<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Quantum Machine Learning using the ZXW-Calculus · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2210.11523/</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/2210.11523/feed.xml" rel="self" type="application/rss+xml" /><item><title>Quantum Machine Learning using the ZXW-Calculus — mentioned by StackOverlord</title><link>https://news.ycombinator.com/item?id=36738166</link><guid isPermaLink="false">urn:hackerpapers:mention:2210.11523:36738166</guid><pubDate>Sat, 15 Jul 2023 16:11:14 GMT</pubDate><description>&lt;p&gt;Quantinuum is already tackling NLP question-answering tasks, it runs on quantum hardware. The quantum categorial crowd is adamant they&amp;#x27;ll surpass ChatGPT (the big promise iirc is that it will scale linearly with context length, GPT scales quadratically). For instance see this tweet by Quantinuum head of research and this burgeoning field&amp;#x27;s main rock: https://twitter.com/coecke/status/1655695990739927040?s=20 Coecke went from supervising dozen of thesis at Oxford Quantum (logic) Group to preparing summer camps for high school pupils this year. It&amp;#x27;s also taking off socially/academically, and…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2210.11523/"&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>
