godfather of deep learning, a Turing Award winner, and a fellow of the Royal Society. And he is not sitting on his laurels.
Jaspreet Bindra is the founder of Tech Whisperer Limited, a digital transformation and technology advisory practice.