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    <title>DEV Community: ATEC</title>
    <description>The latest articles on DEV Community by ATEC (@atec_technologies).</description>
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      <title>I built a programming language that trains AI on your own GPU — no Python, no PyTorch</title>
      <dc:creator>ATEC</dc:creator>
      <pubDate>Wed, 11 Nov 2026 18:37:44 +0000</pubDate>
      <link>https://dev.to/atec_technologies/i-built-a-programming-language-that-trains-ai-on-your-own-gpu-no-python-no-pytorch-5f4b</link>
      <guid>https://dev.to/atec_technologies/i-built-a-programming-language-that-trains-ai-on-your-own-gpu-no-python-no-pytorch-5f4b</guid>
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&lt;p&gt;Hi DEV! I'm the 17-year-old developer of &lt;strong&gt;Apsi&lt;/strong&gt;, a programming language for AI and physics. I'd love for you to try it, break it, and help build the community around it.&lt;/p&gt;
&lt;h2&gt;
  
  
  What is Apsi?
&lt;/h2&gt;

&lt;p&gt;Apsi is designed to be simple and direct: code you can read once and understand. It looks like Python, but it checks &lt;strong&gt;physical units and tensor shapes before the program runs&lt;/strong&gt;, so a whole class of bugs never reaches run time.&lt;/p&gt;

&lt;p&gt;It comes as &lt;strong&gt;one installer&lt;/strong&gt; for Windows and Linux. No Python, no PyTorch, no CUDA toolkit to set up first.&lt;/p&gt;
&lt;h2&gt;
  
  
  Train a model on your own GPU
&lt;/h2&gt;

&lt;p&gt;Apsi trains models on NVIDIA cards with &lt;strong&gt;its own kernels&lt;/strong&gt;, generated on your machine from the display driver alone (LLVM → PTX):&lt;br&gt;
&lt;/p&gt;

&lt;div class="highlight js-code-highlight"&gt;
&lt;pre class="highlight python"&gt;&lt;code&gt;&lt;span class="n"&gt;use&lt;/span&gt; &lt;span class="n"&gt;layers&lt;/span&gt;

&lt;span class="c1"&gt;# a GPT, trained with Apsi's own GPU kernels&lt;/span&gt;
&lt;span class="n"&gt;let&lt;/span&gt; &lt;span class="n"&gt;model&lt;/span&gt; &lt;span class="o"&gt;=&lt;/span&gt; &lt;span class="nf"&gt;transformer_lm&lt;/span&gt;&lt;span class="p"&gt;(&lt;/span&gt;&lt;span class="mi"&gt;257&lt;/span&gt;&lt;span class="p"&gt;,&lt;/span&gt; &lt;span class="n"&gt;d&lt;/span&gt;&lt;span class="o"&gt;=&lt;/span&gt;&lt;span class="mi"&gt;384&lt;/span&gt;&lt;span class="p"&gt;,&lt;/span&gt; &lt;span class="n"&gt;heads&lt;/span&gt;&lt;span class="o"&gt;=&lt;/span&gt;&lt;span class="mi"&gt;6&lt;/span&gt;&lt;span class="p"&gt;,&lt;/span&gt; &lt;span class="n"&gt;layers&lt;/span&gt;&lt;span class="o"&gt;=&lt;/span&gt;&lt;span class="mi"&gt;6&lt;/span&gt;&lt;span class="p"&gt;,&lt;/span&gt; &lt;span class="n"&gt;context&lt;/span&gt;&lt;span class="o"&gt;=&lt;/span&gt;&lt;span class="mi"&gt;128&lt;/span&gt;&lt;span class="p"&gt;)&lt;/span&gt;
&lt;span class="n"&gt;let&lt;/span&gt; &lt;span class="n"&gt;r&lt;/span&gt; &lt;span class="o"&gt;=&lt;/span&gt; &lt;span class="nf"&gt;fit&lt;/span&gt;&lt;span class="p"&gt;(&lt;/span&gt;&lt;span class="n"&gt;model&lt;/span&gt;&lt;span class="p"&gt;,&lt;/span&gt; &lt;span class="n"&gt;model&lt;/span&gt;&lt;span class="p"&gt;.&lt;/span&gt;&lt;span class="nf"&gt;init&lt;/span&gt;&lt;span class="p"&gt;(&lt;/span&gt;&lt;span class="n"&gt;seed&lt;/span&gt;&lt;span class="o"&gt;=&lt;/span&gt;&lt;span class="mi"&gt;0&lt;/span&gt;&lt;span class="p"&gt;)&lt;/span&gt;&lt;span class="p"&gt;,&lt;/span&gt; &lt;span class="no"&gt;X&lt;/span&gt;&lt;span class="p"&gt;,&lt;/span&gt; &lt;span class="no"&gt;Y&lt;/span&gt;&lt;span class="p"&gt;,&lt;/span&gt;
            &lt;span class="n"&gt;loss&lt;/span&gt;&lt;span class="o"&gt;=&lt;/span&gt;&lt;span class="s2"&gt;"cross_entropy"&lt;/span&gt;&lt;span class="p"&gt;,&lt;/span&gt; &lt;span class="n"&gt;opt&lt;/span&gt;&lt;span class="o"&gt;=&lt;/span&gt;&lt;span class="nf"&gt;adamw&lt;/span&gt;&lt;span class="p"&gt;(&lt;/span&gt;&lt;span class="n"&gt;lr&lt;/span&gt;&lt;span class="o"&gt;=&lt;/span&gt;&lt;span class="mf"&gt;1e-3&lt;/span&gt;&lt;span class="p"&gt;)&lt;/span&gt;&lt;span class="p"&gt;,&lt;/span&gt;
            &lt;span class="n"&gt;epochs&lt;/span&gt;&lt;span class="o"&gt;=&lt;/span&gt;&lt;span class="mi"&gt;3&lt;/span&gt;&lt;span class="p"&gt;,&lt;/span&gt; &lt;span class="n"&gt;batch_size&lt;/span&gt;&lt;span class="o"&gt;=&lt;/span&gt;&lt;span class="mi"&gt;32&lt;/span&gt;&lt;span class="p"&gt;,&lt;/span&gt; &lt;span class="n"&gt;backend&lt;/span&gt;&lt;span class="o"&gt;=&lt;/span&gt;&lt;span class="s2"&gt;"gpu"&lt;/span&gt;&lt;span class="p"&gt;)&lt;/span&gt;

&lt;span class="c1"&gt;# physical units are checked before the program runs&lt;/span&gt;
&lt;span class="n"&gt;let&lt;/span&gt; &lt;span class="n"&gt;g&lt;/span&gt; &lt;span class="o"&gt;=&lt;/span&gt; &lt;span class="mf"&gt;9.81&lt;/span&gt;&lt;span class="p"&gt;[&lt;/span&gt;&lt;span class="n"&gt;m&lt;/span&gt;&lt;span class="o"&gt;/&lt;/span&gt;&lt;span class="n"&gt;s&lt;/span&gt;&lt;span class="o"&gt;^&lt;/span&gt;&lt;span class="mi"&gt;2&lt;/span&gt;&lt;span class="p"&gt;]&lt;/span&gt;
&lt;span class="k"&gt;print&lt;/span&gt;&lt;span class="p"&gt;(&lt;/span&gt;&lt;span class="mf"&gt;0.5&lt;/span&gt; &lt;span class="o"&gt;*&lt;/span&gt; &lt;span class="n"&gt;g&lt;/span&gt; &lt;span class="o"&gt;*&lt;/span&gt; &lt;span class="p"&gt;(&lt;/span&gt;&lt;span class="mf"&gt;2.5s&lt;/span&gt;&lt;span class="p"&gt;)&lt;/span&gt; &lt;span class="o"&gt;**&lt;/span&gt; &lt;span class="mi"&gt;2&lt;/span&gt;&lt;span class="p"&gt;)&lt;/span&gt;    &lt;span class="c1"&gt;# 30.65625 m&lt;/span&gt;
&lt;/code&gt;&lt;/pre&gt;

&lt;/div&gt;



&lt;p&gt;Under the hood:&lt;/p&gt;

&lt;ul&gt;
&lt;li&gt;tiled tensor-core matrix products with the bias, activation and residual fused in&lt;/li&gt;
&lt;li&gt;fused attention and a one-kernel AdamW&lt;/li&gt;
&lt;li&gt;the dataset stays on the card, so the GPU never waits for the CPU&lt;/li&gt;
&lt;li&gt;every matrix product has several builds; your card times them on the real shapes and keeps the fastest&lt;/li&gt;
&lt;li&gt;the GPU is held near &lt;strong&gt;77 °C&lt;/strong&gt; by moving its power limit, so long runs stay at a steady speed instead of throttling&lt;/li&gt;
&lt;/ul&gt;

&lt;h2&gt;
  
  
  Numbers
&lt;/h2&gt;

&lt;p&gt;Measured on a &lt;strong&gt;Ryzen 5 5500 + RTX 3060 12GB&lt;/strong&gt;, same model and same data file for both:&lt;/p&gt;

&lt;div class="table-wrapper-paragraph"&gt;&lt;table&gt;
&lt;thead&gt;
&lt;tr&gt;
&lt;th&gt;Training (10.9M-param GPT, bf16, 3 epochs)&lt;/th&gt;
&lt;th&gt;Speed&lt;/th&gt;
&lt;th&gt;Time&lt;/th&gt;
&lt;/tr&gt;
&lt;/thead&gt;
&lt;tbody&gt;
&lt;tr&gt;
&lt;td&gt;&lt;strong&gt;Apsi&lt;/strong&gt;&lt;/td&gt;
&lt;td&gt;&lt;strong&gt;151,744 tokens/s&lt;/strong&gt;&lt;/td&gt;
&lt;td&gt;11.2 s&lt;/td&gt;
&lt;/tr&gt;
&lt;tr&gt;
&lt;td&gt;PyTorch 2.14&lt;/td&gt;
&lt;td&gt;126,993 tokens/s&lt;/td&gt;
&lt;td&gt;13.4 s&lt;/td&gt;
&lt;/tr&gt;
&lt;/tbody&gt;
&lt;/table&gt;&lt;/div&gt;

&lt;p&gt;That's &lt;strong&gt;1.19× PyTorch&lt;/strong&gt; on this model, with every epoch at the same speed.&lt;/p&gt;

&lt;p&gt;Running language models fully on the same card:&lt;/p&gt;

&lt;div class="table-wrapper-paragraph"&gt;&lt;table&gt;
&lt;thead&gt;
&lt;tr&gt;
&lt;th&gt;Model&lt;/th&gt;
&lt;th&gt;Speed&lt;/th&gt;
&lt;/tr&gt;
&lt;/thead&gt;
&lt;tbody&gt;
&lt;tr&gt;
&lt;td&gt;Qwen2.5 0.5B&lt;/td&gt;
&lt;td&gt;~210 tokens/s&lt;/td&gt;
&lt;/tr&gt;
&lt;tr&gt;
&lt;td&gt;Qwen2.5 3B&lt;/td&gt;
&lt;td&gt;~46 tokens/s&lt;/td&gt;
&lt;/tr&gt;
&lt;tr&gt;
&lt;td&gt;Qwen2.5 14B&lt;/td&gt;
&lt;td&gt;~20 tokens/s&lt;/td&gt;
&lt;/tr&gt;
&lt;/tbody&gt;
&lt;/table&gt;&lt;/div&gt;

&lt;p&gt;The benchmarks page has the raw logs of every run.&lt;/p&gt;

&lt;h2&gt;
  
  
  Bring your Python
&lt;/h2&gt;

&lt;p&gt;&lt;code&gt;apsi convert script.py&lt;/code&gt; turns Python and PyTorch code into Apsi with the same behaviour. Converted code still being Python-shaped means you can move existing work over instead of starting from zero.&lt;/p&gt;

&lt;h2&gt;
  
  
  It's young — help me test it
&lt;/h2&gt;

&lt;p&gt;Apsi still has its limitations and rough edges. The most useful thing right now is people running it on &lt;strong&gt;their own hardware and their own code&lt;/strong&gt; and telling me what fails. Bug reports, benchmark results from other GPUs, and conversion attempts on real projects are all very welcome.&lt;/p&gt;

&lt;p&gt;Apsi was built by one developer working with Claude (Anthropic).&lt;/p&gt;

&lt;ul&gt;
&lt;li&gt;🌐 Website, docs and downloads: &lt;a href="https://apsi.dev/" rel="noopener noreferrer"&gt;https://apsi.dev/&lt;/a&gt;
&lt;/li&gt;
&lt;li&gt;💻 GitHub: &lt;a href="https://github.com/ATECTechnologies/apsi" rel="noopener noreferrer"&gt;https://github.com/ATECTechnologies/apsi&lt;/a&gt;
&lt;/li&gt;
&lt;/ul&gt;

&lt;p&gt;Thanks for reading. I'll be in the comments!&lt;/p&gt;

</description>
      <category>ai</category>
      <category>showdev</category>
      <category>machinelearning</category>
      <category>programming</category>
    </item>
    <item>
      <title>Introducing Apsi — A Programming Language for AI, Physics, and High-Performance Computing</title>
      <dc:creator>ATEC</dc:creator>
      <pubDate>Tue, 10 Nov 2026 14:38:57 +0000</pubDate>
      <link>https://dev.to/atec_technologies/introducing-apsi-a-programming-language-for-ai-physics-and-high-performance-computing-2c0b</link>
      <guid>https://dev.to/atec_technologies/introducing-apsi-a-programming-language-for-ai-physics-and-high-performance-computing-2c0b</guid>
      <description>&lt;p&gt;&lt;a href="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.us-east-2.amazonaws.com%2Fuploads%2Farticles%2Fe76iw0qcbejr9rcnllk6.png" class="article-body-image-wrapper"&gt;&lt;img src="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.us-east-2.amazonaws.com%2Fuploads%2Farticles%2Fe76iw0qcbejr9rcnllk6.png" alt=" " width="800" height="383"&gt;&lt;/a&gt;&lt;br&gt;
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&lt;a href="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.us-east-2.amazonaws.com%2Fuploads%2Farticles%2Fiwf43yj18t2nq7kfifhp.png" class="article-body-image-wrapper"&gt;&lt;img src="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.us-east-2.amazonaws.com%2Fuploads%2Farticles%2Fiwf43yj18t2nq7kfifhp.png" alt=" " width="327" height="639"&gt;&lt;/a&gt;&lt;/p&gt;

&lt;p&gt;Introducing &lt;strong&gt;Apsi&lt;/strong&gt; — a programming language for AI, physics, and high-performance computing.&lt;/p&gt;

&lt;p&gt;Python-like syntax. Native compilation. One powerful ecosystem.&lt;/p&gt;

&lt;p&gt;Explore Apsi:&lt;br&gt;
🌐 &lt;a href="https://apsi.dev/" rel="noopener noreferrer"&gt;https://apsi.dev/&lt;/a&gt;&lt;br&gt;
💻 &lt;a href="https://github.com/ATECTechnologies/apsi" rel="noopener noreferrer"&gt;https://github.com/ATECTechnologies/apsi&lt;/a&gt;&lt;/p&gt;

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