Foundation models and intelligent decision-making: Progress, challenges, and perspectives - Jincai Huang; Yongjun Xu; Qi Wang; Qi (Cheems) Wang; Xingxing Liang; Fei Wang; Zhao Zhang; Wei Wei; Boxuan Zhang; Libo Huang; Jingru Chang; Liantao Ma; et al. (The Innovation)
Intelligent decision-making (IDM) is a cornerstone of artificial intelligence (AI) designed to automate or augment decision processes. Modern IDM paradigms integrate advanced frameworks to enable intelligent agents to make effective and adaptive choices and decompose complex tasks into manageable steps, such as AI agents and high-level reinforcement learning. Recent advances in multimodal foundation-based approaches unify diverse input modalities—such as vision, language, and sensory data—into a cohesive decision-making process. Foundation models (FMs) have become pivotal in science and industry, transforming decision-making and research capabilities. Their large-scale, multimodal data-processing abilities foster adaptability and interdisciplinary breakthroughs across fields such as healthcare, life sciences, and education. This survey examines IDM’s evolution, advanced paradigms with FMs and their transformative impact on decision-making across diverse scientific and industrial domains, highlighting the challenges and opportunities in building efficient, adaptive, and ethical decision systems. Public summary: • Decision intelligence evolved from rule-based to AI-driven, enabling adaptive, context-aware choices. • Foundation models unify knowledge to enable scalable, adaptive decision-making in healthcare and other fields. • The decision-making foundation model’s progress hinges on security, privacy, and human-AI ethics.