Uber bets on artificial intelligence with acquisition and new lab

(FILES) This file photo taken on September 13, 2016 shows a pilot model of the Uber self-driving car is displayed at the Uber Advanced Technologies Center in Pittsburgh, Pennsylvania. Uber announced December 5, 2016 it was buying the artificial intelligence group Geometric Intelligence, to form the core of the ride-sharing giant's own research center. The move signals a stepped-up effort in artificial intelligence, helping research efforts to bring self-driving car technology into the mainstream. / AFP PHOTO / Angelo MerendinoANGELO MERENDINO/AFP/Getty Images less (FILES) This file photo taken on September 13, 2016 shows a pilot model of the Uber self-driving car is displayed at the Uber Advanced Technologies Center in Pittsburgh, Pennsylvania. Uber announced December 5, ... more Photo: ANGELO MERENDINO, AFP/Getty Images Photo: ANGELO MERENDINO, AFP/Getty Images Image 1 of / 1 Caption Close Uber bets on artificial intelligence with acquisition and new lab 1 / 1 Back to Gallery

Uber envisions a future in which a fleet of vehicles can make the most complex maneuvers while carting passengers around without the help of a driver. To achieve that, cars will need to get a whole lot smarter.

Enter Gary Marcus and Zoubin Ghahramani. The two men are being appointed as co-directors of Uber’s new in-house research arm on artificial intelligence, which the San Francisco ride-hailing company unveiled Monday. The research arm’s aim is to apply AI in areas like self-driving vehicles, along with solving other technological challenges through machine learning.

The two are joining Uber through an acquisition of their startup, Geometric Intelligence. Unlike most AI startups that generally follow one method of study of artificial intelligence, Geometric Intelligence takes a multidisciplinary approach.

All 15 people from the startup will be absorbed by Uber. Terms of the deal were not disclosed.

The acquisition and new research arm, which will be called Uber’s AI Labs, exemplifies how seriously Bay Area tech companies are betting on artificial intelligence. Google, Facebook and others have also pushed into AI, which underlies voice recognition software, digital assistants like Amazon’s Alexa and Apple’s Siri, and technologies like self-driving cars. Many companies are racing to hire AI talent to compete.

“Every major company realizes how essential AI is to what they’re doing,” Marcus said in an interview. “Because of the scale of data people are operating on, even the smallest gains in efficiency can turn out enormous changes at these companies, especially in terms of profit.”

Uber, now valued at close to $70 billion, said it hopes the Geometric Intelligence team could harness the wealth of data it collects from the millions of daily Uber rides. The company wants to use the data to make major advances in how computers behind self-driving vehicles think and make decisions on the road.

Many big tech companies have tried to commercialize artificial intelligence through algorithms modeled largely on how the human brain functions. This method, called deep learning, leans heavily on the vast data sets that private technology companies own and that are used to train computers to do simple tasks, such as match patterns or recognize faces in photographs.

Part of what drew Uber to Marcus’ team is that his startup is tackling artificial intelligence in a different way. Rather than taking just one approach like deep learning, Geometric Intelligence combines data scientists who use varying techniques to study artificial intelligence, including the Bayesian and “evolutionary” methods.

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Marcus, who helped found Geometric Intelligence in late 2014, said the gist of his philosophy goes something like this: Instead of training machines by feeding them enormous amounts of data, what if computers were capable of learning more like humans by extrapolating a system of rules from just a few or even a single example?

Researchers at such institutions as the Massachusetts Institute of Technology, New York University and the University of Toronto have worked on similar theories. Using this approach, some reported a breakthrough in “one-shot” machine learning last December, in which artificial intelligence advances surpassed human capabilities for a narrow set of vision-related tasks.

Besides vehicles, Uber said it expected its AI Labs to apply its method to other tasks, such as combatting fraud, extracting information from street signs and learning to improve its mapping research and capabilities.

“When step function changes in this field occur, we’re going to see very significant differences in how businesses run themselves,” said Jeff Holden, Uber’s chief product officer. He said the AI Labs and Uber’s Advanced Technologies Center, home to the company’s self-driving car research, will work in tandem.

“It’s going to be a very long time before a self-driving car will be able to make all the kinds of trips that Uber does every single day,” Holden said. “But the answers to this are all going to come in the form of artificial intelligence.”

Holden said recruiting AI research talent is highly competitive, especially as Google, Apple and Tesla are also developing self-driving cars or related projects.

“From a defensive perspective, if someone else develops them first, we’re in trouble,” he said.