Cloudsmith, providers of an artifact management platform, announced its ML Model Registry, which can act as a single source of truth for all AI models and datasets a company is using.
The registry integrates with the Hugging Face Hub and SDK so that developers can push, pull, and manage models and datasets from Hugging Face and then use Cloudsmith to maintain centralized control, compliance, and visibility.
Once data has been pushed from Hugging Face to Cloudsmith, security and compliance data can be utilized by Enterprise Policy Management so that teams can apply consistent policies to automatically quarantine, block, and approve specific models.
It can also integrate with training, validation, and deployment pipelines, and provides protection of proprietary models and datasets via fine-grained access controls, entitlement tokens, and audit trails.
Models and datasets are also managed in the same repositories as a company’s other artifacts, and can be organized by project, environment, or customer delivery needs.
“The rapid adoption of AI/ML is transforming the kinds of software enterprises are building, but most organizations still lack the governance to manage models and datasets safely,” said Alison Sickelka, VP of product of Cloudsmith. “With this launch, we’re bringing the same enterprise-grade controls, traceability, and security to AI/ML assets that Cloudsmith customers rely on for every other part of their software supply chain.”
The post Cloudsmith launches ML Model Registry to provide a single source of truth for AI models and datasets appeared first on SD Times.
Source: Read MoreÂ
