<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Machine Learning on BeyondTopics</title><link>https://www.beyondtopics.com/en/tags/machine-learning/</link><description>Recent content in Machine Learning on BeyondTopics</description><generator>Hugo</generator><language>en</language><lastBuildDate>Sat, 14 Nov 2026 09:18:35 +0100</lastBuildDate><atom:link href="https://www.beyondtopics.com/en/tags/machine-learning/index.xml" rel="self" type="application/rss+xml"/><item><title>LLM Costs: A Practical Guide to Reducing Them</title><link>https://www.beyondtopics.com/en/llm-costs-a-practical-guide-to-reducing-them/</link><pubDate>Sat, 14 Nov 2026 09:18:35 +0100</pubDate><guid>https://www.beyondtopics.com/en/llm-costs-a-practical-guide-to-reducing-them/</guid><description>&lt;p&gt;The integration of large language models into business processes has transformed exciting prototypes into critical infrastructure. However, when an application moves from the testing phase to large-scale use with thousands of daily users, the monthly bill from compute providers or API platforms can grow at unsustainable rates. Without a precise strategy for controlling consumption, the profitability of a digital product risks being compromised before it even reaches commercial maturity.&lt;/p&gt;</description></item></channel></rss>