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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Accelerated Analog Neuromorphic Computing · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2003.11996/</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/2003.11996/feed.xml" rel="self" type="application/rss+xml" /><item><title>Accelerated Analog Neuromorphic Computing — mentioned by hnaccount_rng</title><link>https://news.ycombinator.com/item?id=40363726</link><guid isPermaLink="false">urn:hackerpapers:mention:2003.11996:40363726</guid><pubDate>Wed, 15 May 2024 06:28:14 GMT</pubDate><description>&lt;p&gt;You can get 8bit analog signal resolution reasonablyish easyish. The Hagen mode [1] of BrainScaleS [2] is essentially that. But.. yeah. No way in hell you are getting more than 16bit with that kind of technology, let alone more. And those things are huge which lead to very small network sizes. This is partially due to the fabrication node, but also simply because there is even less well developed tooling for analog circuits compared to digital ones compared to software compilers [1] https://electronicvisions.github.io/documentation-brainscale... [2]…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2003.11996/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.NE</category></item></channel></rss>
