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. Mohammad Alizadeh, Manya Ghobadi, Dina Katabi, Tim Kraska, Sam Madden