Facebook's AI director explained how he convinces the smartest minds to work for him instead of Google DeepMind
Business Insider/Sam Shead
Part of this effort involves finding and hiring the brightest minds in the world. But with so many large companies involved in the so-called "AI race" it's not always easy to recruit the best talent.
Yann LeCun, the director of Facebook AI Research and one of the world's most prominent AI academics, told Business Insider last week that he employs certain tactics to get people to come and work for him.
"There's various things ... but a lot of it is nurturing relationships with academic laboratories that have a track record of producing interesting students," said LeCun, who is also a professor at New York University.
He went on to say that allowing scientists to publish their work - something that Apple does not do - is also key. "It's very important for a scientist because the currency of the career as a scientist is the intellectual impact," he said. "So you can't tell people 'come work for us but you can't tell people what you're doing' because you basically ruin their career. That's a big element, which I think we pioneered within this context."
LeCun could not be drawn on how much Facebook is willing to pay the top AI people who hold expertise in fields like machine learning, computer vision, mobile robotics, and computational neuroscience. However, online forums suggest the tech giants are willing to pay the best candidates salaries that run into the hundreds of thousands of dollars.
"[Salary] is important," said LeCun. "Particularly when there is a competitive situation with Microsoft, DeepMind, Google etc. But the other fundamentals have to be right. If they're not right, people are just not even considering coming to work for you."
LeCun added that the FAIR group, who refer to themselves internally as the "FAIRies", is now about 75 people strong, with offices in New York, Palo Alto, Seattle, and Paris.
"The role of FAIR is to advance the science and the technology of AI and do experiments that demonstrate that technology for new applications like computer vision, dialogue systems, virtual assistants, speech recognition, natural language understanding, translation, things like that," he said.
"There's a lot of basic science behind it which is not particularly geared towards an application; it's more about making progress and understanding intelligence and AI.
"Then we work very closely with another group, which is about twice our size, called applied machine learning. They turn the science into visible technology and build platforms for the company that product groups can use to deploy AI-based services in the company."
LeCun's comments were made as part of a longer interview which will be published on Business Insider at a future date.
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