
OpenAI: Control Room: A central system to track and stop model workloads across our research infrastructure
Learn how OpenAI’s Control Room tracks model workloads across our research infrastructure and can rapidly stop them when safety or security concerns arise.
Control Room is a centralized system that monitors and can stop model workloads across research infrastructure when safety or security concerns arise. The system works by requiring approval before research jobs run agentic inference, then checking with Control Room before each model generates output, stopping any job deemed problematic within 35 seconds of a decision to intervene. This matters because as models become more powerful, the ability to quickly detect and halt potential issues becomes increasingly critical. The system is designed to remain functional even if other systems fail, and stops all inference requests if Control Room itself goes down, ensuring safety protections cannot be bypassed through workarounds in research workload code.
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Learn how OpenAI’s Control Room tracks model workloads across our research infrastructure and can rapidly stop them when safety or security concerns arise.

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