<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom" ><generator uri="https://jekyllrb.com/" version="3.10.0">Jekyll</generator><link href="https://blog.ddc.ac/feed.xml" rel="self" type="application/atom+xml" /><link href="https://blog.ddc.ac/" rel="alternate" type="text/html" /><updated>2026-09-03T05:27:47+00:00</updated><id>https://blog.ddc.ac/feed.xml</id><title type="html">DDC Academy R&amp;amp;D Center</title><subtitle>DDC Academy R&amp;D Center Official Blog. We will keep updating the information in here.</subtitle><entry><title type="html">Introduction to DDC Academy R&amp;amp;D Center</title><link href="https://blog.ddc.ac/2026/08/20/welcome-to-ddc.html" rel="alternate" type="text/html" title="Introduction to DDC Academy R&amp;amp;D Center" /><published>2026-08-20T08:11:59+00:00</published><updated>2026-08-20T08:11:59+00:00</updated><id>https://blog.ddc.ac/2026/08/20/welcome-to-ddc</id><content type="html" xml:base="https://blog.ddc.ac/2026/08/20/welcome-to-ddc.html"><![CDATA[<p>Welcome to DDC Academy R&amp;D Center. This site is under building right now.</p>

\[\label{eq:transformer_equation}
Attention(Q, K, V) = \text{softmax}\left(\frac{QK^T}{\sqrt{d_k}}\right)V\]

<p>如公式 $\eqref{eq:transformer_equation}$ 所示，注意机制的核心在于…</p>

<div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="c1"># 这是一个 Python 代码示例
</span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="n">np</span>

<span class="k">def</span> <span class="nf">matrix_multiply</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">):</span>
    <span class="s">"""计算两个矩阵的乘积"""</span>
    <span class="k">return</span> <span class="n">np</span><span class="p">.</span><span class="n">dot</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">)</span>

<span class="c1"># 结果输出
</span><span class="n">matrix_a</span> <span class="o">=</span> <span class="n">np</span><span class="p">.</span><span class="n">array</span><span class="p">([[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">],</span> <span class="p">[</span><span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">]])</span>
<span class="n">matrix_b</span> <span class="o">=</span> <span class="n">np</span><span class="p">.</span><span class="n">array</span><span class="p">([[</span><span class="mi">5</span><span class="p">,</span> <span class="mi">6</span><span class="p">],</span> <span class="p">[</span><span class="mi">7</span><span class="p">,</span> <span class="mi">8</span><span class="p">]])</span>
<span class="n">result</span> <span class="o">=</span> <span class="n">matrix_multiply</span><span class="p">(</span><span class="n">matrix_a</span><span class="p">,</span> <span class="n">matrix_b</span><span class="p">)</span>
<span class="k">print</span><span class="p">(</span><span class="s">"Result matrix:"</span><span class="p">)</span>
<span class="k">print</span><span class="p">(</span><span class="n">result</span><span class="p">)</span>
</code></pre></div></div>]]></content><author><name></name></author><summary type="html"><![CDATA[Welcome to DDC Academy R&amp;D Center. This site is under building right now.]]></summary></entry></feed>