<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Practical guides on Deterministic AI</title><link>https://www.deterministicai.org/topics/</link><description>Recent content in Practical guides on Deterministic AI</description><generator>Hugo -- gohugo.io</generator><language>en-us</language><lastBuildDate>Sun, 11 Oct 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://www.deterministicai.org/topics/index.xml" rel="self" type="application/rss+xml"/><item><title>How do you test whether an AI system is deterministic?</title><link>https://www.deterministicai.org/topics/how-to-test-determinism/</link><pubDate>Sun, 11 Oct 2026 00:00:00 +0000</pubDate><guid>https://www.deterministicai.org/topics/how-to-test-determinism/</guid><description>What claim are you testing? Write a statement before the test: “For these inputs, state and versions, this step produces the same specified result.” Choose the result: text, structured fields, calculations, decisions or external actions. Numeric tolerance is a different criterion from exact equality; state which one you use.
This protocol is our practical recommendation. Its emphasis on environment boundaries follows PyTorch&amp;rsquo;s documented limits across releases, commits, platforms and CPU/GPU. Read the source.</description></item><item><title>Is an LLM deterministic?</title><link>https://www.deterministicai.org/topics/is-an-llm-deterministic/</link><pubDate>Sun, 11 Oct 2026 00:00:00 +0000</pubDate><guid>https://www.deterministicai.org/topics/is-an-llm-deterministic/</guid><description>Why is the prompt only part of the input? Thinking Machines Lab describes practical LLM inference that can vary even when sampling is theoretically deterministic at temperature zero. Its introduction separates the sampling setting from the computation used to produce the result. Read the introduction.
PyTorch&amp;rsquo;s reproducibility guidance makes another boundary explicit: identical seeds do not guarantee agreement across CPU and GPU, releases or platforms. These are limits of the stated guarantee, not a claim that every pair of runs must differ.</description></item><item><title>What is deterministic AI?</title><link>https://www.deterministicai.org/topics/what-is-deterministic-ai/</link><pubDate>Sun, 11 Oct 2026 00:00:00 +0000</pubDate><guid>https://www.deterministicai.org/topics/what-is-deterministic-ai/</guid><description>What does the definition cover? This is the working definition used by this reference. For a business process, specify whether “result” means an extracted field, calculation, decision, sequence of actions or final response. Also specify the state and versions included in “same input.”
Environment matters in real computation. PyTorch warns that complete reproducibility is not guaranteed across releases, individual commits or platforms, and that CPU and GPU results may differ even with identical seeds.</description></item></channel></rss>