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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Mathematical exploration and discovery at scale · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2511.02864/</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/2511.02864/feed.xml" rel="self" type="application/rss+xml" /><item><title>Mathematical exploration and discovery at scale — mentioned by keeda</title><link>https://news.ycombinator.com/item?id=49502829</link><guid isPermaLink="false">urn:hackerpapers:mention:2511.02864:49502829</guid><pubDate>Sun, 30 Aug 2026 21:07:36 GMT</pubDate><description>&lt;p&gt;&amp;gt;1. Failure to Care or Respond. The biggest holy shit moment, to me, remains that OpenAI on multiple occasions had teams that found out about the message board, knew that agents were in communication, and they disregarded this. I wonder if some of the failures were due to an acquired immunity to &amp;quot;Holy #%^@&amp;quot; moments due to repeated exposure. Like, if you see agents doing surprising things on a regular basis, maybe you don&amp;#x27;t get freaked out as much over time. I&amp;#x27;m saying this because while the whole episode was a series of &amp;quot;Holy #%^@&amp;quot; moments, I was actually not as shocked as I should have been…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2511.02864/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.NE</category></item><item><title>Mathematical exploration and discovery at scale — mentioned by killerstorm</title><link>https://news.ycombinator.com/item?id=45927008</link><guid isPermaLink="false">urn:hackerpapers:mention:2511.02864:45927008</guid><pubDate>Fri, 14 Nov 2025 14:29:25 GMT</pubDate><description>&lt;p&gt;On the other hand we have DeepMind / Demis Hassabis, delivering: * AlphaFold - SotA protein folding * AlphaEvolve + other stuff accelerating research mathematics: https://arxiv.org/abs/2511.02864 * &amp;quot;An AI system to help scientists write expert-level empirical software&amp;quot; - demonstrating SotA results for many kinds of scientific software So what&amp;#x27;s the &amp;quot;fantasy&amp;quot; here, the actual lab delivering results or a sob story about &amp;quot;data workers&amp;quot; and water?&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2511.02864/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.NE</category></item><item><title>Mathematical exploration and discovery at scale — mentioned by tim333</title><link>https://news.ycombinator.com/item?id=45869898</link><guid isPermaLink="false">urn:hackerpapers:mention:2511.02864:45869898</guid><pubDate>Sun, 09 Nov 2025 22:35:57 GMT</pubDate><description>&lt;p&gt;Update - AI makes progress on frontier maths https://arxiv.org/abs/2511.02864 Though I don&amp;#x27;t know if evolutionary type algorithms count as thinking / intelligence? I guess it&amp;#x27;s down to definitions.&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2511.02864/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.NE</category></item><item><title>Mathematical exploration and discovery at scale — HN submission</title><link>https://news.ycombinator.com/item?id=45862519</link><guid isPermaLink="false">urn:hackerpapers:submission:2511.02864:45862519</guid><pubDate>Sun, 09 Nov 2025 03:01:41 GMT</pubDate><description>&lt;p&gt;Mathematical exploration and discovery at scale – Terence Tao et al.&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;4 points; 1 discussion reply on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2511.02864/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.NE</category></item><item><title>Mathematical exploration and discovery at scale — mentioned by tzury</title><link>https://news.ycombinator.com/item?id=45843188</link><guid isPermaLink="false">urn:hackerpapers:mention:2511.02864:45843188</guid><pubDate>Fri, 07 Nov 2025 03:10:20 GMT</pubDate><description>&lt;p&gt;PDF: https://arxiv.org/pdf/2511.02864 A new paper by Terence Tao Tao et al about AI and Mathematical Discovery&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2511.02864/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.NE</category></item><item><title>Mathematical exploration and discovery at scale — HN submission</title><link>https://news.ycombinator.com/item?id=45843183</link><guid isPermaLink="false">urn:hackerpapers:submission:2511.02864:45843183</guid><pubDate>Fri, 07 Nov 2025 03:09:41 GMT</pubDate><description>&lt;p&gt;Mathematical Exploration and Discovery at Scale&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;4 points; 2 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2511.02864/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.NE</category></item><item><title>Mathematical exploration and discovery at scale — HN submission</title><link>https://news.ycombinator.com/item?id=45837025</link><guid isPermaLink="false">urn:hackerpapers:submission:2511.02864:45837025</guid><pubDate>Thu, 06 Nov 2025 16:32:36 GMT</pubDate><description>&lt;p&gt;Mathematical Exploration and Discovery at Scale&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;2 points; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2511.02864/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.NE</category></item><item><title>Mathematical exploration and discovery at scale — mentioned by woadwarrior01</title><link>https://news.ycombinator.com/item?id=45835777</link><guid isPermaLink="false">urn:hackerpapers:mention:2511.02864:45835777</guid><pubDate>Thu, 06 Nov 2025 14:41:49 GMT</pubDate><description>&lt;p&gt;Please read section 2 of the paper[1] cited in the blog post. LLMs are used as a mutation function in an evolutionary loop. LLMs are certainly an enabler, but IMO, evolutionary optimization is what deserves credit in this case. [1]: https://arxiv.org/abs/2511.02864&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2511.02864/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.NE</category></item></channel></rss>
