AI 中文总结
本文综述AI科学家的过去与未来，指出其核心挑战是多技术集成，现有技术已支持构建更通用系统，其有望变革科学，诺贝尔图灵挑战目标进展超前。
AI 中文摘要
本文对AI科学家（即能够实现科学自动化的机器）的过去与未来进行了综述。AI科学家可生成假设、推导其结果、设计并执行实验、解释实验结果以及修正自身信念，这类系统是集成化的科学智能体，与文献、形式化知识、数学模型、模拟系统、数据分析系统及物理实验室相连。Adam是首个通过假设生成与物理实验循环实现新颖科学发现的机器；Eve确立了现代自动驾驶实验室的架构；当前的基础模型、自主智能体与实验室机器人技术，使得构建比Adam或Eve更通用的系统成为可能。核心问题已不再是科学的单个组成部分能否被自动化（答案是肯定的），而是如何实现集成：AI科学家必须将神经学习与逻辑、概率、数学、因果推理、模拟、实验设计、机器人技术及形式化科学记录相结合。AI科学家有潜力推动科学变革，使科学更快速、低成本、更具系统性与可重复性，还可探究未借助人类科学的过于复杂的系统，并让数千个AI科学家协同解决单一问题。诺贝尔图灵挑战设定了到2050年开发出能实现诺贝尔奖级发现自动化的AI系统的目标，目前进展已超前于计划，成功后将创造新的科学形式并改变世界。
英文摘要
We present a survey of the past and future of AI Scientists: machines capable of automating science. AI Scientists can originate hypotheses, deduce their consequences, design and execute experiments, interpret their results, and revise their beliefs. Such systems are integrated scientific agents, connected to the literature, formal knowledge, mathematical models, simulations, data-analysis systems and physical laboratories. Adam was the first machine to make novel scientific discoveries through cycles of hypothesis formation and physical experimentation. Eve established the architecture of the modern self-driving laboratory. Foundation models, autonomous agents and laboratory robotics now make it possible to build systems far more general than either Adam or Eve. The central problem is no longer whether individual components of science can be automated. They can. The problem is integration. AI Scientists must combine neural learning with logic, probability, mathematics, causal reasoning, simulation, experimental design, robotics and formal scientific records. AI Scientists have the potential to transform science: to make science faster, cheaper, more systematic and more reproducible. AI Scientists could investigate systems too complicated for unaided human science, and enable thousands of AI scientists to work together on single problems. The Nobel Turing Challenge sets the goal of developing by 2050 AI systems capable of automating Nobel-quality discoveries. Progress is ahead of schedule. When we succeed it will create a new form of science and transform the world.
