Core Insights - Ant International announced the open-source release of its AI predictive model "Falcon TST" at the Singapore FinTech Festival (SFF2025), marking it as the first large-scale time-series prediction model based on a multi-segment pattern and a mixture of experts architecture, with over 2.5 billion parameters and optimal performance in various benchmark evaluations [1][3] Group 1: Model Capabilities - The "Falcon TST" model was initially developed for internal cash flow and foreign exchange risk predictions, achieving an accuracy rate exceeding 90% and helping businesses reduce foreign exchange costs by up to 60% [3] - The model can predict on an hourly, daily, or weekly basis and is applicable beyond finance, including weather changes, holiday consumption, financial market fluctuations, and cross-border human flow [3] Group 2: Industry Applications - In the aviation sector, the model is being used to optimize foreign exchange hedging strategies, with pilot projects showing significant reductions in foreign exchange costs [3] - The model can assist in corporate fund management, potentially reducing operational costs by 30% to 50% depending on the business model [3] - According to the International Airports Council (ACI World), global air passenger volume is expected to reach 9.8 billion by September 2025, highlighting the importance of AI-driven precise predictions for both corporate profits and consumer benefits such as ticket price reductions and service stability [3] Group 3: Open Source Initiative - Ant International's Chief Innovation Officer, Yang Jiangming, stated that the decision to open-source the "Falcon TST" model aims to empower various industries and collaborate with academia and industry to advance AI technology and its application in the real economy [3]