Guide
In order to fully implement the strategy of innovation-driven development and rejuvenating the country through science and education, thoroughly implement the deployment requirements of the "National New Generation Artificial Intelligence Development Plan", mobilize the enthusiasm and creativity of the majority of intelligent science and technology leading talents, promote the integrated development of general artificial intelligence and future industries, accelerate the development of new quality productivity and new industrialization, and build an industrial science and technology innovation center with global influence. From April 12th to 14th, 2024, the Chinese Society of Artificial Intelligence will hold the "'Innovation-Driven • Digital Intelligence Power' - The 13th Wu Wenjun Artificial Intelligence Science and Technology Award Ceremony and the 2023 Chinese Artificial Intelligence Industry Annual Conference" in Suzhou Industrial Park.
01
Background of the event
In recent years, with the rapid development of a new round of global scientific and technological revolution and industrial transformation, generative AI, large models and general artificial intelligence have become key areas for the emergence of new industries, new forms of business and new models. It is particularly important to promote the optimization and upgrading of the industrial chain and supply chain, strengthen the research of key core technologies of artificial intelligence, focus on solving major application and industrialization problems, actively cultivate emerging industries and future industries, strengthen the national strategic scientific and technological strength, accelerate the construction of new quality productivity, and build a digital industrial cluster with international competitiveness.
Encourage innovation and take responsibility intelligently. 2024 is the 30th anniversary of the development and construction of Suzhou Industrial Park by the Chinese government and the Singapore government, and it is also a key year for the Society to implement the spirit of the National People's Congress and the National People's Congress and the National People's Congress of the People's Republic of China, empower Suzhou to actively carry out the "Artificial Intelligence +" action, give full play to the exploration, leading and exemplary role of Suzhou Industrial Park, promote the deep integration of artificial intelligence and the real economy, and take high-quality development to a new level, strive to build a world-class high-tech park with openness and innovation, and expand exchanges and cooperation between the Society and local governments.
02
Forum features
The 2023 Chinese Artificial Intelligence Industry Annual Conference China Artificial Intelligence Industry Annual Conference (CAIIAC2023) was initiated and hosted by the Chinese Industrial Intelligence Society, and has successfully held nine industry annual conferences so far. As the theme supporting activity of the Wu Wenjun Artificial Intelligence Science and Technology Award Ceremony, the conference integrates closed-door discussions, honorary commendations, high-end forums, product displays, report releases and other core sections, and is an annual artificial intelligence landmark awards event with high authority, large scale, strong brand power and far-reaching industry influence in China.
With the theme of "Innovation-driven, Digital Intelligence Power", the conference set up a "1+10+X" model, including 1 main forum, 10 special forums, as well as authoritative awards, launching ceremonies, report releases, science nights and other special activities. The organizer invites leading experts from ministries and commissions, academicians of the Chinese Academy of Sciences and the Chinese Academy of Sciences, members of Wu Wenjun's Artificial Intelligence Science and Technology Award Committee, nominating and judging experts, award-winning representatives and entrepreneurs to discuss and exchange, give full play to the academic, talent, technological and industrial advantages of the award-winning project team and the achievements of artificial intelligence colleges, and set up a special report meeting of the president of "Intelligent System - Artificial Intelligence" in the theme report link, focusing on how to promote the coordinated development of the application of cutting-edge artificial intelligence technology and industrial ecology. By looking forward to the future trend of artificial intelligence, exchanging key core technologies and future industrial innovation, the intelligent system promotes the in-depth thinking and collision of views on the integration of industry and education in colleges and universities.
03
Report Highlights:
On the morning of April 14, the organizing committee of the conference will grandly launch the special forum on "Large Models and General Artificial Intelligence", and invite Changjiang Scholar Distinguished Professor of the Ministry of Education, Deputy Director of the Youth Working Committee of the Chinese Society of Image and Graphics, and Professor Xu Mai of Beijing University of Aeronautics and Astronautics to serve as the chairman of the forum. The forum is also honored to invite authoritative scholars and outstanding experts from well-known universities and leading enterprises across the country, who have made remarkable achievements in the field of large models and general artificial intelligence, including the winners of the National Fund for Distinguished Young Scholars, the leading talents of the National "Ten Thousand Talents Program", and the winners of the Lu Jiaxi Young Talent Award of the Chinese Academy of Sciences. This forum focuses on the key technologies of large models and general artificial intelligence, discusses the optimization and generalization of large models, the implementation of general artificial intelligence, etc., explores the theoretical development of important AI technologies such as embodied intelligence, multi-modal multi-task learning, and semantic space alignment, and the application of AI technologies such as intelligent human-computer interaction, OCR, and content generation, and shares the key technologies, innovation difficulties and development trends of large models and general artificial intelligence with professional peers.
This forum aims to provide a platform for a comprehensive understanding of the application of artificial intelligence in large models and general artificial intelligence, promote industrial innovation and digital transformation, and help government departments, scientific research institutions, commercial enterprises, science and technology parks and financial departments to provide direction guidance and decision-making support through the exchange and collision of views, help enterprises achieve intelligent production and operation management, improve production efficiency and other aspects, and promote the industrialization of artificial intelligence scientific and technological achievements in mainland China. Promote the high-quality development of the digital economy and the real economy, and build a high-level exchange and cooperation platform.
Here, the organizing committee of the forum sincerely invites colleagues from all walks of life to come to this conference to discuss the new changes, new opportunities and new challenges in the era of artificial intelligence.
04
Agenda of the Forum
05
Forum Organizing Committee
Science Technology
Chairman of the Forum - Xu Mai
He is a Changjiang Scholar Distinguished Professor of the Ministry of Education and Deputy Director of the Youth Working Committee of the Chinese Society of Image and Graphics. In the past five years, as the first/corresponding author, he has published more than 100 papers (all of which are SCI/EI indexed) in top international journals such as IJCV, IEEE TPAMI, JSAC, TIP, TMI, JSTSP, TCSVT and top conferences such as CVPR, ICCV, ECCV, AAAI, DCC, ACM MM, etc., including 60+ SCI indexed papers (50+ papers in JCR1 area and 40+ IEEE journal papers). In the past five years, Google has been cited more than 5,000 times, SCI has been cited more than 1,000 times, and many papers have been selected as ESI highly cited papers/hot papers. He has won 4 IEEE International Conference/Journal Best Paper Awards and 2 Nomination Awards. He serves as the Associate Editor of IEEE TIP, IEEE TMM, and IEEE J-STSP, an authoritative journal in the field of signal processing. As the person in charge, he has undertaken more than 20 scientific research projects, including the first batch of original exploration projects of the National Natural Science Foundation of China, excellent youth projects, general projects, youth projects, Beijing Outstanding Youth Project, Science and Technology Commission Innovation Special Zone Project of the Military Commission, and 863 Project. He has been selected as a Young Changjiang Scholar by the Ministry of Education, and has been honored by the Fok Yingdong Foundation of the Ministry of Education, the Outstanding Scientific and Technological Worker of the Chinese Institute of Electronics, and the Outstanding Speaker of the China Computer Federation. The research results won the first prize of technological invention of the Chinese Society of Artificial Intelligence in 2017 (the second completer), the first prize of the technological invention of the Ministry of Education in 2020 (the first completer), and the 24th China Association for Science and Technology Qiushi Outstanding Youth Achievement Transformation Award.
Since 2013, he has been responsible for the teaching of "Digital Image Processing" for undergraduates, and won the 2021 Outstanding Teacher Award for Computing in Colleges and Universities. Since 2016, he has been responsible for the teaching of the "Introduction to Machine Learning" course for graduate students, and won the 2021 Beihang University Graduate Course Teaching Excellence Award, and in 2014, he won the "I Love My Teacher" Top Ten Teacher Award of Beihang University. 2 undergraduates under his guidance have won the "Shen Yuan Gold Medal" of Beihang University (the highest honor for undergraduate students of Beihang University), and 5 outstanding undergraduate graduation projects of Beihang University. The doctoral students supervised by him have won the Beijing Outstanding Doctoral Dissertation Award, the Outstanding Doctoral Dissertation Award of the Chinese Society of Image and Graphics, and the master's students supervised by him have won 3 Outstanding Master's Thesis Awards (including 1 nomination award) of the Chinese Institute of Electronics. The graduate students supervised by him have won 6 "Top Ten Graduate Students" (the highest honor for graduate students of Beihang University), 1 nomination, and more than 10 national scholarships.
Science Technology
Chairman of the Forum - Zhao Jian
He is a young scientist and a researcher at the Institute of Optoelectronics and Intelligence of Northwestern Polytechnical University, and graduated from the National University of Singapore with a Ph.D. degree.
He has published more than 40 CCF-A papers, including 2 T-PAMI (IF: 24.314) and 3 IJCV (IF: 13.369), etc., and the first inventor has authorized 5 national invention patents, and his technical achievements have been applied to 6 leading enterprises in the technology industry, such as Baidu, Ant Financial, and Qihoo 360. He was selected into the "Young Talent Lifting Project" of China Association for Science and Technology and Beijing Association for Science and Technology, and presided over 6 projects such as a special zone project of JKW and the National Natural Youth Science Foundation. He has won the 2023 Wu Wenjun Artificial Intelligence Outstanding Youth Award of the Chinese Society of Artificial Intelligence, the first prize of the 2022 Wu Wenjun Artificial Intelligence Natural Science Award of the Chinese Society of Artificial Intelligence (2/5), the only best student paper award of ACM MM'18 at the CCF-A conference (1 work, 1/208), and won the championship in 7 important international science and technology competitions.
He is a director of the Beijing Society of Image and Graphics, an editorial board member of the internationally renowned journals "Artificial Intelligence Advances" and "IET Computer Vision", a guest editor of the special issues of "Pattern Recognition Letters" and "Electronics", a senior field chair of VALSE, and the chairman of the ACM Multimedia 2021 sub-forum, CICAI 2022/2023 Field Chairman, CCBR 2024 Forum Chairman, Senior Member of Chinese Society of Artificial Intelligence/Chinese Society of Image and Graphics, Judge of "Challenge Cup" College Student Science and Technology Works Competition, Member of the Expert Committee of Chinese Artificial Intelligence Competition, etc.
Home: https://zhaoj9014.github.io
06
Invited speaker
Science Technology
Topic: Sparse Optimization and Generalized Design for General Vision Large Models
Speaker: Xiong Hongkai
Graduated from Shanghai Jiao Tong University, he is currently a distinguished professor and doctoral supervisor of the School of Electronic Information and Electrical Engineering of Shanghai Jiao Tong University. He has been engaged in information theory and coding, signal processing, and machine learning research for a long time, and has published more than 110 papers in SCI journals including Nature and IEEE TPAMI, more than 90 long articles in IEEE Transactions Transactions, and top international academic conferences ICML, NeurIPS, He has published more than 60 papers such as CVPR, and has won the Shanghai Youth Science and Technology Outstanding Contribution Award, the first prize of Shanghai Science and Technology Progress Award, the first prize of Natural Science Award of the Chinese Institute of Electronics, the first prize of Shanghai Technological Invention Award, etc., and has won the Top Paper Award of the international conference ACM Multimedia.
Summary of the report
Aiming at the design of Transformer, the basic architecture for building large models, and the efficient generalization methods of data in different scenarios and geometries are discussed. Firstly, sparse optimization and generalization adaptation are carried out for the learnable similarity composition, and the learnable filtering is extended to anisotropy based on frequency domain analysis, so as to further form an isotropic representation of the signal on the generalized manifold and form a unified framework. Based on the hierarchical structure of token and feature graph, sparse optimization gradually removes redundancy, discusses the problem of information forgetting for modal hybrid adaptation, and carries out lossless adaptive adjustment of information according to the reversible normalized stream, and constructs a dynamic model topology of multiple tasks. The Transformer structure is extended to form a learnable anisotropic filter to achieve multi-scale geometric frequency analysis. For the generalized manifold signal, dynamic routing can be carried out to learn the composition, design the specification and isovariable network, and improve the generalization performance under different local coordinate systems, different 3D grid structures and resolutions.
Science Technology
Topic: Some Thoughts on Visual Basic Model and OCR Vertical Large Model
Speaker: Jin Lianwen
He is also the second-level professor of South China University of Technology, the chairman of the Guangdong Image and Graphics Society, the executive director of the Chinese Society of Image and Graphics (CSIG), and the director of the CSIG Document Image Analysis and Recognition Committee. His main research areas are text recognition, document image understanding, computer vision, etc., and he has published more than 200 papers in important academic journals and international conferences (including SCI
Q1 area + more than 100 CCFA papers), Google Scholar papers have been cited more than 14,000 times, H-Index 61. In the past four years, he has been selected into the annual list of "Stanford University's Top 2% Global Top Scientists". He has won 5 provincial and ministerial science and technology awards (including 2 first prizes and 3 second prizes), won 3 second prizes of scientific and technological progress awards of national societies such as CAI, CIE, CIG, etc., and guided students to participate in academic competitions in international and domestic well-known conferences such as CVPR, ICDAR, ICPR, ICFHR, PRCV and won more than 20 championships.
Summary of the report
With the rise of large language models (LLMs), artificial general intelligence (AGI) for natural language processing has made a major breakthrough. This report will briefly review the progress of representative technologies related to multimodal large models, visual basic models, and OCR vertical domain basic models in recent years, introduce some of the latest basic large model construction methods and technical routes for OCR, and discuss and look forward to the development trends and future research directions of OCR and other vertical fields in the era of large models.
Science Technology
Topic: Structural Design and Physical Inspiration of Visual Representation Models
Speaker: Ye Qixiang
Distinguished Professor of the University of Chinese Academy of Sciences, winner of the National Fund for Distinguished Young Scholars, winner of the Lu Jiaxi Young Talent Award of the Chinese Academy of Sciences, Outstanding Doctoral Supervisor of the Chinese Academy of Sciences, CVPR2023, NeurIPS2023, ICLR2024 Area Chairs, international journal IEEE TITS, IEEE TCSVT editorial board member. From 2013 to 2014, he was a visiting assistant professor at the Institute of Advanced Computer Technology (UMIACS) at the University of Maryland, and a visiting scholar at the Institute of Information Technology (IID) at Duke University in 2016. He has published more than 100 papers in international conferences such as CVPR, ICCV, NeurIPS and journals such as TPAMI, TNNLS, TIP, etc., which have been cited more than 13,000 times by Google. It undertook key projects of the Natural Science Foundation and developed high-precision target perception methods to support the application systems of Huawei, aerospace and other units. He has won the championship of the remote sensing target interpretation competition of ICCV2017, CVPR2019 and high-resolution earth observation major projects, and the first prize of natural science of the Chinese Institute of Electronics. He has trained many doctoral students to win the President Award of the Chinese Academy of Sciences, 100 outstanding doctoral dissertations of the Chinese Academy of Sciences, and the support of the Postdoctoral Innovative Talent Program.
Summary of the report
The complementarity and dialectical relationship between the local convolution operation and the global attention operation are analyzed, and the local features and global features are coupled to form a Conformer network structure, which significantly enhances the visual representation ability and improves the lower limit of the performance of the representation model. This paper discusses the problem of information leakage of Mask Image Modeling (MIM) self-supervised learning caused by local convolution operations, and proposes a token merging operation to break through the local constraints of convolution or local operations to form an efficient hierarchical Transformer representation (HiViT) and a fully pre-trained Transformer Pyramid Network (iTPN). In the ImageNet classification task, iTPN-Base, iTPN-Large, and iTPN-Huge achieved Top-1 classification accuracy of 88.0%, 89.2%, and 89.7%, respectively.
From the perspective of model structure design, the performance of visual object detection and segmentation has been improved to a new level. On the basis of the model structure, the next generation of basic models was explored, and the new source of the characterization model was explored from the perspective of heat conduction, and preliminary results were obtained github.com/MzeroMiko/VMamba github.com/sunsmarterjie/iTPN github.com/pengzhiliang/Conformer.
Science Technology
Topic: Technical Links and Bottlenecks from Text Synthesis to Video Synthesis
Speaker: Wu Fei
His main research areas are artificial intelligence, multimedia analysis and retrieval. Secretary of the Party Committee of the School of Computer Science, Zhejiang University, Director of the Institute of Artificial Intelligence, Zhejiang University. He is the winner of the National Fund for Distinguished Young Scholars, a member of the Intelligent Science and Technology Discipline Evaluation Group of the Academic Degrees Committee of the State Council, and the winner of the 9th Yongping Outstanding Teaching Contribution Award of Zhejiang University, and has won the first prize of the 2022 Ministry of Education Science and Technology Progress Award (ranked first) and the first prize of the 2021 Science and Technology Progress Award of the Chinese Institute of Electronics (ranked first). He is the person in charge of the core course "Introduction to Artificial Intelligence" of the Ministry of Education's Pilot Work Plan for Undergraduate Education Teaching Reform in the Field of Computer Science (101 Program), and has set up the first batch of national online first-class courses "Artificial Intelligence: Models and Algorithms", and is the author of "Introduction to Artificial Intelligence", "Introduction to Artificial Intelligence: Models and Algorithms", "Into Artificial Intelligence" and "Artificial Intelligence Preliminary" (high school information technology) and other textbooks and popular science books.
Summary of the report
In this report, we will introduce Google's 2016 self-attention neural network transformer that captures local/global associations between text words, Google's Vision transformer, which expanded the transformer from text to image in 2021, Stability AI's Stable Diffusion in 2022, In 2023, the University of California, Berkeley and New York University proposed the development of core algorithms such as Diffusion Transformers (DiTs), an image synthesis technology, to reveal the mechanism and ceiling of meaningful association and combination of the smallest units in the synthetic content.
Science Technology
Topic: Application and Innovation of AIGC FaceChain
Speaker: Sun Baigui
In 2014, he graduated from the State Key Laboratory of CAD&CG of Zhejiang University with a master's degree in computer science, and his supervisors were Zhang Guofeng and Bao Hujun. He joined Alibaba in the same year and has 10 years of AI experience and has been engaged in deep learning research and development. 3 years in Taobao Technology Department & Search Division, 6 years in Damo Academy, currently in charge of AIGC in Tongyi Laboratory, has won the best newcomer in Taobao Technology Department, Alibaba open source pioneer and other awards. The representative work of large-scale applications involved in the research and development includes: Pailitao, Tujing/Yundun, DeepCTR, DingTalk attendance machine, Alibaba Cloud Face API section, FaceChain, etc. He has won 6 championships in WiderFace detection and 6 open source projects/individual awards at home and abroad. At present, he has published 26+ papers in the top conferences/journals of cooperation, and the open source Star 8.1K+.
Summary of the report
Driven by the wave of AIGC technology, image content generation has shown broad application potential on the C-end and B-side. This report introduces FaceChain's research achievements in popular application scenarios such as character portraits, virtual fittings, and character videos. facechain has been successfully implemented in a number of applications such as Fliggy Digital Travel Photography and Tongyi Wanxiang Photo Museum, and its open API has the advantages of out-of-the-box, custom templates, flexible configuration styles, and training-free technical paths. At the same time, the facechain team actively promotes the construction of open source communities, and has received more than 8.1K stars on GitHub, and has won 6 domestic and foreign open source projects and individual awards.
Science Technology
Topic: Representation and Compression Methods for Visual Semantic Reconstruction
Speaker: Li Shengxi
He is a professor at the School of Electronic and Information Engineering, Beihang University, and graduated from Imperial College London with a Ph.D. in intelligent signal processing and probability generation models. He has been committed to the theoretical and applied technology research of image signal modeling, characterization and compression for a long time, and has published more than 30 papers in IEEE journals such as IEEE TPAMI AND TNNLS, as well as CCF conferences such as NeurIPS and CVPR, and has written 2 books. As the chief guest editor, he organized the special issue of IEEE TCSVT Generative Artificial Intelligence: AIGC for Multimedia, and contributed more than 10 MPEG standard organization proposals, which have been applied in many of the latest standards of international standardization ISO and ITU organizations. He has won the China Outstanding Self-financed International Student Award, the Imperial College London Lee Family Award, and the China Electronics Association Outstanding Master's Thesis Nomination. Selected for the 2022 National Overseas Young Talent Program.
Summary of the report
In the era of big data and large models, the continuous progress of intelligent algorithms is often accompanied by the steady improvement of their representation capabilities, and probability generation models perform probabilistic representation of signals in an unsupervised way, which plays an extremely key role in artificial intelligence with its advantages such as probability interpretation. This report analyzes the representation performance of generative adversarial networks based on visual semantic refactoring-oriented representation and reversibility methods, and then introduces the generative adversarial networks oriented to semantic refactoring with feature functions as statistical measures, and its theoretical completeness can ensure the completeness of semantic representations. Furthermore, a reversible method for generative adversarial networks is constructed to greatly improve the accuracy and reliability of semantic representation.
Science Technology
Topic: Practice and research of large language models in the field of network security
Speaker: Ran
Doctor/postdoctoral fellow in engineering, head of Sangfor Security GPT business, chief expert of Sangfor Security Solutions, responsible for the planning and operation of Sangfor Security GPT and security solutions. He has led and participated in a number of national and industry standards for zero trust, big data security, and edge computing security, and has taken the lead in supporting a number of data security, zero trust, and security operation projects at the provincial and ministerial levels and central enterprise groups. He has published 10 papers in top international journals and conferences, and his research interests include AI security, network security architecture, zero trust security, data security, and cloud security.
Summary of the report
Large language models have received extensive attention in various fields. In the field of network security, it is considered to be very suitable for the implementation and effectiveness of large language models. This report introduces the latest progress and implementation practices of large language models in the field of network security at home and abroad, including attack detection, threat research and judgment, data security, etc. It also discusses how large language models in the security field will develop with the rapid development of new large language model technologies such as RAG, ultra-long context, and AI agent.
Science Technology
Topic: Integration of AI software and hardware
Speaker: Zhao Bin
Associate Professor of Northwestern Polytechnical University, Young Scientist of Shanghai Artificial Intelligence Laboratory. Engaged in the integration of artificial intelligence software and hardware, including front-end detection equipment, visual perception methods and intelligent mobile platforms, to promote the application of artificial intelligence technology. He has published more than 50 academic papers in TPAMI/Artificial Intelligence/TIP/Optics Express/CVPR/ICCV/NeurIPS/ICML/ICRA/CoRL, and applied for more than 10 national invention patents. He has won the Young Talent Lifting Project of China Association for Science and Technology, the first prize of Science and Technology Progress Award of China Society of Aeronautics and Astronautics, the Excellent Doctor of Chinese Optical Engineering Society, and the Excellent Doctor of Shaanxi Province. The relevant achievements have been applied to national aerospace projects, and the public technology has been reported by domestic and foreign media such as The SUN, Asia Times, People's Daily, Xinhuanet, etc.
Summary of the report
Since the beginning of life, the evolution of biological intelligence has not only been reflected in the evolution of the way of thinking, but also in the transformation of body structures such as body shape and limbs. Artificial intelligence is a series of technologies formed with reference to biological intelligence, and its theoretical development and technology implementation require the collaboration of software and hardware. Driven by this idea, it is necessary to pay attention to the integration of artificial intelligence software and hardware research to promote the application of artificial intelligence. This report condenses the three-dimensional interaction model of "thinking computing-entity control-environment perception" of biological intelligence, and focuses on the relevant research of large models driving embodied agents, including high-level semantic understanding, self-skill cognition, and complex task execution, so as to provide new ideas for the development of artificial intelligence software and hardware in the era of large models.
Science Technology
Panelist: Shan Shiguang
Researcher/Ph.D. supervisor of the Institute of Computing Technology, Chinese Academy of Sciences, Director of the Key Laboratory of Intelligent Information Processing, Deputy Director of the Key Laboratory of Intelligent Algorithm Security (Chinese Academy of Sciences), IEEE Fellow. His research interests include computer vision, pattern recognition, and machine learning. He has published more than 400 papers, including more than 180 CCF A papers, and his papers have been cited more than 36,000 times by Google Scholar. The research results won the second prize of the National Science and Technology Progress Award in 2005, the second prize of the National Natural Science Award in 2015, the second prize of the Beijing Science and Technology Progress Award in 2021, and the first prize of the Natural Science Award of the Chinese Society of Image and Graphics in 2022. He is a leading talent of the National Special Support Program, an excellent young person of the National Foundation of China, an expert with special allowance from the State Council, a rising star of science and technology in Beijing, a young and middle-aged expert with outstanding contributions to the National Millions of Talents Project of the Ministry of Human Resources and Social Security, a winner of the CCF Young Scientist Award, an outstanding member of the Youth Promotion Association of the Chinese Academy of Sciences, and a winner of the Tencent Science Exploration Award. He is the deputy director of the Pattern Recognition Committee of the Chinese Society of Artificial Intelligence (CAAI), the deputy director of the CAAI Emotional Intelligence Committee, the deputy director of the Youth Working Committee of the China Computer Federation (CCF), and the standing committee member of the CCF Computer Vision Committee.
07
Topics and guests of the roundtable dialogue
Conversation topics
Moderator: Zhao Jian, Young Scientist of China Telecom Artificial Intelligence Research Institute, Researcher of Northwestern Polytechnical University
Topic: 1. What is the impact of large models on visual research?
2. Will the big model dominate everything?
3. How is general artificial intelligence (GE) realized?How is dedicated AI and GEI combined?
Panelist: Zhao Bin, Associate Professor of Northwestern Polytechnical University, Young Scientist of Shanghai Artificial Intelligence Laboratory
Sun Baigui is the person in charge of AIGC in Alibaba Tongyi Laboratory
Jin Lianwen is a second-level professor at South China University of Technology
Shiguang Shan is a researcher/laboratory director at the Institute of Computing Technology, Chinese Academy of Sciences
Zi Ran is the head of security GPT business of Sangfor Technology Co., Ltd
Science Technology
Special Forum on Large Models and General Artificial Intelligence
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