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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>APRIL: Active Preference-learning based Reinforcement Learning · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1208.0984/</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/1208.0984/feed.xml" rel="self" type="application/rss+xml" /><item><title>APRIL: Active Preference-learning based Reinforcement Learning — mentioned by godelski</title><link>https://news.ycombinator.com/item?id=44859864</link><guid isPermaLink="false">urn:hackerpapers:mention:1208.0984:44859864</guid><pubDate>Mon, 11 Aug 2025 01:11:29 GMT</pubDate><description>&lt;p&gt;Jack has a lot of really bad takes and frequently makes lots of mistakes. Honestly, I don&amp;#x27;t know why people take him seriously. I mean you can go read his blog post that&amp;#x27;s pinned where he argues that there&amp;#x27;s no new ideas and it is all data. He makes the argument that architecture doesn&amp;#x27;t matter, which is just so demonstrably false that it is laughable. He&amp;#x27;s a scale maximalist. I also expect an AI researcher from a top university to not make such wild mistakes &amp;gt; 3. RLHF: first proposed (to my knowledge) in the InstructGPT paper from OpenAI in 2022 I mean if you go read the instruct paper on…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1208.0984/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item></channel></rss>
