Generative AI (Gen AI) is a branch of AI that can create novel and realistic content, such as text, images, audio, and video. Gen AI has many potential applications in various domains, but also poses significant challenges for edge computing. Gen AI models, especially LLMs, require high-performance computing, large memory, and massive data, which are not always available at the edge. How can cloud native technologies, such as Kubernetes, containers, and microservices, help overcome these challenges and enable Gen AI at the edge? What are the trade-offs between cloud and edge for Gen AI? And what are the benefits and opportunities for the cloud native and edge computing ecosystems?
Join this panel with us to discuss the state and future trends of Gen AI at the edge, the best practices and tools for cloud native Gen AI development and deployment, and the challenges and solutions for optimizing the performance, efficiency, and security of Gen AI models on different edge devices, etc.