Uber’s artificial-intelligence lab is less than a year old, but researchers there have already built their own programming language for AI applications—and now they’re releasing it for anyone to use. Quite a generous move for a company known more for its hard-nosed business tactics than for handing out in-house innovations to potential competitors.
“It’s more important for us to engage with the whole community instead of keeping it ourselves,” says Zoubin Ghahramani, the chief scientist at Uber’s AI Labs.
Operating a ride-hailing empire means relying on a lot of software-mediated educated guesswork to sort out things like where demand for rides will be, what route is best, and even what pool passengers should be put into. Uber’s language, Pyro, is built to improve the way such parameters are analyzed.
Pyro is designed to perform a technique known as deep probabilistic modeling, a mixture of two artificial-intelligence methods: deep learning and Bayesian modeling. Combining the two makes Pyro a specialist at dealing with uncertainty in models—like where demand will be high in the future—while also absorbing prior knowledge, like where cars were needed on a given day in the past.
Ghahramani says his colleagues want to be full participants in the research community, taking part in conferences and presenting papers, and that Uber’s AI lab may release more open-source projects in the future.
Being active in the larger research community is, of course, also a great recruiting tool in the fiercely competitive market for AI talent. Top AI researchers want to publish papers and work on interesting projects. Even secretive Apple is publishing research papers to attract talent these days, so Uber’s big release is a matter of self-interest as much as it is a gift to the larger AI community.
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