Future Reasoning
Future reasoning research explores how artificial intelligence systems can predict, plan, and understand temporal dynamics. Current efforts concentrate on improving the accuracy and efficiency of AI-driven forecasting across diverse domains, from weather prediction using large meteorological models and graph neural networks to financial market analysis and even generating synthetic data for training other models. This field is crucial for advancing AI capabilities in areas like autonomous systems, personalized medicine, and risk management, ultimately impacting both scientific understanding and real-world applications.
Papers
Predicting the Future of the CMS Detector: Crystal Radiation Damage and Machine Learning at the LHC
Bhargav Joshi, Taihui Li, Buyun Liang, Roger Rusack, Ju Sun
ChatGPT for Shaping the Future of Dentistry: The Potential of Multi-Modal Large Language Model
Hanyao Huang, Ou Zheng, Dongdong Wang, Jiayi Yin, Zijin Wang, Shengxuan Ding, Heng Yin, Chuan Xu, Renjie Yang, Qian Zheng, Bing Shi