Though Stanford University professor Fei-Fei Li began her career during the most recent artificial intelligence (AI) winter, she's responsible for one of the insights that helped precipitate its thaw. By creating Image-Net, a hierarchically organized image database with more than 15 million images, she demonstrated the importance of rich datasets in developing algorithms—and launched the competition that eventually brought widespread attention to Geoffrey Hinton, Ilya Sutskever, and Alex Krizhevsky's work on deep convolutional neural networks. Today Li, who was recently named an ACM Fellow, directs the Stanford Artificial Intelligence Lab and the Stanford Vision and Learning Lab, where she works to build smart algorithms that enable computers and robots to see and think. Here, she talks about computer vision, neuroscience, and bringing more diversity to the field.
Your bachelor's degree is in physics and your Ph.D. is in electrical engineering. What drew you to computer vision and artificial intelligence (AI)?
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