As IBMers describe it, such a system could, for example, monitor a county's historical and real-time traffic information while tapping data sources on where accidents occur most, where the most speeding tickets are given, and where the public transportation routes are. The system could then be queried by a city planner: Where should we add more traffic lights? Where should we raise or lower speed limits? Where should we add a carpool lane? What should we do to make traffic safer and more efficient? Watson's analytical data-mining capabilities would pore over troves of data, looking for connections and patterns to come up clear suggestions.
Similarly, IBM sees this sort of technology having use in the world of health care. Given access to a wealth of data about cancer -- symptoms, treatments, geographic factors (that is, characteristics of regions where cancer is prevalent), biological factors, and so forth -- the system could find previously unrecognized correlations that could lead to potential causes and cures.
Watson also has impressive applications in the business world. In its current iteration, the system needs to be fed its "Jeopardy" questions in text form; voice recognition isn't its strong suit. But imagine an automated email or IM-based customer service system where a customer could ask any number of questions in natural language and theoretically get quick and accurate answers from a machine drawing from an array of data sources in real time instead of a overworked customer-service rep tapping away at a keyboard.
And who knows? Once voice recognition technology achieves perfection, Watson might be able to sit in on board meetings in place of a human VP of marketing, providing insights and recommendations extracted from unrecognized patterns among large swatch of data instead of being extracted, from, well, somewhere less reliable.
Follow Ted Samson on Twitter at tsamson_iw.
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