Artificial Intelligence
Building intelligent machines that complement human reasoning and extend what people can do.
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Research talk: Learning and pretraining strategies for dense retrieval in search and beyond
In this talk, we’ll quickly go through our recent observations and findings with dense retrieval. First, we’ll recap the standard setup and training strategies for dense retrieval models in search. We’ll then share our recent…
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Research talk: An intelligent data-driven paradigm towards cloud reliability
Cloud systems are perhaps the most complicated computing systems developed so far, yet our daily lives depend heavily on their continuous and reliable operations. To achieve systematic cloud reliability, we propose an intelligent data-driven paradigm…
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Keynote: Extreme classification for dense retrieval and personalized recommendation
Extreme classification is a new research area pioneered by scientists at Microsoft dealing with classification problems involving millions, or even billions, of categories. In this keynote, partner researcher Manik Varma demonstrates how extreme classification can…
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Closing remarks: Causal Machine Learning
Causal machine learning is an increasingly important, but not well understood, technology. It’s a necessary precursor to building more human-like machine intelligence, and an integral factor in the fields of information, data and computer science.…
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Opening Remarks: The Future of Privacy and Security
Security and privacy are key components to building trust in the technologies that we use, whether that be for applications for individuals, businesses, or in government. As new challenges and threats emerge in this area,…
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Research talk: New Future of Work Overview
Our experience in the past year with virtual events has emphasized that planning an event in the virtual world must take into account the span of attention of the audience. We are implementing a new…
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Research talk: Can causal learning improve the privacy of ML models?
Ensuring privacy of data used to train machine learning models is important for safe and responsible deployment of these models. At the same time, models are required to generalize across different data distributions to enable…
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Panel: Perspectives on the new future of hybrid meetings
Hybrid meetings—meetings in which there is a mix of remote and in-person participants—aren’t a new phenomenon, but the impact of the COVID-19 pandemic has brought their opportunities and challenges to center stage. The Microsoft approach…
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Opening remarks: Deep Learning and 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…
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Research talk: Approximate nearest neighbor search systems at scale
Building deep learning-based search and recommendation systems at internet scale requires a complete redesign of the search index. Key to this redesign is a fast, accurate, and cost-efficient indexing system for approximate nearest neighbor search.…
