Google explains why it chose Princeton for its newest AI lab (slideshow)

By Alex Wolmart
Princeton | Dec 19, 2018 at 1:15 pm

Artificial intelligence is taking over Princeton.

A new Google AI lab in Princeton, run by two Princeton University computer science professors, will open in January. Princeton says the lab expects to expand the state’s innovation ecosystem by advancing research in artificial intelligence.

The lab will start with a small staff of faculty members, graduate and undergraduate student researchers, recent graduates and software engineers. The collaboration builds on the relationship between Google and professors Elad Hazan and Yoram Singer. They will split their time between Google and Princeton.

Machine learning, computers learning from existing information and developing the ability to draw conclusions and make decisions in new situations that were not in the original data, will be the focus within the lab. Speech recognition systems that transcribe a wide spectrum of voices and self-driving cars that process complex visual cues are a few examples. The work builds on advances made by Hazan, Singer and their colleagues to improve speed and accuracy of, while reducing the required power for, machine learning.

“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,” Singer said.

Hazan discussed Princeton’s longstanding strength in the mathematics and theory of machine learning. “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,” he said.

“A primary focus of the group is developing efficient methods for faster training of learning machines,” Hazan said. An algorithm developed by Hazan and Singer with their colleague, Stanford University professor John Duchi, called AdaGrad is a popular method to train deep neural networks, a powerful approach to machine learning.

“The study of efficient mathematical optimization has deep roots in Princeton,” said Hazan, “starting from the work of John von Neumann,” a former visiting Princeton faculty member.

“Computing started at Princeton more than 80 years ago, when alumnus Alan Turing first introduced a theory for how machines could calculate,” said Emily Carter, dean of the School of Engineering and Applied Science. “This collaboration 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.”

The chair of the Department of Computer Science, Jennifer Rexford, said the venture comes at a time of growth in the area of study at Princeton.

“The work with Google will complement all three pillars of excellence that make data science at Princeton strong today: a foundation in the theory and math behind computing; collaborations that are accelerating discovery across fields such as genomics, neuroscience, chemistry, psychology and sociology; and leadership, through our Center for Information Technology Policy, in the broader societal implications of computing such as bias and ethics in AI, privacy and security,” Rexford said.

The lab’s opening reflects Google’s collaboration with academic researchers, supporting the open-source community and publishing results in peer-reviewed conferences and journals, said Google program manager Andrew Pierson. Pierson said Google’s computing resources give researchers the ability to run experiments that would be difficult because they optimize algorithms that deal with millions of variables and perform trillions of calculations.

Google technical program manager Amy McDonald Sandjideh said talent is the main motivation for collaborating with Princeton.

“We specifically chose a location very close to the university to promote such collaborations,” McDonald Sandjideh said. “Particularly having access to graduate students and even undergrads can provide a lot of inspiration. Sometimes you learn the most from teaching and helping younger people understand what you’ve been working on and that can really push you in new directions. That is a great benefit for Google in working more closely with universities like Princeton that have really excellent minds.”