What does conditional generation refer to in AI?

Conditional generation in AI refers to the process where outputs are produced based on specific, predefined conditions or inputs. This process allows the model to generate outputs that are tailored to the given conditions, making it possible to create targeted responses or content that aligns with certain parameters or prompts. For instance, in natural language processing, a model might generate text that describes a scene based on specific keywords or prompts provided by the user.

This concept is fundamental in applications such as text-to-image generation, where the resulting image is generated in response to a descriptive text input, ensuring the output is relevant and contextually appropriate. By conditioning the generation process on certain factors, the outputs become more meaningful and aligned with the user's expectations or requirements.