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        <title>Transformer - Tag - Daily Deep Think</title>
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        <description>Transformer - Tag - Daily Deep Think</description>
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            <webMaster>blog@baifan.site (ByF)</webMaster><lastBuildDate>Tue, 05 Aug 2025 14:00:00 &#43;0800</lastBuildDate><atom:link href="https://blog.baifan.site/en/tags/transformer/" rel="self" type="application/rss+xml" /><item>
    <title>Transformer Architecture Deep Dive: The Attention Mechanism</title>
    <link>https://blog.baifan.site/en/transformer-attention-mechanism-deep-dive/</link>
    <pubDate>Tue, 05 Aug 2025 14:00:00 &#43;0800</pubDate><author>
                    <name>ByF</name>
                </author><guid>https://blog.baifan.site/en/transformer-attention-mechanism-deep-dive/</guid>
    <description><![CDATA[<div class="featured-image">
                <img src="/pictures/note/ai-tutorial-2-transformer.jpg" referrerpolicy="no-referrer">
            </div><h1 id="ai-tutorial--transformer" class="headerLink">
    <a href="#ai-tutorial--transformer" class="header-mark"></a>AI Tutorial — Transformer</h1><h2 id="-1-what-is-the-transformer" class="headerLink">
    <a href="#-1-what-is-the-transformer" class="header-mark"></a>🧩 1. What Is the Transformer?</h2><blockquote>
  <p><strong>The Transformer is a deep learning architecture for processing sequential information — text, speech, code, and so on.</strong></p>

</blockquote><p>It was first proposed by Google in the 2017 paper <em>Attention Is All You Need</em>.</p>
<p>That paper laid the foundation for nearly every large language model today. GPT, BERT, Claude, Gemini, Qwen, ERNIE Bot — all of them are built on the Transformer.</p>]]></description>
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    <title>A Complete Guide to LLMs: Tokens and Vectors in Depth</title>
    <link>https://blog.baifan.site/en/ai-llm-tutorial-token-vector-basics/</link>
    <pubDate>Tue, 22 Jul 2025 14:00:00 &#43;0800</pubDate><author>
                    <name>ByF</name>
                </author><guid>https://blog.baifan.site/en/ai-llm-tutorial-token-vector-basics/</guid>
    <description><![CDATA[<div class="featured-image">
                <img src="/pictures/note/ai-llm-token-vector-basics-featured.svg" referrerpolicy="no-referrer">
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    <a href="#ai-tutorial-a-guide-to-ai-llms-from-basics-to-depth" class="header-mark"></a>AI Tutorial: A Guide to AI LLMs, from Basics to Depth</h1><p>This article takes you deep into the core concepts of large language models — from basic principles to vector representation — building a complete knowledge system step by step.</p>
<hr>
<h2 id="1-foundations-of-ai-application-development" class="headerLink">
    <a href="#1-foundations-of-ai-application-development" class="header-mark"></a>1. Foundations of AI Application Development</h2><h3 id="11-basic-principles-and-concepts" class="headerLink">
    <a href="#11-basic-principles-and-concepts" class="header-mark"></a>1.1 Basic Principles and Concepts</h3><h4 id="in-plain-words" class="headerLink">
    <a href="#in-plain-words" class="header-mark"></a>In Plain Words</h4><ul>
<li><strong>Core mechanism</strong>: predict the next word from the previous one — like a word-chain game</li>
<li><strong>How it works</strong>: output is generated token by token</li>
</ul>
<h4 id="a-deeper-look" class="headerLink">
    <a href="#a-deeper-look" class="header-mark"></a>A Deeper Look</h4><p>A large AI model involves two key stages:</p>]]></description>
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