Sébastien Bubeck's guest appearances

Sébastien Bubeck

Microsoft Research Podcast

Chris White

Max Welling

Peter Lee

Peyton Jones

Kevin Scott

Amos Miller

Brad Smith

Nathalie Riche

Ben Zorn

Layla El Asri

Desmond Patton

Mark Hamilton

Jennifer Chayes

Andy Gordon

David Rothschild

OwlTail

Powerful new large-scale AI models like GPT-4 are showing dramatic improvements in reasoning, problem-solving, and language capabilities. This marks a phase change for artificial intelligence—and a signal of accelerating progress to come.In this new Microsoft Research Podcast series, AI scientist and engineer Ashley Llorens hosts conversations with his collaborators and colleagues about what these new models—and the models that will come next—mean for our approach to creating, understanding, and deploying AI, its applications in areas such as health care and education, and its potential to benefit humanity.The first episode features Sébastien Bubeck, who leads the Machine Learning Foundations group at Microsoft Research in Redmond. He and his collaborators conducted an extensive evaluation of GPT-4 while it was in development, and have published their findings in a paper that explores its capabilities and limitations—noting that it shows “sparks” of artificial general intelligence.https://www.microsoft.com/research

Powerful new large-scale AI models like GPT-4 are showing dramatic improvements in reasoning, problem-solving, and language capabilities. This marks a phase change for artificial intelligence—and a signal of accelerating progress to come. In this new Microsoft Research Podcast series, AI scientist and engineer <a href="https://www.microsoft.com/en-us/research/people/allorens/" rel="nofollow" target="_blank">Ashley Llorens</a> hosts conversations with his collaborators and colleagues about what these new models—and the models that will come next—mean for our approach to creating, understanding, and deploying AI, its applications in areas such as health care and education, and its potential to benefit humanity. The first episode features <a href="https://www.microsoft.com/en-us/research/people/sebubeck/" rel="nofollow" target="_blank">Sébastien Bubeck</a>, who leads the Machine Learning Foundations group at Microsoft Research in Redmond. He and his collaborators conducted an extensive evaluation of GPT-4 while it was in development, and have published their findings in a paper that explores its capabilities and limitations—noting that it shows “sparks” of artificial general intelligence. <a href="https://www.microsoft.com/research" rel="nofollow" target="_blank">https://www.microsoft.com/research</a>

136 - AI Frontiers: The Physics of AI with Sébastien Bubeck

Dr. Sébastien Bubeck is a mathematician and a senior researcher in the Machine Learning and Optimization group at Microsoft Research. He’s also a self-proclaimed “bandit” who claims that, despite all the buzz around AI, it’s still a science in its infancy. That’s why he’s devoted his career to advancing the mathematical foundations behind the machine learning algorithms behind AI. Today, Dr. Bubeck explains the difficulty of the multi-armed bandit problem in the context of a parameter- and data-rich online world. He also discusses a host of topics from randomness and convex optimization to metrical task systems and log n competitiveness to the surprising connection between Gaussian kernels and what he calls some of the most beautiful objects in mathematics. https://www.microsoft.com/research

Dr. Sébastien Bubeck is a mathematician and a senior researcher in the Machine Learning and Optimization group at Microsoft Research. He’s also a self-proclaimed “bandit” who claims that, despite all the buzz around AI, it’s still a science in its infancy. That’s why he’s devoted his career to advancing the mathematical foundations behind the machine learning algorithms behind AI. Today, Dr. Bubeck explains the difficulty of the multi-armed bandit problem in the context of a parameter- and data-rich online world. He also discusses a host of topics from randomness and convex optimization to metrical task systems and log n competitiveness to the surprising connection between Gaussian kernels and what he calls some of the most beautiful objects in mathematics. <a href="https://www.microsoft.com/research" rel="nofollow" target="_blank">https://www.microsoft.com/research</a>

053r - Chasing convex bodies and other random topics with Dr. Sébastien Bubeck