Presented by

  • JJ Asghar

    JJ Asghar

    JJ works as a Developer Advocate representing the IBM worldwide. He focuses on the IBM’s watsonx service, the Open Source AI ecosystem, and Kubernetes x with a core focus on OpenShift. He is always trying to make companies and users have a successful onboarding to the AI and Cloud Native ecosystem. He’s also been known in the DevOps ecosystem and generalized Linux communities. If he isn’t building automation to streamline his work, he’s building the groundwork to do just that. He’s been an avid homelab and self-hoster of open source software for years and gives back to that community as much as physically possible. He lives and grew up in Austin, Texas. A father and husband, trying to learn to balance his natural nerdiness with family life. He enjoys a good strong dark ale, hoppy IPA, some team building Artemis, and epic Gloomhaven campaigning. He has dove headfirst into Fedora since IBM buying Redhat, but still secretly wants FreeBSD everywhere. He’s always trying to become a better web technology developer, though normally just uses bash to get the job done.


Engaging in the AI ecosystem can be a daunting task. There are multiple options to start engaging, but no one gives you a clear path to some level of success. There are stories of advanced math or massive computing required; there must be an easier way. Or, in another way to describe it, we all don’t need to develop Microsoft Word, but it’s essential to know how to use Microsoft Word. In this talk, I’ll be walking through an Open Source project called Caikit which is an Open Source wrapper around multiple AI portions of the ecosystem, so you can see the flexibility that it can give you. We will start with a simple whistle-stop tour of how to understand the AI space then how to access public Open Source models. Then we will move over to my laptop live demoing the Caikit via local containers and cached models to show how easy it is to play with it locally. From there, we will take the demo to the cloud and show a way to deploy it to OpenShift and be able to have an API that can respond with said model(s). Walking out of this room, you’ll see how easy it can be with Open Source software; with a little effort on your computer and downloading some Open Source models, you can start leveraging AI with confidence.