Pharos Network, the modular Layer-1 blockchain, has announced a research project in collaboration with the Hong Kong-Standard Chartered Foundation FinTech Academy. The goal is to deepen the ties between the academic and blockchain worlds while giving students a chance to get hands-on with technology they can use to aid their research into AI decision-making in the context of prediction markets.
The joint research initiative is being operated in conjunction with the Master’s Capstone Project running at HKU Business School, an open practicum program for students. Eight Master’s students will participate in a three-month study that will delve deep into the capabilities of AI models when it comes to predictive decision-making – and Pharos will be supplying the onchain data for them to work with.
Real data, real outcomes
In addition to supplying students with real onchain datasets, Pharos will be providing expert guidance and support throughout the program. Any projects that emerge from the three-month program showing real potential will be entered into the Pharos incubation program, fast-tracking their route to development.
From validating the underlying technology to assisting with market implementation, Pharos will assist every step of the way. For students, the upside to this is significant, since it presents an opportunity to move beyond theoretical modeling to building systems that are activated on a live Layer-1 network. In the process, this will help to grow the Pharos ecosystem of applications and burnish its reputation as a leading blockchain built for AI and institutional finance.
Engineering smarter predictions
It’s no secret that AI is rapidly infiltrating everything, transforming it in ways that are still being discovered. When it comes to prediction markets, there are clear applications for artificial intelligence, particularly when it comes to structured modeling of event probabilities. In theory, AI should be able to do this sort of stuff with greater accuracy than humans – but the only way to find out, of course, is to test this thesis. Which is exactly what the HKU students will be doing.
Pharos’ tech stack will be put to use in facilitating this including its Smart Access List Inference (SALI) Parallel Execution Engine, which can deliver up to 30,000 TPS. This is the sort of throughput that prediction markets demand, given their need to handle real-time settlement and advanced probability models.
In addition, Pharos has deployed the X402 AI module that’s been designed for agent interaction. This provides a framework for agents to participate in automated predictions while also handling payments between different agents. All combined, the end result is that Pharos’ Layer-1 network has all the tools a Master’s student could conceivably need to develop AI-based solutions focused on prediction markets.
From Lab to Layer-1
Ultimately, the collaboration between Pharos and HKU’s FinTech Academy will give students a practical grounding in what AI can do and how its decision-making can be improved. The ability to tap into vast amounts of real-time data, all delivered onchain, should prove invaluable.
As Dr. You Yang, Assistant Professor of Finance at the University of Hong Kong, succinctly puts it, “Our collaboration with Pharos Network offers students a unique opportunity to test these theoretical frameworks in a real-world tech environment. I anticipate that their rigorous empirical analysis will contribute valuable insights to this field.”
With the three-month program poised to commence, the results of all this research will soon become manifest – starting with real-world data and ending, for the most promising proposals, with live deployment on Pharos Network.
