<rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Hacker News: nhmllms</title><link>https://news.ycombinator.com/user?id=nhmllms</link><description>Hacker News RSS</description><docs>https://hnrss.org/</docs><generator>hnrss v2.1.1</generator><lastBuildDate>Sat, 30 May 2026 22:38:24 +0000</lastBuildDate><atom:link href="https://hnrss.org/user?id=nhmllms" rel="self" type="application/rss+xml"></atom:link><item><title><![CDATA[New comment by nhmllms in "Reflection 70B, the top open-source model"]]></title><description><![CDATA[
<p>This make me think we should be introducing 'tokens required to answer questions correctly' dimension to each metric. Since letting the model think more verbosely is essentially giving it more compute and memory to answer the question correctly.
(not that this is a bad thing, but I would be curious if other models get the answer correctly with the first couple of tokens, or after hundreds of reasoning)</p>
]]></description><pubDate>Fri, 06 Sep 2024 10:02:03 +0000</pubDate><link>https://news.ycombinator.com/item?id=41464599</link><dc:creator>nhmllms</dc:creator><comments>https://news.ycombinator.com/item?id=41464599</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=41464599</guid></item></channel></rss>