This is a presentation on Real-Time Robust Adaptive Traffic Light System and Reservoir Engineering with Machine-Learning-Based Seismicity Forecasting and Data-Driven Ground Motion Prediction (RT Forecast) by Lawrence Berkeley National Laboratory, presented by Nori Nakata. This video slide presentation outlines the development of a near-real-time Adaptive Traffic Light System (ATLS) that combines machine-learning seismicity forecasting, generative AI ground-motion prediction, and high-pressure laboratory experiments to improve induced seismicity forecasting and reservoir engineering for Enhanced Geothermal Systems (EGS). This presentation was featured at the Utah FORGE R&D Annual Workshop on September 9, 2025. The workshop offered a valuable opportunity to review the progress of Research and Development projects funded under Solicitation 2022-2, which aim to improve our understanding of the key factors influencing Enhanced Geothermal System (EGS) reservoir and resource development.