HKU AI+ Competition Experience

From Problem to Pitch in 2 days

The 48-hour deadline

In just 48 hours, we were expected to build a complete product and pitch it to Intel executives, directors, and the university faculty. On August 24 and 25, I represented my school along with six others at the HKU AI+ Competition in Mumbai. We were selected based on our academic record and interest in STEM. Our teacher told us he was not sure how exactly the competition would work. A live meeting was supposed to happen, but it did not take place. The HKU team uploaded a recording. This video explained the presentation they forwarded. Based on that recording, we thought we could ideate and present in two days.

Learning from the professors

The competition was a hackathon and business pitch event. Teams had to first choose between two tracks. These tracks were AI+ Biodiversity and Smart City, or AI+ Creative Media and Business Innovation. We went into the event without any specific problems in mind or product ideas prepared. The schedule for the first day started with us arriving at 9:00 AM. HKU professors conducted several sessions.

Prof. Joseph Chan represented the business school and gave his perspective as the principal advisor of the hackathon. I remember him quoting Einstein: “If I had an hour to solve a problem, I’d spend 55 minutes thinking about the problem and 5 minutes thinking about solutions.” He told us we should spend 90 percent of our time finding a problem and the rest on the solution. He advised us to look for problems in our daily schedules to identify a community pain point.
Prof. Christophe Coupé talked about connecting computation and artificial intelligence to literature and reading. He explained how he uses these tools to analyze books and stories. He also talked about creating better verbal pitches by using a narrative to gain audience attention.
Professor Frank Van Der Wouden came later to share his insights regarding geography. He was definitely one of the most built professors.
Prof. Xuguang Wang gave a technical presentation. He talked about his projects. He uses computation to create 3D models of structures for applications like natural disaster testing. He showed us an example, and we failed to recognize it was computer-generated.

Market research and building Furwings

Our team then had to do market research. In our case, this meant finalizing and reviewing problems. When the professors came for the mentorship session, we pitched whatever ideas we had and gained their insights. After a short presentation session, we broke for the day. Our group still did not have a solid idea. We decided to go home and keep working. While deliberating on a pet translator idea suggested by a member, another teammate asked what would happen if we made a fur collection device. That is when Furwings was born.
Furwings is a smart wearable strap for dogs that uses motion sensors to detect when your dog is shedding. This happens during shaking or scratching.

It responds by deploying soft, organic wings that create a gentle airflow. This guides loose fur into a two-stage capture system. A mesh catches larger strands, and electrostatics attract fine particles. The collected hair is stored in a detachable pouch you empty weekly. Furwings is a proactive device. It captures fur before it hits your floor. This keeps your home clean while your dog stays comfortable and free to move. After we had our product idea in place, we divided the work. We focused on specific parts like costs and market research. We also worked on scaling, the physical mechanisms, and the artificial intelligence integration.

Pitching to the panel

The next day, we were the first team to pitch and had to hurry. In the morning, we had a few more sessions where professors discussed issues we should address in our market. One professor noted they had a dog and would not want it wearing something heavy. They said if the device was light, it would work well. We learned how people are allergic to dog fur and how this product could help them. We received feedback on how we could reuse the collected material for other purposes.
We worked on our pitch and presentation. Due to the time limit, our presentation was not exactly what we wanted. We had to submit our slides at 11:30 AM. Following the submission, we practiced our pitch. We were rushed, but we had enough material to speak on stage.
The judges for the second day were Ditty Varghese, an AI/ML Consultant, and Lena Phoo, Managing Principal at CETIC Foundation. Anshul Sonak, Head and Global Director of Intel Digital Readiness Programs, also judged the event alongside the three professors from the first day. After we pitched to them, they asked a few questions. The judges said they loved our idea. If our pitch had been stronger and our presentation more detailed, we had the potential to win.
Anshul Sonak had to leave early, but he gave a short talk before departing. He shared an interesting concept. He said the acronym AI can also stand for Authentic Intent. He explained that we must first figure out our own Authentic Intent before applying the technology to work on it.

Competition takeaways

This experience had an impact on me. I learned how to create presentations about the different arenas behind a product. Building a startup involves defining the problem and forming the idea. It requires analyzing the market and designing the mechanics. We also learned how to calculate costs and plan for scaling and growth. The direct feedback from the professors clarified these business stages. The competition taught me how to work under pressure and showed me the amount of detail required to pitch an actual product. We still have this idea, and we will keep working on it for future competitions.

Thank you for reading!