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NewsTopic · LLM进化汇编程序1 min read·2026-10-14

MLST Interview: Akarsh Kumar on Evolving Assembly Programs with LLMs

Machine Learning Street Talk released an interview featuring guest Akarsh Kumar, who discusses using Large Language Models (LLMs) to evolve small assembly programs for the game 'Core War'.

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2026-10-08 18:30 GMT+8

Machine Learning Street Talk published a video interview titled "Game of Thrones: Turing Edition | Akarsh Kumar on Core War" on October 8, 2026. Guest Akarsh Kumar presented an experiment where he used Large Language Models (LLMs) to evolve small assembly programs designed to compete against each other in the classic programming game "Core War".

According to the episode description, Kumar noted that zero-shot generation of this assembly language by LLMs performs poorly. However, when combined with an evolutionary process and a verifier, the resulting programs proved to be highly effective. This resource is relevant for technical professionals interested in LLM applications for code generation, automated optimization, and evaluation mechanisms.

Sources

  • 原始出处youtube.com↗
Topic

LLM进化汇编程序

MIT与Sakana AI团队提出“数字红皇后”(DRQ)算法,利用大语言模型(LLM)在经典编程游戏《Core War》中进化汇编程序。不同于传统的静态优化,DRQ采用自我对弈机制,让LLM生成的“战士”程序必须击败所有历史对手才能存活,…

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Updated 2026-10-14 21:35

How it got here

  1. 2026-01-06MIT与Sakana AI联合发布论文《Digital Red Queen: Adversarial Program Evolution in Core War with LLMs》,提出DRQ算法。
  2. 2026-01-06官方开源代码仓库 SakanaAI/drq 上线,提供基于GPT-4.1-mini的最小化实现。
  3. 2026-10-14Machine Learning Street Talk发布访谈,第一作者Akarsh Kumar详解如何利用LLM进化汇编程序参与Core War竞争。

What is still unsettled

  • DRQ发现的“行为趋同”现象是否在其他非对称或高噪声的真实世界对抗环境中同样存在?
  • 除了GPT-4.1-mini,其他架构的LLM在作为变异算子时,其进化效率与策略多样性有何差异?
  • 该方法能否有效迁移至实际网络安全场景,以自动发现或修补零日漏洞?
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