<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>AI Basics on AI VOID</title><link>https://ai-blog.noorshomelab.dev/tags/ai-basics/</link><description>Recent content in AI Basics on AI VOID</description><generator>Hugo</generator><language>en</language><lastBuildDate>Sun, 18 Jan 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://ai-blog.noorshomelab.dev/tags/ai-basics/index.xml" rel="self" type="application/rss+xml"/><item><title>Data: The Fuel for AI&amp;#39;s Brain</title><link>https://ai-blog.noorshomelab.dev/ai-ml-journey-2026/data-the-fuel-of-ai/</link><pubDate>Sun, 18 Jan 2026 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/ai-ml-journey-2026/data-the-fuel-of-ai/</guid><description>&lt;h2 id="chapter-3-data-the-fuel-for-ais-brain"&gt;Chapter 3: Data: The Fuel for AI&amp;rsquo;s Brain&lt;/h2&gt;
&lt;p&gt;Welcome back, future AI explorer! You&amp;rsquo;re doing an amazing job diving into these exciting new ideas. In our last chapters, we started to understand what Artificial Intelligence (AI) and Machine Learning (ML) are all about. We imagined AI as a super-smart &amp;ldquo;thinking helper&amp;rdquo; and ML as the way we &amp;ldquo;teach&amp;rdquo; that helper by showing it examples.&lt;/p&gt;
&lt;p&gt;Today, we&amp;rsquo;re going to talk about the most crucial ingredient in this whole teaching process: &lt;strong&gt;data&lt;/strong&gt;. Think of data as the &lt;strong&gt;fuel&lt;/strong&gt; for AI&amp;rsquo;s brain, or even better, the &lt;strong&gt;ingredients&lt;/strong&gt; for a super-smart chef. Just like a chef can&amp;rsquo;t cook without ingredients, an AI can&amp;rsquo;t learn or make decisions without data. It&amp;rsquo;s truly the foundation of everything!&lt;/p&gt;</description></item><item><title>Core Concepts: Prompts, Completions, and Parameters</title><link>https://ai-blog.noorshomelab.dev/any-llm-guide-2025/core-concepts/</link><pubDate>Tue, 30 Dec 2025 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/any-llm-guide-2025/core-concepts/</guid><description>&lt;h2 id="introduction-to-llm-core-concepts"&gt;Introduction to LLM Core Concepts&lt;/h2&gt;
&lt;p&gt;Welcome back, future AI architect! In the previous chapter, we successfully set up our &lt;code&gt;any-llm&lt;/code&gt; environment and even ran our very first LLM interaction. That&amp;rsquo;s a huge step! But what really happened behind the scenes? How did the AI know what to do?&lt;/p&gt;
&lt;p&gt;In this chapter, we&amp;rsquo;re going to pull back the curtain and explore the foundational concepts that power every interaction with a Large Language Model: &lt;strong&gt;Prompts&lt;/strong&gt;, &lt;strong&gt;Completions&lt;/strong&gt;, and &lt;strong&gt;Parameters&lt;/strong&gt;. Think of these as the language you use to speak to the AI, how the AI speaks back, and the nuanced controls you have over its responses.&lt;/p&gt;</description></item><item><title>Chapter 7: Supervised Learning: Learning with a Teacher</title><link>https://ai-blog.noorshomelab.dev/ai-ml-journey-2026/supervised-learning-intro/</link><pubDate>Sun, 18 Jan 2026 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/ai-ml-journey-2026/supervised-learning-intro/</guid><description>&lt;h2 id="introduction-learning-with-a-teacher"&gt;Introduction: Learning with a Teacher&lt;/h2&gt;
&lt;p&gt;Welcome back, aspiring AI explorer! In our previous chapters, we laid the groundwork by understanding what AI and ML are, how data powers them, and the concept of a &amp;ldquo;model&amp;rdquo; that learns patterns. Now, it&amp;rsquo;s time to dive into the most common and perhaps easiest-to-grasp type of machine learning: &lt;strong&gt;Supervised Learning&lt;/strong&gt;.&lt;/p&gt;
&lt;p&gt;Imagine you&amp;rsquo;re learning something new, like identifying different types of birds. How do you usually learn? You probably look at pictures, maybe listen to their calls, and someone (a teacher, a parent, or even an app) tells you, &amp;ldquo;This is a robin,&amp;rdquo; or &amp;ldquo;That&amp;rsquo;s a blue jay.&amp;rdquo; You learn by being &lt;em&gt;shown examples with their correct answers&lt;/em&gt;. That&amp;rsquo;s exactly what supervised learning is all about!&lt;/p&gt;</description></item></channel></rss>