eventually coding with IBM's Watson and related AI. See this related conversation, for example -
"Poster Title: Not Elementary, My Dear Watson - Extending Watson for Question Answering on Linked Open Government Data
RPI doctoral student Amar Viswanathan Kannan, working with Prof. James Hendler, presented this poster at yesterday's Cognitive Colloquium at Yorktown:
Linked Data, stored as RDF graphs lets users to traverse through heterogeneous knowledge bases with relative ease. In addition it also allows for data to be viewed from different perspectives and is also able to provide multiple conceptualizations of data. This becomes very important owing to the heterogeneous nature of the web. While traditional linked data technologies like the Simple Protocol and RDF Query Language(SPARQL) allow us to access the Linked Data knowledge bases, it requires considerable skill to design queries to access Linked Data triple stores. It is also a shift from looking at data as traditional RDBMS databases to knowledge graphs. The growing acceptance of Linked Data triple stores as general purpose knowledge bases for a variety of domains has necessitated the need for accessing such knowledge with greater ease. Enter Watson, IBMs flagship Question Answering System. It has been at the forefront of Question Answering systems for being able to answer factoid questions on the “Jeopardy!” quiz game show with pinpoint precision. The architecture of the DeepQA system, of which Watson is an application has captured the imaginations of the Artificial Intelligence Community, which has long strived to build Cognitive Systems. The DeepQA system excels at generating hypotheses and gathering evidence to refute or support these hypotheses. It also evaluates all the evidence and provides analytics."