Explore the intersection of large language models (LLMs) and federated learning in this 28-minute conference talk by Fangchi Wang and Layne Peng from VMware. Discover how FATE-LLM, an open-source federated learning platform, addresses challenges in LLM development such as data scarcity and privacy concerns. Learn about the integration of popular LLMs like ChatGLM and LLaMA into the federated learning paradigm, and understand the technical considerations for efficiency and security. Gain insights into KubeFATE, a cloud-native solution for managing FATE on Kubernetes, and its role in accelerating FATE-LLM workflows. Examine real-world experiments, evaluations, and the future roadmap of this innovative approach to empowering large language models.