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Learning web search intent representations from massive web search logs

Published July 21, 2019

Have you ever wondered what happens when you ask a search engine to search for something as seemingly simple as “how do you grill salmon”? Have you found yourself entering multiple searches before arriving at a webpage with a satisfying answer? Perhaps it was only after finally entering “how to cook salmon on a grill” that you found the webpage you wanted in the first place, leaving you wishing search engines simply had the intelligence to understand that when you entered your initial search, your intent was to cook the salmon on a grill.

Microsoft makes it easier to build popular language representation model BERT at large scale

Published July 17, 2019

The open sourcing of our recipe to pre-train BERT (Bidirectional Encoder Representations from Transformers) built by the Bing team, including code that works on Azure Machine Learning, so that customers can unlock the power of training custom versions of BERT-large models using their own data. This will enable developers and data scientists to build their own general-purpose language representation beyond BERT.