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    <title>Determinism on Programmer.ie: Modern AI programming</title>
    <link>http://programmer.ie/tags/determinism/</link>
    <description>Recent content in Determinism on Programmer.ie: Modern AI programming</description>
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    <lastBuildDate>Mon, 14 Sep 2026 05:00:15 +0100</lastBuildDate>
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      <title>If There&#39;s Any Doubt, It&#39;s Deterministic</title>
      <link>http://programmer.ie/books/applied-ai/03-chapter/</link>
      <pubDate>Mon, 14 Sep 2026 05:00:03 +0100</pubDate>
      <guid>http://programmer.ie/books/applied-ai/03-chapter/</guid>
      <description>&lt;p&gt;&lt;em&gt;Part 1 — Where You Stand&lt;/em&gt;&lt;/p&gt;&#xA;&lt;h2 id=&#34;seven-operations-one-of-them-intelligent&#34;&gt;Seven operations, one of them intelligent&lt;/h2&gt;&#xA;&lt;p&gt;Take the paragraph review from Chapter 1 and write down everything the process actually has to do. Not the prompt — the process.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Select the paragraph to review.&lt;/li&gt;&#xA;&lt;li&gt;Decide whether it has changed since the last review.&lt;/li&gt;&#xA;&lt;li&gt;Decide whether there is budget left for a call.&lt;/li&gt;&#xA;&lt;li&gt;Identify claims in the paragraph that need supporting evidence.&lt;/li&gt;&#xA;&lt;li&gt;Extract the flagged sentence and its position.&lt;/li&gt;&#xA;&lt;li&gt;Check that a cited source resolves and that its year matches the bibliography.&lt;/li&gt;&#xA;&lt;li&gt;Decide whether to write the change to the file.&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;Six of those have exactly one correct answer, computable without a model. Selection is an index lookup and change detection is a hash comparison. Budget is arithmetic; extraction is parsing. Source checking resolves the request and compares it against the bibliography. The write decision evaluates policy.&lt;/p&gt;</description>
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      <title>Regressions: Did the Model Change, or the Measurement?</title>
      <link>http://programmer.ie/books/pytorch-from-first-principles/14-chapter/</link>
      <pubDate>Sat, 29 Aug 2026 18:00:00 +0100</pubDate>
      <guid>http://programmer.ie/books/pytorch-from-first-principles/14-chapter/</guid>
      <description>&lt;p&gt;Here is a refactor. The old training script set the seed at the top; the new one moves that line below model construction, where it reads more naturally, and draws the batch-shuffle permutation from a local &lt;code&gt;torch.Generator()&lt;/code&gt; instead of the global RNG, so the shuffling is &amp;ldquo;self-contained.&amp;rdquo; The training procedure is mathematically the same and the model architecture is unchanged. But the concrete initialized parameters are no longer coupled to the old run, because model construction now consumes randomness before &lt;code&gt;manual_seed&lt;/code&gt; is applied. Run it once:&lt;/p&gt;</description>
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    <item>
      <title>Context Is an Input, Not a Transcript</title>
      <link>http://programmer.ie/books/applied-ai/15-chapter/</link>
      <pubDate>Mon, 14 Sep 2026 05:00:15 +0100</pubDate>
      <guid>http://programmer.ie/books/applied-ai/15-chapter/</guid>
      <description>&lt;p&gt;&lt;em&gt;Part 3 — Give Intelligence a Runtime&lt;/em&gt;&lt;/p&gt;&#xA;&lt;h2 id=&#34;the-question-the-acceptance-could-not-answer&#34;&gt;The question the acceptance could not answer&lt;/h2&gt;&#xA;&lt;p&gt;Chapter 14 ended with a task that was provably complete. The acceptance cited the task&amp;rsquo;s criteria, the call, its final attempt, the interpretation, the exact artifact bytes and the checks run on them.&lt;/p&gt;&#xA;&lt;p&gt;It did not cite what the model was shown.&lt;/p&gt;&#xA;&lt;p&gt;Ask most systems that question and you get one of two answers. The first is &amp;ldquo;the conversation so far&amp;rdquo;: everything that happened, in the order it happened. The second is &amp;ldquo;whatever was in the prompt&amp;rdquo;: a string someone assembled and nobody recorded. Neither answer can be checked afterwards, and neither was decided on purpose.&lt;/p&gt;</description>
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