IBM Research & MIT Roundtable: Solving AI's Big Challenges Requires a Hybrid Approach

At IBM Research's recent "The Path to More Flexible AI" virtual roundtable, a panel of MIT and IBM experts discussed some of the biggest obstacles they face in developing artificial intelligence that can perform optimally in real-world situations. The solution, they agreed during the July 8 panel, is to embrace an integrated AI paradigm that amplifies the strengths and compensates for the weaknesses found in different approaches, including symbolic programming and deep learning. AI and automation are largely synonymous when you talk about industrial uses, said panelist David Cox, IBM Director of the MIT-IBM Watson AI Lab. "A lot of what people mean when they talk about AI today is automation," he added. "But automation is incredibly labor-intensive today, in a way that really just doesn't work for the problems we want to solve."