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
Securing the Future of GenAI: Policy and Technology
Mihai Christodorescu, Ryan Craven, Soheil Feizi, Neil Gong, Mia Hoffmann, Somesh Jha, Zhengyuan Jiang, Mehrdad Saberi Kamarposhti, John Mitchell, Jessica Newman, Emelia Probasco, Yanjun Qi, Khawaja Shams, Matthew Turek
The future of cosmological likelihood-based inference: accelerated high-dimensional parameter estimation and model comparison
Davide Piras, Alicja Polanska, Alessio Spurio Mancini, Matthew A. Price, Jason D. McEwen
Future You: A Conversation with an AI-Generated Future Self Reduces Anxiety, Negative Emotions, and Increases Future Self-Continuity
Pat Pataranutaporn, Kavin Winson, Peggy Yin, Auttasak Lapapirojn, Pichayoot Ouppaphan, Monchai Lertsutthiwong, Pattie Maes, Hal Hershfield