AI is the ambitious attempt to teach machines to think—mostly so they can handle the stuff we’re too bored to do ourselves.
3 articles in this category
Master the internals of modern AI with 23 interactive visualizations covering attention, KV-cache, tokenization, MoE, speculative decoding, and production optimizations.
Master the art of running multiple Claude Code instances in parallel using git worktrees, tmux, and automation. An interactive guide to AI-powered parallel development.
Interactive guide to machine learning model serving in 2025. Covers serving paradigms, confidential computing, GPU optimization, vLLM, quantization, RAG pipelines, and MLOps best practices.