<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Recursive-Self-Improvement on Greycloak</title><link>https://greycloak.com/tags/recursive-self-improvement/</link><description>Recent content in Recursive-Self-Improvement on Greycloak</description><generator>Hugo -- gohugo.io</generator><language>en-us</language><copyright>Copyright © 2023, Vince Wadhwani; all rights reserved.</copyright><lastBuildDate>Wed, 16 Sep 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://greycloak.com/tags/recursive-self-improvement/index.xml" rel="self" type="application/rss+xml"/><item><title>China's open-source labs are racing toward self-improving AI</title><link>https://greycloak.com/post/2026-09-16-the-race-toward-recursive-self-improvement-heats-up/</link><pubDate>Wed, 16 Sep 2026 00:00:00 +0000</pubDate><guid>https://greycloak.com/post/2026-09-16-the-race-toward-recursive-self-improvement-heats-up/</guid><description>
&lt;p&gt;Any company betting its roadmap on an AI slowdown should reconsider the timeline. The pacing proposals dominating the industry conversation this month all assume the major labs can coordinate to slow the release of ever-more-capable models. That assumption weakens the moment a lab outside that circle announces it is building the exact capability the slowdown is meant to contain. This week, one did, and the practical takeaway for planning is that a regulatory or voluntary pause is unlikely to actually stop the technology from advancing.&lt;/p&gt;</description></item></channel></rss>