Title: Collaborative Innovation Technologies and Applications for Large and Small Models
题目：大小模型协同创新技术与应用
Abstract: With the advancement of large model technologies, numerous research institutions worldwide have engaged in competitions regarding model parameter scale and computing power, sparking critical reflections in academia about the current development path of artificial intelligence. On one hand, the research and application of large models still heavily rely on high-performance computing ecosystems dominated by foreign technologies, making it difficult to ensure autonomous security in large model development. On the other hand, most current industrial intelligent scenarios demonstrate a disproportionate relationship between the utilization of large model capabilities and the computational costs invested, highlighting the need for more efficient and lightweight models. Addressing these developmental challenges, this lecture will analyze future industrial trends in AI by examining current research progress in both large and small models, with a focus on the potential of hybrid development approaches combining different model scales.
摘要：随着大模型技术的发展，国内外大量的研究机构都开始进行大模型参数量竞赛与算力竞赛，这引发了学术界对当前人工智能发展道路的批判性思考。一方面，大模型研究与应用仍高度依赖以国外为主的高性能计算生态，对于大模型技术的自主安全难以把控。另一方面，当前大部分的工业智能化场景对于大模型性能的利用与付出的计算成本不成正比，反而需要更高效、更轻量的模型。针对这一发展问题，本次讲座将结合当前的大模型与小模型的研究现状，分析未来人工智能的大小模型混合发展对于未来产业发展的趋势。
Bio: C. L. Philip Chen is the Chair Professor and Dean of the School of Computer Science and Engineering, South China University of Technology. Prior to this position he worked in the US in two different universities as a tenured professor, department chair and associate dean, and in University of Macao as the dean. He is a Life Fellow of IEEE, Fellow of AAAS, IAPR, CAA, CAAI, and HKIE; a member of Academia Europaea (AE), a member of European Academy of Sciences and Arts (EASA), and a Full Foreign Member of Russia Academy of Engineering (FFM-RAE). He received the IEEE Norbert Wiener Award in 2018, for his contribution in systems and cybernetics, and machine learnings, the IEEE Joseph G. Wohl Outstanding Career award, Wu WenJun Outstanding Contribution award from Chinese AI Association, and 2016 Outstanding Electrical and Computer Engineers Award from his alma mater, Purdue University.
He is a highly cited researcher by Clarivate Analytics from 2018-2023 and is listed in Stanford University/Elsevier World’s Top 2% Scientists in “Lifetime Scientific Impact” and in “Annual Scientific Impact (951 world-rank in 2024)” Rankings since 2019. His current research interests include cybernetics, systems, and computational intelligence. For his contribution in these research areas, he received two times best transactions paper award from IEEE Transactions on Neural Networks and Learning Systems for his papers in 2014 and 2018 and received three-time Macau natural science award. In professional service, he was the Editor-in-Chief of the IEEE Transactions on Cybernetics, the Editor-in-Chief of the IEEE Transactions on Systems, Man, and Cybernetics: Systems, the President of IEEE Systems, Man, and Cybernetics Society. Currently, he is the director of two Guangdong Key Labs, the director of a research lab funded by the Ministry of Education, a Vice President of Chinese Association of Automation, and Co-President of Guangdong AI Industrial Association.
简介：
C. L. Philip Chen（陈俊龙）现任华南理工大学计算机科学与工程学院院长、讲席教授。此前，他曾在美国两所大学担任终身教授、系主任及副院长，并在澳门大学任院长。他是 IEEE终身会士、美国科学促进会（AAAS）会士、国际模式识别协会（IAPR）会士、中国自动化学会（CAA）会士、中国人工智能学会（CAAI）会士 及 香港工程师学会（HKIE）会士，同时为 欧洲科学院院士、欧洲科学与艺术科学院院士，以及 俄罗斯工程院外籍院士。
他因在系统与控制论及机器学习领域的贡献，于2018年获 IEEE诺伯特·维纳奖，并曾获 IEEE Joseph G. Wohl杰出职业成就奖、中国人工智能学会吴文俊杰出贡献奖，以及母校普渡大学颁发的 2016年度杰出电气与计算机工程师奖。2018至2023年连续入选 科睿唯安全球高被引学者，2019年起稳居 斯坦福大学/爱思唯尔全球前2%顶尖科学家榜单（“终身科学影响力”及“年度科学影响力”榜单，2024年全球排名第951位）。在高排名学者（Highly Ranked Scholars™ ) 计算机类（Computer Science）近五年的影响力全国排名中名列第一，位列全球第8名。其研究聚焦控制论、系统科学与计算智能，相关成果于2014年与2018年 两度荣获IEEE神经网络与学习系统汇刊最佳论文奖，并 三次荣获澳门自然科学奖。
曾任《IEEE Transactions on Cybernetics》与《IEEE Transactions on Systems, Man, and Cybernetics: Systems》主编、IEEE系统-人-控制论学会主席；现任 两个广东省重点实验室主任、教育部重点科研实验室主任、中国自动化学会副理事长 及 广东省人工智能产业协会联席会长。
主要从事计算智能系统，数据挖掘和知识发现，信息和视频索引、检索、系统、控制论和机器人的研究。他围绕智能系统与控制、计算智能、数据科学等科研方向开展研究工作超过40年，在该领域取得一系列学术创新性成果。他曾获中国自动化学会自然科学奖及广东省科技进步奖一等奖。