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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>General Intelligence Requires Rethinking Exploration · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2211.07819/</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/2211.07819/feed.xml" rel="self" type="application/rss+xml" /><item><title>General Intelligence Requires Rethinking Exploration — mentioned by visarga</title><link>https://news.ycombinator.com/item?id=34298448</link><guid isPermaLink="false">urn:hackerpapers:mention:2211.07819:34298448</guid><pubDate>Sun, 08 Jan 2023 12:13:43 GMT</pubDate><description>&lt;p&gt;There are two ways to learn: from imitation (language models are stochastic parrots) and from validation (problem solving, playing games). Many people only remember the first and forget the second. But the second one has the key to increasing intelligence. I don&amp;#x27;t know what the authors mean by &amp;quot;current algorithmic frame of AI research&amp;quot; because it is very diverse. But evolutionary methods work well with neural networks, they are not just next token predictors. &amp;gt; Evolution through Large Models https://arxiv.org/abs/2206.08896 It is true that simply using a dataset or a bunch of environments is…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2211.07819/"&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>
