Closing remarks: Deep Learning and Large Scale AI
- Jianfeng Gao | Microsoft Research Redmond
- Microsoft Research Summit 2021 | Deep Learning & Large-Scale AI
AI has undergone a transformation in recent years with the emergence of large-scale models and deep learning. AI models continue to be able to achieve in areas like language and vision. Large AI models also create new challenges, from cost and sustainability of models to their privacy and trustworthiness. This track will explore advancing deep learning and large-scale AI in language, vision, and multimodality responsibly while considering its future impact on people and society.
Learn more about the 2021 Microsoft Research Summit: https://Aka.ms/researchsummit (opens in new tab)
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Jianfeng Gao
Distinguished Scientist & Vice President
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Deep Learning & Large-Scale AI
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Opening remarks: Deep Learning and Large-Scale AI
- Ahmed Awadallah
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Roundtable discussion: Efficient and adaptable large-scale AI
- Ahmed Awadallah,
- Jianfeng Gao,
- Danqi Chen
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Panel: Large-scale neural platform models: Opportunities, concerns, and directions
- Eric Horvitz,
- Miles Brundage,
- Yejin Choi
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Research talk: WebQA: Multihop and multimodal
- Yonatan Bisk
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Roundtable discussion: Beyond language models: Knowledge, multiple modalities, and more
- Yonatan Bisk,
- Daniel McDuff,
- Dragomir Radev
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Closing remarks: Deep Learning and Large Scale AI
- Jianfeng Gao
