Data Science

This year's top articles on AI include an introduction to GPU programming, a guide to integrating AI code assistants, and the KServe open source project. 

In our previous blog post, we introduced the RamaLama project, a bold initiative

Join us as we get ready for the holidays with a few  AI holiday treats! We will demo AI from laptop to production using Quarkus and LangChain4j with ChatGPT, Dall-E, Podman Desktop AI and discover how we can get started with Quarkus+LangChain4j, use memory, agents and tools, play with some RAG features, and test out some images for our holiday party.

Learn how a developer can work with RAG and LLM leveraging their own data chat for queries.

Discover how to integrate NVIDIA NIM with Red Hat OpenShift AI to create and deliver AI-enabled applications at scale.

A practical example to deploy machine learning model using data science...

Explore AMD Instinct MI300X accelerators and learn how to run AI/ML workloads using ROCm, AMD’s open source software stack for GPU programming, on OpenShift AI.

Learn how to apply supervised fine-tuning to Llama 3.1 models using Ray on OpenShift AI in this step-by-step guide.

Learn how to generate word embeddings and perform RAG tasks using a Sentence Transformer model deployed on Caikit Standalone Serving Runtime using OpenShift AI.

In today's fast-paced IT landscape, the need for efficient and effective

Add knowledge to large language models with InstructLab and streamline MLOps using KitOps for efficient model improvement and deployment.

Get an overview of Explainable and Responsible AI and discover how the open source TrustyAI tool helps power fair, transparent machine learning.

In this blog we look at how we use OpenShift AI with Ray Tune to perform

A cloud service that gives data scientists and developers a powerful AI/ML

Discover how InstructLab simplifies LLM tuning for users.

Learn how to deploy and use the Multi-Cloud Object Gateway (MCG) from Red Hat OpenShift Data Foundation to support development and testing of applications and Artificial Intelligence (AI) models which require S3 object storage.

BERT, which stands for Bidirectional Encoder Representations from Transformers

This article explains how to use Red Hat OpenShift AI in the Developer Sandbox for Red Hat OpenShift to create and deploy models.

An intelligent, distributed caching solution that boosts application performance

End-to-end AI-enabled applications and data pipelines across the hybrid cloud

Learn a simplified method for installing KServe, a highly scalable and standards-based model inference platform on Kubernetes for scalable AI. 

A practical example to deploy machine learning model using data science...

Learn how to fine-tune large language models with specific skills and knowledge

This guide will walk you through the process of setting up RStudio Server on Red Hat OpenShift AI and getting started with its extensive features.

Are you curious about the power of artificial intelligence (AI) but not sure