How do we figure out where to look for answers amid the offerings from computation, search, wikis, social networks, semantic web, and so on? Datasets differ. Would be nice to handle user preferences, history, context, word-based problems, voice, and local state of knowledge. Caches allow them to provide up-to-the-minute FAQs. Timestamps are able show historical answers. Text-driven user input can be cut, piped to functions, and the answer returned or posted somewhere, e.g. an editor. Questions can be sent to all and merged or integrated, or the APIs can make them recombinant. The hardware scales from cells to chips. Cloud-based services seek to be more platform than killer app because various industries each have idiosyncracies, so there will likely be multiple solutions. Also started a basic wolframalpha experiment as way to observe learning curves for utility and user. There seem to be more variables than controls initially, so will need to characterize what is (un)settling and how.
Human-based textual image parsing this week included Farrell-Vinay 2008 on test management, McDonald 2008 on QA, Burns 2007 on security, Holzmann 2003 on SPIN model checker, Krepinevich 2009 on futurism, and Oreilly 2009 on the microblog.
“When you have eliminated the impossible, then whatever remains, however improbable, must be the truth.”