PUDA为自动实验室提供可追溯的命令行硬件接口,让AI直接控制实验。
PUDA: An AI-Native Hardware Harness for Self-Driving Laboratories

- 用命令行替代图形界面,实现确定性、可审计的实验执行
- 通过运行标识符和时间戳关联实验协议与数据产物,全程可追溯
- 适合构建自主科研代理,推动物理世界AI系统的落地
物理统一设备架构(PUDA)是一种面向自动实验室(SDLs)的AI原生硬件接口。不同于构建以人为中心的图形化操作层,PUDA设计为无头环境,通过可发现的命令行接口呈现设备,使用分布式消息系统路由JSON协议,所有命令响应、数据产品与报告均以结构化记录保存。PUDA将协议、运行、样本、测量及命令日志组织成由运行标识符和时间戳链接的AI原生数据结构,从提交协议到硬件响应再到数据产出,完整保留溯源信息。它将科学编排与物理操作、数据遥测分离:代理决定实验内容,而PUDA执行经验证的命令并捕获带溯源的状态、响应与数据。本工作并非另一个优化器、编排器或配方语言,而是为智能体驱动的自动实验室提供实用的执行与数据环境;更广泛的意义在于,PUDA为AI系统与物理工具交互提供了AI原生的硬件支撑。
原文摘要 · Abstract (English)
Physical Unified Device Architecture (PUDA) is an AI-native hardware harness for self-driving laboratories (SDLs). Rather than building a human-centered graphical user interface (GUI) orchestration layer, PUDA creates a command-line runtime environment that lets agents observe, orient, decide, and act over experiments while hardware execution remains deterministic, atomic, and auditable. Headless by design, devices appear through discoverable command-line interfaces, JSON protocols are routed through a distributed messaging system, and command responses, data products, and reports are preserved as structured records. PUDA organizes protocols, runs, samples, measurements, and command logs into an AI-native data structure linked by run identifiers and timestamps, preserving provenance from submitted protocol through hardware response to resulting data products. PUDA separates scientific orchestration from physical operation and data telemetry: agents choose experiments, while PUDA executes validated commands and captures provenance-linked state, responses, and data. The contribution is not another optimizer, orchestrator, or recipe language. It is a practical execution and data environment for agentic SDLs; the broader physical AI implication is that PUDA provides an AI-native hardware harness for AI systems to interact with physical tools.
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