Amin Vahdat, Google
We are in a time of massive transition across technology and society. This talk explores key lessons and insights that we can learn from history as we stand at the precipice of a new epoch of computing, the era of intelligence. To prepare for this future, we first start with a historical view for parallels to inform both what we work on but also how we do so. Building on this historical perspective, we delve into the architecture of intelligence, showing that efficient scaling of compute is central to advances in the field. This scaling will come from advances in many fields, though we focus on the central role networked systems play in scaling intelligence, from TPU on-chip networks to rack-scale serving, to ML training supercomputers, to distributed control and transport over Gigawatt-scale regional computing hubs. We conclude the talk with research opportunities for the future, again drawing lessons from history to ensure that we as technologists also focus on addressing the costs of scaling intelligence, from sustainability to safety to security to societal policy.
Amin Vahdat is a Fellow and Chief Technologist for AI Infrastructure at Google, where his team is responsible for delivering industry-leading infrastructure which spans custom silicon, data centers, network, and supply chain and operations. This infrastructure serves Alphabet, Google and the world, and Artificial Intelligence technologies that empower ML developers and solve customers’ most pressing business challenges. In the past, he was Vice President and General Manager for Google's compute, storage, and network hardware and software infrastructure. Until 2019, he was the Technical Lead and Vice President for the Networking organization at Google.
Before joining Google, Amin was the Science Applications International Corporation (SAIC) Professor of Computer Science and Engineering at UC San Diego (UCSD). He received his doctorate from the University of California Berkeley in computer science, and is a Fellow of the Association for Computing Machinery (ACM).
Amin has been recognized with a number of awards, including the National Science Foundation (NSF) CAREER award, the UC Berkeley Distinguished EECS Alumni Award, the Alfred P. Sloan Fellowship, the Association for Computing Machinery's SIGCOMM Networking Systems Award, and the Duke University David and Janet Vaughn Teaching Award. Amin was awarded the SIGCOMM lifetime achievement award for his contributions to data center and wide area networks. He was inducted into the National Academy of Engineering in 2023 for his contributions to the design and implementation of datacenter and planet-scale networks that power cloud computer systems.
author = {Amin Vahdat},
title = {The Physics of Thought and the Architecture of Intelligence},
year = {2026},
address = {Renton, WA},
publisher = {USENIX Association},
month = may
}