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        <title><![CDATA[Stories by Aditya Inamdar on Medium]]></title>
        <description><![CDATA[Stories by Aditya Inamdar on Medium]]></description>
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            <title>Stories by Aditya Inamdar on Medium</title>
            <link>https://medium.com/@inamdaraditya?source=rss-2bfbfa3bca8f------2</link>
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        <item>
            <title><![CDATA[Build an n8n Agent That Can Explain Why It Refused a Refund]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://inamdaraditya.medium.com/build-an-n8n-agent-that-can-explain-why-it-refused-a-refund-bb2f8327a053?source=rss-2bfbfa3bca8f------2"><img src="https://cdn-images-1.medium.com/max/2600/0*zG0urRvzV2bsJ-7k" width="3902"></a></p><p class="medium-feed-snippet">Wire a chat model to two tools, inspect a wrong decision, and fix it by changing what the model is allowed to pass between them.</p><p class="medium-feed-link"><a href="https://inamdaraditya.medium.com/build-an-n8n-agent-that-can-explain-why-it-refused-a-refund-bb2f8327a053?source=rss-2bfbfa3bca8f------2">Continue reading on Medium »</a></p></div>]]></description>
            <link>https://inamdaraditya.medium.com/build-an-n8n-agent-that-can-explain-why-it-refused-a-refund-bb2f8327a053?source=rss-2bfbfa3bca8f------2</link>
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            <category><![CDATA[n8n-agent]]></category>
            <dc:creator><![CDATA[Aditya Inamdar]]></dc:creator>
            <pubDate>Sat, 14 Nov 2026 07:20:54 GMT</pubDate>
            <atom:updated>2026-11-14T07:21:20.842Z</atom:updated>
        </item>
        <item>
            <title><![CDATA[How to Spend $4 of AMD’s $100 GPU Credit on a Benchmark Worth Keeping]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://inamdaraditya.medium.com/how-to-spend-4-of-amds-100-gpu-credit-on-a-benchmark-worth-keeping-3b2e267c6d0a?source=rss-2bfbfa3bca8f------2"><img src="https://cdn-images-1.medium.com/max/2600/0*ozSeKGvftqcxr1wT" width="7952"></a></p><p class="medium-feed-snippet">Run your first ROCm experiment on an Instinct MI300X and find out what batching does to vector-search throughput.</p><p class="medium-feed-link"><a href="https://inamdaraditya.medium.com/how-to-spend-4-of-amds-100-gpu-credit-on-a-benchmark-worth-keeping-3b2e267c6d0a?source=rss-2bfbfa3bca8f------2">Continue reading on Medium »</a></p></div>]]></description>
            <link>https://inamdaraditya.medium.com/how-to-spend-4-of-amds-100-gpu-credit-on-a-benchmark-worth-keeping-3b2e267c6d0a?source=rss-2bfbfa3bca8f------2</link>
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            <category><![CDATA[amd-developer-program]]></category>
            <dc:creator><![CDATA[Aditya Inamdar]]></dc:creator>
            <pubDate>Sat, 14 Nov 2026 06:51:45 GMT</pubDate>
            <atom:updated>2026-11-14T06:52:09.703Z</atom:updated>
        </item>
        <item>
            <title><![CDATA[Stable Diffusion Starts With 32 KiB of Noise. Where Does the GPU Memory Go?]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://inamdaraditya.medium.com/stable-diffusion-starts-with-32-kib-of-noise-where-does-the-gpu-memory-go-40f49f6d67a6?source=rss-2bfbfa3bca8f------2"><img src="https://cdn-images-1.medium.com/max/2600/0*-HVIIa9hFZG9dDI1" width="5184"></a></p><p class="medium-feed-snippet">Follow a single prompt through Stable Diffusion v1, from 77 text positions to 4,096 image positions. Along the way, a few lines of Python&#x2026;</p><p class="medium-feed-link"><a href="https://inamdaraditya.medium.com/stable-diffusion-starts-with-32-kib-of-noise-where-does-the-gpu-memory-go-40f49f6d67a6?source=rss-2bfbfa3bca8f------2">Continue reading on Medium »</a></p></div>]]></description>
            <link>https://inamdaraditya.medium.com/stable-diffusion-starts-with-32-kib-of-noise-where-does-the-gpu-memory-go-40f49f6d67a6?source=rss-2bfbfa3bca8f------2</link>
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            <category><![CDATA[attention]]></category>
            <category><![CDATA[stable-diffusion]]></category>
            <dc:creator><![CDATA[Aditya Inamdar]]></dc:creator>
            <pubDate>Sat, 14 Nov 2026 05:25:27 GMT</pubDate>
            <atom:updated>2026-11-14T05:25:55.184Z</atom:updated>
        </item>
        <item>
            <title><![CDATA[Your Stable Diffusion Autoencoder Can Pass Its Test With the Wrong Latents]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://inamdaraditya.medium.com/your-stable-diffusion-autoencoder-can-pass-its-test-with-the-wrong-latents-a617bac682c9?source=rss-2bfbfa3bca8f------2"><img src="https://cdn-images-1.medium.com/max/2600/0*4cyQNvl8REKyfzGj" width="4000"></a></p><p class="medium-feed-snippet">Follow one image, one prompt, and one noise prediction through Stable Diffusion v1. Then reproduce a scaling bug that an image round trip&#x2026;</p><p class="medium-feed-link"><a href="https://inamdaraditya.medium.com/your-stable-diffusion-autoencoder-can-pass-its-test-with-the-wrong-latents-a617bac682c9?source=rss-2bfbfa3bca8f------2">Continue reading on Medium »</a></p></div>]]></description>
            <link>https://inamdaraditya.medium.com/your-stable-diffusion-autoencoder-can-pass-its-test-with-the-wrong-latents-a617bac682c9?source=rss-2bfbfa3bca8f------2</link>
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            <category><![CDATA[latent-diffusion-model]]></category>
            <dc:creator><![CDATA[Aditya Inamdar]]></dc:creator>
            <pubDate>Fri, 13 Nov 2026 14:25:33 GMT</pubDate>
            <atom:updated>2026-11-13T14:25:57.780Z</atom:updated>
        </item>
        <item>
            <title><![CDATA[A Diffusion Model Sees the Number 1. Should It Push Left or Right?]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://blog.gopenai.com/a-diffusion-model-sees-the-number-1-should-it-push-left-or-right-04873c04490f?source=rss-2bfbfa3bca8f------2"><img src="https://cdn-images-1.medium.com/max/2600/0*PcRGMu4r3Owlc9sx" width="4000"></a></p><p class="medium-feed-snippet">Build a denoising diffusion probabilistic model from its training target to its sampling loop, then debug it against a distribution whose&#x2026;</p><p class="medium-feed-link"><a href="https://blog.gopenai.com/a-diffusion-model-sees-the-number-1-should-it-push-left-or-right-04873c04490f?source=rss-2bfbfa3bca8f------2">Continue reading on GoPenAI »</a></p></div>]]></description>
            <link>https://blog.gopenai.com/a-diffusion-model-sees-the-number-1-should-it-push-left-or-right-04873c04490f?source=rss-2bfbfa3bca8f------2</link>
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            <category><![CDATA[diffusion-models]]></category>
            <dc:creator><![CDATA[Aditya Inamdar]]></dc:creator>
            <pubDate>Fri, 13 Nov 2026 09:45:01 GMT</pubDate>
            <atom:updated>2026-11-13T09:45:01.720Z</atom:updated>
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        <item>
            <title><![CDATA[How a Feature With Zero Weight Can Break an 8-Bit Linear Layer]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://inamdaraditya.medium.com/how-a-feature-with-zero-weight-can-break-an-8-bit-linear-layer-59c6cb5b3ca5?source=rss-2bfbfa3bca8f------2"><img src="https://cdn-images-1.medium.com/max/2002/0*FCVd9_k0lBtIJQnK" width="2002"></a></p><p class="medium-feed-snippet">Inside LabML&#x2019;s GPT-NeoX implementation of LLM.int8(), with a CPU lab that lets you watch a projection lose its answer and recover it.</p><p class="medium-feed-link"><a href="https://inamdaraditya.medium.com/how-a-feature-with-zero-weight-can-break-an-8-bit-linear-layer-59c6cb5b3ca5?source=rss-2bfbfa3bca8f------2">Continue reading on Medium »</a></p></div>]]></description>
            <link>https://inamdaraditya.medium.com/how-a-feature-with-zero-weight-can-break-an-8-bit-linear-layer-59c6cb5b3ca5?source=rss-2bfbfa3bca8f------2</link>
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            <category><![CDATA[attention]]></category>
            <dc:creator><![CDATA[Aditya Inamdar]]></dc:creator>
            <pubDate>Fri, 13 Nov 2026 07:21:35 GMT</pubDate>
            <atom:updated>2026-11-13T07:22:07.074Z</atom:updated>
        </item>
        <item>
            <title><![CDATA[We Tracked the Shape of a Neural Network as It Learned. The Shape Didn’t Tell Us Enough.]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://inamdaraditya.medium.com/we-tracked-the-shape-of-a-neural-network-as-it-learned-the-shape-didnt-tell-us-enough-0128dba52a7b?source=rss-2bfbfa3bca8f------2"><img src="https://cdn-images-1.medium.com/max/2600/0*UMZSS_KEL4SJxfHD" width="3648"></a></p><p class="medium-feed-snippet">Persistent homology can reveal how neural-network weights reorganize during training. But can those geometric changes distinguish learning&#x2026;</p><p class="medium-feed-link"><a href="https://inamdaraditya.medium.com/we-tracked-the-shape-of-a-neural-network-as-it-learned-the-shape-didnt-tell-us-enough-0128dba52a7b?source=rss-2bfbfa3bca8f------2">Continue reading on Medium »</a></p></div>]]></description>
            <link>https://inamdaraditya.medium.com/we-tracked-the-shape-of-a-neural-network-as-it-learned-the-shape-didnt-tell-us-enough-0128dba52a7b?source=rss-2bfbfa3bca8f------2</link>
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            <category><![CDATA[persistant-homology]]></category>
            <dc:creator><![CDATA[Aditya Inamdar]]></dc:creator>
            <pubDate>Thu, 12 Nov 2026 08:15:15 GMT</pubDate>
            <atom:updated>2026-11-12T08:15:15.252Z</atom:updated>
        </item>
        <item>
            <title><![CDATA[Qwen Got 31 Fewer Math Problems Right When Attention Heads Dropped Out in Bursts]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://inamdaraditya.medium.com/qwen-got-31-fewer-math-problems-right-when-attention-heads-dropped-out-in-bursts-0c8e1b817769?source=rss-2bfbfa3bca8f------2"><img src="https://cdn-images-1.medium.com/max/2600/0*2n2xfycGcBPnVElp" width="3456"></a></p><p class="medium-feed-snippet">Two runs can lose the same planned amount of attention and take different paths through a calculation. A paired experiment on 250 math&#x2026;</p><p class="medium-feed-link"><a href="https://inamdaraditya.medium.com/qwen-got-31-fewer-math-problems-right-when-attention-heads-dropped-out-in-bursts-0c8e1b817769?source=rss-2bfbfa3bca8f------2">Continue reading on Medium »</a></p></div>]]></description>
            <link>https://inamdaraditya.medium.com/qwen-got-31-fewer-math-problems-right-when-attention-heads-dropped-out-in-bursts-0c8e1b817769?source=rss-2bfbfa3bca8f------2</link>
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            <category><![CDATA[attention-heads]]></category>
            <dc:creator><![CDATA[Aditya Inamdar]]></dc:creator>
            <pubDate>Thu, 12 Nov 2026 06:36:39 GMT</pubDate>
            <atom:updated>2026-11-12T06:37:05.979Z</atom:updated>
        </item>
        <item>
            <title><![CDATA[The User Is Testing Your Code. Should the LLM Keep Their Conversation in Memory?]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://inamdaraditya.medium.com/the-user-is-testing-your-code-should-the-llm-keep-their-conversation-in-memory-d6cdd3081483?source=rss-2bfbfa3bca8f------2"><img src="https://cdn-images-1.medium.com/max/2600/0*15XvJXQbYfKzIr1-" width="5504"></a></p><p class="medium-feed-snippet">An LLM server has to decide which conversation it can afford to forget. Intent-aware caching turns the pause between messages into an&#x2026;</p><p class="medium-feed-link"><a href="https://inamdaraditya.medium.com/the-user-is-testing-your-code-should-the-llm-keep-their-conversation-in-memory-d6cdd3081483?source=rss-2bfbfa3bca8f------2">Continue reading on Medium »</a></p></div>]]></description>
            <link>https://inamdaraditya.medium.com/the-user-is-testing-your-code-should-the-llm-keep-their-conversation-in-memory-d6cdd3081483?source=rss-2bfbfa3bca8f------2</link>
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            <category><![CDATA[deep-learning]]></category>
            <category><![CDATA[llm]]></category>
            <dc:creator><![CDATA[Aditya Inamdar]]></dc:creator>
            <pubDate>Wed, 11 Nov 2026 15:22:02 GMT</pubDate>
            <atom:updated>2026-11-11T15:22:32.400Z</atom:updated>
        </item>
        <item>
            <title><![CDATA[The AI Changed Its Answer 25.8% of the Time. Nobody Changed the Question.]]></title>
            <description><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://blog.gopenai.com/the-ai-changed-its-answer-25-8-of-the-time-nobody-changed-the-question-d547a3f70b1b?source=rss-2bfbfa3bca8f------2"><img src="https://cdn-images-1.medium.com/max/2600/0*-tAEJw7qtyFZCgRw" width="5152"></a></p><p class="medium-feed-snippet">Researchers tested a 421-million-parameter decision model by rearranging the same answer choices. The model often changed its mind&#x2026;</p><p class="medium-feed-link"><a href="https://blog.gopenai.com/the-ai-changed-its-answer-25-8-of-the-time-nobody-changed-the-question-d547a3f70b1b?source=rss-2bfbfa3bca8f------2">Continue reading on GoPenAI »</a></p></div>]]></description>
            <link>https://blog.gopenai.com/the-ai-changed-its-answer-25-8-of-the-time-nobody-changed-the-question-d547a3f70b1b?source=rss-2bfbfa3bca8f------2</link>
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            <category><![CDATA[maya-a1]]></category>
            <dc:creator><![CDATA[Aditya Inamdar]]></dc:creator>
            <pubDate>Wed, 11 Nov 2026 13:04:44 GMT</pubDate>
            <atom:updated>2026-11-11T13:05:17.013Z</atom:updated>
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