Private AI for model research and post-training

Factory Private describes an on-premises, potentially air-gapped AI deployment model for research environments containing sensitive unreleased model weights, evaluation data, and proprietary training code. NVIDIA’s Nemotron research team used the platform during post-training of Nemotron 3 Ultra to support evaluation and optimization, with detailed task trajectories and verified outcomes informing later training cycles. The material emphasizes that protecting research requires controls over runtime systems, model inference endpoints, telemetry, tool outputs, and external gateway providers, rather than merely hosting execution on customer infrastructure. It also recommends reproducible evaluations that preserve model versions, dependencies, tools, test fixtures, and independent validation results, while treating telemetry content as optional sensitive data subject to explicit configuration, access, and retention policies. For initial adoption, organizations are advised to use bounded tasks with existing acceptance tests, compare results against current workflows, and document both the agent’s permitted access and actual activity without assuming universal performance or efficiency gains.

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