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Google drives automakers back to school

Automakers didn’t build the self-driving car: Google did. That’s a big problem for them. Hoping to catch up, Ford, Toyota, and Volkswagen are betting on academics. Along with Nvidia, Samsung, Qualcomm and Panasonic, they’re each giving $300,000 to the University of California at Berkeley to fund artificial intelligence research.

The alliance, called DeepDrive, is a rare moment of AI cooperation among car companies, which are racing one another to create the kind of brains that propel Google’s prototype gumdrop-shaped vehicles around Mountain View. It also highlights the new position universities find themselves in. Their AI lab work is in high demand — and corporations don’t want to wait months or years to get their hands on it.

The companies’ money will go to projects selected by UC-Berkeley. In return, the automakers get to give feedback on research proposals; meet the academics toiling away on the tech; and, thanks to the upfront payment, can commercialize any of the research without having to go through the headache of an additional licensing stage.

“They’ve essentially pre-negotiated access to software,” said Trevor Darrell, a professor at the university who leads DeepDrive. In corporate terms, $300,000 may not seem like a lot of money, but altogether the donations will back between 20 and 30 graduate students a year.

It’s a cheap way for the companies to get a bead on a dangerous, unpredictable future. “If vehicle manufacturers, five years from now, haven’t been to the drawing boards to figure out how to get self-driving tech into their cars, then those companies will be left out,” said Thilo Koslowski,top car analyst at the research firm Gartner. “It’s that dramatic.” For UC-Berkeley, it’s an opportunity to get funding without having to delay publication at the behest of a sponsor. That’s the normal protocol for corporate-backed research, where companies can ask to review results prior to general publication, delaying publication for months — or more.

Openness has become a big deal in artificial intelligence as the pace of research speeds up. No one wants to be caught reinventing the wheel (or the car). With DeepDrive, the university “can have open research with no publication restrictions, no lock down of early review for patenting, so the research can move as fast as it possibly can,” Darrell says.

It also gives the university a way to test its theoretical ideas in the real world, says Pieter Abbeel, a professor at UC- Berkeley and one of the principal investigators at DeepDrive. “We do all this research, but unless you do a startup where’s it going to go?” Abbeel said.

Through the project, UC-Berkeley researchers could get access to driving data from the companies and be able to run their software on the automakers’ vehicle simulators, letting them test out new approaches without risking crashing real cars, he said.

The types of problems DeepDrive’s researchers will tackle read like an index page from a science fiction novel: custom semiconductors for vision systems, software to predict how a pedestrian will behave; AI that can drive in unusual terrain; techniques that let machines learn from human drivers.

DeepDrive is emblematic of the new interest in university research projects around artificial intelligence and robotics, says Andrew Moore, the dean of Carnegie Mellon University’s school of computer science and a former Google employee. “We’ve hit this inversion where the stuff the universities are doing is applicable right now to industry,” he said.

Typically, university research needs to be adapted for specific industries or problem areas. That’s not the case with the current crop of AI technology, which is generating such excitement because it can be applied easily and quickly to new areas.

“It’s a real boom time,” Moore said. Google and Facebook regularly turn research papers into products in a matter of months, as opposed to years. In 2014, Uber partnered with Carnegie Mellon to develop self-driving car technology. By 2015 it had hired away academics from the lab.


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