Federated Learning and Large Language Models

With the rapid development of large language models, Artificial Intelligence (AI) has entered a new era of innovation and application. However, transferring the knowledge of general-purpose large models to localized smaller models presents important challenges, particularly in relation to privacy, data security and responsible deployment.

In this public lecture, Professor Qiang Yang will explore key challenges facing large AI models and explore how the “Federated LLM” framework can help enable knowledge sharing and model development while protecting sensitive data. Drawing on his extensive expertise in federated learning, transfer learning, and AI, the lecture will offer insights into emerging approaches to building more secure and privacy-preserving AI systems.

The lecture will be held in English. 
 

Speaker