<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Simulation on GiveMeTechnology</title><link>https://givemetechnology.com/tags/simulation/</link><description>Recent content in Simulation on GiveMeTechnology</description><generator>Hugo -- gohugo.io</generator><language>en-us</language><lastBuildDate>Thu, 26 Mar 2026 15:54:11 +0000</lastBuildDate><atom:link href="https://givemetechnology.com/tags/simulation/index.xml" rel="self" type="application/rss+xml"/><item><title>GM Trains Self-Driving AI 50,000x Faster Than Real Time</title><link>https://givemetechnology.com/2026/03/gm-trains-self-driving-ai-50000x-faster-than-real-time/</link><pubDate>Thu, 26 Mar 2026 15:54:11 +0000</pubDate><guid>https://givemetechnology.com/2026/03/gm-trains-self-driving-ai-50000x-faster-than-real-time/</guid><description>What Happened General Motors has revealed its approach to training autonomous driving AI at unprecedented speeds, using simulation environments that operate 50,000 times faster than real-time driving conditions. The automaker is combining large-scale simulation, reinforcement learning, and foundation-model-based reasoning to develop what it calls &amp;ldquo;scalable driving AI.&amp;rdquo;
The system specifically targets what engineers call the &amp;ldquo;long tail&amp;rdquo; problem in autonomous driving—the rare, ambiguous, and unexpected events that occur infrequently but pose the greatest safety challenges.</description></item></channel></rss>