The prominent player in open-source solution provider, Red Hat, has introduced multiple upgrades to Red Hat AI, which is a suite of products and services designed to boost the deployment of AI across hybrid cloud environments.
In the latest updates, Red Hat equipped its AI suite with new advancements, including Red Hat OpenShift AI 2.18 and Red Hat Enterprise Linux AI (RHEL AI) 1.4. New upgrades will help businesses to create more efficient and secure AI models to meet their business needs.
In a crucial development, Red Hat AI merged OpenShift AI and RHEL AI to develop a complete platform for managing the entire life cycle of AI models, from training and fine-tuning to deployment and monitoring.
Also, the platform supports both predictive AI and generative AI (GenAI), helping organizations create smarter models. It also ensures they run efficiently across a wide range of accelerated compute architectures.
Key Upgrades in Red Hat OpenShift AI 2.18
Here are some key advancements:
- Distributed Serving with vLLM- OpenShift AI now provides “distributed model serving” across multiple GPUs, which reduces the burden on individual servers, improves speed, and enhances resource utilization.
- End-to-End Model Tuning- This feature can simplifies fine-tuning of large language models (LLMs) by using InstructLab and OpenShift AI’s data pipelines. This makes them more manageable and scalable in production environments.
- AI Guardrails- It introduces measures to detect and mitigate harmful content, personally identifiable information, and competitive data. At the same time, it ensures AI models align with corporate policies.
- Model Evaluation- Using the language model evaluation (lm-eval) component, data scientists can benchmark LLM performance across diverse tasks. It enhances model responsiveness and effectiveness.
RHEL AI 1.4
RHEL AI, which is a key part of the Red Hat AI portfolio, provides a reliable platform to develop, test, and run enterprise-grade LLMs. The latest version, RHEL AI 1.4, introduces:
- Granite 3.1 8B Model- This new addition supports multilingual inference and taxonomy/ knowledge customization with an extended 128k context window, which improves summarization and retrieval-augmented generation (RAG) tasks.
Source: https://www.aninews.in/news/business/red-hat-boosts-enterprise-ai-across-the-hybrid-cloud-with-red-hat-ai20250327190933/
Latest Stories:
Alibaba Unveils Qwen2.5-Omni-7B for Cost-Effective AI Agents
