Accelerate AI with Red Hat: Secure Deployment and Scaling Across Hybrid Cloud

With the shift in technology, companies are now more focused on adopting Artificial Intelligence (AI) automation technology for creativity improvement, productivity increase, and business capture differentiation. The usage of AI development in a hybrid cloud setup poses integration, security, and even management resources issues. Red Hat, a leader in open infrastructure platform AI solutions, has developed a profound portfolio of AI solutions, which enables organizations to implement AI and safeguard their information across various contexts and structures. 

Red Hat AI: Empowering Enterprises Across Hybrid Clouds 

Red Hat AI boasts an impressive set of services and products designed to optimize the building and implementation of AI systems in hybrid cloud environments. By delivering a powerful and versatile system, Red Hat AI supports model training and inference on-premises, in the cloud, and at the core, periphery, and edge of the network while maintaining productivity and security. 

Red Hat OpenShift AI: A Comprehensive AI Platform 

At the heart of Red Hat's AI offerings is Red Hat OpenShift AI, an integrated platform that supports the entire AI/ML lifecycle. Built on the robust foundation of Red Hat OpenShift, this platform enables organizations to develop, train, test, and deploy AI models seamlessly across hybrid cloud environments. 

Key Features of Red Hat OpenShift AI: 

• Model Development Tooling: Provides an interactive, collaborative interface based on JupyterLab for exploratory data science and model training. 
   

• Distributed Model Training: Uses multiple cluster nodes simultaneously, boosting efficiency in training and tuning predictive and generative AI models. 
   

• Data Science Pipelines: Automates steps to deliver and test models in development and production, reducing errors and accelerating workflows. 
   

• Model Serving and Monitoring: Supports serving models from various providers and frameworks, with tools to monitor metrics such as inference requests and response times. 
   

• AI Guardrails: Enhances model accuracy and safety by monitoring and protecting user interactions and model outputs. 

These features collectively empower organizations to manage AI workloads effectively, ensuring scalability and security across diverse environments. 

Red Hat Enterprise Linux AI: Foundation for AI Innovation 

The Red Hat enterprise now has AI and RHEL AI augmenting Openshift AI. This platform's underlying model enables the development, testing, and deployment of LLMs to power enterprise applications. It encompasses a collection of sophisticated language models, model alignment tools, and a bootable Red Hat Enterprise Linux server image for convenient deployment across hybrid cloud environments.  

Updates in RHEL AI Available:  

• Support for Advanced Language Models: These include multilingual models which have improved context windows for summarization and retrieval-augmented generation.  

• Graphical Interface for Knowledge Contributions: Makes the domain-specific data ingestion and customization processes easier.  

• Evaluation Benchmarks: Customization tools of evaluation models allow for contextual comparison against baseline models and guarantee effectiveness.