Monday, June 9, 2014

AI: A Return To Meaning - David Ferrucci

The conclusion to Ferrucci's comment on the video: "This talk draws an arc from Theory-Driven AI to Data-Driven AI and positions Watson along that trajectory. It proposes that to advance AI to where we all know it must go, we need to discover how to efficiently combine human cognition, massive data and logical theory formation. We need to boot strap a fluent collaboration between human and machine that engages logic, language and learning to enable machines to learn how to learn and ultimately deliver on the promise of AI."

The most interesting stuff starts at 1:22:00 or so. Ferrucci talks about an interactive system where the computer uses human input to learn how to build-out an internal knowledge representation, where the internal model is based on classical principles. Watson-style "shallow" technology is an "ingredient" for creating the technology to support the interaction. Ten people could create a qualitative leap forward in three to five years.

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