20 Concepts to Understand AI in 2026

sairahul1's two-part thread distils modern AI into twenty concepts, working up from the single neuron to the systems behind the products people use every day: neural networks, tokenisation, embeddings, attention and transformers; then LLMs, context windows, temperature, hallucination and prompt engineering; the training techniques (transfer learning, fine-tuning, RLHF, LoRA, quantisation); and the system-level pieces (RAG, vector databases, agents, chain-of-thought, diffusion). I used the thread as the skeleton for a full write-up — 20 Concepts to Understand AI in 2026 — giving each concept its own chapter: plain-language explanation, how it works under the hood, and where it sits in 2026 practice, every claim linked to a source. Original thread: part 1 · part 2.

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