Alibaba Cloud
Global AI Innovation Challenge

Win a Total of $116,000 in Prizes with Your Innovative AI Projects!

Challenge Overview
As cloud and AI technologies are shaping all industries globally and driving numerous innovations, Alibaba Cloud has launched the Machine Learning Platform for AI (PAI) service to empower AI developers and innovators by lowering technical barriers and development costs. The Alibaba Cloud Global AI Innovation Challenge is an open competition for global AI developers, researchers, startups and solution providers to make and/or enhance their products or projects based on machine learning using PAI.
Open to All AI Developers and Innovators
$50,000+ Computing Combability and Exclusive Resources for Participants
$116,000 in Total Worth in Prizes for Winners

Prizes and Benefits

The winners of the challenge will share $55,000 USD cash prizes and $61,000 cloud credits in total.

1st Place: 1 Team
$20,000 Cash Prize (Pre-Tax)
$5,000 Alibaba Cloud Credits
$5,000 PAI Credits
2nd Place: 2 Teams
$10,000 Cash Prize (Pre-Tax)
$4,000 Alibaba Cloud Credits
$4,000 Alibaba Cloud Credits
3rd Place: 3 Teams
$5,000 Cash Prize (Pre-Tax)
$2,500 Alibaba Cloud Credits
$2,500 PAI Credits
Innovation Award: 10 Teams
$1,000 Alibaba Cloud Credits
$1,000 PAI Credits
In addition, all winners will also get the following benefits:
Award Certificates
Priority to become Alibaba Cloud MVP or Student Ambassador
Global Exposure

Schedule

  • 2020.9.17
    Challenge starts, registration opens
  • 2020.11.1
    Deadline for 1st round submission
  • 2020.11.4
    1st round results announced; 2nd round starts
  • 2020.11.22
    Deadline for final round submission
  • 2020.12.4
    Final results announced

How to Join the Challenge

The challenge is open to anyone who is using machine learning for their projects. Please follow the steps to register to the challenge and claim your benefits (see step-by-step guide).

Create an account >

Sign up to Alibaba Cloud for free and complete your basic information

Register for the Challenge >

Please register for the challenge on Tianchi

Submit Your Project for the 1st Round >

The deadline for the 1st round submission is Nov 1

Submit Your Project for the Final Round >

If you enter the final round, please submit your project by Nov 22

Requirements for registration
  • Participants must have an account on Alibaba Cloud International Site before registering for the challenge.
  • In order to get PAI coupon and start using PAI, you are required to add a valid payment method to your account.
  • A team may consist one or more participants. The coupon and award will be only given to one account for a team and cannot be seperated.

Tasks and Topics

The challenge is open to all developers, startups and researchers, and its tasks are: 1) use machine learning in your products/projects; and 2) use Alibaba Cloud Machine Learning Platform for AI (PAI) to train your models (assessed in the final round only). The challenge welcomes innovative projects powered by machine learning in any field or industries. The following topics are for reference, and other topics are also encouraged. The choice of topic/industry will have no impact on your results.

AI + Internet Applications
E-commerce
Short-form Videos
Social Media
Online Education
AI + Production
Healthcare
Energy
Transportation
AI for Public Good
Wildlife Conservation
Pollution Prevention
Caregiving

Judges

Selina Yuan
Vice President of Alibaba Group, President for International Business, Alibaba Cloud Intelligence

Selina Yuan leads the international division of Alibaba Cloud Intelligence Group, heading a global team across APAC, Europe, Americas and Middle East, and enabling cloud technology for millions of customers around the world. Selina brings more than 20 years of experience in leading and growing technology businesses globally.

Xiangwen Liu
Vice President of Alibaba Group, General Manager for Marketing and Public Affairs, Alibaba Cloud Intelligence

Xiangwen Liu joined Alibaba Group in 2010 as one of the founding members of Alibaba Cloud Computing Business. She now serves as the General Manager for Marketing & Public Affairs and VP of Cloud Intelligence Business Group at Alibaba. She is also the assistant of the director of Alibaba Damo Academy. She received her master degree in Managemement at Nankai University.

Yangqing Jia
Vice President of Alibaba Group, Senior Fellow of Compute Platform, Alibaba Cloud Intelligence

Yangqing Jia provides Big Data and Artificial Intelligence solutions for both Alibaba internal use and Alibaba Cloud Intelligence. Prior to Alibaba, Yangqing served as Director of AI Infrastructure at Faceboook and research scientist at Google Brain. He has years of experience in open source AI solutions and standards, with prior work including Caffe, TensorFlow, PyTorch 1.0 and ONNX.

Daniel Jiang
International Chief Architect, Alibaba Cloud Intelligence

Daniel Jiang is responsible for Cloud Intelligence International’s Solutions across multiple industries and technologies, including IaaS, PaaS, Big Data, Security, and AI. Daniel’s mission is to enable his customers to achieve success by helping them adapt and thrive in the age of “Data Intelligence.” He has over 19 years of work experience in communication, IT, and cloud domains.

Rongshan Yu
Professor and Deputy Head, National Institute for Data Science in Health and Medicine, Xiamen University

Rongshan Yu is currently with Department of Computer Science of Xiamen University as Min Jiang Distinguished Professor. His research interests include statistical signal processing and its application in data compression, multimedia and bioinformatics. He holds more than 20 US/international patents. He received a PhD degree from the National University of Singapore in 2004.

Lukas
Chairman of Indonesia AI Society
Associate Professor at EE Dept. Faculty of Engineering, Universitas Katolik Indonesia Atma Jaya

Lukas, has been lecturing for 23 years, as an associate professor at the Atma Jaya Catholic University in Jakarta, Indonesia. His main interests are in artificial intelligence (AI), natural language processing (NLP), image processing, biomedical engineering, computer network security. He received a PhD degree in Electrical Engineering both at Katholieke Universiteit Leuvena.

Donny Siu
Head of Entrepreneurship Center, Hong Kong University of Science & Technology

An illustrious and recognised startup community builder in HKSAR and beyond, Donny has proven record in helping develop various startups and entrepreneurship projects. Being a creative intrapreneur in a world top ranked university, he serves in various governing committees and holds senior advisory positions in NGOs and government authorities in HKSAR and the Mainland China.

Manoj Awasthi
VP of Engineering at Tokopedia

Manoj Awasthi leads the Data Science team, the engineering team for Seller platform, Category, Shop and Product experiences within the C2C/B2C marketplace. Prior to Tokopedia, Manoj worked at Adobe and received an engineering degree in Computer Science from NIT, Allahabad in India.

Submission and Judging Criteria

Submission
In the final round, you are required to use PAI in certain part of your project. Please submit the follow file in a zip file to Tianchi:

An updated summary of your project in PDF or PPT format within 15 pages, including:

  • Project introduction: what problem(s) it solves and how it solves the problem(s)
  • The main value and innovation of your project.
  • How you leverage machine learning for the project, and what is your dataset.
  • How you use PAI (and other Alibaba Cloud products) in your project?
  • Introduction to your team and other necessary information.

A file that shows you have used PAI in your project (choose one in the following two options):

  • The machine learning source code of your project, which has been used in in PAI; or
  • A video which shows you are using PAI

(Optional) a demo of your project, if possible (choose one in the following two options):

  • A link to a web demo of your project; or
  • A video clip showing how your project works
Judging Criteria
After the deadline of the final round, all submitted projects in this round will be reviewed by judges. The assessment will be based on the following aspects:

Innovation and Creativity: 20%

    How original and creative is the project? Is there any technological and/or social innovation in the project? (An existing project created by your own team can be submitted to the challenge and will be consider as an original one.)

Technical Complexity: 30%

    How much does the project leverage machine learning algorithms? Can the machine learning model(s) the project uses solve the problem(s) it targets? Is the project technically scalable?

Social or Business Value: 20%

    How much does the project contribute to a certain industry or field? Can the project be widely used?

Integration of Alibaba Cloud products: 30%

    Using Alibaba Cloud PAI in your solution is required for final winners, and using other Alibaba Cloud products will give you an advantage. Please note, this section will be reviewed by Alibaba Cloud team only in the final round assessment.
Submission
In the 1st round, you are required to submit (please zip your file(s) before submission):

A proposal of your project in PPT or PDF format, showing

  • The executive summary of your project.
  • The main value and innovation of your project.
  • How you leverage machine learning for the project.
  • Introduction to you or your team.

A Screen shot showing you are using PAI

  • The screenshot can be included in the PDF/PPT file or submitted separately in png or jpg format.
  • It shows you are using PAI-DSW or PAI-Studio.
  • You are required to start using PAI in the 1st round, though it will not be assessed.
Judging Criteria
After the deadline of the 1st round, all submitted projects will be reviewed. The assessment will be based on the following aspects:

Innovation and Creativity: 30%

    How original and creative is the project? Is there any technological and/or social innovation in the project? (An existing project created by your own team can be submitted to the challenge and will be consider as an original one.)

Technical Feasibility and Complexity: 40%

    How much does the project leverage machine learning algorithms? Can the machine learning model(s) the project uses solve the problem(s) it targets? Is the project technically scalable?

Social or Business Value: 30%

    How much does the project contribute to a certain industry or field? Can the project be widely used?

Organizers & Partners

Organizers
Partners