Get the latest tech news
A stubborn computer scientist accidentally launched the deep learning boom
“You’ve taken this idea way too far,” a mentor told Prof. Fei-Fei Li.
I didn’t know it at the time, but a team at Princeton—in the same computer science building where I was attending lectures—was working on a project that would upend the conventional wisdom and demonstrate the power of neural networks. In a landmark 1986 paper, Hinton teamed up with two of his former colleagues at UCSD, David Rumelhart and Ronald Williams, to describe a technique called backpropagation for efficiently training deep neural networks. “This meant that we wouldn’t be presenting our work in a lecture hall to an audience at a predetermined time but would instead be given space on the conference floor to prop up a large-format print summarizing the project in hopes that passersby might stop and ask questions… After so many years of effort, this just felt anticlimactic.”
Or read this on r/technology