Machine Learning and the End of Search

Video produced by Steve Nathans-Kelly

Does the wider adoption of machine learning mean the end of search as we know it? Northern Light CEO David Seuss explained why he believes it does and how search must leverage smart taxonomies going forward during his presentation at Data Summit Connect 2021.

"We are approaching the era when users will no longer search for information in the traditional way. They will expect the machine to find what they need on its own and bring it to them. To do this, search must evolve to have an in-depth understanding of the search material and the ways of knowing in the user's domain so you can't just throw a generic search solution at a generic content set and have this work," Seuss said. 

"The content has got to be about the topic. It's got to be the right content that will have the insights that you're looking for and the search technology  from especially the taxonomy viewpoint  needs to really be based on an in-depth understanding of the material and the ways of knowing," Seuss explained. To accomplish this, you have to take advantage of smart taxonomies that deeply tag the content with context-specific and meaning-loaded entities, use smart summarization of the important ideas in a document across documents and across sources, and use smart distribution of insights—powered by learning what each user cares about, andthen find the relevant material without being asked.

Instead of searching material, it would be more accurate to say the material finds you, said Seuss. "The impact of these analytics and machine learning trends on the socialization and utilization of competitive intelligence in your company will be profound and they will change everything you're doing in your competitive intelligence knowledge management system."