Jon McLoone from Wolfram Research presented their latest platform work on Wolfram|Alpha in KMi today: the new computational knowledge engine. By layering computational knowledge on large sets of curated, semantically marked up data, this new engine attempts to provide direct bespoke answers to users’ queries. There is even an iPhone App version.
In his talk, Jon gave insights into the working principles behind Wolfram|Alpha, specifically discussing with us issues related to semantic interpretation and disambiguation, collation, and presentation of information and the encoding of knowledge. Wolfram|Alpha’s long-term goal is to make all systematic knowledge immediately computable and accessible to everyone. They aim to collect and curate all objective data; implement every known model, method, and algorithm; and make it possible to compute whatever can be computed about anything!
Wolfram|Alpha aims to bring expert-level knowledge and capabilities to the broadest possible range of people-spanning all professions and education levels. And with a goal to accept completely free-form input, and to serve as a knowledge engine that generates powerful results and presents them with maximum clarity. This ambition clearly chimes with many of the scientific targets of KMi research and stimulated a wide discussion with the laboratory. Jon was then introduced to a number of wider OU research communities – this work has very wide impact.
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