How AI is reshaping the future of healthcare and medical research

The book passage I read at the top is from “Chapter 10: The Big Black Bag.”  In imagining AI in medicine, Carey, Zak, and I included in our book two fictional accounts. In the first, a medical resident consults GPT-4 on her personal phone as the patient in front of her crashes. Within seconds, it offers an alternate response based on recent literature. In the second account, a 90-year-old woman with several chronic conditions is living independently and receiving near-constant […]

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BenchmarkQED: Automated benchmarking of RAG systems

One of the key use cases for generative AI involves answering questions over private datasets, with retrieval-augmented generation (RAG) as the go-to framework. As new RAG techniques emerge, there’s a growing need to benchmark their performance across diverse datasets and metrics.  To meet this need, we’re introducing BenchmarkQED, a new suite of tools that automates RAG benchmarking at scale, available on  

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What AI’s impact on individuals means for the health workforce and industry

The book passage I read at the top is from “Chapter 4: Trust but Verify,” which was written by Zak. You know, it’s no secret that in the US and elsewhere shortages in medical staff and the rise of clinician burnout are affecting the quality of patient care for the worse. In our book, we predicted that generative AI would be something that might help address these issues. So in this episode, we’ll delve into how individual performance gains that […]

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Abstracts: Zero-shot models in single-cell biology with Alex Lu

ALEX LU: Yeah, I’m really excited to be joining you today.  HUIZINGA: So let’s start with a little background of your work. In just a few sentences, tell us about your study and more importantly, why it matters.  LU: Absolutely. And before I dive in, I want to give a shout out to the MSR research intern who actually did this work. This was led by Kasia Kedzierska, who interned with us two summers ago in 2023, and she’s the […]

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Abstracts: Aurora with Megan Stanley and Wessel Bruinsma

This is such exciting work about environmental forecasting, so we’re happy to have the two of you join us today.   Megan and Wessel, welcome.  MEGAN STANLEY: Thank you. Thanks. Great to be here.  WESSEL BRUINSMA: Thanks.  TINGLE: Let’s jump right in. Wessel, share a bit about the problem your research addresses and why this work is so important.  BRUINSMA: I think we’re all very much aware of the revolution that’s happening in the space of large language models, which have […]

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Collaborators: Healthcare Innovation to Impact

JONATHAN CARLSON: From the beginning, healthcare stood out to us as an important opportunity for general reasoners to improve the lives and experiences of patients and providers. Indeed, in the past two years, there’s been an explosion of scientific papers looking at the application first of text reasoners and medicine, then multi-modal reasoners that can interpret medical images, and now, most recently, healthcare agents that can reason with each other. But even more impressive than the pace of research has […]

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Magentic-UI, an experimental human-centered web agent

Modern productivity is rooted in the web—from searching for information and filling in forms to navigating dashboards. Yet, many of these tasks remain manual and repetitive. Today, we are introducing Magentic-UI, a new open-source research prototype of a human-centered agent that is meant to help researchers study open questions on human-in-the-loop approaches and oversight mechanisms for AI agents. This prototype collaborates with users on web-based tasks and operates in real time  

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Coauthor roundtable: Reflecting on real world of doctors, developers, patients, and policymakers

[THEME MUSIC FADES]   The passage I read at the top is from the book’s prologue.    When Carey, Zak, and I wrote the book, we could only speculate how generative AI would be used in healthcare because GPT-4 hadn’t yet been released. It wasn’t yet available to the very people we thought would be most affected by it. And while we felt strongly that this new form of AI would have the potential to transform medicine, it was such a different […]

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Abstracts: Heat Transfer and Deep Learning with Hongxia Hao and Bing Lv

HONGXIA HAO: Nice to be here. BING LV: Nice to be here, too. HUIZINGA: So Hongxia, let’s start with you and a brief overview of this paper. In just a few sentences. Tell us about the problem your research addresses and more importantly, why we should care about it. HAO: Let me start with a very simple yet profound question. What’s the fastest the heat can travel through a solid material? This is not just an academic curiosity, but it’s […]

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