Researchers at Stanford University are using 600,000 fictional stories to inform their new knowledge base called Augur. The team considers the approach to be an easier, more affordable, and more effective way to train computers to understand and anticipate human behavior. Augur is designed to power vector machines in making predictions about what an individual user might be about to do, or want to do next. The system's current success rate is 71 percent for unsupervised predictions of what a user will do next, and 96 percent for recall, or identification of human events. The researchers report dramatic stories can introduce comical errors into a machine-based prediction system. "While we tend to think about stories in terms of the dramatic and unusual events that shape their plots, stories are also filled with prosaic information about how we navigate and react to our everyday surroundings," they say. The researchers note artificial intelligence will need to put scenes and objects into an appropriate context. They say crowdsourcing or similar user-feedback systems will likely be needed to amend some of the more dramatic associations certain objects or situations might inspire.
Note to recruiters
Note to recruiters: We are quite aware that recruiters, interviewers, VCs and other professionals generally perform a Google Search before they interview someone, take a pitch from someone, et cetera. Please keep in mind that not everything put on the Internet must align directly to one's future career and/or one's future product portfolio. Sometimes, people do put things on the Internet just because. Just because. It may be out of their personal interests, which may have nothing to do with their professional interests. Or it may be for some other reason. Recruiters seem to have this wrong-headed notion that if somebody is not signalling their interests in a certain area online, then that means that they are not interested in that area at all. It is worth pointing out that economics pretty much underlies the areas of marketing, strategy, operations and finance. And this blog is about economics. With metta, let us. by all means, be reflective about this whole business of business. Also, see our post on "The Multi-faceted Identity Problem".
Saturday, July 2, 2016
INNOVATION: Computers read 1.8 billion words of fiction to learn how to anticipate human behaviour
Meanwhile at Stanford: