The ongoing proliferation of AI coding tools is not only boosting developers’ efficiency, it also signals a future where AI will generate a growing share of all new code.

In this issue: We introduce a new dataset designed to assist renewable energy infrastructure planners, a new method for denoising MRI imagery, and an AI tool for analyzing distant galaxies. Check out our latest research and other updates.  NEW RESEARCH Global Renewables Watch: A Temporal Dataset of Solar and Wind Energy Derived from Satellite Imagery

[THEME MUSIC FADES]  The passage I read at the top there is from Chapter 7 of the book, “The Ultimate Paperwork Shredder.”   Paperwork plays a particularly important role in healthcare. It helps convey treatment information that supports patient care, and it’s also used to help demonstrate that providers are meeting regulatory responsibilities, among other things. But if we’re being honest, it’s taxing—for everyone—and it’s a big contributor to the burnout our clinicians are experiencing today. Carey, Zak, and I identified […]

Every day, countless videos are uploaded and processed online, putting enormous strain on computational resources. The problem isn’t just the sheer volume of data—it’s how this data is structured. Videos consist of raw pixel data, where neighboring pixels often store nearly identical information. This redundancy wastes resources, making it harder for systems to process visual content effectively and efficiently. To tackle this, we’ve developed a new approach to compress visual data into a  

[MUSIC FADES]  I’m excited to share the mic today with three guests to talk about a really cool program called Accelerating Foundation Models Research, or AFMR for short. With me is Cesar Torres, an assistant professor of computer science at the University of Texas, Arlington, and the director of a program called The Hybrid Atelier. More on that soon. I’m also joined by Muhammed Idris, an assistant professor of medicine at the Morehouse School of Medicine. And finally, I welcome […]

[THEME MUSIC FADES] What I read there at the top is a passage from Chapter 2 of the book, which captures part of what we’re going to cover in this episode.  In our book, we predicted how AI would be leveraged in the clinic. Some of those predictions, I felt, were slam dunks, for example, AI being used to listen to doctor-patient conversations and write clinical notes. There were already early products coming out in the world not using generative […]

While large language models (LLMs) are capable of synthesizing vast amounts of information, they sometimes produce inaccurate or unsubstantiated content. To mitigate this risk, tools like Azure AI’s Groundedness Detection (opens in new tab) can be used to verify LLM outputs.  A common strategy for fact-checking LLM-generated texts –  

Large language models (LLMs) have demonstrated remarkable capabilities in reasoning, language understanding, and even creative tasks. Yet, a key challenge persists:  

AI tools are proving useful across a range of applications, from helping to drive the new era of business transformation to helping artists craft songs. But which applications are providing the most value to users? We’ll dig into that question in a series of blog posts that introduce the Semantic Telemetry project at Microsoft Research. In this initial post, we will introduce a new data science approach that we will use to analyze topics and task complexity of Copilot in […]

Transcript [MUSIC] PETER LEE: This is The AI Revolution in Medicine, Revisited. I’m Peter Lee, president of Microsoft Research, and I’m pretty excited to introduce this series of conversations as part of the Microsoft Research Podcast. About two years ago, with Carey Goldberg and Zak Kohane, we wrote a book, The AI Revolution in Medicine. This was a book that was intended to educate the world of healthcare and the world of medical research about this new thing that was […]