Terms related to generative AI that you might find useful.

Harold Robert Meyer and The ADD Resource Center                              04/23/2025 

“Artificial intelligence is not merely a technological advancement; it is the ultimate force multiplier for human potential, broadening what is achievable for individuals, enhancing national competitiveness, and equipping humanity with powerful tools to tackle our greatest global challenges.”  Harold Meyer

TermDefinition
PromptThe text or other input you provide to a generative AI model to tell it what you want it to create (e.g., “a cat wearing a hat,” “write a short story about a robot”).
HallucinationWhen a generative AI model produces information that is false, nonsensical, or not based on the training data or the provided prompt. It might present this incorrect information confidently.
AI-generated contentAny text, images, audio, video, or other media that has been created by artificial intelligence models.
Style transferA technique where the artistic style of one image is applied to the content of another image (e.g., making a photo look like a Van Gogh painting).
DeepfakeA manipulated video or audio recording that realistically depicts someone saying or doing something they did not actually say or do. Often created using generative AI.
Latent spaceThink of this as a hidden, abstract space where the AI stores compressed representations of the data it has learned. By navigating this space, the AI can generate new variations.
Training dataThe large amounts of real-world data (text, images, etc.) that are used to teach a generative AI model how to understand patterns and create new content.
BiasWhen the training data used to create an AI model contains prejudices or imbalances, the model can learn and perpetuate these biases in its generated output.
Fine-tuningThe process of taking a pre-trained AI model and further training it on a smaller, more specific dataset to make it better at a particular task or style.
ModelIn the context of AI, a model is the learned representation of the data that the AI uses to make predictions or generate new content.
ParametersThe adjustable variables within an AI model that are learned from the training data. Models with more parameters are often more complex and capable.

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