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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Scaling Synthetic Data Creation with 1,000,000,000 Personas · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2406.20094/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:27:26 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/2406.20094/feed.xml" rel="self" type="application/rss+xml" /><item><title>Scaling Synthetic Data Creation with 1,000,000,000 Personas — HN submission</title><link>https://news.ycombinator.com/item?id=42387852</link><guid isPermaLink="false">urn:hackerpapers:submission:2406.20094:42387852</guid><pubDate>Wed, 11 Dec 2024 14:13:34 GMT</pubDate><description>&lt;p&gt;LLM Synthetic Conversations Unlock?&lt;/p&gt;&lt;p&gt;I&amp;#x27;m looking for experts that have similar line of research that I find quite interesting. I&amp;#x27;m a ML eng with ~10 yrs of experience but previously I was a psychologist (unusual transition I know ha). Reading over the research, I kept thinking LLM personas were underutilized or not fully understood. I finally found the Qwen paper on 1 Billion personas to capture more complete &amp;amp; diverse stores of information within a FM. The paper intention was for synthetic data generation for LLM training data. This paper was very cool and triggered my hypothesis that distinct personas collaborating with each…&lt;/p&gt;&lt;p&gt;1 point; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2406.20094/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item></channel></rss>
