Pursuing the Next Level of Artificial Intelligence

Stanford University researcher Daphne Koller‘s work in artificial intelligence, which has earned her the first-ever ACM-Infosys Foundation Award in Computing Sciences, taps an 18th-century probability theorem, and her methods have been used to enhance computer vision systems and in understanding natural language, while future applications are expected to drive the augmentation of Web search. She developed tools that helped facilitate a new type of cancer gene map based on analyzing the behavior of a large number of genes that are active in an assortment of tumors, which yielded a new explanation of how breast tumors spread into bone. Koller’s work has concentrated on the Bayes rule, which describes how to convert a current assumption about an event into an amended, more accurate assumption after observing additional evidence. The application of her theoretical work into the area of information extraction could potentially lead to software systems capable of reading Web pages, organizing the information, and comprehending unstructured text. Koller is currently working with biologists at the University of California, San Francisco, and her expertise is seen as valuable in gaining a deeper understanding of cellular processes because computation is playing an increasingly important role in biology. Her work has already had a profound commercial impact, and her peers say this will expand in the coming decade. “She’s on the bleeding edge of the leading edge,” says Willow Garage machine vision researcher Gary Bradski.
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