Harness cognitive computing and AI with Verint and Northern Light
A new era of cognitive computing is unfolding. Its impact is already being felt across a multitude of industries, from manufacturing to health care and beyond. It is integral to the rise of sophisticated chatbots ready to assist us across the connected world.
The goal of cognitive computing seems straightforward—to simulate human thought processes in complex situations via AI-enabled computerized models.
However, building, refining, and reaping business value from cognitive computing systems and applications requires thoughtful planning about how to harness the technology.
KMWorld held a webinar featuring John Chmaj, senior director, product strategy knowledge management, Verint and David Seuss, CEO, Northern Light who discussed how cognitive search differs from other approaches to deliver intuitive, flexible, yet highly accurate results.
Knowledge drives support and service, Chmaj said. Our expectations of receiving relevant, personalized and tailored information are ubiquitous—for most every electronic interaction. Almost every electronic device has some knowledge delivery (and often AI) component. Our online interactions are becoming consistently personalized. Knowledge is being embedded into transactions, social interactions, tools, even our vehicles, he said.
Search needs to match how users think. We think conceptually, we reason associatively, and we draw our concepts and probabilities together into answers, according to Chmaj.
A cognitive indexing approach gives users deep, real-time statistical correlation of the probable relations between terms (docs and queries); layers in domain-specific focusing mechanisms (term relationships in Banking, Insurance, etc.); and adds organization-specific terms to round out the context.
Cognitive search offers real-time rich indexing of content sources, enables “zero-click” predictive next-best answers, supports authoring automation – dynamic link generation, enhances reporting—good search relevance drives better analysis, and can be leveraged in many other tools via API.
According to Seuss, “Currently, 80% of U.S. CEOs believe that AI will change the way they do business in the next five years,” said Scott Likens, PwC, “The Future of AI in America: What All Leaders Should Consider.”
Successful cognitive search implementations involve more than one AI discipline and not infrequently a half-dozen, Seuss said.
Smart taxonomies can be the basis for finding and communicating insights from vast amounts of content. Smart taxonomies are industry and use case specific, and look for concepts—not just terms.
Use machine learning to semantically analyze the text in the tweets in candidate hashtags to the text in the training model to find those whose content is similar, i.e., part of the same social media conversation. The difference machine learning makes is dramatic, Seuss said.
An archived on-demand replay of this webinar is available here.
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