Artificial Intelligence
Building intelligent machines that complement human reasoning and extend what people can do.
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Closing remarks: Cloud Intelligence/AIOps
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. The AIOps & Cloud Intelligence track brings together researchers from…
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Roundtable discussion: Efficient and adaptable large-scale AI
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,…
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Panel: The future of human-AI collaboration
The increase in productivity resulting from artificial intelligence (AI) has been revolutionary, but there is a risk of developing AI systems incorrectly. We have spent considerable energy expanding the capabilities of intelligent systems and less…
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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
