Artificial Intelligence
Building intelligent machines that complement human reasoning and extend what people can do.
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Panel: The future of search and recommendation: Beyond web search
The increasing ability to learn representations of text, code, and even medical chemical compounds is changing what and how people search in every domain. In this panel, we bring together experts from industry and academia…
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Research talks: Generalization and adaptation
The limitations of big data-driven deep learning in scalability and adaptation to real-world scenarios hinder its practical applications. To address these limitations, it’s extremely important to develop architectures and algorithms that can capture the fundamentals…
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Opening remarks: New future of work
Learn more about the 2021 Microsoft Research Summit: https://Aka.ms/researchsummit
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Opening remarks: Empowering software developers and mathematicians with next-generation AI
Machine learning systems have become increasingly capable of making fast, plausible predictions in diverse situations. Combining this capability with the reliability of symbolic reasoning will produce next generation AI that will empower developers and mathematicians…
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Lightning talks: Advances in fairness in AI: New directions
Over the past few years, we’ve seen that artificial intelligence (AI) and machine learning (ML) provide us with new opportunities, but they also raise new challenges. Most notably, these challenges have highlighted the various ways…
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Research talk: Optimizing the cloud supply chain
The cloud supply chain includes multiple business-critical stages, such as procuring hardware from multiple suppliers, building racks in datacenters and placing servers on top. While supply chain management has been widely studied, the cloud domain…
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Panel: Causal ML at Microsoft
Causal reasoning and machine learning is widely deployed across Microsoft, to support high-stakes internal decision-making and to build products that help our customers make better use of their own data. This panel, moderated by AI…
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Research talk: WebQA: Multihop and multimodal
Web search is fundamentally multimodal and multihop. Often, even before asking a question, individuals go directly to image search to find answers. Further, rarely do we find an answer from a single source, opting instead…
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Tutorial: Create human-centered AI with the Human-AI eXperience (HAX) Toolkit
There’s been a push to build AI technologies that benefit people and society while also mitigating potential harm. To accomplish this, it’s important to take a holistic approach. We aim to help AI creators make…
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Research talk: Local factor models for large-scale inductive recommendation
In many domains, user preferences are similar locally within like-minded subgroups of users, but typically differ globally between those subgroups. Local recommendation models were shown to substantially improve top-k recommendation performance in such settings. However,…
