Peter Lee

Wow this is impressive. One of those tech bio advances that is both expected and yet still very surprising when you see it working for real.

For the past 16 years, I'm pretty sure I've had the best job in all of tech. But an opportunity has come up that forced me to ask the question, "Considering my stage of life and career, will I regret it if I pass on this?" The answer I came up with was "Yes," and so I've taken a big leap and decided to retire from Microsoft.

Working at Microsoft, having the privilege of leading @MSFTResearch, and most recently serving as President of Microsoft Science, has been an incredible experience, full of personal growth and the satisfaction of positive global impact on people and on Microsoft. My colleagues, every day, created a working environment that felt like living in the inevitable future. In my view, @satyanadella, @kevin_scott, @judsonalthoff, and the entire senior leadership of Microsoft have created the modern-day equivalent of Camelot, seeking to align Microsoft's business priorities with the goal of global empowerment and prosperity for all. I've been proud to be a part of it all.

As for what I'll be doing next, what I can say at this point is that it is a once-in-a-lifetime opportunity to join an elite team, fulfilling a dream I've had since childhood. It's a major detour from what I've been doing over the past 2+ decades, but rest assured that I'll be able to continue my participation with @MayoClinic, @KPMedSchool, @seattlechildren, and other great organizations that seek to improve and advance healthcare delivery and medical science.

We @MSFTResearch consistently find that more general AI models outperform specialized models, even on the specialized tasks. Yet another example is the PRISM2 model for digital pathology, in Nature Medicine today. With Paige (now a part of @TempusAI). news.microsoft.com/signal/article…

Many have long believed that real-world evidence can accelerate discovery in medicine. But how, exactly? This new piece in @NatureMedicine talks to @hoifungpoon and others on the leading edge to look at how AI is making the dream of RWE come to life. nature.com/articles/s4159…

Medical diagnoses can be improved by reanalyzing genomic data in rare disease cases. This is normally very burdensome, but today in @NatureMedicine we present Talos, a tool that in iterative monthly reanalysis reduces the burden to 1 variant per 200 cases nature.com/articles/s4159…