Princeton may not have landed Amazon, but it did get Google, at least a small — very small — part of it.

Princeton University has announced that Google will open an artificial intelligence lab and collaborate with university researchers in a workspace to open in January at 1 Palmer Square. The lab will be led by Princeton computer science professors Elad Hazan and Yoram Singer.

According to a university press release, the lab “will start with a small number of faculty members, graduate and undergraduate student researchers, recent graduates, and software engineers. The lab builds on several years of close collaboration between Google and professors Hazan and Singer, who will split their time working for Google and Princeton.”

The lab’s focus, according to the statement, will be on “a discipline within artificial intelligence known as machine learning, in which computers learn from existing information and develop the ability to draw conclusions and make decisions in new situations that were not in the original data. Examples include speech recognition systems that transcribe a wide spectrum of voices, and self-driving cars that process complex visual cues. In particular, the work will build on recent advances by Hazan, Singer, and colleagues in optimization methods for machine learning to improve their speed and accuracy while reducing the required computing power.”

Singer said, “we feel it’s a great opportunity, both for machine learning theorists at Princeton to benefit from exposure to real-world computing problems, and for Google to benefit from long-term, unconstrained academic research that Google may incorporate into future products.”

Princeton has longstanding strength in the mathematics and theory behind machine learning, optimization, and computing in general, Hazan said. “As academics we try to think about theory for solving problems that are, many times, in the abstract, and it’s very helpful for us to be in touch with real-world problems.”

The Princeton-Google collaboration, said Emily Carter, dean of the Princeton’s engineering school, “is another excellent example of how fundamental insights in mathematics and theoretical computer science drive new technologies with benefits far beyond the original domain of the work.”

Facebook Comments