{"id":144735,"date":"1998-03-27T00:12:37","date_gmt":"1998-03-27T08:12:37","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/group\/natural-language-computing\/"},"modified":"2025-03-13T02:40:31","modified_gmt":"2025-03-13T09:40:31","slug":"general-artificial-intelligence","status":"publish","type":"msr-group","link":"https:\/\/www.microsoft.com\/en-us\/research\/group\/general-artificial-intelligence\/","title":{"rendered":"General Artificial Intelligence"},"content":{"rendered":"
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General Artificial Intelligence<\/h1>\n\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t<\/div>\n\t<\/div>\n<\/section>\n\n\n\n\n\n

The General Artificial Intelligence (GenAI)<\/strong> Group (formerly Natural Language Computing) is focusing on research of Large Foundation Models and General AI, Natural Language Processing, Speech Processing, Multimodal AI, and AI Agent.<\/p>\n\n\n\n

In the past few years, we have published and open sourced pioneering and high-impact research works and models, including UniLM, InfoXLM, XLM-E, MiniLM(-2), (m)E5, Layout(X)LM(-3), WavLM, BEiT(-3), Kosmos(-2), VALL-E, DeepNet, LongNet, (Gated) RetNet, YOCO \/ Decoder-Decoder Architecture, 1-bit LLMs \/ BitNet (b1.58 | a4.8), Q-Sparse \/ Fully Sparsely-Activated LLMs, DIFF (Differential Transformer), LatentLM \/ Multimodal Latent Language Modeling, among others.<\/p>\n\n\n\n

Research Areas<\/b>
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