<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Abstraction on English AI Terms Dictionary</title><link>https://terms-en.ai-term-hub.com/en/tags/abstraction/</link><description>Recent content in Abstraction on English AI Terms Dictionary</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Sat, 18 Jul 2026 11:44:44 +0000</lastBuildDate><atom:link href="https://terms-en.ai-term-hub.com/en/tags/abstraction/index.xml" rel="self" type="application/rss+xml"/><item><title>high-level</title><link>https://terms-en.ai-term-hub.com/en/terms/high_level/</link><pubDate>Sat, 18 Jul 2026 09:38:34 +0000</pubDate><guid>https://terms-en.ai-term-hub.com/en/terms/high_level/</guid><description>&lt;h2 id="definition">Definition&lt;/h2>
&lt;p>In AI, &amp;lsquo;high-level&amp;rsquo; denotes abstractions that simplify complex processes. High-level languages (like Python) or APIs allow developers to build models without managing memory or hardware specifics. Similarly, high-level features in deep learning represent complex patterns (e.g., &amp;lsquo;face&amp;rsquo;) rather than raw pixels. This abstraction enhances productivity and accessibility, enabling focus on problem-solving rather than infrastructure management.&lt;/p>
&lt;h3 id="summary">Summary&lt;/h3>
&lt;p>Refers to abstract representations or programming interfaces that hide low-level implementation details from the user.&lt;/p></description></item></channel></rss>