-------- Forwarded Message -------- From: claire <[email protected]> To: Alperen Erkan <[email protected]> Subject: Re: Subject: Help testing a vibe-coded neuron project on Debian GNU/Hurd (QEMU) — and advice on building toward a neural network / LLM Date: 09/25/2026 11:46:33 PM
> Hello, > Thank you for this very valuable information and for your interest. > To be honest, I don't know much more about it than you do, and I > think the documentary references you've given me will help me > greatly. > Of course, I know Hurd is still in the development phase, but it's > the ideal architecture for my project :) > > On Sat, 2026-09-26 at 00:27 +0300, Alperen Erkan wrote: > > Hi Claire, > > This is a fascinating project! "Vibe coding" a single neuron with > > the ultimate goal of running a neural network and LLMs on GNU/Hurd > > is quite an ambitious and exciting journey. > > Since you are looking to set up a testing environment and want to > > dive deeper into how neural networks and LLMs work, here is a > > breakdown to help you get started: > > 1. Setting Up Your Testing Environment (Debian Hurd + QEMU)To test your > > C/C++ code inside the Hurd environment you were > > setting up earlier, here is a quick checklist: > > * Booting Hurd: Make sure your QEMU image boots successfully (using > > the -drive format=raw fix we discussed earlier). > > * Environment Prep: Once inside Debian Hurd via QEMU, update your > > package lists and install the essential build tools (gcc, make, > > git):sudo apt updatesudo apt install build-essential git > > * Cloning & Testing: Clone your repository (git clone > > > > [https://github.com/coralieayabie/hurd-translator-neuronne](https://github.com/coralieayabie/hurd-translator-neuronne) > > ) and try compiling your single neuron code. Since Hurd uses the > > Mach microkernel and GNU Mach/Hurd translators, keeping your code as > > POSIX-compliant and dependency-free as possible will make your life > > much easier! > > 2. Understanding Neural Networks: The RoadmapTo scale from a single neuron > > to a full network, I recommend > > breaking your learning down into these core milestones: > > * The Single Neuron (Perceptron): Understand how inputs ($x$), weights > > ($w$), and a bias ($b$) are multiplied and passed through an > > activation function (like Sigmoid, ReLU, or Tanh) to produce an > > output. > > * Feedforward Networks & Backpropagation: Learn how multiple neurons > > connect in layers and how the network learns by calculating errors > > and adjusting weights backward (calculus/gradient descent). > > * From Networks to Transformers: Once you master basic Multi-Layer > > Perceptrons (MLPs), look into sequence modeling, attention > > mechanisms, and the Transformer architecture—which forms the > > backbone of modern LLMs like GPT. > > 3. Recommended Resources & PapersHere are a few classic, highly recommended > > resources for your > > level: > > * Books & Courses:Neural Networks and Deep Learning by Michael Nielsen > > (an incredible, free online book that explains the math and > > intuition brilliantly).Andrej Karpathy's "Neural Networks: Zero to > > Hero" video series on YouTube (starts from micrograd and builds up > > to GPT—extremely practical and hands-on). > > * Key Paper to Read Later: “Attention Is All You Need” (Vaswani et > > al.) when you are ready to tackle transformers. > > Kudos for taking on such a unique project combining low-level > > systems (Hurd) with AI architecture. Let us know how the QEMU > > testing goes, or if you hit any compilation snags on Hurd! > > I have no background in artificial intelligence; this is just a > > little knowledge I’ve picked up from articles and theses over the > > years, so someone more knowledgeable might be able to set you on a > > clearer path. > > > > And I’d like to offer a word of caution: HURD is still a > > microkernel in the development phase. Loading an LLM onto the > > kernel all at once will significantly increase the likelihood of > > freezes, panic, and ‘Oops’ loops. However, you can use this to your > > advantage – if you report the part causing the crash or error to > > us, we can take action more quickly. > > > > Best regards, > > Alperen ERKAN >
