DeepInsight: A Unified Evaluation Infrastructure Across the Physical AI Stack

DeepInsight is a newly proposed evaluation infrastructure designed to assess the entire Physical AI stack, spanning from foundation-model decoding to whole-body control simulations. It introduces three abstractions—task, resource, and result—allowing for a unified runtime that maintains the heterogeneity of different subsystems while providing a shared trace identity for diagnostics. This framework enhances benchmarking by enabling faster execution and localized regression tracking across layers, making it a significant tool for practitioners aiming to streamline evaluation processes in complex AI systems.