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5/14/24, 2:32 PM Red Hat Delivers Accessible, Open Source Generative AI Innovation with Red Hat Enterprise Linux AI - Middle East News 247
Procuring AI infrastructure or consuming AI services
The complex process of tuning AI models for specific business needs
Integrating AI into enterprise applications
Managing both the application and model lifecycle.
To truly lower the entry barriers for AI innovation, enterprises need to be able to expand the roster of who can
work on AI initiatives while simultaneously getting these costs under control. With InstructLab alignment tools,
Granite models and RHEL AI, Red Hat aims to apply the benefits of true open source projects – freely
accessible and reusable, transparent and open to contributions – to GenAI in an effort to remove these
obstacles.
Building AI in the open with InstructLab
IBM Research created the Large-scale Alignment for chatBots (LAB) technique, an approach for model
alignment that uses taxonomy-guided synthetic data generation and a novel multi-phase tuning framework.
This approach makes AI model development more open and accessible to all users by reducing reliance on
expensive human annotations and proprietary models. Using the LAB method, models can be improved by
specifying skills and knowledge attached to a taxonomy, generating synthetic data from that information at
scale to influence the model and using the generated data for model training.
After seeing that the LAB method could help significantly improve model performance, IBM and Red Hat
decided to launch InstructLab, an open source community built around the LAB method and the open
source Granite models from IBM. The InstructLab project aims to put LLM development into the hands of
developers by making, building and contributing to an LLM as simple as contributing to any other open
source project.
As part of the InstructLab launch, IBM has also released a family of select Granite English language and
code models in the open. These models are released under an Apache license with transparency on the
datasets used to train these models. The Granite 7B English language model has been integrated into the
InstructLab community, where end users can contribute the skills and knowledge to collectively enhance this
model, just as they would when contributing to any other open source project. Similar support for Granite
code models within InstructLab will be available soon.
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