<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Determinism on Matt Suiche</title><link>https://www.msuiche.com/tags/determinism/</link><description>Recent content in Determinism on Matt Suiche</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Sun, 14 Sep 2025 00:00:00 +0200</lastBuildDate><atom:link href="https://www.msuiche.com/tags/determinism/index.xml" rel="self" type="application/rss+xml"/><item><title>The Hidden Math Bug That Makes AI Unpredictable</title><link>https://www.msuiche.com/posts/the-hidden-math-bug-that-makes-ai-unpredictable/</link><pubDate>Sun, 14 Sep 2025 00:00:00 +0200</pubDate><guid>https://www.msuiche.com/posts/the-hidden-math-bug-that-makes-ai-unpredictable/</guid><description>&lt;p&gt;This &lt;a href="https://x.com/awnihannun/status/1966953027451118012" target="_blank" rel="noopener"&gt;tweet from Awni Hannun&lt;/a&gt; demonstrates in one line of MLX code the nondeterminism phenomenon detailed in &lt;a href="https://thinkingmachines.ai/blog/defeating-nondeterminism-in-llm-inference/" target="_blank" rel="noopener"&gt;Thinking Machines&amp;rsquo; research&lt;/a&gt;. We will explore the PyTorch equivalent that reveals a fundamental issue in AI systems, because I&amp;rsquo;ve found that tweet extremely helpful to understand what the original blogpost was about.&lt;/p&gt;
&lt;blockquote class="twitter-tweet"&gt;&lt;p lang="en" dir="ltr"&gt;Here&amp;#39;s a one-line code summary in MLX of the &lt;a href="https://x.com/thinkymachines?ref_src=twsrc%5Etfw"&gt;@thinkymachines&lt;/a&gt; blog post on non-determinism in LLM inference.&lt;br&gt;&lt;br&gt;I&amp;#39;d guess the difference is larger the lower the precision, as you get larger affects from non-associativity of FP math.&lt;br&gt;&lt;br&gt;Interestingly, that implies that training at low… &lt;a href="https://t.co/jYcDK9GiLn"&gt;pic.twitter.com/jYcDK9GiLn&lt;/a&gt;&lt;/p&gt;</description></item></channel></rss>