发表机构
Argonne National Laboratory; The University of Chicago; NVIDIA Corporation; Northwestern University; Lila Sciences, Inc.; PsiQuantum; University of Toronto; Vector Institute for Artificial Intelligence（阿贡国家实验室; 芝加哥大学; 英伟达公司; 西北大学; Lila Sciences公司; PsiQuantum公司; 多伦多大学; 向量人工智能研究所）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文基于TPC26会议，探讨AI推理、自主实验、高性能计算与量子计算在材料科学发现中的汇聚效应，指出化学科学正处于变革性突破的临界点。
AI 中文摘要
本文评论源自TPC26会议（见https URL），该会议汇聚了来自学术界、国家实验室和工业界的领导者，他们正在重塑材料科学发现。会议探讨了AI、自主智能体、自动驾驶实验室、高性能计算与量子计算如何汇聚，以放大各自对材料科学发现的影响。文中观点反映了这些前沿领域研究者的第一手经验，并捕捉了这一全球性努力的精髓。随着AI驱动的推理、自主智能体框架、自动驾驶实验室和容错量子处理器同步成熟，我们提供此评论，作为我们认为化学科学正处于变革性进展和生产性颠覆临界点的参考。
英文摘要
This Comment emerges from TPC26 (https://tpc26.org), a conference convening leaders from academia, national laboratories, and industry who are reshaping materials science discovery. The meeting explored how AI, autonomous agents, self-driving labs, higher performance and quantum computing converge to amplify their individual impact on materials science discovery. The perspectives here reflect the firsthand experiences of researchers at these frontiers and capture the essence of this global endeavor. As AI-driven reasoning, autonomous agentic frameworks, self-driving laboratories, and fault-tolerant quantum processors mature simultaneously, we offer this Comment as a reference at what we believe is a tipping point of transformative advances and productive disruption in the chemical sciences.
Comments10 pages, 24 references
