Red Hat OpenShift AI's new model registry allows for effective sharing, versioning, deploying, and tracking of machine learning models, promoting better collaboration and accountability among data scientists.
With enhanced data drift detection, data scientists can now monitor input data changes, ensuring their models remain reliable and relevant even with evolving real-world data sources.
Bias detection tools from the TrustyAI community equip developers with the means to ensure their AI models operate fairly, significantly contributing to ethical AI deployment in real-world environments.
The introduction of LoRA fine-tuning capabilities allows organizations to optimize large language models efficiently, thus scaling AI operations while minimizing expenses and resource utilization.
Collection
[
|
...
]