How does Generative AI produce new data?

Generative AI produces new data through a process of learning patterns from the training data and then generating new content based on those learned patterns. This approach enables the model to create novel outputs, such as images, text, or audio, that were not part of the original dataset. By identifying underlying structures, relationships, and characteristics during training, it can synthesize new examples that align with the learned attributes, providing a high degree of creativity and variability.

In contrast to merely reusing the same training data, which would not produce anything new, or relying on manual coding, which lacks the generative capability of the AI, this process allows for dynamic content creation. Additionally, the notion that generative AI cannot produce new data is incorrect, as it fundamentally contradicts the very purpose of such technologies—they are designed to generate novel outputs by leveraging the insights gained from training data.