Roundtable discussion: Efficient and adaptable large-scale AI

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Published on ● Video Link: https://www.youtube.com/watch?v=tXGWTHl4Cn4



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Speakers:
Ahmed Awadallah, Senior Principal Research Manager, Microsoft Research Redmond
Jianfeng Gao, Distinguished Scientist & Vice President, Microsoft Research Redmond
Danqi Chen, Assistant Professor, Princeton University
Song Han, Assistant Professor, MIT

The AI landscape has been transformed by the advent of large-scale models like BERT, Turing, and, most recently, GPT-3. Researchers have brought language models to new heights in terms of performance, propelling advancements in search, language translation, and more. As models are growing in size and capability, their applications are also expanding. But they are also becoming harder to deploy and adopt efficiently. Join us for a roundtable discussion hosted by Senior Principal Researcher Ahmed Awadallah to discuss the many ways we can improve efficiency and adaptability in next-generation AI. He will be joined by Microsoft Distinguished Scientist Jianfeng Gao, Princeton University Assistant Professor Danqi Chen, and Song Han, Assistant Professor in MIT’s Electrical Engineering and Computer Science program.

Learn more about the 2021 Microsoft Research Summit: https://Aka.ms/researchsummit




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Tags:
deep learning
large-scale models
large-scale AI models
AI
artificial intelligence
microsoft research summit