ITEM: Ride-sharing service Uber Technologies has taken two major steps in the artificial intelligence space by creating an AI research lab and buying an AI research startup to work in it.
In a blog post, Uber’s chief product officer Jeff Holden announced the creation of Uber AI Labs, a new division of Uber that will be dedicated to cutting-edge research in artificial intelligence and machine learning. Holden also announced that the company purchased AI research startup Geometric Intelligence, whose 15 members will form the initial core of the AI Labs team.
Holden said Uber’s interest in AI has to do with “negotiating the real world” in various ways, from determining an optimal route to computing when an Uber car or UberEATS order will arrive to matching riders for uberPOOL.
However, Uber is also very interested in self-driving cars (to include flying ones), and sees AI as a key component of enabling the driverless vehicles that will serve Uber’s various services. By perhaps no coincidence, the self-driving car sector is where Uber is going to see heavy competition as car manufacturers announce plans to add ride-sharing services to their autonomous-car service portfolios.
From the blog post:
In spite of notable wins with machine learning in recent years, we are still very much in the early innings of machine intelligence. The formation of Uber AI Labs, to be directed by Geometric’s Founding CEO Gary Marcus, represents Uber’s commitment to advancing the state of the art, driven by our vision that moving people and things in the physical world can be radically faster, safer and accessible to all.
Marcus is a pretty big name in the AI research field, and his team will focus on challenges that existing systems can’t solve, reports Technology Review:
“We’re especially interested in the edge cases—in what happens if the lighting is different, or it’s a vehicle you haven’t seen before,” he says. “We’re going to be working a lot on those problems.”
Marcus hasn’t revealed many details about what Geometric Intelligence has been developing, and the company hasn’t published any of its work. But among other things, his team has been working on a form of deep learning that requires less data (see “Algorithms That Learn with Less Data Could Expand AI’s Power”). He says such approaches could prove useful to both Uber’s current business and its long-term research objectives. “There are always going to be cases where you don’t have enough data. You might have enough information to predict what happens at nine in the morning, but what happens at 2 a.m. and there’s less data?” Marcus says. “And [in automated driving] there’s not so much data when you get into the edge cases.”
While Uber is sure to benefit from having direct access to leading-edge AI research, it won’t be alone, Karl Iagnemma, founder and CEO of nuTonomy, which is testing self-driving taxis in Singapore and the US, told Technology Review:
“It’s very much an arms race,” he adds. “If your competitors are doing it, even if you’re unsure of the likelihood that fundamental research will lead to significant impact on your product, you can’t afford not to compete.”
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