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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>P=NP · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2405.08051/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/2405.08051/feed.xml" rel="self" type="application/rss+xml" /><item><title>P=NP — mentioned by andylizf</title><link>https://news.ycombinator.com/item?id=44841209</link><guid isPermaLink="false">urn:hackerpapers:mention:2405.08051:44841209</guid><pubDate>Fri, 08 Aug 2025 20:14:45 GMT</pubDate><description>&lt;p&gt;This is fantastic work. The focus on a local, sandboxed execution layer is a huge piece of the puzzle for a private AI workspace. The `coderunner` tool looks incredibly useful. A complementary challenge is the knowledge layer: making the AI aware of your personal data (emails, notes, files) via RAG. As soon as you try this on a large scale, storage becomes a massive bottleneck. A vector database for years of emails can easily exceed 50GB. (Full disclosure: I&amp;#x27;m part of the team at Berkeley that tackled this). We built LEANN, a vector index that cuts storage by ~97% by not storing the…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2405.08051/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CC</category></item></channel></rss>
