<rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Hacker News: Ajay__soni</title><link>https://news.ycombinator.com/user?id=Ajay__soni</link><description>Hacker News RSS</description><docs>https://hnrss.org/</docs><generator>hnrss v2.1.1</generator><lastBuildDate>Mon, 18 May 2026 09:34:18 +0000</lastBuildDate><atom:link href="https://hnrss.org/user?id=Ajay__soni" rel="self" type="application/rss+xml"></atom:link><item><title><![CDATA[New comment by Ajay__soni in "Show HN: OpenGravity – A zero-install, BYOK vanilla JS clone of Antigravity"]]></title><description><![CDATA[
<p>Good luck for your exams!</p>
]]></description><pubDate>Mon, 11 May 2026 21:29:45 +0000</pubDate><link>https://news.ycombinator.com/item?id=48100921</link><dc:creator>Ajay__soni</dc:creator><comments>https://news.ycombinator.com/item?id=48100921</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=48100921</guid></item><item><title><![CDATA[Show HN: MicroGPT-C – C99 GPT for Edge Training and Tiny Model Pipelines]]></title><description><![CDATA[
<p>TL;DR: Pure C99 GPT-2 engine, zero dependencies. Sub-1M-parameter “organelles” coordinate via a Planner-Worker-Judge pipeline and beat random opponents up to 91 % on logic games, all on CPU.<p>I’m a C/C++ architect focused on low-latency systems. Last year, I tried building agentic pipelines with SLMs/LLMs and hit the usual wall: latency and orchestration overhead killed real-time edge use cases.<p>Initial research video: <a href="https://www.youtube.com/watch?v=q-rs9VZ1-0I" rel="nofollow">https://www.youtube.com/watch?v=q-rs9VZ1-0I</a><p>So I asked: how far can you push specialised logic at <1M parameters with nothing but local CPU?<p>MicroGPT-C is a from-scratch C99 port of Karpathy’s microgpt.py (<a href="https://gist.github.com/karpathy/8627fe009c40f57531cb18360106ce95" rel="nofollow">https://gist.github.com/karpathy/8627fe009c40f57531cb1836010...</a>). Zero deps, single-header, localised KV cache. Speed was never the goal (Andrej’s nanoGPT and llm.c already showed what’s possible). The real experiment was orchestration.<p>Organelle Pipeline Architecture (OPA): Agile-style Planners, Workers and Judges talking through tiny structured strings (board=XO_|valid=1,3) parsed by a safety-gated stack VM (3.7–5.8M ops/s). A 64K model needed 181 manual interventions; a 460K model trained on those traces internalised everything and needed zero.<p>Beyond the research: fully auditable AI, great for education (~3k lines of readable C), rapid prototyping, and embedded.<p>Personal itch: fraud/risk engines. I want agents that hunt “unknown-unknowns” in a sandbox where every decision is inspectable.<p>Happy to talk implementation, the 97 tests, 22 benchmarks, or anything else. FAQ: <a href="https://github.com/enjector/microgpt-c/blob/main/FAQ.md" rel="nofollow">https://github.com/enjector/microgpt-c/blob/main/FAQ.md</a><p>Quick try (macOS/Linux/Windows):
git clone <a href="https://github.com/enjector/microgpt-c" rel="nofollow">https://github.com/enjector/microgpt-c</a> && cd microgpt-c
mkdir build && cd build && cmake .. -DCMAKE_BUILD_TYPE=Release && cmake --build . 
./connect4_demo   # 460K params, ~21 min train, 88% win rate vs random<p>Performance (Apple M2 Max):
- 4.2K params names: 685k tok/s train, 110k tok/s infer
- 841K Shakespeare char: 28k / 16k tok/s
- 510K Shakespeare word: 12.5k / 40k tok/s<p>Full leaderboard (11 games), market-regime experiment (57% holdout = 2.8× baseline), and the book PDF:
<a href="https://github.com/enjector/microgpt-c/blob/main/docs/book/MicroGPT-C_Composable_Intelligence_at_the_Edge.pdf?raw=true" rel="nofollow">https://github.com/enjector/microgpt-c/blob/main/docs/book/M...</a>
GitHub: <a href="https://github.com/enjector/microgpt-c" rel="nofollow">https://github.com/enjector/microgpt-c</a></p>
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<p>Comments URL: <a href="https://news.ycombinator.com/item?id=47123730">https://news.ycombinator.com/item?id=47123730</a></p>
<p>Points: 1</p>
<p># Comments: 0</p>
]]></description><pubDate>Mon, 23 Feb 2026 15:39:21 +0000</pubDate><link>https://github.com/enjector/microgpt-c</link><dc:creator>Ajay__soni</dc:creator><comments>https://news.ycombinator.com/item?id=47123730</comments><guid isPermaLink="false">https://news.ycombinator.com/item?id=47123730</guid></item></channel></rss>