Model Basics
A guided path through how AI models learn, generate content, process input, and produce responses.
8 terms
Model Basics starts with machine learning and generative AI, then focuses on language models. It connects tokens, prompts, and context windows to the inputs a model processes, before exploring inference and the possibility of plausible but unsupported outputs through hallucination.
Along this line
8 terms
1.Machine LearningAn approach to AI in which models learn patterns from data and use them to make predictions or produce other outputs.AI & Automation2.Generative AIAI that produces content such as text, images, audio, video, or code using patterns learned during training.AI & Automation3.LLMA large language model: an AI model trained on large amounts of text to understand and generate language.AI & Automation4.TokenA unit of text, such as a word, word fragment, or punctuation mark, that a language model processes or generates.AI & Automation5.PromptInput supplied to an AI model, such as a question, instruction, or example, to guide its response.AI & Automation6.Context WindowThe amount of information a language model can consider at one time when processing an input and generating a response.AI & Automation7.InferenceThe process of using a trained AI model to generate predictions, answers, or other outputs from new inputs.AI & Automation8.HallucinationAn AI output that presents incorrect, unsupported, or invented information as though it were reliable.AI & Automation