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How to simplify AI model fine-tuning

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How to simplify AI model fine-tuning

Red Hat AI simplifies AI fine-tuning for enterprises by replacing monolithic workflows with modular building blocks. Discover how to bridge the gap between general-purpose large language models (LLMs) and your unique enterprise data.

Body: While experimentation starts with push-button simplicity, moving AI to production requires expertise in data processing and synthetic data generation. Host Aditi explains the shift from InstructLab to a modular architecture featuring Docling, Synthetic Data Generation Hub (SDG Hub), and Training Hub. Learn how these enterprise-ready components integrate with Red Hat OpenShift AI to make your models smarter and faster.

00:00 Intro: Beyond monolithic AI training
01:20 Docling for enterprise document intelligence
01:48 SDG Hub: Building synthetic data pipelines
02:27 Training Hub for stable fine-tuning algorithms
03:23 Why your enterprise data matters for AI

Learn more:
🚀 Explore Red Hat AI products → https://www.redhat.com/en/products/ai
🛠️ Get started with OpenShift AI → https://www.redhat.com/en/technologies/cloud-computing/openshift/openshift-ai

#RedHat #AI #FineTuning #OpenShiftAI #Docling #LLM #MachineLearning

Date: January 19, 2026