Welcome to Research Focus, a series of blog posts that highlights notable publications, events, code/datasets, new hires and other milestones from across the research community at Microsoft. In this article NEWS Bing’s gendered translations tackle bias in machine translation Machine translation (MT) models are designed to learn from large amounts of data collected from real-world sources. However, this training  

We have had quite good text generation models for some time. You could actually prompt a model with asking it to describe an imaginary scene, and it will produce a very good description of what you have asked it to do. And then we started making a lot of progress on image generation, as well. With models like DALL-E 2 and Imagen and even models coming out from such startups like Midjourney and Stability AI, we have been getting to […]

Today I’m sitting down with Sébastien Bubeck, who leads the Machine Learning Foundations Group at Microsoft Research. In recent months, some of us at Microsoft had the extraordinary privilege of early access to GPT-4. We took the opportunity to dive deep into its remarkable reasoning, problem-solving, and the many other abilities that emerge from the massive scale of GPT-4. Sébastien and his team took this opportunity to probe the model in new ways to gain insight into the nature of […]

Welcome to Research Focus, a series of blog posts that highlights notable publications, events, code/datasets, new hires and other milestones from across the research community at Microsoft. In this article NEW RESEARCH Hide and seek with Spectres Attack methods like Spectre exploit speculative execution, one of the key performance optimizations of modern CPUs. Microsoft researchers  

Welcome to Research Focus, a new series of blog posts that highlights notable publications, events, code/datasets, new hires and other milestones from across the research community at Microsoft. In this article NEW RESEARCH Self-supervised Multi-task pretrAining with contRol Transformers (SMART) Many real-world applications require sequential decision making, where an agent interacts with a stochastic environment to perform a task.