Customize Consent Preferences

We use cookies to help you navigate efficiently and perform certain functions. You will find detailed information about all cookies under each consent category below.

The cookies that are categorized as "Necessary" are stored on your browser as they are essential for enabling the basic functionalities of the site. ... 

Always Active

Necessary cookies are required to enable the basic features of this site, such as providing secure log-in or adjusting your consent preferences. These cookies do not store any personally identifiable data.

No cookies to display.

Functional cookies help perform certain functionalities like sharing the content of the website on social media platforms, collecting feedback, and other third-party features.

No cookies to display.

Analytical cookies are used to understand how visitors interact with the website. These cookies help provide information on metrics such as the number of visitors, bounce rate, traffic source, etc.

No cookies to display.

Performance cookies are used to understand and analyze the key performance indexes of the website which helps in delivering a better user experience for the visitors.

No cookies to display.

Advertisement cookies are used to provide visitors with customized advertisements based on the pages you visited previously and to analyze the effectiveness of the ad campaigns.

No cookies to display.

在上海浦东滨江公园观赏外滩建筑群-20240824在上海浦东滨江公园观赏外滩建筑群-20240824
0

三年前的AI设计芯片造假?谷歌深陷学术不端丑闻,吹哨人被开除并已起诉

引言

2021年,谷歌在《自然》杂志上发表了一篇关于AI芯片设计的论文,声称其研发的强化学习算法可以自动生成芯片布局,效率远超人类工程师。该论文引发了科技界的轰动,被誉为芯片设计领域的重大突破。然而,三年过去了,质疑声不断,这篇论文的真实性也饱受争议。近日,Synopsys的杰出架构师Igor Markov在《Communications of the ACM》上发表文章,总结了人们对这篇论文的各种质疑,并指出该论文存在严重的学术不端行为。

谷歌的“革命性”论文:吹嘘还是真相?

谷歌的这篇论文声称,其研发的强化学习算法可以快速、高效地生成芯片布局,在功耗、性能和芯片面积等关键指标上都优于或媲美人类工程师。该论文还将这一方法推广到芯片设计之外,表示强化学习在组合优化方面的表现优于最先进的技术。

然而,这篇论文缺乏公开测试示例的结果,也没有分享所使用的专有TPU芯片块。源代码在论文发表后七个月才发布,并且缺少重现方法和结果所需的关键部分。

质疑声不断:独立评估揭示真相

来自谷歌和学术界的十多位研究人员对谷歌的实验提出了质疑,并对所报告的研究结果提出了担忧。加州大学圣地亚哥分校(UCSD)的研究人员对谷歌开源代码中缺少的关键组件进行了逆向工程,并完全重新实现了代码中缺失的模拟退火 (SA) 基线。结果表明,谷歌的强化学习代码的表现并不如其论文中所宣称的那样出色,甚至不如模拟退火和商业电子设计自动化EDA工具。

吹哨人被开除,诉讼揭露更多内幕

2022年,谷歌解雇了内部吹哨人,并拒绝批准发表一篇批评谷歌研究的文章。这位吹哨人依据吹哨人保护法,对谷歌提起了错误解雇的诉讼,法庭文件详细列出了与谷歌论文相关的欺诈和科学不端行为的指控。

学术界反思:科学研究的诚实可信至关重要

谷歌的这篇论文引发了学术界的反思。为了维护科学研究的诚实可信,必须迅速果断地采取行动,对学术不端行为进行严厉打击。

结论

谷歌的这篇论文事件再次提醒我们,科学研究必须以诚实可信为基础。学术界应该加强对研究成果的审查和评估,并对学术不端行为保持高度警惕。同时,科研人员也应该秉持科学道德,严谨治学,为推动科学进步做出贡献。

参考文献

  • Markov, I. (2023). A graph placement methodology for fast chip design: A critical analysis. Communications of the ACM, 66(11), 82-87.
  • Mirhoseini, A., et al. (2021). A graph placement methodology for fast chip design. Nature, 590(7845), 240-245.
  • https://www.nytimes.com/2022/06/02/technology/google-ai-chip-design-paper.html
  • https://www.reuters.com/technology/google-whistleblowers-say-ai-chip-design-paper-fraudulent-2022-06-02/


>>> Read more <<<

Views: 0

0

发表回复

您的邮箱地址不会被公开。 必填项已用 * 标注