The 2023 Global Machine Learning Technology Conference will be held grandly in Beijing in October, a two-way trip with AGI

The 2023 Global Machine Learning Technology Conference (ML-Summit), which has attracted much attention from the industry, will be held grandly at the Westin Jinmao Hotel in Beijing on October 20-21 ! This conference was jointly hosted by Boolan and CSDN. Adhering to the purpose of "global experts, excellent wisdom", nearly 50 technical experts and industry application experts in the field of artificial intelligence and machine learning were specially invited to meet with 1000+ people from the Internet, e-commerce, Elite attendees from many industries, including entertainment, finance, smart cars, communications, Internet of Things, medical care, education, etc., discussed cutting-edge developments and industry best practices in the fields of large language models (LLM) and artificial intelligence.

• Official website of the conference: ml-summit.org (You can also click "Read the original text" at the end of the article to go directly, and you can also apply to receive the full set of PPTs for the conference)

Embracing the era of AGI change

The slogan of this conference is "Embracing the Era of AGI Transformation", focusing on 12 major themes such as the latest developments and application practices in the field of machine learning, including GPT and large model technology evolution, large model system engineering practice, large model application development practice, AIGC and Machine vision, AIGC product innovation exploration and practice, large model empowered software development and transformation, large model operation and maintenance and large model infrastructure, etc.

Speakers

Kenneth Stanley,   former distinguished researcher at OpenAI, author of "Why Greatness Cannot Be Planned", is a representative expert in the field of global innovative thinking and cutting-edge technology, artificial intelligence scientist, and researcher at OpenAI. He was a professor at the University of Central Florida and was deeply involved in the field of machine learning. He published more than 80 professional papers, 10 of which won best paper awards, and was often invited to give lectures around the world. He was also a founding member of the Uber Artificial Intelligence Laboratory and has outstanding influence in the industry.

Speech topic: Great unplanned innovations in the field of AI

Li Zhixing   is the technical vice president of Zhipu AI Large Model Division and a postdoctoral fellow at Tsinghua University. He has successively served as the head of the knowledge question and answer algorithm of Alibaba Artificial Intelligence Laboratory and the AI ​​algorithm director of Manbang Group. Research directions include artificial intelligence, machine learning, and natural language processing. Led the construction of the knowledge question and answer engine of Alibaba’s first smart hardware device, Tmall Genie, and the construction of the AI ​​platform of Manbang Group. He is the principal researcher of XLIKE, the European Union's Seventh Framework International Cooperation Project, and the research backbone of three national key R&D plans. He has hosted and completed one national-level project and three provincial and ministerial-level projects.

Speech topic: ChatGLM: A preliminary study on large-scale cognitive models and applications

Chen Weipeng   is the co-founder of Baichuan Intelligence and the technical leader of large language models. Graduated from Harbin Institute of Technology in 2012 and served as the general manager of Sogou search R&D, responsible for the research and development of Sogou's general/vertical search and recommendation systems. Formerly the technical VP of Soul, he was responsible for building algorithm capabilities and promoting the application and implementation of content understanding, recommendation technology and AIGC technology in social scenarios.

Speech topic: Baichuan Intelligent’s road to research and development of large language models

Zhang Yizhao is the former deputy director of Microsoft Research Asia. He graduated from MIT and is an entrepreneur in the AI+ medical field. He is the former deputy director of Microsoft Research Asia. He is responsible for the technology strategy department and guides the implementation of the research institute's technology in actual scenarios. In the School of Engineering, he led the team to collaboratively develop many core products of Windows and Office, and established a multi-disciplinary technology product incubation team. He was a co-founder of Nuance Communications' corporate research department. Led researchers to develop the world's first open Japanese speech recognition system. He developed a new speech recognition algorithm at MIT's Lincoln Laboratory, invented a new circuit optimization technology at Toshiba's ULSI Research Center, and conducted research on pattern recognition at the General Electric Research Institute.

Speech Topic: Prospects of Maintaining Health with Machine Learning

Hu Luhui   Seeking AI CTO & Co-CEO & Co-founder, former chief engineering leader of Meta, won 10 Meta AI patent applications; former vice president of JD.com and chief architect and CTO of Huawei America Research; early worked at the headquarters of Amazon and Microsoft in the United States For more than ten years, he has led the team to engage in data cloud and AI; he has more than 30 US patents and applications and top international VLDB papers.

Speech topic: Multi-modal large models for machine vision

Zhang Junlin   is the head of new technology research and development of Sina Weibo. Director of the Chinese Information Society of China, Ph.D. of the Institute of Software, Chinese Academy of Sciences. Currently serves as the head of technology research and development for Sina Weibo. Before that, he served as a senior technical expert at Alibaba, responsible for the new technology team. The author of "This is the Search Engine: Detailed Explanation of Core Technology" and "Big Data Rizhilu: Architecture and Algorithms". Currently, his main research and development interests focus on recommendation systems and natural language processing.

Wu Chenglin   is the founder and CEO of Deep Intelligence. He was the chief scientist of Benniao Social (B+ round), leading the construction of AI middle platform, content understanding and distribution system, and global enterprise knowledge graph; he was the youngest T3.3 senior researcher at Tencent, leading the design and implementation of billion-level Users, large-scale recommendation systems (feeds streams) with hundreds of billions of data, search engines, knowledge graphs, natural language understanding, image understanding and many other top projects, published in the top conference KDD 2018, won Tencent's double five-star (1/~500 ) and more than ten awards, the youngest member of the department expert group (15/4000+); served in Huawei's 2012 laboratory and won the top ten new employees, and is the youngest technical expert in the team. In the open source community, many open source projects such as MetaGPT he created have repeatedly topped the Github hot list in the world. He has published papers in TPAMI, KDD, CVPR, and ACL, and won world championships in top competitions such as KDD Cup 2021, NeurIPS 2019 AutoDL, and NeurIPS 2019 AutoWSL. In addition, he has also won honors such as Forbes 30 Under 30 and Hurun 30 Entrepreneurial Leaders Under 30.

Speech Topic: MetaGPT Technical Practice for Building Exclusive AI Agent

Xie Pengjun   is a senior algorithm expert at the Language Technology Laboratory of DAMO Academy. He has worked in Taobao search, e-commerce knowledge graph, Damo Academy NLP and other teams for more than 10 years. Currently responsible for semantic understanding and search technology based on large models at DAMO Academy. He led the team to publish more than 50 papers at ACL, EMNLP, NAACL and other conferences, and won the ACL 2023 outstanding paper, and won multiple championships in MS Marco, SemEval, and TREC. Speech topic: Generative search technology and applications under the LLM paradigm

Michael Wong   is Technical VP of Codeplay, Chairman of the C++ Embedded Development Committee SG14 and Machine Learning Committee SG19. He also serves as Chairman of the C++ Language Direction Evolution Committee, Vice President of R&D at Codeplay, and Head of the Canadian Delegation of the C++ Standards Committee. Michael has extensive work experience in the fields of C++ parallel computing, high-performance computing, and machine learning. He led the formulation of the C++ heterogeneous programming language (SYCL) standard for GPU application development. He has in-depth research and insights into the underlying performance optimization of Tensorflow. . His specific work covers parallel programming, neural networks, computer vision, autonomous driving and other fields. Michael used to be a senior technical expert at IBM, leading the development of IBM XL C++ compiler and XL C compiler.

Speech topic: Using SYCL to implement neural network acceleration on RISC-V platform

Luan Xiaofan Partner and Technical Director of Zilliz

Speech topic: The road to innovation and optimization of tens of billions of vector database architectures

Li Bo , VP of 51job Technology

Speech topic: Exploration of large models in the field of intelligent personnel

Tao Jianrong (Fengtian) CTO of NetEase Intelligent Enterprise Game Department

Speech topic: Application and trends of AIGC in the game industry

Wang Jianqiang, Chief Applied Science Manager, Microsoft

Speech Topic: Current Research and Challenges of Retrieval Augmentation for Large Models (RAG)

Song Guyang, technical expert of Ant Group

Speech topic: Ray: Distributed computing engine architecture and practice in the era of large models

Huang Shiyu, Director of OpenRL Lab, Fourth Paradigm Open Source Reinforcement Learning

Speech topic: OpenRL: General Reinforcement Learning Training Framework

Tian Haowei eBay Senior Technical Expert

Speech topic: Large model reasoning in eBay’s architecture practice

Yang Wenhai ByteDance - Head of Data Platform Visualization

Speech topic: Data visualization practice and exploration based on large models

Chen Yirong, Sina Weibo Machine Learning Algorithm Expert

Speech topic: Application of AIGC technology in Sina Weibo

Yang Zhenyu OPPO Xiaobu Assistant Chief Researcher

Topic of speech: Exploration and practice of AI assistant in the era of large models

Hu Yichuan , CTO of Laiye Technology

Speech topic: From RPA code generation to digital workforce

Lu Jianhui , Microsoft Senior Cloud Technology Evangelist

Speech topic: AIOps driven by multiple data sources

Shi Wenqi, Senior Engineer, Huawei MindSpore

Speech topic: MindSpore ultra-large-scale AI practice

Sun Qiming, head of the intelligent marketing department of 58 TEG-AI Lab in the same city

Speech topic: Application practice of large model of local life service scene

Fang Hanyin, senior algorithm engineer at Bilibili

Topic of speech: Bilibili large model and technical practice of search AI assistant

Zhao Shenyang BentoML Software Engineer

Speech Topic: OpenLLM: Implementation Practice of Open Source Large Language Model

Zhang Luyu Founder of Dify.AI

Speech topic: Technical practice of open source LLMOps platform RAG

For more details about the guests, please consult the official website: www.ml-summit.org

Technical Product Committee

The Technical Production Committee of the 2023 Global Machine Learning Technology Conference is composed of twelve senior experts in the AI ​​field. It provides technical guidance and quality review for the speeches and sharing content of each topic of the conference. The experts on the production committee have a deep background and rich industrial experience in the fields of machine learning and AI, including large models. They provide suggestions for the content setting and guest selection of the conference, ensuring the industry-leading level and height of the conference content.

Conference Highlights

• Specially invited front-line experts from industry flagship companies lead in-depth sharing

The conference invites senior technical experts from the field of artificial intelligence and machine learning at home and abroad, including OpenAI, Zhipu AI, Baichuan Intelligence, Microsoft, Alibaba, Tencent, Huawei, Baidu, NetEase, eBay, OPPO and many other industry first-line flagship companies, bringing together many AI technology authority.

• Insight into global development trends and capture cutting-edge practical information

Through nearly 50 keynote speeches, interactive discussions, round-table forums and other forms, the conference provides insights into the forward-looking development trends in the global machine learning field, multi-faceted brainstorming, in-depth analysis of the best applications in the AI ​​field, and provides cutting-edge practical guidance for enterprises to implement.

• Open up new opportunities for business cooperation and gather potential customer base

The conference brought together more than 1,000 corporate decision-makers, corporate founders, technical directors, and R&D directors from mainstream Internet and IT companies. They communicated with corporate decision-makers on-site and established in-depth connections, expanded business contacts, gathered potential customers, and established long-term cooperation.

• Build a professional communication platform in the AI ​​field and provide excellent opportunities for brand communication

The conference will invite users from the Internet, e-commerce, energy, medical care, enterprise applications, communication electronics, finance, intelligent manufacturing and other fields to participate in the conference. It is expected to cover 300,000+ mainstream Internet IT people online and offline, and is a good way to convey the company's brand Excellent opportunity for value.

About the Global Machine Learning Technology Conference

The Global Machine Learning Technology Conference (ML-Summit) was launched in 2017 and is an important technology exchange and communication platform in the artificial intelligence and machine learning industry. Historical guests of the conference include: Michael I. Jordan, the father of machine learning, Jürgen Schmidhuber, the father of LSTM, Lukasz Kaiser, co-inventor of Transformer and OpenAI research scientist, Gary Bradski, founder of OpenCV, Yang Hongxia, leader of ByteDance large model technology, and Alibaba Damo Huang Fei, director of the language laboratory of the institute, and others have become a technology benchmark conference in the artificial intelligence industry. At the 2023 Global Machine Learning Technology Conference, let us embrace the era of AGI change!

Get the full set of PPT materials for the conference + selected videos of large models

2023 Global Machine Learning Technology Conference

Date: October 20-21 

Location: The Westin Jinmao Hotel, Beijing

Website: www.ml-summit.org

Click to read the original text and browse the official website of the conference