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Established June 13, 2025
Simply & sustainably built
Welcome to TomCon.net, a public site designed from scratch by Thomas Conway. This space is dedicated to sustainable technology and open source development. It's a digital organism that I breathe life into, translating my thoughts into ones and zeros for you to explore. I hope you find something interesting here. Thank you for visiting, enjoy your stay!
The webserver, Gemini server, and encryption certificate handling components of this site are all hosted on a recycled ThinkPad that I plan to power with a solar system I built myself. The open source machine learning model engine runs on a recycled desktop PC optimized for use with a power-efficient GPU (Nvidia 1070ti 8GB).
This website is a learning exercise for me, and I want to turn it into a learning opportunity for anyone interested in this field. I'm taking extra time and effort to share my journey at every notable step: from detailed setup instructions to creating a custom toolchain for my own writing workflow.
Site Infrastructure (Hardware, Software Stack, Networking)
Power usage measurement and operational cost calculations for TomCon.net
About writing pages for this site using gemtext formatting
I've been hosting open source machine learning models locally for over a year now, testing dozens of cutting-edge models on their release day and benchmarking their capabilities. Today I explore their potential for improving people's lives in positive ways. I plan to write a non-technical, step-by-step beginner's tutorial for anyone interested in getting started with this technology.
Want to try it yourself? I provide a free, semi-public LLM service for fellow hobbyists through a kobold.cpp WebUI loaded with several on-demand model configurations. While you might wonder why you'd want to try my quantized sub-30B models, perhaps you want to test kobold without installing it, or you trust a privacy-conscious hobbyist with your data more than big tech companies and want to see what consumer-grade hardware can accomplish. Feel free to message me through one of my contact methods for a password or API key. I'm happy to share my compute resources for your learning journey!
To the kobold service landing page!
I've developed an efficient memory compression system for machine learning models based on archetypal attractors. To better understand this system, I've built a multi-disciplinary framework explaining how machine learning models organize information. I openly share my mathematical framework, theories, findings, and philosophical musings on the nature of models and their relationship to information theory. Note that certain implementation details and optimization algorithms are withheld as they are subject to patent applications and trade secrets.
I was a main developer and active modder for the open source game VoxeLibre for over two years. During that time, I developed skills in parsing and documenting legacy code, building complex logic systems from scratch, graphical art and image editing, 3D model creation and texturing, and gameplay development within a voxel-based engine.
https://git.minetest.land/VoxeLibre/VoxeLibre
My mods for VoxeLibre & Mineclonia
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