前OpenAI技术主管Justin Lebar以访问学者身份加入SemiAnalysis,通过投入1万美元在3小时内进行编译器模糊测试(compiler fuzzing),发现了AMD GPU LLVM、x86 LLVM及NVPTX编译器中的数十个bug。该项目揭示了GPU vs CPU编译器测试的巨大差距,并展示了如何利用LLM阅读代码来发现漏洞。此外,UltraCode模式对代码审计效率影响显著。
Ex-OpenAI Tech Lead, Justin Lebar joins SemiAnalysis as an Visiting Fellow to Burn $10,000 in 3 hours to find dozens of AMDGPU LLVM, x86 LLVM, NVPTX bugs
00:00 - Intro & Justin's background 00:59 - How compiler fuzzing works 01:56 - Why we did this project 02:48 - The gap in GPU vs. CPU compiler testing 04:13 - The major AMD & x86 bugs we found 05:38 - Using LLMs to read code & find vulnerabilities 07:56 - The impact of UltraCode mode 12:18 - Doing this without AI (Time & manual limits) 15:03 - The future of AI in software development 16:17 - What's next + key takeaways for devs