Pharos Network has partnered with the University of Hong Kong (HKU) to initiate a joint research project focusing on prediction markets and AI decision-making. This collaboration, structured within the Master’s Capstone Project framework at HKU Business School, aims to leverage Pharos’ access to on-chain datasets, enabling Master’s students to engage in an intensive three-month study on the application of AI models in predictive decision-making.
The partnership extends Pharos’ collaboration with the University of Hong Kong-Standard Chartered Foundation FinTech Academy, marking a significant deepening of ties with one of Asia’s leading educational institutions. During the study, students will conduct research on a live network, integrating their findings with projects supported by the Pharos ecosystem incubator. This initiative is part of Pharos’ $10 million global incubation program, designed to accelerate projects related to real-world assets (RWA) and decentralized finance (DeFi) on its blockchain.
By establishing a feedback loop from academic research to ecosystem deployment, Pharos aims to create synergies that benefit both the university and its incubation program. The collaboration will see Pharos actively participating by providing expert guidance, particularly in institutional-grade financial systems and its high-performance AI technology. Notably, the company’s Smart Access List Inference (SALI) Parallel Execution Engine offers capabilities of 30,000 transactions per second (TPS) and sub-second finality, crucial for platforms that handle large betting volumes and require real-time settlements.
“The essence of prediction markets lies in the accuracy of data input and value output, aligning perfectly with AI’s capabilities,” said Wish Wu, Co-founder and CEO of Pharos. He elaborated, “Pharos aims to be not only a settlement layer for financial assets but also a verification layer for information.” This ambition reflects a broader strategy to explore how Pharos’ infrastructure can support sophisticated on-chain and AI-driven prediction models, particularly in contexts such as outcome prediction markets for real-world events.
Dr. You Yang, an Assistant Professor of Finance at HKU, noted that the project would academically investigate how binary option mechanisms can be applied to RWA pricing, auction design, and corporate earnings forecasts. “Our collaboration with Pharos Network offers students a unique opportunity to test these theoretical frameworks in a real-world tech environment,” Yang remarked. He expressed optimism that the students’ rigorous empirical analyses would yield valuable insights into the intersection of finance and technology.
As AI agents increasingly transact on blockchain infrastructures, the convergence of artificial intelligence and web3 technology is becoming a focal point in the industry. Pharos’ collaboration with HKU is poised to generate insights that may have significant implications for the future of both sectors. The partnership illustrates a growing trend where academia and industry seek to harness the potential of advanced technology in understanding and predicting market behaviors, setting the stage for innovations that could shape the financial landscape in the years to come.
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