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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Implementing Tensor Logic: Unifying Datalog and Neural Reasoning via Tensor Contraction · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2601.17188/</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/2601.17188/feed.xml" rel="self" type="application/rss+xml" /><item><title>Implementing Tensor Logic: Unifying Datalog and Neural Reasoning via Tensor Contraction — mentioned by AlotOfReading</title><link>https://news.ycombinator.com/item?id=48902416</link><guid isPermaLink="false">urn:hackerpapers:mention:2601.17188:48902416</guid><pubDate>Tue, 14 Jul 2026 04:51:30 GMT</pubDate><description>&lt;p&gt;I don&amp;#x27;t want to rain on discovering a genuinely cool bit of theory, but it&amp;#x27;s not &amp;quot;new&amp;quot; per se. The equivalence with Einstein summation was noted in this paper [0]. Sandia labs wrote an SQL database based around graphBLAS called TenSQL a few years back. And something similar to your idea of relational algebra as the basis for AI had a paper published earlier this year [1], naming it Tensor Logic. Are all of these common operations secretly relational, just with the wrong data model? Sadly not, but you can get a long way before you find the limits. Modern databases are very well optimized for…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2601.17188/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.AI</category></item></channel></rss>
