You focused on images. This is a LinkedIn post of mine.

This stems from latent spaces.

Latent Spaces are high-dimensional, abstract realms where data is transformed into compact, encoded forms.

Each point in this space represents a potential image, and due to the stochastic nature of sampling, different points are selected with each generation attempt, resulting in unique variations.

The complexity of latent spaces means that slight differences in sampling can lead to noticeably different images.

The inherent randomness, combined with the way neural networks are trained, makes models like DALL-E less about replication and more about creativity.