[MUSIC FADES] Let’s dive right in. We are undergoing a paradigm shift where AI models and systems are starting to exhibit characteristics that I and, of course, many others have described as more general intelligence. When I say general in this context, I think I mean systems with abilities like reasoning and problem-solving that can be applied to many different tasks, even tasks they were not explicitly trained to perform. Despite all of this, I think it’s also important to […]

AI systems like Bing and Microsoft Copilot (web) are as good as they are because they continuously learn and improve from people’s interactions. Since the early 2000s, user clicks on search result pages have fueled the continuous improvements of search engines. Recently, reinforcement learning from human feedback (RLHF) brought step-function improvements to response quality of generative AI models. Bing has a rich history of success in improving its AI offerings by learning from user interactions. For example, Bing pioneered the […]

CHANG LIU: Thank you. Thank you for this opportunity to share our work.  HUIZINGA: So in a few sentences, tell us about the issue or problem your paper addresses and why people should care about this research.  LIU: Sure. Since this is an AI4Science work, let’s start from this perspective. About science, people always want to understand the properties of matters, such as why some substances can cure disease and why some materials are heavy or conductive. For a very […]

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. NEW RESEARCH Fewer is More: Boosting LLM Reasoning with Reinforced Context Pruning Large language models (LLMs) have shown impressive capabilities, yet they still struggle with math reasoning. In a recent paper: Fewer is More: Boosting LLM Reasoning with Reinforced Context Pruning, researchers from Microsoft propose CoT-Influx, a