北京雁栖湖应用数学研究院

孙明明 , 王雅晴

孙明明

2024年10月17日 14:00 至 16:00

A3-1-301

Zoom 230 432 7880 (BIMSA)

Inspired by the nervous system of worms, MIT researchers proposed the model of Liquid Neural Networks (LNN) in 2006. In the years that followed, they developed a theoretical framework for LNNs, proving their superior theoretical properties and achieving successful applications in time series modeling, differential equation solving, and bioinformatics. Recently, they introduced Liquid Foundation Models (LFMs), a general AI model based on LNNs. LFMs are large neural networks built upon the theories of dynamical systems, signal processing, and numerical linear algebra. This unique combination allows LFMs to leverage decades of theoretical advances in these fields. The development from LNNs to LFMs illustrates a path from natural phenomena to mathematical models and eventually to AI products. This journey might offer us significant insights.

孙明明现任北京数学科学与应用研究院（BIMSA）教授，专注于人工智能的基础研究。在此之前，他在互联网行业从事人工智能研发工作，曾在百度研究院担任主任研究员和认知计算实验室负责人，领导了认知自然语言处理、自动驾驶系统的创新研究项目，以及“文心一言”语言模型核心子系统的开发工作。他负责建设了世界领先的百度网页搜索推荐系统。他还负责了若干腾讯的数据分析算法的建设。孙明明在互联网行业获得的荣誉，包括2023年世界互联网大会领先科技奖和百度的多项最高技术/产品奖项。在进入互联网行业之前，他曾在南京理工大学任教，担任讲师和博士后研究员。