OpenAI Details GPT-6 Use in Physical-World Engineering, Partnerships with Racing and Auto Firms
On November 3, 2026, OpenAI published a post on accelerating physical-world engineering, describing GPT-6's use in mechanical, electrical, and system design, including an internal device design test and partnerships with Chip Ganassi Racing and Mazda. The post notes that while the model completed a test device design in under a week without manual design edits, prototypes still required human review due to manufacturing constraints.
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机器之心ScienceAI
编辑丨& AI 正在改变软件开发的工作方式，而当模型开始接触真实世界中的机械结构、电路和制造要求时，工程研发也可能成为下一个重要应用领域。 与软件不同，实体产品设计需要同时满足多种约束：机械结构必须能够装配，电路板需要容纳并连接各类电子元件，软件要与硬件正常协同，最终设计还必须符合制造工艺、材料和成本要求。这些环节相互关联，一处修改往往会影响其他部分。 2026 年 11 月 3 日，OpenAI 发布文章「 Accelerating engineering for the physical world 」，介绍其模型在机械工程、电气工程和系统设计中的最新应用进展。从内部团队设计实体设备，到硬件研发部门使用 Codex 处理 CAD 与仿真任务，再到与 Chip Ganassi Racing 和 Mazda 展开合作，OpenAI 正在探索让 AI 参与从概念设计到工程验证的更多环节。 原文链接： https://openai.com/index/accelerating-engineering-for-the-physical-world/ 设计一台真实设备 团队首先介绍了一项内部测试：OpenAI 尝试利用模型设计一台能够与 Codex 交互的实体设备，并检验模型在多模态理解和计算机操作方面的能力。 在这一过程中，GPT-6 负责定义设备的功能需求，并参与设计外壳、印刷电路板（PCB）以及软件集成方案。模型需要处理的任务并不局限于生成外观概念，而是覆盖了多个工程领域。 在机械设计方面，模型设计设备外壳及内部结构，确定各个组件的安装与固定方式；在电气设计方面，它选择电子元件，并完成 PCB 的元件布局和连接设计，使电路板能够适配外壳内部空间；在软件层面，模型还负责设计用户界面、生成固件及相关软件集成方案，使设备能够与 Codex 连接。 图示：由 GPT-6 自主设计的电路板。 最终，两名团队成员利用模型在不到一周的时间内完成了这台测试设备的设计，期间没有直接进行人工设计修改。随后，合同制造商在不到一个月的时间内制作出一小批原型。 不过，从原型设计走向实际制造仍然存在差距。OpenAI 指出，模型在部分设计中未能持续考虑制造商的生产限制、尺寸公差以及装配所需的具体细节，因此设备仍需要经过多轮人工审查和修改。 硬件研发流程 除了单独的设备设计测试，OpenAI 的硬
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