Microsoft Research Lab – Asia
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Data-driven model improves accuracy in predicting EV battery degradation
Microsoft Research and Nissan Motor Corporation have collaborated to develop a machine learning model that improves the accuracy of predicting EV battery degradation by 80%. Learn how this collaboration supports long-term sustainability goals.
Unified Database: Laying the foundation for large language model vertical applications
Unified databases offer better knowledge transfer between multimodal data types. They provide substantial corpus support for large language models and are poised to drive innovation in underlying hardware, laying the foundation for data-enhanced AI.
Awards | USENIX ATC 2024
Best Paper Award at USENIX ATC 2024
Our paper titled “SuperBench: Improving Cloud AI Infrastructure Reliability with Proactive Validation” received the Best Paper Award at the 2024 USENIX Annual Technical Conference (USENIX ATC ’24).
Synergizing habits and goals with variational Bayes: A new framework for biological and artificial embodied agents
| Dongqi Han
The Bayesian behavior framework synergizes habits and goals through variational Bayesian methods, offering new insights on sensorimotor behavior and comprehension of actions.
Author: Chang Xu Diffusion probabilistic models have the capacity to generate high-fidelity samples for generative time series forecasting. However, they also present issues of instability due to their stochastic nature. In order to tackle this challenge, researchers from Microsoft Research…
Research Focus: Week of June 10, 2024
In this issue: RELEVANCE automatically evaluates creative LLM responses; Recyclable vitrimer-based printed circuit boards; Lean Attention: Hardware-aware scalable attention mechanism; WaveCoder: a fine-tuned code LLM; New AutoGen training course.
Microsoft Research Forum Episode 3: Globally inclusive and equitable AI, new use cases for AI, and more
“We’re at the very early stage of generative AI and the impacts it will have on work. This is a fast-moving field, and there’s an immense opportunity to take control of the agenda and build truly globally equitable AI systems”,…
Jiang Bian discusses how generative AI transforms industries by bridging gaps between AI capabilities and sector needs. He will showcase domain-specific foundation models and versatile AI agents, setting new industry standards.
Research Forum Brief | June 2024
| Jiang Bian, Adam Fourney, Tanuja Ganu, Daniela Massiceti, Jacki O'Neill, Sunayana Sitaram, and Tian Xie
In this forum episode, researchers dive into the importance of globally inclusive and equitable AI, share updates on AutoGen and MatterGen, explore novel use cases for AI, and more.