<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Philosophy on hxwk</title><link>https://hxwk.xyz/tags/philosophy/</link><description>Recent content in Philosophy on hxwk</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Thu, 17 Sep 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://hxwk.xyz/tags/philosophy/index.xml" rel="self" type="application/rss+xml"/><item><title>Philosophizing in ML</title><link>https://hxwk.xyz/philosophizing-in-ml/</link><pubDate>Thu, 17 Sep 2026 00:00:00 +0000</pubDate><guid>https://hxwk.xyz/philosophizing-in-ml/</guid><description>&lt;p&gt;Machine learning, like other science and engineering fields, has proofs,&#10;experiments and rigorous math, but it also leaves plenty of room for&#10;philosophizing about the most fundamental and hard-to-explain things,&#10;like why it works in the first place.&lt;/p&gt;&#10;&lt;p&gt;I&amp;rsquo;ve tried to sort this out in my head, with my limited knowledge of the&#10;field, and after a few minutes of thinking in the shower I came up with&#10;an explanation that may not be rigorous, but is a satisfying start.&lt;/p&gt;</description></item></channel></rss>