Andrej Karpathy’s name is strewn across the history of modern AI. In 2015, he was one of the founding members of OpenAI, working as a research scientist. In 2017, he was personally hired by Elon Musk to lead Tesla’s work on computer vision. He later returned to OpenAI in 2023 to work on improving GPT-4. His biggest impact on the world, however, may come not from his research but from his role as one of the world’s foremost educators on neural networks.
In 2015, Karpathy, alongside his colleague Professor Fei-Fei Li, designed Stanford University’s first course dedicated to deep-learning, for which he was the primary instructor. Videos of his lectures have been viewed over 800,000 times. Since then, he has become one of the internet’s most-beloved AI instructors. In recent years, Karpathy has explained intricate subjects like how to build smaller versions of GPT from scratch to a YouTube audience of millions.
“I’m a little bit obsessed with coming to the core of things, ” Karpathy says. He credits this to his physics education, which makes him adept at finding the simplest explanations to complex issues.
Karpathy draws inspiration from figures like Richard Feynman, renowned for his contributions to both research and public education. “People are obviously pre-money if they’re trying to learn a lot of stuff”, he says. “So I get paid in people thanking me.”
His latest venture, Eureka Labs, founded July 2024, aims to build a school that is “AI native.” Its first product will be an undergraduate-level course on AI, designed by a human and guided by an AI teaching assistant. When he first built his AI course at Stanford nine years ago, he was working part-time, and it was done over a few months. “It was a successful course,” he says, “But I think if I really focus on this, I can do a lot better.”
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