What is The News About?
Red Hat, Inc., the world’s largest open source solutions provider, launched Red Hat Enterprise Linux AI (RHEL AI), a foundation model platform that simplifies GenAI model development, testing, and deployment. RHEL AI combines IBM Research’s open-source Granite large language model (LLM) family, InstructLab model alignment tools based on the LAB (Large-scale Alignment for chatBots) methodology, and a community-driven model development process through the InstructLab project. The solution is packaged as an optimized, bootable RHEL image for hybrid cloud server deployments and as part of OpenShift AI, Red Hat’s hybrid MLOps platform, for scaling models and InstructLab across distributed cluster environments.IBM Research developed Large-scale Alignment for chatBots (LAB), a model alignment method that uses taxonomy-guided synthetic data and a novel multi-phase tuning framework. By eliminating costly human annotations and proprietary models, this method makes AI model development more accessible to anyone. The LAB technique improves models by identifying skills and knowledge tied to a taxonomy, providing synthetic data at scale to affect the model, and training the model.
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Why Is It Important?
IBM and Red Hat founded InstructLab, an open source community based on the LAB approach and IBM’s Granite models, after realizing that it could increase model performance. By making LLM development as easy as contributing to any other open source project, InstructLab seeks to empower developers.
IBM also made several Granite English language and code models public as part of InstructLab. The Apache license makes the datasets used to train these models transparent. InstructLab has integrated the Granite 7B English language model, so users can contribute their skills and knowledge to improve it like any other open source project. Granite code models will soon be supported in InstructLab.As organizations experiment and tune new AI models on RHEL AI, they can scale these workflows with Red Hat OpenShift AI, which will include RHEL AI, and use OpenShift’s Kubernetes engine to train and serve AI models at scale and MLOps to manage the model lifecycle. IBM’s watsonx.ai enterprise studio, based on Red Hat OpenShift AI, will benefit from RHEL AI’s inclusion when it’s available, adding enterprise AI development, data management, model governance, and price performance.
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Open source technology have cut IT costs and innovation hurdles for over 30 years, enabling rapid innovation. Red Hat has led this drive for almost as long, from RHEL in the early 2000s to Red Hat OpenShift, which uses containers and Kubernetes to provide open hybrid cloud and cloud-native computing.
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