<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>LLM on Ivo Gasparini</title><link>https://ivogasparini.ch/tags/llm/</link><description>Recent content in LLM on Ivo Gasparini</description><generator>Hugo</generator><language>en</language><copyright>© 2025, Ivo Gasparini</copyright><lastBuildDate>Wed, 17 Sep 2025 00:00:00 +0000</lastBuildDate><atom:link href="https://ivogasparini.ch/tags/llm/index.xml" rel="self" type="application/rss+xml"/><item><title>The weird stuff going on in LLM-land</title><link>https://ivogasparini.ch/blog/weird-llm/</link><pubDate>Wed, 17 Sep 2025 00:00:00 +0000</pubDate><guid>https://ivogasparini.ch/blog/weird-llm/</guid><description>&lt;p&gt;Scaling &lt;a href="https://arxiv.org/pdf/1706.03762" target="_blank" rel="noopener noreferrer"&gt;transformers&lt;/a&gt; (the leading model architecture in AI) to infinity and training them on basically the entirety of human written knowledge has led to the AI revolution with the &lt;a href="https://en.wikipedia.org/wiki/Large_language_model" target="_blank" rel="noopener noreferrer"&gt;LLMs&lt;/a&gt; we know and have mixed feelings about today. While what intelligence is and how it applies to LLMs is a topic far too vast for a single blog post, if we take LLMs at face value, they sure strike us with brilliance from time to time. What is really going on in these models? Is it just very high-dimensional pattern matching? Is the brilliance just a reflection of our own? Do we fundamentally function the same?&lt;/p&gt;</description></item></channel></rss>