learning from physical environments presents new issues: the number of agents is not elastically scalable (increasing the number of concurrent experiments requires power, equipment, and engineering), each experiment can take days, and the results are often ambiguous.
【局限】作者诚实地承认了物理环境中AI学习的局限性，包括实验规模扩展受限、耗时长和结果模糊等问题。这些限制使得物理实验环境中的AI训练比数字环境更具挑战性，可能成为自动化科学发现的瓶颈，文章未提出有效的解决方案。