Pharos Network announces Prediction Markets and AI Research Project with University of Hong Kong’s FinTech Academy

2026-04-15 · Source: Dataconomy · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Blockchain & Distributed Ledger Technology, FinTech & Digital Financial Services · Depth: Advanced, quick

Summary

Pharos Network, a modular Layer-1 blockchain, has partnered with the Hong Kong-Standard Chartered Foundation FinTech Academy for a three-month research project. This initiative, part of HKU Business School's Master's Capstone Project, involves eight Master's students investigating AI decision-making within prediction markets. Pharos will provide real onchain data, expert guidance, and its tech stack, including the Smart Access List Inference (SALI) Parallel Execution Engine, capable of 30,000 transactions per second (TPS), and the X402 AI module for agent interaction. The goal is to test AI's ability to model event probabilities with greater accuracy than humans, moving students beyond theoretical modeling to building systems on a live Layer-1 network. Promising projects will enter the Pharos incubation program for accelerated development and market implementation.

Key takeaway

For research scientists and AI students exploring prediction markets, this collaboration highlights the value of integrating live blockchain data and high-throughput infrastructure. You should consider how direct access to real-time, onchain datasets and specialized AI modules, like Pharos's X402, can accelerate the transition of theoretical AI models into practical, deployable solutions on Layer-1 networks, potentially leading to incubation opportunities.

Key insights

Academic-blockchain collaboration enables students to test AI prediction models using real-world onchain data.

Principles

• Real data improves AI model validation.
• High throughput is critical for prediction markets.

Method

Students will use Pharos's SALI Parallel Execution Engine and X402 AI module to develop and test AI-based solutions for prediction markets, leveraging real onchain datasets.

In practice

• Utilize onchain data for AI model training.
• Deploy AI agents for automated predictions.

Topics

• Pharos Network
• HKU FinTech Academy
• Prediction Markets
• AI Decision-Making
• Layer-1 Blockchain

Best for: AI Scientist, AI Student, Research Scientist

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Editorial summary, takeaway, and curation by AIssential. Original article published by Dataconomy.