A hobbyist ran a 26B-parameter model at roughly 5 tokens per second on decade-old server hardware with no GPU. Here's why that matters and how to try CPU-only inference yourself.
30papers.com turns the legendary reading list Ilya Sutskever gave to incoming OpenAI researchers into accessible, structured breakdowns — a practical on-ramp to the ideas that shaped modern AI.
A single perceptron is the atomic unit of every neural network. Building one by hand in Python — no libraries — is the fastest way to internalize how weights, bias, and gradient descent actually work.
Three reproducible recipes — Zapier, Make, and n8n — that take you from drag-and-drop AI automation to custom Python agent loops.
OpenClaw pairs naturally with DeepSeek's ultra-cheap API. Here's the full setup, real 2026 pricing, model picks — and the security hardening most tutorials skip.
Block's open-source Goose runs autonomous coding tasks on your own machine with any model—no subscription, no rate limits, no cloud dependency. Here's how it works, what it costs in hardware, and where it still trails Claude Code.
Deploy a private AI chatbot using Ollama, Open WebUI, and Docker Compose — no cloud APIs, no data leaks, full control.
Stanford's CS336 course released a CLAUDE.md file governing how AI coding agents should behave on its language-model assignments — a practical template for anyone managing AI agents in educational or constrained coding environments.
