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 was established seven years ago to build on Infer.NET and retrieve facts, schemas, and entities from unstructured data sources while adhering to Microsoft’s robust privacy standards. The goal of the project is to construct a […]

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 the 17-billion-parameter Microsoft Turing Natural Language Generation (Turing-NLG) with state-of-the-art accuracy, achieving the fastest BERT training record, or supporting 10x larger model training using a single GPU, DeepSpeed continues to tackle challenges in AI at […]

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, and writing concurrent software—programs with multiple logical threads of execution—is of paramount importance to scale these growing computing needs. Writing correct concurrent software is challenging. Unit, integration, and even stress testing don’t provide reasonable guarantees about the correctness of a concurrent program. Thus, insidious defects can remain latent in software until the late stages […]

Microsoft Excel is one of the world’s most important software tools, relied upon users worldwide to create, understand, model, predict, and collaborate. As the Excel team works to leverage new areas of computer science – advancements in programming languages, NLP, Artificial Intelligence, Machine Learning – they turned to Microsoft Research both to leverage the incredible work done in the organization as well as to help co-create a vision for what Excel should look like years into the future. The Excel team has […]

From BiT (928 million parameters) to GPT-3 (175 billion parameters), 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 climate impact. As a result, we’re witnessing exciting and emerging research into compressing these models to make them less expensive, small enough to store on any device, and more energy efficient. Perhaps the most popular approach to model compression is pruning, in which […]

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 in the last year. Measuring collaboration using network machine learning provides a powerful diagnostic tool to address issues as they arise. One challenge lies in how we build relationships in the workplace. With many transitioning to work-from-home environments, more flexible schedules, and new methods of working, there is evidence that interactions at work have been […]

Editor’s note: This research was conducted by Sai Vemprala, Senior Researcher, and Ashish Kapoor, Partner Researcher, of Microsoft Research along with Sami Mian, who was a PhD Researcher at the University of Pittsburgh and an intern at Microsoft at the time of the work. Autonomous systems are composed of complex perception-action loops, where observations of the world need to be processed in real time to result in safe and effective actions. A significant amount of research has focused on creating […]