AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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SimHum is presented, a co-training recipe that extracts kinematic priors from simulation and visual priors from human observations, then fine-tunes on a small real-robot dataset, which exhibits strong scene-generalizable and data-efficient capabilities.
This survey establishes workload-level boundaries and connects system architecture, competence acquisition, and evaluation through a seven-dimensional terminal competence profile, and provides a unified basis for studying terminal-mediated agency across software engineering and emerging application domains.
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