Karpathy shared how he builds a local AI knowledge base

Karpathy 分享了他如何构建本地的 AI 知识库

Karpathy uses Obsidian and local Markdown to build a personal wiki, stores source material in a RAW folder, then has an LLM generate summaries, indexes, concept pages, links, and visualizations. The setup can answer questions over the wiki and write reports or new files, but the post also says AI-generated content can pollute the corpus and should be separated from trusted sources; the post does not disclose the model, scale, or automation details.

Why it matters: HKR-H and HKR-R land because Karpathy’s local-first wiki workflow is inherently clickable and discussable for AI practitioners. HKR-K lands on the RAW→LLM→summary/index/link mechanism, but missing model, corpus size, and automation details keep it in the mid-70s.