AI is everywhere from APIs and databases to IDE plugins and code copilots. Yet even experienced developers often find AI jargon confusing or overlapping: embeddings, LLMs, tokens, transformers, diffusion models, RAG, LoRA…

This session cuts through the noise with a developer-focused walkthrough of 42 essential AI terms you should know to confidently read documentation, design AI-integrated systems, and have informed conversations about architecture and ethics.

We’ll group concepts into themes: Models, Data, Training, Inference, Evaluation, and Deployment. You’ll walk away with a solid working vocabulary, mental models for how AI fits into modern software stacks, and a quick-reference glossary to take home.

We have been “using AI” but we want to really understand how it works, this talk will give you the conceptual foundation you need.