But Austin Huang, Associate Director and the Biomedical Data Science lead in Pfizer's Genome Sciences and Technologies group in Kendall Square, Cambridge, Massachusetts, explains that "the methods that companies like Google and Facebook use to study large, complex datasets can also be used to help predict disease and possible treatment outcomes in human health data." If the ultimate goal of a self-driving car is to navigate a busy city street, in pharmaceutical research, the goal is to navigate the connections between a potential treatment and its effectiveness in treating a disease. Austin Huang, Associate Director and the Biomedical Data Science lead in Pfizer's Genome Sciences and Technologies group And if other fields of AI are any indication, he says, "when breakthroughs happen, change can follow very quickly," likening it to a "tipping point." To enable AI to reach those kinds of breakthroughs, it's important to teach computers how to "think" abstractly in discovering patterns in large datasets.
"Toronto and Canada for the past two decades has been at the forefront of AI, and that's the expertise we're bringing to Uber,"says Raquel Urtasun, who will lead Uber's Advanced Technologies Group in Toronto. Uber is launching a research group devoted to driverless car technology in Toronto, creating a third hub -- its first outside the U.S. -- for the company's ambitions in a frenzied field that Uber and its competitors believe will upend transportation, generating billions of dollars in the process. The Advanced Technologies Group will be led by Raquel Urtasun, a University of Toronto computer science professor who holds a Canada Research Chair in machine learning and computer vision. Urtasun uses artificial intelligence, particularly deep learning, to make vehicles and other machines perceive the world around them more accurately and efficiently.