<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Translation on MacWorks</title><link>https://macworks.dev/tags/translation/</link><description>Recent content in Translation on MacWorks</description><generator>Hugo</generator><language>en</language><atom:link href="https://macworks.dev/tags/translation/index.xml" rel="self" type="application/rss+xml"/><item><title>Week 19 Summary</title><link>https://macworks.dev/docs/month/simonwillison/weekly-2026-W19/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://macworks.dev/docs/month/simonwillison/weekly-2026-W19/</guid><description>&lt;h1 id="simon-willison--week-of-2026-04-18-to-2026-05-01"&gt;Simon Willison — Week of 2026-04-18 to 2026-05-01&lt;a class="anchor" href="#simon-willison--week-of-2026-04-18-to-2026-05-01"&gt;#&lt;/a&gt;&lt;/h1&gt;
&lt;h2 id="highlight-of-the-week"&gt;Highlight of the Week&lt;a class="anchor" href="#highlight-of-the-week"&gt;#&lt;/a&gt;&lt;/h2&gt;
&lt;p&gt;The alpha release of &lt;code&gt;llm 0.32a0&lt;/code&gt; marks a foundational architectural pivot for Simon&amp;rsquo;s ecosystem of CLI tools. By moving away from a simple text-in/text-out abstraction to one that natively models complex message sequences and typed streams, the library is now future-proofed to handle the realities of modern frontier models. This opens the door for seamless integration of server-side tool calls, multi-modal inputs, and reasoning tokens.&lt;/p&gt;</description></item><item><title>2026-04-27</title><link>https://macworks.dev/docs/archives/simonwillison/simonwillison-2026-04-27/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://macworks.dev/docs/archives/simonwillison/simonwillison-2026-04-27/</guid><description>&lt;h1 id="simon-willison--2026-04-27"&gt;Simon Willison — 2026-04-27&lt;a class="anchor" href="#simon-willison--2026-04-27"&gt;#&lt;/a&gt;&lt;/h1&gt;
&lt;h2 id="highlight"&gt;Highlight&lt;a class="anchor" href="#highlight"&gt;#&lt;/a&gt;&lt;/h2&gt;
&lt;p&gt;The most substantive post for developers today is Simon&amp;rsquo;s hands-on experiment running Microsoft&amp;rsquo;s VibeVoice model locally via MLX. It&amp;rsquo;s a great example of his signature workflow: taking a newly accessible open-source AI model and immediately figuring out the most frictionless CLI one-liner to get it running on Apple Silicon.&lt;/p&gt;
&lt;h2 id="posts"&gt;Posts&lt;a class="anchor" href="#posts"&gt;#&lt;/a&gt;&lt;/h2&gt;
&lt;p&gt;&lt;strong&gt;[microsoft/VibeVoice]&lt;/strong&gt; · &lt;a href="https://simonwillison.net/2026/Apr/27/vibevoice/#atom-everything"&gt;Source&lt;/a&gt;
Simon explores Microsoft&amp;rsquo;s MIT-licensed VibeVoice, a Whisper-style speech-to-text model that notably includes built-in speaker diarization. He shares a practical one-liner using &lt;code&gt;uv&lt;/code&gt; and &lt;code&gt;mlx-audio&lt;/code&gt; to run a 4-bit quantized version locally on a Mac. Testing it against a one-hour podcast interview, it transcribed the audio in under 9 minutes and impressively distinguished between the host&amp;rsquo;s conversational voice and his &amp;ldquo;sponsor read&amp;rdquo; voice. You&amp;rsquo;ll need to manually split audio files longer than an hour to avoid token limits, but the resulting JSON drops nicely into Datasette Lite for browsing.&lt;/p&gt;</description></item></channel></rss>