I see two important parts to this dialog now: 1) machine support for sifting through mountains of data, and 2) the increasing jeopardy of large corporations controlling data. For part 1, the dialog confirms what some of us already know: "Watson" is a branding exercise, and there is no overall coherent plan for strategic AI. But general open source components for literature-based discovery are being built. Part 2 is scarier, and as noted by two speakers from NSF last Friday (Peter Arzberger, Chaitan Baru), "data IS infrastructure," and so the increasing difficulty for public data sources to compete with Google, Yahoo, Facebook, Baidu, etc. is perhaps the more serious challenge for AI support of humans in the future. University research faculty can't tackle problems that require the de novo or nearly de novo creation of such data infrastructure, so we await public policy of funding agencies to clarify the construction and access to such. (Americans in this forum please note that you need to stop writing and thinking as if there is no other part of the planet ... I would be most grateful if Google brokered access to only American data ;-)