Ai-One Touts Intelligent Agent Advantage
February 6, 2013
Is it another breakthrough in the analysis of unstructured text? Ai-one provides a detailed account of its data-analysis platform ai-BrainDocs in, “Big Data Solutions: Intelligent Agents Find Meaning of Text.” The write-up begins with an summary of the familiar problems many organizations face when trying to make the most of the vast amounts of data they have collected, particularly limitations of the keyword approach. Ai-one describes how they have moved beyond those limitations:
“Our approach generates an ‘ai-Fingerprint’ that is a representational model of a document using keywords and association words. The ‘ai-Fingerprint‘ is similar to a graph G[V,E] where G is the knowledge representation, V (vertices) are keywords, and E (edges) are associations. This can also be thought of as a topic model. . . .
“The magic is that ai-one’s API automatically detects keywords and associations – so it learns faster, with fewer documents and provides a more precise solution than mainstream machine learning methods using latent semantic analysis. Moreover, using ai-one’s approach makes it relatively easy for almost any developer to build intelligent agents.”
The write-up tells us how to build such “intelligent agents,” delving into the perspectives of both humans and conventional machine learning (including natural language processing and latent analysis techniques). It concludes by describing the creation of their ai-BrainDocs prototype. The article is rich in detail—a worthwhile read for anyone interested in such mechanics.
Founded in Zurich in 2003, ai-one is now headquartered in La Jolla, California, with research in Zurich and European operations in Berlin. The company licenses their software to developers around the world, who embed it in their own products.
Cynthia Murrell, February 06, 2013
Sponsored by ArnoldIT.com, developer of Augmentext
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