Dear Commons Community,
Uber is the latest company to invest significant research and development funds into artificial intelligence (A.I.). In making the announcement, representatives from Uber indicated they envision a future in which cars can make the most complex maneuvers without the help of a driver. To achieve that, cars will need to get a whole lot smarter. Gary Marcus and Zoubin Ghahramani, the two men appointed as co-directors of Uber’s lab, aim is to apply A.I. to self-driving vehicles, along with solving other technological challenges through machine learning. As reported by the New York Times:
“Marcus and Ghahramani are joining Uber through an acquisition of their start-up firm, Geometric Intelligence. Unlike most A.I. start-ups that generally follow one method of study of artificial intelligence, Geometric Intelligence takes a multidisciplinary approach to the field.
The acquisition and new research arm, which will be called Uber’s A.I. Labs, exemplifies how seriously Silicon Valley tech companies are betting on artificial intelligence. Google, Facebook and others have also pushed into artificial intelligence, 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 bring on new A.I. talent to compete against one another.
“Every major company realizes how essential A.I. is to what they’re doing,” Dr. 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.”
With the Geometric Intelligence deal, Uber, which is now valued at close to $70 billion, said it hoped that Dr. Marcus’s 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 of Silicon Valley’s biggest tech companies, such as Google and Facebook, have tried to commercialize artificial intelligence through the application of 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 Dr. Marcus’s team is that his start-up 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.
Dr. 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?
In recent years, researchers at institutions such as the Massachusetts Institute of Technology, New York University and the University of Toronto have also 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.”
This is another major step forward in A.I. that deserves attention especially if it is successful in developing applications built on rules extrapolated from a few observable examples. If they work, it brings A.I. much closer to natural machine-man interfaces.