ÜBER DIESE EPISODE
Rangan Majumder is the Partner Group Program Manager of Microsoft’s Search and AI, and he has a simple goal: to make the world smarter and more productive. But nobody said simple was easy, so he and his team are working on better – and faster – ways to help you find the information you’re looking for, anywhere you’re looking for it.
Today, Rangan talks about how three big trends have changed the way Microsoft is building – and sharing – AI stacks across product groups. He also tells us about Project Turing, an internal deep learning moonshot that aims to harness the resources of the web and bring the power of deep learning to a search box near you.
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Englisch
Vereinigte Staaten
IN DIESER FOLGE
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VERGANGENE FOLGEN SUCHEN
Vorhandene Folgen von Microsoft Research Podcast durchsuchen.
WEITERE EPISODEN IN DIESEM PODCAST
In the series finale, Amanda Craig Deckard returns to examine what Microsoft has learned about testing as a governance tool. She also explores the roles of rigor, standardization, and interpretability in testing and what’s next for Microsoft’s AI governance work.
Show notes: https://www.microsoft.c…
For the series finale, Peter Lee, Carey Goldberg, and Dr. Zak Kohane compare their predictions to insights from the series’ most recent guests, including experts on AI’s economic and societal impact, leaders in AI-driven medicine, and doctors in training.
Show notes
Former Washington State Secretary of Health Dr. Umair Shah and Mayo Clinic CEO Dr. Gianrico Farrugia explore how healthcare leaders are approaching AI when it comes to public health, care delivery, the healthcare-research connection, and the patient experience.
Show notes
Next-generation physicians Morgan Cheatham and Daniel Chen discuss how generative AI is transforming medical education, exploring how students and attending physicians integrate new tools while navigating questions on trust, training, and responsibility.
Show notes
Microsoft’s Eric Horvitz and guests Bruce Wittmann, Tessa Alexanian, and James Diggans discuss the Paraphrase Project—a red-teaming effort that exposed and secured a biosecurity vulnerability in AI-driven protein design. The work offers a model for addressing AI’s dual-use risks.
Show notes
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