Prizes and Benefits
The winners of the challenge will share $55,000 USD cash prizes and $61,000 cloud credits in total.
2020.9.17Challenge starts, registration opens
2020.11.1Deadline for 1st round submission
2020.11.41st round results announced; 2nd round starts
2020.11.22Deadline for 2nd round submission
2020.11.27Final 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).
Sign up to Alibaba Cloud for free and complete your basic information
Please register for the challenge on Tianchi
Claim a $50 PAI coupon and start using PAI
The deadline for the 1st round submission is Nov 1
- 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 2nd 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.
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 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 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 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 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.
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.
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 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
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.
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?