Microsoft Research Blog

Research Blog

Microsoft Research collaborates with KAIST in Korea to explore bimanual interactions with haptic feedback in virtual reality

May 6, 2021 | Michel Pahud, Mike Sinclair, and Andrea Bianchi

Editor's Note: Bimanual controllers are frequently used to enhance the realism and immersion of virtual reality experiences such as games and simulations. Researchers have typically relied on mechanical linkages between the controllers to recreate the sensation of holding different objects with both hands. However, those…
Conversations with data: Advancing the state of the art in language-driven data exploration

May 3, 2021 | Alex Polozov, Chris Meek, and Ahmed Awadallah

One key aspiration of AI is to develop natural and effective task-oriented conversational systems. Task-oriented conversational systems use a natural language interface to collaborate with and support people in accomplishing specific goals and activities. They go beyond chitchat conversation. For example, as personal digital assistants,…
EverParse: Hardening critical attack surfaces with formally proven message parsers

May 3, 2021 | Tahina Ramananandro, Aseem Rastogi, and Nikhil Swamy

EverParse (opens in new tab) is a framework for generating provably secure parsers and formatters used to improve the security of critical code bases at Microsoft. EverParse is developed as part of Project Everest (opens in new tab), a collaboration between Microsoft Research labs in…
Alexandria in Microsoft Viva Topics: from big data to big knowledge

April 26, 2021

Project Alexandria is a research project within Microsoft Research Cambridge dedicated to discovering entities, or topics of information, and their associated properties from unstructured documents. This research lab has studied knowledge mining research for over a decade, using the probabilistic programming framework Infer.NET. Project Alexandria…
ZeRO-Infinity and DeepSpeed: Unlocking unprecedented model scale for deep learning training

April 19, 2021 | DeepSpeed Team, Rangan Majumder, and Andrey Proskurin

Since the DeepSpeed optimization library was introduced last year, it has rolled out numerous novel optimizations for training large AI models—improving scale, speed, cost, and usability. As large models have quickly evolved over the last year, so too has DeepSpeed. Whether enabling researchers to create…
Reinforcing program correctness with reinforcement learning

April 14, 2021 | Suvam Mukherjee

Many of our online activities, from receiving and sending emails to searching for information to streaming movies, are driven behind the scenes by cloud-based distributed architectures. Writing concurrent software—programs with multiple logical threads of execution—is of paramount importance to scale to these growing computing needs.…
Factorized layers revisited: Compressing deep networks without playing the lottery

March 24, 2021 | Misha Khodak, Neil Tenenholtz, Lester Mackey, and Nicolo Fusi

From BiT (928 million parameters (opens in new tab)) to GPT-3 (175 billion parameters (opens in new tab)), state-of-the-art machine learning models are rapidly growing in size. With the greater expressivity and easier trainability of these models come skyrocketing training costs, deployment difficulties, and even…
Advancing organizational science using network machine learning to measure innovation in the workplace

March 24, 2021

Is innovation another loss due to the global COVID-19 pandemic? Indicators reveal challenges to overcome—as well as opportunities to build on our collective experience gained (opens in new tab) in the last year. Measuring collaboration using network machine learning provides a powerful diagnostic tool to…
Learning visuomotor policies for autonomous systems from event-based cameras

March 8, 2021 | Sai Vemprala

Editor’s note: This research was conducted by Sai Vemprala, Senior Researcher, and Ashish Kapoor, Partner Researcher, of Microsoft Research along with Sami Mian (opens in new tab), who was a PhD Researcher at the University of Pittsburgh and an intern at Microsoft at the time…
The science behind semantic search: How AI from Bing is powering Azure Cognitive Search

March 2, 2021

Azure Cognitive Search (opens in new tab) is a cloud search service that gives developers APIs and tools to build rich search experiences over private, heterogeneous content in web, mobile, and enterprise applications. It has multiple components, including an API for indexing and querying, seamless integration through Azure data ingestion, deep integration with Azure Cognitive Services, and persistent storage…
HEXA: Self-supervised pretraining with hard examples improves visual representations

February 25, 2021 | Chunyuan Li, Lei Zhang, and Jianfeng Gao

Humans perceive the world through observing a large number of visual scenes around us and then effectively generalizing—in other words, interpreting and identifying scenes they haven’t encountered before—without heavily relying on labeled annotations for every single scene. One of the core aspirations in artificial intelligence…
AAAI 2021: Accelerating the impact of artificial intelligence

February 24, 2021

The purpose of the Association for the Advancement of Artificial Intelligence, according to its bylaws, is twofold. The first is to promote research in the area of AI, and the second is to promote the responsible use of these types of technology. The result was a 35th AAAI Conference on Artificial Intelligence (AAAI-21) (opens in new tab) schedule that broadens the…

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