IBM Watson Upgrades Enterprise Natural Language Processing
IBM has created new natural language processing (NLP) features for the Watson Discovery enterprise AI service. The company designed the upgrades to enable Watson to better parse and analyze complex language from documents and transcripts.
IBM Watson Discovery focuses on aiding insurance, legal, and financial businesses to comb through data for valuable insights, hence the name. Watson is supposed to speed up research and decision-making when the available data would bog down human-only efforts, especially on a deadline. IBM described the Discovery updates as a way for clients to customize the NLP models to fit the kind of language used in their work, including the more technical or industry-specific terminology. The clients can train Watson on the relevant documents without needing to code a program. The upgraded service incorporates a better grasp of visual layouts and a beta version of IBM Research’s new advanced pattern creation feature. The pattern creator enables Watson to spot relevant business text and the context where it comes up within a library’s worth of documents, as seen in the screenshot on the side.
“The stream of innovation coming to IBM Watson from IBM Research is why global businesses in the fields of financial services, insurance and legal services turn to IBM to help detect emerging business trends, gain operational efficiency and empower their workers to uncover new insights,” IBM general manager of data and AI Daniel Hernandez explained. “The pipeline of natural language processing innovations we’re adding to Watson Discovery can continue to provide businesses with the capabilities to more easily extract the signal from the noise and better serve their customers and employees.”
IBM has been rolling out enterprise upgrades for Watson at an accelerated clip of later. In September, Watson simplified how it could be added to call center systems as an add-on for enterprise communications platform IntelePeer. The arrangement coincided with new and improved virtual agent skills useful in call centers, including an “agent app” to smooth the hand-off from the AI to human employees and a short-answer retrieval that summarizes information pulled from its databases.