IAP: Systems That Learn

Wednesday, January 31, 2024 at 9:00am to 12:00pm

Building 45, 8th Floor 51 Vassar Street, Cambridge MA 02139

Machine learning and generative AI promise to redefine computing in the next decade. In this session, we will explore how software and hardware systems for data centers must evolve to meet the demands of these workloads, and similarly how machine learning is redefining the way we build these software systems. In a series of short talks, each of the speakers will look at a different layer of the data center stack, including hardware, networks, operating systems, and databases, and show how new workloads and machine learning capabilities have and will continue to completely transform the way these systems work, resulting in radically different software architectures – with orders of magnitude better performance – than the designs we have used for the past several decades. The session will then conclude with a panel where we look at common trends between these areas of the software stack and make predictions about how systems will continue to evolve.

Speakers: Mohammad Alizadeh, Manya Ghobadi, Dina Katabi, Tim Kraska, Sam Madden

Part of the Expanding Horizons in Computing IAP series presented by the MIT Schwarzman College of Computing. See the full list of activities at computing.mit.edu/ExpandingHorizons.

Event Type

Conferences/Seminars/Lectures, Community Event

Events By Interest


Events By Audience

Students, MIT Community, Faculty, Staff

Events By School

School of Engineering (SoE), Schwarzman College of Computing, School of Architecture and Planning (SA+P), School of Humanities, Arts, and Social Sciences (SHASS), Sloan School of Management (Sloan), School of Science



MIT Schwarzman College of Computing
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