A Cognitive Computing Approach to Automatically Capturing, Storing and Sharing Distributed Knowledge Across the Enterprise

Knowledge Management promised “the right information to the right person and the right time”, but the technology to deliver has been lacking. “Best Practices” are still entombed in document repositories, the attempts of experts to express their knowledge in the hope that others will be able to find and then have time to read them. In contrast, cognitive memories provide instant and autonomous machine learning, more similar to human learning rather than traditional machine learning. Based on reasoning by similarity to experience and the social sharing of experience, proofs of improved accuracy, saved time, reduced care and feeding, and significant ROI business cases will be referenced. These referenced business cases range from national security, healthcare and high tech chip manufacturing. Moreover, a cognitive solution to issue and defect resolution will demonstrate the lookup of similar cases, relevant experts, learned predictions, and proscriptive recommendations, learning from one situation to the next, from one user to another, to bring the knowledge of many to one.

In this session we will discuss:

Cognitive Computing requires autonomous learning to be “smart”
Human learning is memory-based, reasoning from case experience
Memory-based learning instantly captures the tacit behavior of workers
Experience-based reasoning recalls cases, persons, actions, and outcomes
Business benefits gained by applying this cognitive computing technology are demonstrated by differentiated accuracy, time, cost, ROI

Dr. Manuel Aparicio is the visionary behind Saffron’s associative memory technology. With more than 25 years experience in the industrial development and commercialization of software solutions supporting real intelligence for intelligent agents, Aparicio has long been an evangelist for broad adoption of associative-memory technology. Prior to Saffron, Aparicio was Chief Scientist of the IBM Knowledge Management & Intelligent Agent Center, also serving on the board of The Agent Society and the Foundation for Intelligent Physical Agents. Aparicio holds several patents for memory-based technology, and has published numerous papers and journal articles. For example, he wrote “Concepts of Personalization” for The Practical Handbook of Internet Computing, and “Learning by Collaborative and Individual-based Recommendation Agents” in the Journal of Consumer Psychology. He co-edited Neural Networks for Knowledge Representation and Inference Aparicio earned a Ph.D. in Experimental Psychology