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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Cognitive Psychology for Deep Neural Networks: A Shape Bias Case Study · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1706.08606/</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/1706.08606/feed.xml" rel="self" type="application/rss+xml" /><item><title>Cognitive Psychology for Deep Neural Networks: A Shape Bias Case Study — mentioned by runarberg</title><link>https://news.ycombinator.com/item?id=46177942</link><guid isPermaLink="false">urn:hackerpapers:mention:1706.08606:46177942</guid><pubDate>Sun, 07 Dec 2025 00:13:50 GMT</pubDate><description>&lt;p&gt;Yeah, I looked it up yesterday and saw that artificial cognition is a thing, though I must say I am not a fan and I certainly hope this term does not catch. We are already knee deep in bad terminology because of artificial intelligence (“intelligence” already being extremely problematic even with out the “artificial” qualifier in psychology) and machine learning (the latter being infinitely better but still not without issues). If you can‘t tell I find issues when terms are taken from psychology and applied to statistics. The terminology should flow in the other direction, from statistics and…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1706.08606/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>stat.ML</category></item><item><title>Cognitive Psychology for Deep Neural Networks: A Shape Bias Case Study — mentioned by deepnotderp</title><link>https://news.ycombinator.com/item?id=14791415</link><guid isPermaLink="false">urn:hackerpapers:mention:1706.08606:14791415</guid><pubDate>Mon, 17 Jul 2017 19:06:51 GMT</pubDate><description>&lt;p&gt;I&amp;#x27;d like to offer a somewhat contrasting viewpoint (although this might not sit well with people): deep nets aren&amp;#x27;t AGI, but they&amp;#x27;re pretty damn good. There&amp;#x27;s mounting evidence that they learn similar to how we do, at least in vision; https://arxiv.org/abs/1706.08606 and https://www.nature.com/articles/srep27755 There&amp;#x27;s quite a few others but these were the most readily available papers. Are deep nets AGI? No, but they&amp;#x27;re a lot better than Mr.Chollet gives them credit for.&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1706.08606/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>stat.ML</category></item><item><title>Cognitive Psychology for Deep Neural Networks: A Shape Bias Case Study — HN submission</title><link>https://news.ycombinator.com/item?id=14698163</link><guid isPermaLink="false">urn:hackerpapers:submission:1706.08606:14698163</guid><pubDate>Tue, 04 Jul 2017 20:43:18 GMT</pubDate><description>&lt;p&gt;Cognitive Psychology for Deep Neural Networks (DeepMind)&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/1706.08606/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>stat.ML</category></item></channel></rss>
