Estimating LLM Training FLOPs on the Nvidia Jetson Orin Nano

This is a research summary for an ongoing project I am working on as part of the UChicago Existential Risks Laboratory Summer Research Fellowship. I would really appreciate any feedback.IntroductionMotivationIn want of a quantifiable way to decide what counts as a frontier AI model, compute thresholds have emerged as the standard for AI policy: California’s SB 53 uses 10^26 floating-point operations (FLOPs) in the training run as the threshold for what counts as a frontier model and the EU AI Ac...