Separating Intelligence from Inference: A Standard for Edge-Native AI Computing

The document is an arXiv computer science feed containing research on edge AI architectures, GPU kernel optimization, distributed algorithms, HPC communication and power management, federated learning, adversarially robust decentralized learning, satellite networking, and Mixture-of-Experts training. The security-relevant topics include Byzantine model and topology poisoning defenses in federated learning, cryptographic provenance and privacy-preserving telemetry for edge AI, and adversarial conditions in distributed systems. No specific software vulnerability or exploitable security flaw is|C