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.
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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.
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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.
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Report Highlights:
On the morning of April 14, the organizing committee of the conference will launch a special forum on "Intelligent Transportation and Autonomous Driving", and invite Dr. Zhang Yuanfang, a high-level talent in Shenzhen and co-founder of City Light (Shenzhen) Unmanned Driving Co., Ltd., 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 intelligent transportation and autonomous driving, including the national "Ten Thousand Talents Program" scientific and technological innovation leaders, 2014 Google PhD Fellow Program and other scholars and experts gathered together. This forum focuses on the exploration and practice of intelligent transportation and autonomous driving, and conducts in-depth discussions on topics such as the development level, development trend, technical research and judgment, and future practice of intelligent transportation and autonomous driving in mainland China, and shares in-depth information on field-end intelligence, unmanned driving research and development, autonomous driving platform and application practice. Provide high-end intellectual resources for the scientific development of transportation, and promote transportation technology innovation and further development of transportation.
This forum aims to provide a comprehensive understanding of the application platform of intelligent transportation and autonomous driving, and jointly discuss the application of AI technology in autonomous driving through the exchange and collision of views, focusing on the challenges and opportunities on the intelligent road of vehicles and shipping transportation, so as to promote exchanges and cooperation among all parties, promote the implementation of the intelligent transportation industry, and help the high-quality development of the economy.
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.
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Agenda of the Forum
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Forum Organizing Committee
Science Technology
Chairman of the forum - Zhang Yuanfang
Co-founder of City Light (Shenzhen) Unmanned Driving Co., Ltd., Chief Engineer of the Unmanned Intelligent City Service Research Center of Tsinghua University Research Institute in Shenzhen, has published more than 30 papers in international high-level journals or conferences, more than 100 core patents at home and abroad, and won more than 40 awards including top entrepreneurship and innovation competitions at home and abroad. Shenzhen high-level talent, assistant researcher of Imperial College London, Ph.D. from University of Technology Sydney, Ph.D. from Northwestern Polytechnical University. He is the main drafter of the first standard formulation of the "Safety Specification for Low-speed Unmanned Sweepers" in China, and the first batch of specially invited experts in the provincial strategic emerging industry base of Dongguan Water Town.
Science Technology
Forum moderator - Ren Shaoqing
Vice President of Intelligent Driving R&D of NIO, Chief Expert of Algorithm Development and Application, Ph.D. graduated from the Joint Training Program of USTC and Microsoft Research Asia.
Dr. Ren has many years of experience in both academia and industry. His Faster RCNN and ResNet are among the most important works in the field of object detection and deep learning networks in the past decade, respectively, and the latter has won the Best Paper Award at the International Conference on Computer Vision and Pattern Recognition (CVPR). He has been named Forbes Asia's 30 Under 30 list, selected as the 2022 Most Influential Scholar in the World in Artificial Intelligence and AI Young Chinese Scholars, and won the 2023 Future Science Prize - Mathematics and Computer Science Award. He led the team to develop and deliver NIO's latest-generation intelligent driving system, which realizes the global intelligent driving function of connecting highways, urban areas, parking, and battery swapping, and completes the mass production of the first self-developed function across continents in China.
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Invited speaker
Science Technology
Theme: From Open to More Open: Exploration and Practice of Autonomous R&D Based on Capillary Level Urban Roads
Speaker: Zhang Yuanfang
Summary of the report
The rapid development of autonomous driving over the years has brought about rapid changes in intelligent transportation, and the change of technology paradigm is inseparable from the support of basic scenarios. How to implement an effective autonomous driving scheme for capillary-level urban roads has increasingly become a vane to evaluate the technical level of the intelligent society, and a series of R&D exploration and practice are steadily progressing in the face of the demand for special unmanned vehicle operations with cleaning as the main purpose. The technology integration of single-vehicle intelligence and multi-vehicle intelligence has brought more and more valuable data precipitation and information expansion possibilities, so as to maximize operation efficiency and ensure personnel safety.
Science Technology
Topic: Large-scale simulation platform for L4 autonomous driving
Speaker: Xu Yunjing
He received his bachelor's degree from Nanjing University, and his master's and doctorate degrees from the University of Michigan. Since 2018, he has focused on the research and development of autonomous driving related technologies, and during his tenure as a senior R&D manager at Cruise, a L4 autonomous driving company in the United States, he was responsible for building a closed-loop data system for urban autonomous driving, and solving long-tail problems through automated problem analysis, data mining, data annotation, and model training. In 2021, he joined Didi's autonomous driving team as the chief engineer of the simulation platform, and is committed to building a L4 autonomous driving evaluation system based on large-scale simulation to promote the safety and reliability development of autonomous driving technology.
Summary of the report
In the development of Level 4 autonomous driving technology, large-scale simulation technology is particularly critical to meet the complex and diverse challenges of urban transportation to ensure the safety, comfort and efficiency of the system. The challenges of this technology mainly include the integration of real drive test data and highly simulated simulation data to ensure that the simulation is comprehensive and effective, and the construction of a computing platform that can efficiently handle concurrent tasks to improve simulation efficiency. This report showcases Didi's autonomous driving team's innovative practices in building a large-scale simulation platform, including the development of traffic participant behavior simulation, accurate sensor simulation, and large-scale heterogeneous computing technology. These efforts have significantly improved the reliability and development efficiency of autonomous driving, and provided solid technical support for the future of intelligent transportation.
Science Technology
Topic: Application of large models in end-to-end autonomous driving
Speaker: Li Hongyang
Head of OpenDriveLab, Shanghai Artificial Intelligence Laboratory, scientist. Research focuses on autonomous driving and embodied intelligence. He received his Ph.D. from the University of Chinese Hong Kong in 2019 and has worked in the industry for several years, working on the development of Level 2 assisted autonomous driving. In 2021, he established and led the OpenDriveLab team in Shanghai Artificial Intelligence Lab. The bird's-eye perception work BEVFormer was proposed, which won the "Top 100 Papers in AI" award in 2022 and was recognized by Jensen Huang, CEO of NVIDIA, and Professor Shashua, CEO of Mobileye, at the Consumer Electronics Show (CES) in 2024. UniAD, an end-to-end autonomous driving project he led, won the IEEE CVPR 2023 Best Paper Award. UniAD has had a significant impact in both academia and industry, including the recent launch of the product by Tesla to customers in its FSD V12 release. He is the Distinguished Area Chair of NeurIPS 2023 and a senior member of IEEE. For more information, please visit https://opendrivelab.com.
Summary of the report
End-to-end autonomous driving (E2E AD) has recently become very popular, and the main advantage of E2E AD over traditional module-based designs is the ability to globally optimize across the various sub-modules of the system and to have a unified goal for planning and control tasks. Some of the industry's leading companies have also adopted this end-to-end philosophy and launched products to their customers. In this discussion, we will begin by reviewing the key milestones and roadmap of E2E AD, including the UniAD prototype work proposed by OpenDriveLab, which was recognized as the best paper for IEEE CVPR 2023. Next, we will discuss the main challenges that the community is currently facing (e.g., generalization capabilities, world modeling, etc.). With the rise of foundational models, we also discuss how to leverage large language model (LLM) and visual language model (VLM) technologies, as well as how to extract general knowledge from experienced human experts. The discussion will conclude with a future outlook for building common and intelligent systems in a wide range of downstream applications in the coming years.
Science Technology
Theme: From Vehicle-to-Scene Intelligence: Thinking and Practice of Autonomous Valet Parking Technology
Speaker: Yang Ming
Distinguished professor of Shanghai Jiao Tong University, doctoral supervisor, national Baosteel outstanding teacher, national "Ten Thousand Talents Program" scientific and technological innovation leading talent. He received his Ph.D. from Tsinghua University in 2003, worked as a postdoctoral fellow at the French National Institute of Information and Automation from 2003 to 2005, returned to China in 2005 to teach at Shanghai Jiao Tong University, and successively served as Secretary of the Party General Branch/Head of the Department of Automation, Secretary of the Party Committee and Acting Dean of the Joint Institute, and is currently the Secretary of the Party Committee of the United College, the Director of the Intelligent Connected Electric Vehicle Innovation Center of the University, the Deputy Director of the Teaching Committee of the Chinese Society of Automation, the Director of the Chinese Society of Artificial Intelligence, the Deputy Director of the Intelligent Robot Special Committee, and the IEEE Associate Editor-in-Chief of IROS-CPRB, Editorial Board Member of IEEE Transactions on Intelligent Vehicles and IEEE Transactions on Intelligent Transportation Systems. In recent years, he has published more than 200 papers in academic journals at home and abroad, obtained more than 50 national invention patents, and guided students to obtain excellent papers at top conferences at home and abroad, such as IEEE Intelligent Vehicle Symposium and China Intelligent Robot Conference. As the person in charge, he has won the first prize of Shanghai Technological Invention Award, the first prize of Shanghai Teaching Achievement Award, and the Ministry of Education Technological Invention Award.
Summary of the report
Traffic travel is inseparable from parking, and with the progress of society, the phenomenon of "parking difficulty" is becoming more and more severe. Autonomous valet parking technology can liberate drivers and passengers from the parking process, improve efficiency and ensure safety, and is one of the most important and feasible means to solve the parking problem. At this stage, autonomous valet parking is mainly based on vehicle-end intelligence, but because it only considers its own needs, it cannot macroscopically consider the parking spaces and road conditions in the parking lot, and there are perception blind spots. In recent work, many R&D institutions have upgraded vehicle-end intelligence to field-side intelligence, that is, remote control of vehicles through sensors and controllers installed in parking lots, realize full coverage of environmental perception and vehicle positioning, and schedule and control multiple vehicles at the same time, so as to realize the global optimal scheduling in the parking lot and solve the technical limitations of vehicle-end intelligence.
Science Technology
Theme: High-speed rail development vision and design concept
Speaker: Hu Qizhou
Graduated from Southeast University, he worked as a postdoctoral fellow at Tsinghua University, and is now the director and doctoral supervisor of the Institute of High-speed Railway Science of Nanjing University of Science and Technology. He has been engaged in traffic operation management research for a long time, and has published more than 50 papers in academic journals such as "Transportation Research Part D" and "Transportation Research Part A", won 1 excellent science popularization work award of the Ministry of Science and Technology of the People's Republic of China, 10 provincial and ministerial awards, and since 2011, he has served as the international journal "International journal for traffic and". Member of the Editorial Board of Transport Engineering.
Summary of the report
As an important part of the transportation power, high-speed rail has become the mainstream development mode of the world's transportation industry with its safe, reliable, fast and comfortable, and large-capacity transportation mode, which has a certain impact on the country's economic, social and global competitiveness, and the world has also entered the era of high-speed rail. But with the advent of the post-high-speed rail era, the speed of high-speed rail no longer meets people's requirements, and people hope that faster railways will appear. As a result, ultra-high-speed railway has become a research hotspot in various countries. Based on the interpretation of the development trend of high-speed railways, this report analyzes the feasibility of high-speed railways theoretically, the reliability and operability of ultra-high-speed railways from a technical perspective, and the design concept of high-speed trains.
Science Technology
Topic: Visual Language Large Models and Mapless Autonomous Driving
Speaker: Zhao Xing
Assistant Professor, Institute for Interdisciplinary Information Sciences, Tsinghua University. He received his Ph.D. from MIT and worked as a research scientist at Waymo, Google's autonomous vehicle project. The research covers the entire algorithm stack for autonomous driving, as well as multimodal machine learning. A series of framework-based work in autonomous driving perception and prediction is proposed, which is used or used by most companies in the industry. Nominated for the CoRL 2023 Best System Paper Award, the ICCP Best Paper Award, and Forbes China 30Under30.
Summary of the report
With the application of advanced assisted driving, the scene understanding ability of autonomous driving has become particularly important, and the large model based on vision and visual language reflects excellent generalization ability. This report will describe two aspects of work: (1) a new map construction paradigm based on navigation maps, memory networks, neural radiation fields, etc., which can be used to replace traditional high-precision maps and online map perception methods. (2) Based on the visual language model, it helps autonomous driving to achieve complex and long-tail scene understanding.
Science Technology
Panelist: Wang Naiyan
He was the CTO of TuSimple China, where he was responsible for the research and development of autonomous truck technology, and led the team to complete China's first fully unmanned autonomous truck demonstration on an open expressway. He received his bachelor's degree from Zhejiang University in 2011 and his Ph.D. degree from the Hong Kong University of Science and Technology in 2015. He was also selected for the 2014 Google PhD Fellow Program (only four people from China were selected). He has been ranked among the best in international data mining (KDD Cup/Kaggle Challenge) and computer vision (ImageNet LSVRC) competitions for many times, and has published more than 70 papers in top conferences and journals on computer vision and machine learning, with more than 20,000 citations.
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Topics and guests of the roundtable dialogue
Conversation topics
Moderator: Ren Shaoqing, Vice President of Intelligent Driving R&D of NIO, Chief Expert of Algorithm Development and Application
Topic of dialogue: The current situation and prospects of autonomous driving in the past ten years
Panelist: Zhang Yuanfang, Co-founder of City Light (Shenzhen) Unmanned Driving Co., Ltd., Chief Engineer of the Unmanned Intelligent City Service Research Center of Tsinghua University Research Institute in Shenzhen
Xu Yunjing is the chief engineer of Didi autonomous driving
Yang Ming is a distinguished professor at Shanghai Jiao Tong University
Hu Qizhou is the director of the Institute of High-speed Railway Science and Technology of Nanjing University of Science and Technology
Zhao Xing is an assistant professor at the Institute for Interdisciplinary Information Sciences, Tsinghua University
Naiyan Wang, CTO of TuSimple Future China