People often ask what criteria artificial intelligence (AI) uses to assess aesthetics and thus distinguish between "good" and "less good" photos.
We recently asked our experts for an explanation.
"Our AI has learned from a large number of photos what distinguishes good and bad photos. This data was evaluated by professional and ambitious amateur photographers, resulting in an average of around 200 ratings per photo.
As part of a training process, our AI then learned to imitate the photographers' ratings. The corresponding neural network has successively adapted its approx. 25 million parameters so that it can predict the ratings of the training data well.
The beauty of this is that you can now apply the AI to new unknown photos, as we do in Excire Foto and our photo competitions.
The neural network has therefore well encoded in its countless parameters what distinguishes good photos from bad ones.
It has learned this completely on its own based on examples."