Red Hat OpenShift AI unveils model registry, data drift detection [Video]

Cloud-based AI and machine learning platform also adds support for Nvidia NIM, AMD GPUs, the vLLM runtime for KServe, KServe Modelcars, and LoRA fine-tuning.

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Red Hat has updated Red Hat OpenShift AI, its cloud-based AI and machine learning platform, with a model registry with model versioning and tracking capabilities, data drift detection and bias detection tools, and LoRA (low-rank adaptation) fine-tuning capabilities. Stronger security also is offered, Red Hat said.

Version 2.15 of Red Hat OpenShift AI will be generally available in mid-November. Features highlighted in the release include:

• A model registry, currently in a technology preview state, that provides a structured way to share, version, deploy, and track models, metadata, and model artifacts.
• Data drift detection, to monitor changes in input data distributions for deployed ML models. This capability allows data scientists to detect when the live data used for model interference significantly deviates from the data upon which the model was trained. Drift detection helps …