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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Quantum processor-inspired machine learning in the biomedical sciences · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1909.06206/</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/1909.06206/feed.xml" rel="self" type="application/rss+xml" /><item><title>Quantum processor-inspired machine learning in the biomedical sciences — mentioned by ArtWomb</title><link>https://news.ycombinator.com/item?id=21334965</link><guid isPermaLink="false">urn:hackerpapers:mention:1909.06206:21334965</guid><pubDate>Wed, 23 Oct 2019 14:29:41 GMT</pubDate><description>&lt;p&gt;Last line of the paper is destined to resonate into history: &amp;quot;We’re only one creative algorithm away from valuable near-term applications&amp;quot; Reminds me of the last line from Watson and Cricks 1953 Structure of DNA paper: &amp;quot;It has not escaped our notice that the specific pairing we have postulated immediately suggests a possible copying mechanism for the genetic material&amp;quot; ;) I bring up genomics specifically because the main profit driver appears to be biotech. Predicting near-instantaneously whether regulatory proteins bind to a target genome site could revolutionize drug discovery. And while…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1909.06206/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>quant-ph</category></item></channel></rss>
