<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Latent Dynamics</title><link>https://latentdynamics.io/</link><description>Recent content on Latent Dynamics</description><generator>Hugo -- 0.156.0</generator><language>en-us</language><lastBuildDate>Fri, 20 Mar 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://latentdynamics.io/index.xml" rel="self" type="application/rss+xml"/><item><title>Precision: The Hidden Currency of Intelligence</title><link>https://latentdynamics.io/posts/precision-bayesian-inference/</link><pubDate>Fri, 20 Mar 2026 00:00:00 +0000</pubDate><guid>https://latentdynamics.io/posts/precision-bayesian-inference/</guid><description>&lt;p&gt;Your language model scored well on the benchmark. It predicted the next token with impressive accuracy across a held-out test set. Now you deploy it. It hallucinates confidently on inputs that are slightly out of distribution. It has no mechanism to distinguish a confident extrapolation from a &lt;em&gt;lucky interpolation&lt;/em&gt;. It treats a familiar paraphrase and a genuinely novel question with the same apparent certainty.&lt;/p&gt;
&lt;p&gt;You are not losing on prediction. You are losing on something the benchmark doesn&amp;rsquo;t measure.&lt;/p&gt;</description></item><item><title>About</title><link>https://latentdynamics.io/about/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://latentdynamics.io/about/</guid><description/></item></channel></rss>