ICBC Asia's new competition gives Hong Kong students a chance to test their fintech ideas beyond the classroom.
Updated
October 2, 2026 9:16 AM
Main Building of the University of Hong Kong. PHOTO: ADOBE STOCK
Hong Kong university students are being invited to take part in the first Hong Kong University Students Fintech Innovation Competition, organised by Industrial and Commercial Bank of China (Asia). The competition gives students a chance to develop ideas around financial technology, with cash prizes, internship opportunities and a route to the national finals of the ICBC Cup on offer.
The competition is part of the 17th ICBC Cup and marks the first time ICBC has established a competition zone in Hong Kong. It is supported by the Financial Services and the Treasury Bureau and the Hong Kong Monetary Authority, with 12 Hong Kong universities also backing the initiative.
The participating universities are the University of Hong Kong, the Chinese University of Hong Kong, Hong Kong University of Science and Technology, Hong Kong Polytechnic University, City University of Hong Kong, Hong Kong Baptist University, Hong Kong Metropolitan University, Lingnan University, Hong Kong Shue Yan University, the Education University of Hong Kong, Hang Seng University of Hong Kong and St. Francis University.
For ICBC Asia, the competition is also intended to support the development of fintech in Hong Kong and expand the city's fintech talent pool. Dr. Liu Yagan, Chairman and Executive Director of Industrial and Commercial Bank of China (Asia), said the competition is designed to encourage students to develop practical applications for financial technology and explore new banking business models.
"This competition encourages university students across Hong Kong to propose practical solutions for fintech applications and banking business model innovation from the perspective of financial products and services, providing a platform for Hong Kong youth to connect with cutting-edge industries and unleash their innovative potential."
The initiative will also connect Hong Kong students with the wider ICBC Group. Liu said this would help deepen exchanges between young talent in Hong Kong and the Mainland.
The competition is open to full-time university students in Hong Kong and carries the theme "Digital Banking, Creating the Future." Students can develop ideas across 10 areas, ranging from fintech and digital finance to green finance, inclusive finance, pension finance and wealth management. The categories also include financial security services, specialised financial services, youth services and open innovation services.
The competition also offers cash prizes: the First Prize winner will receive HK$50,000; two Second Prize winners will receive HK$30,000 each; three Third Prize winners will receive HK$20,000 each; and four Honorable Mention recipients will receive HK$10,000 each.
Beyond the prize money, qualifying winners will have the opportunity to undertake internships at ICBC (Asia). The team that wins the Hong Kong First Prize will also have the opportunity to travel to Beijing in December for the ICBC Cup national finals, where it will compete against teams from across the country.
With registration now open, the competition gives Hong Kong university students an opportunity to take ideas in financial technology from the classroom into areas such as banking products, services and business models.
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Robots that learn on the job: AgiBot tests reinforcement learning in real-world manufacturing.
Updated
January 8, 2026 6:34 PM
A humanoid robot works on a factory line, showcasing advanced automation in real-world production. PHOTO: AGIBOT
Shanghai-based robotics firm AgiBot has taken a major step toward bringing artificial intelligence into real manufacturing. The company announced that its Real-World Reinforcement Learning (RW-RL) system has been successfully deployed on a pilot production line run in partnership with Longcheer Technology. It marks one of the first real applications of reinforcement learning in industrial robotics.
The project represents a key shift in factory automation. For years, precision manufacturing has relied on rigid setups: robots that need custom fixtures, intricate programming and long calibration cycles. Even newer systems combining vision and force control often struggle with slow deployment and complex maintenance. AgiBot’s system aims to change that by letting robots learn and adapt on the job, reducing the need for extensive tuning or manual reconfiguration.
The RW-RL setup allows a robot to pick up new tasks within minutes rather than weeks. Once trained, the system can automatically adjust to variations, such as changes in part placement or size tolerance, maintaining steady performance throughout long operations. When production lines switch models or products, only minor hardware tweaks are needed. This flexibility could significantly cut downtime and setup costs in industries where rapid product turnover is common.
The system’s main strengths lie in faster deployment, high adaptability and easier reconfiguration. In practice, robots can be retrained quickly for new tasks without needing new fixtures or tools — a long-standing obstacle in consumer electronics production. The platform also works reliably across different factory layouts, showing potential for broader use in complex or varied manufacturing environments.
Beyond its technical claims, the milestone demonstrates a deeper convergence between algorithmic intelligence and mechanical motion.Instead of being tested only in the lab, AgiBot’s system was tried in real factory settings, showing it can perform reliably outside research conditions.
This progress builds on years of reinforcement learning research, which has gradually pushed AI toward greater stability and real-world usability. AgiBot’s Chief Scientist Dr. Jianlan Luo and his team have been at the forefront of that effort, refining algorithms capable of reliable performance on physical machines. Their work now underpins a production-ready platform that blends adaptive learning with precision motion control — turning what was once a research goal into a working industrial solution.
Looking forward, the two companies plan to extend the approach to other manufacturing areas, including consumer electronics and automotive components. They also aim to develop modular robot systems that can integrate smoothly with existing production setups.