The objective is to accelerate the artificial intelligence (AI) business in companies centered on the deep learning business, as well as in Japan and China and their neighboring countries, which are focused on research and human resources related to deep learning. (1) AI human resource development, academic meetings, academic lectures, seminars, etc.

(2) Information exchange and collaboration with related organizations

(3) AI solution consulting, promotion of AI utilization

(4) Exchange and cooperation between Japan and China and globalization

(6) Other businesses necessary to achieve the purpose of this corporation

(6) The business under the preceding paragraph shall be conducted in Japan and overseas.

We will carry out activities as the following five pillars.

(1) AI human resource development

We will hold various seminars and workshops for researchers and students who will support and support the AI ​​industry in the future.

(2) AI industry employment support

For those who want to find employment in the AI ​​industry and those who want to study AI technology, we will support employment through company briefing sessions.

(3) AI solution consulting

(4) Promotion of AI utilization

(5) Exchange and cooperation between Japan and China and globalization

We will promote cooperation with related organizations in Japan and China and their neighboring countries. We will organize information such as news about AI, trends in the AI ​​industry, trends in AI technology development, cases of utilizing AI products and services, interviews with experts, etc., and provide it to our members.

For the sound development of the industry, such as promoting the utilization of industry, human resource development, making recommendations to public institutions and industries, international cooperation, dialogue with society, etc., led by companies and experts with deep learning as the core of their business. We will carry out the necessary activities

About the board

The board consists of the president, directors, auditors, and special advisors.

About the committee

Industrial Utilization Promotion Committee

We will promote the utilization of deep learning in industry by collecting cases, extracting issues, and disseminating information such as symposiums and guidebooks.

Public policy committee

We will engage in international collaboration and dialogue with the society on which deep learning will be implemented. We will cooperate with various organizations to disseminate information to society as an association.

Human Resource Development Committee

We will examine the skill set for using deep learning and formulate a syllabus for the JCDLA and CJDLA exams. We will test, confirm, organize the test questions, and carry out the test.

 

Member merit (excerpt)

・ You can use association certification (logo mark) and association membership sign.

-You can get the latest information and network through member-only events, member-only pages, and access to the internal Slack of the association.

・ By participating in the committee, you can make industry-university collaboration activities and make institutional recommendations for government agencies.

・ You can use advertising space for various media issued by the association etc.

* Member benefits vary depending on type and rank. Please contact us for details.

This association aims to improve the industrial competitiveness of Japan and China through technologies centered on deep learning.

Therefore, companies and experts with deep learning as the core of the business will play a central role in promoting the sound development of industry, such as promotion of industrial utilization, human resource development, recommendations to public institutions and industries, international collaboration, and dialogue with society. We will carry out the necessary activities for

This association aims to improve the industrial competitiveness of Japan and China through technologies centered on deep learning.

Therefore, companies and experts with deep learning as the core of the business will play a central role in promoting the sound development of industry, such as promotion of industrial utilization, human resource development, recommendations to public institutions and industries, international collaboration, and dialogue with society. We will carry out the necessary activities for

 

Association member

A company whose core is the deep learning business, and an expert who is focused on research and personnel training related to deep learning ・ Approval is required after the recommendation of two or more regular members + approval of the board of directors.

Operates the association as a director and committee member and performs activities such as attending general meetings (with voting rights).

* Regular members are listed in alphabetical order or alphabetical order, and supporting members are listed in the order of enrollment.

* The * next to the company name represents the member at the time of establishment

Regular member companies

ABEJA *

Liaro

 Nvidia LLC *

Regular member Expert

Country dragon

 

GUOLONG of the Japan-China Deep Learning Association Doctor of Computer Science at Cambridge University, Professor of Top Scientist, Top Research Institute, LCFI Lab, UK, Oxford University Professor of ERP consulting, cloud technology, big data, blockchain and artificial intelligence. Research direction: multimedia technology, deep learning, machine learning, computer vision, natural language processing, recommended system, machine learning, data science, data mining, etc.Artificial Intelligence Researcher, Chinese Academy of Science JSAI Artificial Intelligence Society Full member, IEEE member, SIGIR member, CAAI Chinese Artificial Intelligence Association member, AAA1 International Artificial Intelligence Association member, British Artificial Intelligence China British Artificial Intelligence Association member ACM member. AI, IoT, RPA, ICT, 5G, 3D, AR, VR, iCLIP, core industrial software, core algorithm cutting edge technology Education / Medical / Finance, Manufacturing, Logistics, Agriculture, Retail, Manufacturing, Transportation, Sports, Aerospace , Advertising, IOT, ICT and other industries

IEEE, NIPS, ICML, COLT, CVPR, ICCV, ECVC, IJCAI, AAAI, UAI, KDD, SIGIR, WWW, ACL, PAMI, IJCV, JMLR and AIJ have been published more than 100 times. A Chinese-British born in Japan.

 

 

YUHONGHONG

Director of Japan-China Deep Learning Association, Doctor of Computer Science, Harvard University, Researcher of Artificial Intelligence, Scholar of Chinese Academy of Sciences JSAI Artificial Intelligence Society full member, IEEE member, SIGIR member, CAAI Chinese Artificial Intelligence Association member, AAA1 International Artificial Intelligence Association member, British Artificial Intelligence China A member of ACM, a member of the British Association for Artificial Intelligence, and his main research fields are ERP consulting, cloud technology, big data, blockchain, artificial intelligence specialists computer vision, multimedia technology, machine learning, etc. AI, IoT, RPA, OCR-AI, ERP, cloud, big data, blockchain, ICT, 5G, 3D, AR, VR, iCLIP, core industrial software, core algorithms, neutrinos, state-of-the-art technology for government / local government Education / Medical / Healthcare, Finance, Manufacturing, Logistics, Communications / Broadcasting, Construction / Real Estate, Electricity / Gas / Water, Networks, Pharmaceuticals, Agriculture, Retail, Manufacturing, Transportation, Sports, Aerospace, Advertising, IOT, ICT and Other industries

IEEE, NIPS, ICML, COLT, CVPR, ICCV, ECVC, IJCAI, AAAI, UAI, KDD, SIGIR, WWW, ACL, PAMI, IJCV, JMLR, AIJ have been published 100 times or more.

 

Sho Sho

Researcher Google / Google Brain

Researcher at Google Brain. Specializes in deep learning, reinforcement learning, robotics, and Bayesian machine learning. Completed a doctoral course at the University of Cambridge and Max Planck Institute, Ph.D. (machine learning). Geoffrey Hinton is a graduate professor of engineering from the University of Toronto. Visiting researcher at the University of Tokyo (Matsuo Lab). CoRL 2019 Best Paper Award, Google Specialized Research Award. The research results were featured in the Google Research Blogpost, MIT Technology Review, and so on. A Japanese Canadian born in Japan.

 

 

Takayuki Okaya

Professor, Graduate School of Information Sciences, Tohoku University

Completed the doctoral course at the Department of Numerical Engineering, Graduate School of Engineering, the University of Tokyo in 1999, Ph.D. in engineering. Currently a professor at the Graduate School of Information Sciences, Tohoku University. Since 2016, he has also served as the team leader of the RIKEN Center for Innovative Intelligence Research. Specializes in perceptual information processing and intelligent robotics (computer vision).

The main book "Deep Learning" (Kodansha 2015) is positioned as a textbook for AI learning.

http://www.vision.is.tohoku.ac.jp/jp/home/

 

Tetsuya Ogata

Professor, Department of Expression Engineering, Waseda University

Graduated from Department of Mechanical Engineering, Faculty of Science and Engineering, Waseda University in 1993. Since 2012, he has been an assistant professor at the same university, a visiting lecturer / associate professor at the Humanoid Research Institute, a researcher at the Brain Science Institute, RIKEN, and a lecturer / associate professor at the Graduate School of Informatics, Kyoto University. He has served as a board member of the Robotics Society of Japan, a member of the Artificial Intelligence Society, and a member of the Society of Instrument and Control Engineers. Since 2017, he has also served as a specific fellow of AI Research Center, National Institute of Advanced Industrial Science and Technology. Served as a technical advisor to Exa Wizards Co., Ltd.

https://ogata-lab.jp/ja/

 

Taichi Kakinuma

Representative Partner Lawyer, STORIA Law Office

1997 Graduated from Faculty of Law, Kyoto University. 2000 Registered as a lawyer. In 2015, he co-founded a STORIA law firm that focuses on start-up support, and continues to the present. Specializes in startup legal affairs and data / AI legal affairs. Currently, he is supporting many AI startups of various genres (medical, manufacturing, platform, etc.) as a corporate lawyer. Held and participated in numerous seminars on AI development, use, and responsibility. A member of the “AI / Data Contract Guidelines” Review Committee of the Ministry of Economy, Trade and Industry (-2018.3).

https://storialaw.jp/lawyer/3041

 

 

Yutaka Matsuo

Professor, Department of Artificial Engineering Research, Graduate School of Engineering, The University of Tokyo

Graduated from the Department of Electronic Information Engineering, Faculty of Engineering, The University of Tokyo in 1997. Completed the doctoral course at the same graduate school in 2002. Doctor (Engineering). Since the same year, he has been a researcher at AIST. Since 2005, he has been a visiting researcher at Stanford University. Current position since 2019. Specializes in artificial intelligence, web mining, and big data analysis. Previously served as editorial chairperson (2012-2014) and ethics chairperson (2014-2018) at Artificial Intelligence Society. In 2017, he became the representative director of Japan Deep Learning Association. His books include "Is Artificial Intelligence Beyond Humans? Beyond Deep Learning" (KADOKAWA).

https://weblab.t.u-tokyo.ac.jp/

 

Hiroshi Maruyama

Preferred Networks PFN Fellow

Completed the master's course at the Graduate School of Science and Engineering at Tokyo Institute of Technology in 1983. In the same year, joined IBM Japan, Ltd. Engaged in research on artificial intelligence, natural language processing, machine translation, etc. 1995 Doctoral degree from Kyoto University. Visiting Associate Professor, Graduate School of Information Science and Technology, Tokyo Institute of Technology, Director, Tokyo Research Laboratories, IBM Japan Ltd., Deputy Director, Digital Platform Development Division, Canon Inc., Professor, Institute of Statistical Mathematics, Institute for Information and Systems Research 2016 Appointed Chief Strategy Officer of Preferred Networks, Inc. Current position since April 2018.

 

Supporting member

Companies and organizations that support the purpose of this association and are enthusiastic about social implementation of deep learning and recruitment of human resources.

Performs activities such as directors, advisors, promotion of candidate candidates, and attendance at general meetings (no voting rights).

Huawei Technology Co., Ltd.

 Google LLC

NTT Docomo, Inc.

Deloitte Touche Tohmatsu LLC

About qualification test
• Examination / qualification summary
• Exam schedule
• Changes in the number of examinees
• Implementation report
• About JCDLA test
• Understand the deep learning theory and certify that you have the ability and knowledge to select and implement an appropriate method.
Qualification for examination JCDLA certification program (* 1) Completed within two years of the exam date (* 2)

Implementation overview Test time: 120 minutes
Knowledge problem (multiple choice, about 100 questions)
Take the test at designated test sites in various locations
Select the desired venue when applying for the test venue (* 3)
Scope of questions Questions from the syllabus at the completion level of the JCDLA certification program (* 4)
Examination fee General: 33,000 yen (tax included) (* 5)
Student: 22,000 yen (tax included)
Member: 27,500 yen (tax included) (* 6)
• Click here for details of the annotation (*)
• About CJDLA qualification
• Have a basic knowledge of deep learning, determine an appropriate usage policy, and test whether you have the ability or knowledge to use the business.
Examination qualification No restrictions
Implementation overview Test time: 120 minutes
Knowledge problem (multiple choice, 220 questions)
Conduct online (take an examination at home)
Question range Question from syllabus
Examination fee general: 12,000 yen (excluding tax)
Student: 5,000 yen (excluding tax)
* Only 2020 # 2 General: 6,000 yen (tax excluded) Students: 2,500 yen (tax excluded)
• About MIT University Exam
• Understand the deep learning theory and certify that you have the ability and knowledge to select and implement an appropriate method.
Eligibility to take the exam Must have completed the MIT certification program (* 1) within the past two years on the exam date (* 2)

Implementation overview Test time: 120 minutes
Knowledge problem (multiple choice, about 100 questions)
Take the test at designated test sites in various locations
Select the desired venue when applying for the test venue (* 3)
Scope of questions Questions from the syllabus at the MIT certification program completion level (* 4)
Examination fee General: 330,000 yen (tax included) (* 5)
Student: 220,000 yen (tax included)
Member: 270,500 yen (tax included) (* 6)
• Click here for details of the annotation (*)
• Cambridge University Qualifications
• Have a basic knowledge of deep learning, determine an appropriate usage policy, and test whether you have the ability or knowledge to use the business.
Examination qualification No restrictions
Implementation overview Test time: 120 minutes
Knowledge problem (multiple choice, 220 questions)
Conduct online (take an examination at home)
Question range Question from syllabus
Examination fee General: 1200,000 yen (excluding tax)
Student: 500,000 yen (excluding tax)
* Only for 2020 # 2 General: 60,000 yen (excluding tax) Student: 20,500 yen (excluding tax)
• About Oxford University Certification
• Understand the deep learning theory and certify that you have the ability and knowledge to select and implement an appropriate method.
Qualification for Examination Completed the Oxford University Accreditation Program (* 1) within the past two years on the exam date (* 2).

Implementation overview Test time: 120 minutes
Knowledge problem (multiple choice, about 100 questions)
Take the test at designated test sites in various locations
Select the desired venue when applying for the test venue (* 3)
Scope of questions Questions from the syllabus at the completion level of the Oxford University Accreditation Program (* 4)
Examination fee General: 330,000 yen (tax included) (* 5)
Student: 220,000 yen (tax included)
Member: 270,500 yen (tax included) (* 6)
• Click here for details of the annotation (*)


Click here for inquiries and applications

Auditor Tetsuzo Ota New Japan Audit Corporation
Chairman Kuniryu Professor, Cambridge University / LCFI researcher
President and CTO, HOCIntelligent Technology
Director in Hong Kong, PhD in Harvard Graduate School of Engineering, enrolled in NTT DATA for more than 20 years
President and CEO of HOC Intelligent Technology
Edwin Catmaru ACM Turing Award
Professor, MIT University / Google / AI Research Director
Oxford University Doctor Professor /
Professor, University of Cambridge
Professor, Tsinghua University
Professor, The University of Tokyo
Harvard Graduate School of Engineering / Amazon AI Research Director / Alibaba Artificial Intelligence
MIT University PhD Professor / Chief AIlab Research Director
Special Advisor Pat Hanrahan IEEE Chief Executive Officer / Microsoft AI Research Director
ACM A.M.Turing Award
Secretary General Tahara Steel
Date of establishment 2020
Location 577-0831 4-9-35, Shundecho, Higashiosaka-shi, Osaka TAHARA Building 2F
URL www.jcdla.org www.cjdla.com

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Partner NEKKYOAI (https://www.nekkyo.org)

Xinhua China
Alibaba Group
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Contact Tel: 81 080-2432-1609,81 090-87479395 (Weekdays 10: 00-17: 00 / Exam day 11: 00-16: 00)
Mail: info@jcdla.org
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Tel: 86 15358411774 (Weekdays 10: 00-17: 00 / Training day 11: 00-16: 00
Mail: info@cjdla.com
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