arXiv:2608. 11221v1 Announce Type: new Abstract: Cyber-physical systems (CPS) are typically developed by multiple stakeholders who produce artefacts tailored to their specific domains of expertise.
By Barbara da Silva Oliveira (UniCA, Laboratoire I3S - COMRED, KAIROS), Julien Deantoni (UniCA, Laboratoire I3S - COMRED, KAIROS), Nicolas Ferry (Laboratoire I3S - COMRED, KAIROS, UniCA)
arXiv:2606. 00090v1 Announce Type: cross Abstract: Physical AI systems increasingly map multimodal observations, language instructions, and learned world representations into physically consequential actions.
By Barak Or
arXiv:2607. 22877v1 Announce Type: new Abstract: With the emergence of Physical AI, artificial intelligence is extending beyond screen-based applications to embodied systems that perceive, interact with, and act in the physical world.
By Wang Yang, Shaobo Wang, Hongxuan Liu, Xiaoran Cai, Yunyu He, Jingzong Zhou, Mengzhong Ma, Yi Yu, Rohit Sharma, Jingjing Fu, Peng Qi
arXiv:2606. 18532v1 Announce Type: cross Abstract: AI systems are increasingly evaluated in bounded environments that combine isolation, simulation, instrumentation, supervision, and evidence capture.
By Inderjeet Singh, Haitham Mahmoud, Andr\'es Murillo
The paper reviews how large language models have evolved into agents that can influence external environments through tool use, interface operation, delegation, state retention, virtual world inhabitation, and robotic control. It critiques the narrative of a single march toward autonomy, distinguishing model competence from system integration, persistence, and safe authority. The authors find that action-interface expansion is well documented, while robust completion, recovery, authorization, and independent verification remain less proven, and they propose a framework of justified delegation to guide future research.
By Linsen Zhu, Mengqing Cai
The paper argues for a Foundation Model Operating System (FMOS) to virtualize foundation model interactions, similar to how operating systems abstract hardware. Current AI stacks are fragmented, with each framework embedding its own runtime for state, memory, budgets, and guardrails, leading to non-portable behavior and brittle governance. An FMOS would orchestrate knowledge across memory tiers, manage model selection and resource allocation, and enforce verification and policy, learning when to intervene or allow direct inference based on operational experience.
By Suparna Bhattacharya, Tarun Kumar, Cong Xu, Satish Kumar Mopur, Jiahao Li, Ashish Mishra, Aalap Tripathy, Annmary Justine Koomthanam, Martin Foltin, Ian Foster