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WASHINGTON, D.C.—Massively parallel supercomputing hardware and advanced artificial intelligence algorithms are being harnessed to deliver powerful new research tools in science and medicine, according to Dr. France A. Córdova, director of the National Science Foundation.
Córdova spoke Oct. 26 at the GPU Technology Conference organized by Nvidia, a company that got its start making video cards for PCs and gaming systems and now manufactures advanced graphics processors for high-performance servers and supercomputers.
Córdova, who is directing long-term research in AI at the NSF, said the research there is being used already in the Cancer Moonshot project currently spearheaded by Vice President Joe Biden, whose son Beau Biden died of brain cancer in 2015 at the age of 46. The Cancer Moonshot is a major effort to focus resources and funding on the fight to cure cancer on a scale similar to the original mission by NASA to land on the moon.
The future of AI is a major focus by the Obama administration, which recently released a multi-year report, “Preparing for the Future of Artificial Intelligence.” Dr. Córdova said similar efforts are moving forward in the study of quantum physics and a related field, quantum computing, which she said has the potential to revolutionize research by bringing to bear computing resources with unprecedented processing power.
The problem, she said, is that industry needs to do more than it has so far. “We’re under-investing in AI,” Córdova said. She added that all of the work in AI depends on the availability of big data to do its work. “AI feeds on data.”
The level of effort being put forth by the NSF on AI was explained later by Lynne Parker, NSF division director for information and intelligence systems. “NSF has been making significant research investments in AI systems that are more robust and flexible in complex, realistic environments. One existing NSF program focused on this research challenge is the Robust Intelligence program,” Parker said in an email to eWEEK.
“This program has specific goals of creating AI systems that are characterized by flexibility and resourcefulness, among other traits. Of course, it is very difficult to create truly robust AI systems, so much additional research is needed, as is called out in the National AI R&D Strategic Plan,” Parker wrote.
Córdova illustrated common uses of AI by referring to Apple’s Siri, who she briefly interviewed in preparing her presentation. She used Siri to demonstrate both how good AI has become, but also to demonstrate its limitations. When she asked Siri to dance, for example, the digital assistant demurred, saying it would “sit this one out.”