A learning system can continuously incorporate real-world data in a way that numerical solvers fundamentally cannot, capturing and compounding the knowledge that is currently trapped out there in the real world.
揭示了AI驱动设计的另一大优势：打通仿真与现实的闭环。传统求解器难以穷尽制造公差等现实复杂因素，而学习系统能持续吸收实测数据，形成越用越聪明的“数据飞轮”。将现实中散落的隐性知识固化为模型能力，这是传统工具无法企及的质变。