Red Hat differentiates itself from the competition in a few key ways. First, they have a focus on open source and a hybrid approach. They believe that AI is not fundamentally different from applications and that it should be able to run anywhere. Second, Red Hat has a proven track record of optimizing performance across different hardware stacks. They can maximize performance across various hardware options while still providing location and hardware optionality. Finally, Red Hat’s open source approach ensures that customers retain ownership of their intellectual property.
According to Red Hat CEO Matt Hicks, these unique differentiators will be key in the fast-moving AI market. RHEL AI combines open source language models, such as the Granite family of models developed by IBM Research, with tools from the InstructLab project to allow customization and enhancement of the models. It provides an optimized RHEL operating system image with hardware acceleration support and enterprise technical support from Red Hat.
The InstructLab project aims to enable domain experts without data science skills to enhance language models by contributing their knowledge. It uses a novel method called LAB (Large-scale Alignment for chatBots) developed by IBM Research to generate high-quality synthetic training data from a small number of examples. This allows models to be continuously improved and fine-tuned through community contributions in a cost-effective way.
Red Hat’s commitment to open source innovation is evident through its offerings. Developers can get started immediately with the InstructLab community project to enhance open source models with domain knowledge. RHEL AI is also launching in developer preview to provide an optimized foundation for these models with enterprise support. The latest updates to OpenShift AI, Red Hat’s AI platform for Kubernetes, are generally available now, delivering MLOps capabilities to serve both predictive and generative AI models at scale.
With RHEL AI and InstructLab, Red Hat aims to make powerful AI technologies accessible to a broad community through open source, similar to what they did for Linux and Kubernetes. This could accelerate the adoption of generative AI in the enterprise by enabling domain experts to enhance models with their knowledge and deploy them in production environments with trust and support.
Red Hat’s focus on open source and their ability to optimize performance across different hardware stacks sets them apart in the AI market. By providing a platform for customization and enhancement of language models, they empower domain experts to contribute their knowledge and improve AI models in a cost-effective way. With the launch of RHEL AI and InstructLab, Red Hat continues its commitment to open source innovation and aims to expand what “open” means in the context of AI.
