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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Position: The Need for Ultrafast Training · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2602.02005/</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/2602.02005/feed.xml" rel="self" type="application/rss+xml" /><item><title>Position: The Need for Ultrafast Training — mentioned by ag2718</title><link>https://news.ycombinator.com/item?id=48467206</link><guid isPermaLink="false">urn:hackerpapers:mention:2602.02005:48467206</guid><pubDate>Tue, 09 Jun 2026 20:26:08 GMT</pubDate><description>&lt;p&gt;Yes, this work is focused on accelerating very small models, typically for real-time systems that require extremely low power or low latency. One primary application of this work is in high-energy physics (https://home.cern/smarter-decisions-at-the-speed-of-collisio...). Ultrafast and real-time learning is also very applicable for problems in quantum computing, plasma control, etc. (https://arxiv.org/pdf/2602.02005).&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2602.02005/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.AR</category></item></channel></rss>
