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arXiv AI By Suparna Bhattacharya, Tarun Kumar, Cong Xu, Satish Kumar Mopur, Jiahao Li, Ashish Mishra, Aalap Tripathy, Annmary Justine Koomthanam, Martin Foltin, Ian Foster

Position: It is Time to Virtualize Foundation Models with a Self-evolving Operating System Layer

Read the original on arXiv AI →

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.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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