文章背景与核心概要
随着大语言模型（LLMs）和具备工具使用能力的自主智能体不断演进，其在复杂的芯片设计领域的应用已成为前沿研究热点。本文旨在探讨半导体这一高度精密的行业究竟需要何种具体的AI能力，并提出了一种全新的建模框架：将芯片设计超级智能建模为一个“AI组织”（AI-organization），通过有效编排多个智能体来应对自主硬件开发的复杂需求。
这项研究切中了当前AI赋能硬件设计（AI for EDA/Chip Design）的核心痛点。传统的单智能体或松散的AI工具调用难以应对芯片设计中长周期、多学科交叉（如架构、RTL编码、验证、物理综合等）的复杂挑战。作者通过引入组织化、协同化的多智能体编排理念，为未来实现全自动化芯片设计提供了重要的理论基础与框架指导。
Agent-Orchestration in Autonomous Chip Design
arXiv ID: 2608.14035
Subject: Artificial Intelligence (cs.AI)
Author: Linyang Li
Submitted: August 14, 2026
arXiv ID: 2608.14035
Subject: Artificial Intelligence (cs.AI)
Author: Linyang Li
Submitted: August 14, 2026
Summary
随着大语言模型（LLMs）和自主智能体的持续演进，它们在复杂的芯片设计领域的应用已成为一个重要的研究领域。本文探讨了一个根本性问题：在这个高度精密的半导体行业中，究竟需要什么样的具体AI能力。作者提出了一种新颖的框架：将芯片设计超级智能建模为一个“AI组织”，通过有效编排多个智能体来处理自主硬件开发的错综复杂的需求。
Summary
As Large Language Models (LLMs) and autonomous agents continue to evolve, their application in the complex field of chip design has become a significant area of research. This paper addresses the fundamental question of what specific AI capabilities are required for the sophisticated semiconductor industry. The author proposes a novel framework: modeling chip-design superintelligence as an "AI-organization," effectively orchestrating multiple agents to handle the intricate requirements of autonomous hardware development.
Abstract
大语言模型（LLMs）和工具使用智能体近期的发展，促使人们探索在芯片设计中使用智能体的潜力。核心问题在于，在这个如此精密的行业中，我们真正需要的是何种AI。为此，我们提出了将芯片设计超级智能建模为一个庞大AI组织的构想。
Abstract
Recent developments in large language models (LLMs) and tool-using agents encourage people to explore the potential of using agents in chip design. The core question is what kind of AI we really need in such a sophisticated industry. To this end, we bring the idea of modeling a chip-design superintelligence as an enormous AI-organization.
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Accessing the Paper
Citation & Metadata
- DOI: 10.48550/arXiv.2608.14035
- 文献计量工具： NASA ADS | Google Scholar | Semantic Scholar
Citation & Metadata
- DOI: 10.48550/arXiv.2608.14035
- Bibliographic Tools: NASA ADS | Google Scholar | Semantic Scholar
Submission History
- [v1] 2026年8月14日 星期五 07:26:02 UTC
Submission History
- [v1] Fri, 14 Aug 2026 07:26:02 UTC