O’Reilly Launches Powerful New Tool for Learning in the Flow of Work: O’Reilly Answers
NLP-driven contextual search engine now accessible through O’Reilly online learning; fully integrated with Slack
BOSTON–(BUSINESS WIRE)–#NLP—O’Reilly, the premier source for insight-driven learning on technology and business, today announced the launch of O’Reilly Answers, an advanced natural language processing (NLP) engine that delivers quick, contextually relevant answers to challenging technical questions posed by users through O’Reilly online learning. With a one-click integration into Slack, O’Reilly Answers helps users learn from and discover the content that moves business forward.
Leveraging advanced machine learning techniques, the O’Reilly Answers search engine provides relevant highlights and snippets from O’Reilly’s library of expert content across thousands of O’Reilly’s titles, pointing users directly to only the most applicable resources and eliminating noise. To encourage deeper discovery, the feature allows users to drill down into full content pieces from referenced titles. To further improve productivity, all functions of O’Reilly Answers are available through a simple Slack Integration.
“Over half of all O’Reilly usage is non-linear learning – finding fast solutions that can quickly be applied to work. Taking time to dig up resources can mean the difference between moving to the next step or stalling on a project,” said Laura Baldwin, President, O’Reilly Media. “As we fall into step with the new pace of organizational change, O’Reilly Answers helps bridge the gap between learning and knowledge, eliminating the need for lengthy training sessions and helping users get back to work with the tools they need to get the job done.”
According to Dynamic Signal’s State of Employee Communication and Engagement study, 85% of employees lose at least one to two hours of productivity a week searching for information. For O’Reilly users, O’Reilly Answers creates a critical way to answer technical questions quickly and efficiently in order to solve a problem. The feature also creates opportunities for deeper exploration into the most challenging technologies, including AI, quantum computing, robotics, virtual reality and more.
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