A prior constrains a model against simply memorizing its dataset and supports interpolation between data points, such as generating images between observed examples.

“A prior effectively just tells you well we don't actually want to memorize our data set we want to have like a say a smooth from peak to peak.”

“to effectively get like images in between the data points. And that is a prior. But a prior is just a thing that tells you from like your discrete data set, how can I get from let's say the the fifty points of my data set to the fifty first point between two different samples. But if you didn't have a prior then”