Get Answers in Context with Semantic Search in Microsoft 365

This course is a part of DEVintersection 2019, a 20-course Paths series from Pluralsight.

For human beings, reading comprehension is a basic task, performed daily. As early as in elementary school, we can read an article, and answer questions about its key ideas and details. But for AI, full reading comprehension is still an elusive goal but a necessary one if we’re going to measure and achieve general intelligence AI. In search applications, machine comprehension will give a precise answer rather than a URL that contains the answer somewhere within a lengthy web page. Moreover, machine comprehension models can understand specific knowledge embedded in articles that usually cover narrow and specific domains, where the search data that algorithms depend upon is sparse. In this session, see and learn from Bill Baer about the latest innovation with natural language and machine reading comprehension in Microsoft search.