Jargon Buster

AI borrows heavily from statistics, computer science, and neuroscience. As it becomes mainstream, highly technical terms are being used in everyday contexts.

LLM (Large Language Model) is the foundation of almost all modern text-based AI. Understanding that it predicts the next word based on patterns is crucial.

No. ChatGPT is an LLM, a form of narrow AI specialized in text. AGI (Artificial General Intelligence) does not exist yet.

We update the glossary continuously as new architectures, models, and techniques emerge in the AI space.

AI is the broadest term (machines mimicking intelligence). ML is a subset (machines learning from data). Deep Learning is a subset of ML using neural networks with many layers.

An open-source AI model has its weights and architecture publicly available for anyone to download, modify, and run locally. Examples include Llama, Mistral, and Stable Diffusion.

Parameters are the adjustable values inside a neural network. More parameters generally means the model can learn more nuanced patterns. GPT-4 is rumored to have over 1 trillion parameters.

A large, general-purpose AI model trained on broad data that can be adapted (fine-tuned) for specific tasks. GPT-4, Gemini, and Claude are all foundation models.

Yes, intentionally. We prioritize clarity and accessibility over technical precision. Each definition is written in ELI5 (Explain Like I'm Five) style while remaining accurate.

The glossary is provided for educational purposes. You may reference individual definitions with attribution to AI Days.