LEXICON / V1
AI Dictionary
Plain-English explanations of AI terms and concepts.
CONCEPTS
API Key A unique secret string that authenticates your requests to an AI provider's servers, like a password for programmatic access. Context Window The maximum amount of text (measured in tokens) that an AI model can process in a single conversation or request. Embeddings Dense numerical vectors that represent text (or other data) in a way that captures semantic meaning, enabling similarity search and retrieval. Hallucination When an AI model generates information that sounds plausible but is factually incorrect, fabricated, or not grounded in its training data. Inference The process of running input data through a trained AI model to generate predictions or outputs, as opposed to training the model. LLM (Large Language Model) A type of artificial intelligence model trained on massive text datasets to understand and generate human-like text. Multimodal AI models capable of understanding and generating multiple types of content — text, images, audio, video, or code — within a single interaction. Streaming A method of delivering AI responses token by token in real-time, so users see the output as it's generated rather than waiting for the complete response. Tokens The smallest units of text that AI models process. Words, parts of words, or punctuation marks are each converted into tokens.
TECHNIQUES
Fine-Tuning The process of further training a pre-trained AI model on a specific dataset to improve its performance for a particular task or domain. Prompt Engineering The practice of crafting effective instructions and inputs to get better, more accurate responses from AI models. RAG (Retrieval-Augmented Generation) A technique that enhances AI responses by retrieving relevant information from external sources before generating an answer. System Prompt A set of instructions given to an AI model before the conversation begins, defining its behavior, persona, and constraints. Temperature A parameter that controls how random or creative an AI model's responses are. Lower values produce more predictable output, higher values produce more creative output.