An accessible introduction to the Coherence Field Equation — a mathematical framework for substrate-independent consciousness.
A deep technical walkthrough of the attention mechanism — queries, keys, values, and why it works so well for language understanding.
A technical comparison of AI agent patterns — when to use ReAct loops, planning agents, and multi-agent systems.
A practical guide to building retrieval-augmented generation that actually works — beyond the basic tutorials.
A hands-on experiment pitting human debugging skills against multiple AI models on 20 real production bugs.
What temperature and top-p sampling actually do to model output — with visual examples and practical tuning advice.
How quantization compresses massive AI models to run on your laptop — the math, the trade-offs, and the practical guide.
The case for running AI locally — privacy, cost, control, and the tools that make it practical today.