A small autonomous monitor for a home network: snapshot the state that should not drift, diff it against an accepted baseline, and let a language model decide whether the changes are explainable.
Category
Engineering
6 articles in this topic.
How I use a free local model as a delegated investigator for my AI assistant, trading wall-clock time for dollar cost — and what the research literature says about why this works.
We tend to mistake the effort we put into a feature for the user's need for it, and a landing page is a poor place to learn that lesson.
Why I skipped the FFT needle and built a pitch tuner around autocorrelation, parabolic interpolation, and a fading quarter-tone visualization — all client-side with the Web Audio API.
A sketch for a self-directed learning loop: let an agent propose its own tasks, judge its own results, and only ask for help when it genuinely gets stuck.
What I learned setting up local LLMs on consumer GPUs with Ollama — VRAM math, thinking-mode traps, and the cascade architecture I use for daily AI assistant work.