Artificial Intelligence
Building intelligent machines that complement human reasoning and extend what people can do.
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Demo: User-centric graph for building intelligence and Meeting Insights
In this digital age, enterprise users use different entities to accomplish their tasks—conversations, emails, meetings, documents, and others. We envision the real power of intelligence for productivity will come when we link all the entities…
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Research talk: Reinforcement learning with preference feedback
Speaker: Aadirupa Saha, Postdoctoral Researcher, Microsoft Research NYC In Preference-based Reinforcement Learning (PbRL), an agent receives feedback only in terms of rank-ordered preferences over a set of selected actions, unlike the absolute reward feedback in…
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Research talk: System frontiers for dense retrieval
The Microsoft Bing search engine combines classic information retrieval and dense retrieval in multiple stages of the search funnel. Handling hundreds of billions of documents with constant updates creates massive system challenges to inference, search,…
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Panel: Causal ML in industry
Causal ML is widely used by data science teams in the tech world to give business decision makers data-driven answers. In this panel data science leaders at Amazon, LinkedIn, Netflix and Toyota will offer their…
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Research talk: Causal ML and fairness
Observing heterogeneous treatment effects across different demographic groups is an important mechanism for evaluating fairness. However, relatively little data is available for certain demographics, in which case researchers may combine multiple data sources to increase…
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Keynote: Cloud Intelligence: Infusing AI into cloud computing systems
Cloud computing platforms have become part of the basic infrastructure of the world, bringing unprecedented opportunities of digital transformation to business, society, and human life. Therefore, the quality of cloud computing platforms, including availability, reliability,…
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Closing remarks: Reinforcement Learning
Speaker: John Langford, Partner Research Manager, Microsoft Research NYC Learn more about the 2021 Microsoft Research Summit: https://Aka.ms/researchsummit
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Research talk: Building towards a responsible data economy
Speaker: Dawn Song, Professor, UC Berkeley Data is a key driver of the modern economy and AI/machine learning. However, a lot of this data is sensitive, and handling sensitive data has caused unprecedented challenges for…
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Research talk: Transformer efficiency: From model compression to training acceleration
At Microsoft Research, we are approaching large-scale AI from many different perspectives, which include not only creating new, bigger models, but also developing unique ways of optimizing AI models from training to deployment. One of…
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Research talk: Towards data-efficient machine learning with meta-learning
At Microsoft Research, we are approaching large-scale AI from many different perspectives, which include not only creating new, bigger models, but also developing unique ways of optimizing AI models from training to deployment. One of…
