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GigaPath: Whole-Slide Foundation Model for Digital Pathology
Digital pathology helps decode tumor microenvironments for precision immunotherapy. In joint work with Providence and UW, we’re sharing Prov-GigaPath, the first whole-slide pathology foundation model, for advancing clinical research.
Moshe Tennenholtz is an accomplished man. An Israel-based principal researcher with Microsoft Research New England, he has performed pioneering work bridging computer science, artificial intelligence, and game theory. He also has co-founded several e-commerce companies. Given such a varied, successful background, there’s little these days that can faze him.
Yet when he learned he had been named winner of the 2012 Allen Newell Award from the Association for Computing Machinery (ACM) and the Association for the Advancement of Artificial Intelligence, he couldn’t have been more surprised.
“It was announced to me by phone by the chair of the committee [Eric Grimson, chancellor of the Massachusetts Institute of Technology],” Tennenholtz says. “I didn’t even know what he wanted to talk to me about.”
Others might have not been so shocked. Tennenholtz has pioneered several approaches to the design and analysis of interactions between decision-makers in computational settings. He created RMax, a general, efficient algorithm applicable to learning by interacting with an environment, and he introduced the concept of program equilibrium, an ingenious application of computer science to the analysis of Internet economies.
Such contributions were instrumental in Tennenholtz’s selection as the Newell Award winner, a prestigious honor, announced April 9, that goes to individuals for career contributions with broad appeal within computer science or that connect computer science and other disciplines. He accepted the award in San Francisco on June 15 during the ACM Awards Banquet, sharing the honor with frequent collaborator Yoav Shoham, a computer-science professor at Stanford University and former director of that school’s Artificial Intelligence Lab.
Tennenholtz and Shoham were recognized, the awards’ accompanying citation reads, for their “fundamental contributions at the intersection of computer science, game theory, and economics, most particularly in multiagent systems and social coordination (broadly construed), which have yielded major contributions to all three disciplines.”
Tennenholtz says he’s delighted with the honor—for a couple of reasons.
“The Allen Newell Award is the recognition I’m most proud of,” he says. “I was extremely happy and deeply excited to hear about it. I really feel very honored.”
Not only is Tennenholtz thrilled with the award, he also finds it appropriate that he is being recognized in conjunction with one of his longtime collaborators. Shoham has performed pioneering work of his own, in agent-oriented programming that provided a methodology for specifying distributed multiagent systems. His work in combinatorial auctions and mechanism design has been no less foundational.
“Getting the award together with Yoav makes things even more exciting to me,” Tennenholtz says. “The work with Yoav was influential to my academic career—and I hope also influenced his.
“Before collaborating with Yoav, I was a Ph.D. student pursuing an incredibly ambitious vision of ‘artificial social systems,’ and together with Yoav, we were able to continue that agenda and influence the community. We were working on topics in the interplay between computer science and game theory/economics much before most computer scientists and game theorists/economists started to notice the bridge, and we pursued together related topics in academia and in industry.”
Tennenholtz and Shoham, each of whom individually has won the Autonomous Agents Research Award from the ACM’s Special Interest Group on Artificial Intelligence, provided foundational contributions to the areas of social coordination, preceding the recent growth of activity in social networks. They established a framework for addressing coordination of multiple agents in distributed settings and established a basis for examining a wide range of important questions and for developing influential applications in electronic commerce, combinatorial auctions, social computing, equilibrium computation, mechanism design, and multiagent systems.
Allen Newell, who died in 1992, was one of the founders of the field of artificial intelligence. He established foundational concepts about the field and designed groundbreaking systems, all focused on a single, fundamental issue: the nature of the human mind.
Tennenholtz is well aware of Newell’s career—and what it means to receive an award named after him.
“Unfortunately, I did not meet Allen Newell in person,” he says, “but as a student and young researcher, I was highly impressed by his work. It was a model of deep scientific work that enables us to bridge several disciplines and was a real inspiration.
“More technically, my work on mental-level modeling and axiomatic approaches to Internet algorithms has the flavor of his work on the ’knowledge level’ treatment of computer programs, although they come from different angles.”