Join us for an exciting exploration of cutting-edge technologies that are revolutionizing the world of Edge AI. In this session, we'll dive deep into the realms of Kubernetes, open-source software, and machine learning operations (MLOps) to unveil the secrets behind creating intelligent, environment-aware solutions at the edge.

Discover how Kubernetes is transforming the deployment landscape, enabling scalable and flexible AI applications right where you need them. We'll also explore the power of open source, as we navigate through the GitHub repository of KubeAI Application Nucleus (KAN), uncovering its hidden gems and the vibrant developer community behind it.

Learn about the art of MLOps and how it plays a crucial role in maintaining and evolving AI models at the edge. Whether you're a seasoned developer or just beginning your journey in AI, this session will provide valuable insights into the technologies shaping the future of AI at the edge. Don't miss out on this opportunity to level up your skills and stay at the forefront of innovation.

Technical Requirements: To fully engage with this session, it is recommended to have a basic understanding of Kubernetes, open-source concepts, and some familiarity with AI technologies. Access to a computer or device with internet connectivity is necessary for exploring the KubeAI Application Nucleus (KAN) GitHub repository during the session.

Target Audience: Developers, DevOps engineers, data scientists, and anyone interested in the convergence of Kubernetes, open-source technologies, and AI at the edge. Whether you're a beginner or an experienced professional, there will be insights and takeaways tailored to your level of expertise.

Preferred Session Duration: The optimal duration for this session is approximately 60 minutes, including time for Q&A. However, it can be adapted to fit shorter or longer time slots, depending on the event's schedule.