Peter Schmidt-Nielsen

Peter Schmidt-Nielsen is a hardware and machine learning engineer working on FPGA-accelerated servers at Saturn Data, building high-memory, high-bandwidth systems for workloads such as vector search. He previously worked as an ML engineer at Redwood Research and is a co-author of the NeurIPS 2022 paper "Adversarial Training for High-Stakes Reliability" on adversarial training methods for high-stakes AI reliability.

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