Moving Beyond Transformers: Microsoft Enhances Bing Search Results With MEB

Microsoft has recently introduced ‘Make Every feature Binary’ (MEB) to improve its search engine Bing. MEB is a large scale parse model that goes beyond pure semantics and reflects a more nuanced relationship between search queries and documents. To make the search more accurate and dynamic, MEB harnesses the power of large data and accepts an input feature space with over 200 billion binary features. DNN & Transformers for Bing The Bing search stack depends on natural language models to improve the core search algorithm’s understanding of user search intent and related web pages. Deep learning computer vision techniques are used to enhance the discoverability of billions of images even when text descriptions or summary metadata does not accompany the queries. Machine learn