JJ Asghar
JJ works as a Developer Advocate representing IBM worldwide. He engages in the IBM’s watsonx service, the Open Source AI ecosystem, and Kubernetes ecosystem with a focus on Red Hat’s OpenShift. He attempts to teach enterprises and users succesful skills to onboard to the AI and Cloud Native ecosystem though he learned his trade in the DevOps ecosystem. If he isn’t building high level automation to streamline his work, he’s building the groundwork to prepare for that need. He’s been an avid homelaber and self-hoster of open source software for years and gives back to that community as much as 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 and python to get the job done.
Sessions
In a world of fast-moving AI adoption, the big players want you to play with their versions of AI. The problem, though, is that their AI is usually built in a way that is closed off from the eyes of our tech community, with little or no oversight for choices and legal grey areas for usage and adoption.
What if I told you there was a way to get the best of both worlds? An AI solution that can be externally verified and trusted legally, and we want you, yes, you, to join us in building a genuinely transparent AI solution.
This is what the Granite and Granite-Code foundational models are. You can read the paper on how the model was initially trained and have IBM's lawyers back up claims made from using Granite or Granite-Code usage. Can your other AI providers say that? Will they give you the design documents on how they built it from the ground up? Or will they put their lawyers behind your usage of their AI? Would you put your business at risk of using something like this when the legal area is so grey and ever-changing?
But that's only a point in time; you also need to add skills and knowledge to the ever-growing AI system, which is where InstructLab comes into play. During this presentation/workshop, we will be showing you why you should care about Open Source AI, teach you how to leverage a purely Open Source AI for a local "co-pilot" like experience, and then help train the Granite foundational model with new knowledge, giving you the skills to help build a genuinely transparent AI.
Join us and learn with us. We want to build a future of transparency and legal protection for AI engineers.
You’ve heard about emacs vs vim , or maybe vscode vs jetbrains, I’m here to tell you there’s a text editor that is on every POSIX machine none of us know. ed, and in this ignite talk I’ll tell you everything you need to know to use it.