Cedric Clyburn

Kickstart your generative AI application development journey with Podman AI Lab, an open-source extension for Podman Desktop to build applications with LLMs on a local environment. The Podman AI Lab helps to make AI more accessible and approachable, providing recipes for example use cases with generative AI, curated models sourced from Hugging Face, model serving with integrated code snippets, and a playground environment to test and adjust model performance. Learn more on Red Hat Developer https://developers.redhat.com/product... and download Podman Desktop today to get started!

Let's take a look at how you can get started working with generative AI in your application development process using open-source tools like Podman AI Lab (https://podman-desktop.io/extensions/...) to help build and serve applications with LLMs, InstructLab (https://instructlab.ai) to fine-tune models locally from your machine, and OpenShift AI (https://developers.redhat.com/product...) to handle the operationalizing of building and serving AI on an OpenShift cluster.

Podman Desktop is a free, open-source tool that lets developers work with containers and Kubernetes from their local environment. It offers an easy-to-use dashboard to interact with and manage containers, images, pods, and more, powered by the Podman container engine. For developers and IT operations, Podman Desktop provides the capabilities to streamline the container development lifecycle, and bridges with the Kubernetes environment for simplified development and testing of containerized applications.

Learn how to use and build bootable containers for disk image operating system deployment with Podman Desktop.

The rapid advancement of generative artificial intelligence (gen AI) has unlocked incredible opportunities. However, customizing and iterating on large language models (LLMs) remains a complex and resource intensive process. Training and enhancing models often involves creating multiple forks, which can lead to fragmentation and hinder collaboration.

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

As enterprises seek to utilize the power of generative AI, they often struggle with the transition from experimentation to production-ready solutions. This talk will guide you through the steps needed to build an enterprise-grade generative AI application, starting with local experimentation using Podman AI Lab and finishing in a scalable, secure deployment on Red Hat OpenShift AI.

With GPU acceleration for Podman AI Lab, developers can inference models faster and build AI-enabled applications with quicker response times.