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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Prompt-to-Parts: Generative AI for Physical Assembly and Scalable Instructions · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2512.15743/</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/2512.15743/feed.xml" rel="self" type="application/rss+xml" /><item><title>Prompt-to-Parts: Generative AI for Physical Assembly and Scalable Instructions — mentioned by vunderba</title><link>https://news.ycombinator.com/item?id=49938219</link><guid isPermaLink="false">urn:hackerpapers:mention:2512.15743:49938219</guid><pubDate>Fri, 02 Oct 2026 20:29:09 GMT</pubDate><description>&lt;p&gt;Nice job. I actually read a paper on Arxiv last year about this exact thing - using LLMs to drive model building through LDraw that might be worth reading [1]. They had some interesting experiments like giving the LLM a fixed set of parts as a constraint and asked it to &amp;quot;build&amp;quot; tools out of those available lego. I think they were using Opus 4.5 so I&amp;#x27;m sure with even more powerful models it&amp;#x27;ll be even better. [1] - https://arxiv.org/pdf/2512.15743&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2512.15743/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.AI</category></item></channel></rss>
