探讨大模型在硬件设计中是革命还是炒作，厘清其真实能力边界。
Revolution or Hype? Seeking the Limits of Large Models in Hardware Design
- 集结学界与产业专家，系统分析大模型在电路设计中的实际能力。
- 指出可靠性、可扩展性与可解释性是制约大模型落地的核心瓶颈。
- 适合关注AI赋能EDA的工程师与研究者参考，尤其关心技术真实性的读者。
近期大型语言模型（LLMs）与大型电路模型（LCMs）的突破，引发电子设计自动化（EDA）领域的广泛关注，预示着电路设计与优化的变革。然而，这种热情伴随着强烈质疑：这些AI模型究竟是硬件设计的真正革命，还是短暂的夸大期待？本文作为ICCAD 2025专题研讨的奠基性文献，汇聚了学术界与工业界的顶尖专家观点，深入审视大模型在硬件设计中的实际能力、根本局限与未来前景。论文整合了关于可靠性、可扩展性与可解释性的核心论点，提出是否能实质性超越或补充传统EDA方法的争议框架。最终呈现一份权威综述，为当前最具争议且影响深远的技术趋势提供新视角。
原文摘要 · Abstract (English)
Recent breakthroughs in Large Language Models (LLMs) and Large Circuit Models (LCMs) have sparked excitement across the electronic design automation (EDA) community, promising a revolution in circuit design and optimization. Yet, this excitement is met with significant skepticism: Are these AI models a genuine revolution in circuit design, or a temporary wave of inflated expectations? This paper serves as a foundational text for the corresponding ICCAD 2025 panel, bringing together perspectives from leading experts in academia and industry. It critically examines the practical capabilities, fundamental limitations, and future prospects of large AI models in hardware design. The paper synthesizes the core arguments surrounding reliability, scalability, and interpretability, framing the debate on whether these models can meaningfully outperform or complement traditional EDA methods. The result is an authoritative overview offering fresh insights into one of today's most contentious and impactful technology trends.
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