<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Liquid-Neural-Networks on BRYSGO</title><link>https://www.brysgo.com/tags/liquid-neural-networks/</link><description>Recent content in Liquid-Neural-Networks on BRYSGO</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Thu, 01 Oct 2026 14:04:18 +0000</lastBuildDate><atom:link href="https://www.brysgo.com/tags/liquid-neural-networks/index.xml" rel="self" type="application/rss+xml"/><item><title>What a 302-Neuron Worm Knows That a 100-Billion-Parameter Model Doesn't</title><link>https://www.brysgo.com/post/2026-10-01-what-a-302-neuron-worm-knows-that-a-100-billion-parameter-model-doesn-/</link><pubDate>Thu, 01 Oct 2026 14:04:18 +0000</pubDate><guid>https://www.brysgo.com/post/2026-10-01-what-a-302-neuron-worm-knows-that-a-100-billion-parameter-model-doesn-/</guid><description>&lt;p&gt;What a 302-Neuron Worm Knows That a 100-Billion-Parameter Model Doesn&amp;rsquo;t&lt;/p&gt;&#10;&lt;p&gt;C. elegans has 302 neurons. That&amp;rsquo;s not a typo, and it&amp;rsquo;s not a metaphor for something bigger — it&amp;rsquo;s the whole nervous system, wired the same way in every individual, mapped down to the synapse since the 1980s. And yet this worm navigates chemical gradients, avoids danger, remembers, and adapts to novel environments well enough that researchers have spent forty years failing to fully replicate what it does with software. Meanwhile we&amp;rsquo;ve built driving models with parameter counts a million times higher that still get confused by a shadow on the road. If scale were really the answer, this shouldn&amp;rsquo;t be a fair fight.&lt;/p&gt;</description></item></channel></rss>