Microsoft Turing NLG
A 17-billion-parameter language model by MicrosoftDetails
Microsoft Turing Academic Program (MS-TAP)
Share Microsoft advances with Microsoft’s Turing family of natural language models in responsible mannerLearn More
Microsoft Turing Universal Language Representation Model
Microsoft T-ULRv2 tops XTREME leaderboardWatch
November 4–8, 2019, Orange County Convention Center | Orlando, FL
We were in Orlando to talk about AI-powered search for Enterprise!Watch
PyTorch Developer Conference
October 10, 2019, The Midway | San Francisco, CA
Watch our session at PyTorch 2019 Developer Conference in San Francisco!Watch
Microsoft Turing Academic API
Microsoft Generic Intent Encoder API is now available to academic researchers.Learn More
Generate Chatbot training data with QBox — powered by Microsoft Turing NLG
One of the primary challenges when building any kind of chatbot is producing or obtaining high-quality, diversified training data. The training data that you use across your model’s intents will determine how readily your model picks up on a real user’s true intent when exposed to queries it’s never seen before. So no matter what chatbot framework you’re using (e.g. Microsoft LUIS, IBM Watson, etc.), having high-quality training data is a must..
Microsoft trains world’s largest Transformer language model
Microsoft AI & Research today shared what it calls the largest Transformer-based language generation model ever and open-sourced a deep learning library named DeepSpeed to make distributed training of large models easier.
Assistive AI Makes Replying Easier – Microsoft Research
Microsoft’s mission is to empower every person and organization to achieve more. So, we are constantly looking for opportunities to simplify workflows and save people time and effort. Sending replies to email or chat messages is a common activity and people spend considerable amount of time on it.
Microsoft details how it improved Bing’s autosuggest recommendations with AI
Earlier in the year, Microsoft detailed the ways Bing has benefited from AI at Scale, an initiative to apply large-scale AI and supercomputing to language processing across Microsoft’s apps, services, and managed products. AI at Scale chiefly bolstered the search engine’s ability to directly answer questions and generate image captions, but in a blog post today, Microsoft says it has led to Bing improvements in things like autocomplete suggestions.
Better Document Previews using the Microsoft Turing Model for Natural Language Representations
Knowledge workers spend close to 20% of their time searching for and gathering information. When using document management systems such as Microsoft OneDrive and SharePoint people find themselves looking at directories full of documents. Interacting with such a list of documents can be time-consuming without a mechanism for previewing the documents.
Here's how Microsoft is looking to make search smarter and more natural
Microsoft is continuing to evolve its unified Microsoft Search service. The latest pieces it is integrating into Microsoft Search involve its 'Project Turing' deep-learning work, as well as advances it is making around semantic meaning and intent.