Glossary
A plain-English glossary of the methods and ideas behind modern AI. Search, sort, or jump to a letter.
8 terms
| Definition | ||
|---|---|---|
| Ablation | An experiment that removes or changes one component of a model or training setup to measure how much it actually contributes. | May 22, 2026 |
| Adam Optimizer | A widely-used adaptive optimizer for training neural networks. | May 21, 2026 |
| Agentic Reinforcement Learning | Training LLMs with RL where the model takes multi-step actions in an environment (tools, code, web search) and is rewarded on task outcomes. | May 21, 2026 |
| AI Agents | Systems where a model plans, uses tools, and acts over multiple steps. | May 21, 2026 |
| AI Alignment | Making AI systems pursue what people actually intend. | May 21, 2026 |
| Attention | A mechanism that lets a model weigh which other tokens matter for each token. | May 21, 2026 |
| Autoencoder | A network that compresses data and reconstructs it. | May 21, 2026 |
| Autoregressive Models | Models that generate output one token at a time, left to right. | May 21, 2026 |