Artificial intelligence

Learn how to access a large language model using Node.js and LangChain.js. You

Discover the benefits of KServe, a highly scalable machine learning deployment tool for Kubernetes.

This blog summarises key changes for Red Hat Ansible Lightspeed with IBM watsonx

VMware Cloud Foundation 5.1 now supports Red Hat OpenShift Container Platform 4.13 and NVIDIA AI Enterprise, offering automated, consistent infrastructure and more.

Learn how Intel Graphics Processing Units (GPUs) can enhance the performance of machine learning tasks and pave the way for efficient model serving.

Learn how to create a Java application that uses AI and large-language models (LLMs) by integrating the LangChain4j library and Red Hat build of Quarkus.

Discover how to integrate cutting-edge OpenShift AI capabilities into your Java applications using the OpenShift AI integration with Quarkus.

4-bit and 8-bit quantized LLMs excel in long-context tasks, retaining over 99% accuracy across 4K to 64K sequence lengths.

MLOps with Kubeflow Pipelines can improve collaboration between data scientists and machine learning engineers, ensuring consistency and reliability at every stage of the development workflow.

Discover how to use machine learning techniques to analyze context, semantics, and relationships between words and phrases indexed in Elasticsearch.

Explore features that enhance automation productivity for developers in Ansible Lightspeed with IBM watsonx Code Assistant, now generally available.

Learn how to communicate with OpenAI ChatGPT from a Quarkus application using the ChatGPT API in this demo.

Sparse fine-tuning in combination with sparsity-aware inference software, like DeepSparse, unlocks ubiquitous CPU hardware as a deployment target for LLM inference.

GPT4All is an open source tool that lets you deploy large language models locally without a GPU. Learn how to integrate GPT4All into a Quarkus application.

This article explores leveraging AI to generate Apache Camel routes using ChatGPT.

Get up and running with Ansible Lightspeed, a new generative AI service for Ansible automation, and the Ansible VS Code extension by Red Hat.

Discover the power of AI/ML in software testing with Bunsen, a Python-based toolkit that lets you analyze and report test-suite logs using an SQLite database.

Walk through the basics of fine-tuning a large language model using Red Hat OpenShift Data Science and HuggingFace Transformers.

Learn how to use the Red Hat OpenShift Data Science platform and Starburst to develop a fraud detection workflow with an AI/ML use case.

Compress large language models (LLMs) with SparseGPT to make your machine learning inference fast and efficient. Prune in one-shot with minimal accuracy loss.

Learn why graphics processing units (GPUs) have become the foundation of artificial intelligence and how they are being used.

In this article, you will learn how to perform inference on JPEG images using the gRPC API in OpenVINO Model Server in OpenShift. Model servers play an important role in smoothly bringing models from development to production. Models are served via network endpoints which expose an APIs to run predictions.

Intel AI tools save cloud costs, date scientists' time, and time spent developing models. Learn how the AI Kit can help you.

Online events and regional events held around the world with Red Hat's Developer Advocates.