Kernel development and machine learning seem like vastly different areas of
endeavor; there are not, yet, stories circulating about the vibe-coding of
new memory-management algorithms.  There may well be places where machine
learning (and large language models — LLMs — in particular) prove to be
helpful on the edges of the kernel project, though.  At the <a href="https://events.linuxfoundation.org/open-source-summit-north-america/">2025
North-American edition of the Open Source Summit</a>, Sasha Levin presented
some of the work he has done putting LLMs to work to make the kernel better