1-2. school daze
3. the maud couple
4. fake it 'til you make it
5. grannies gone wild
6. surf and/or turf
7. horse play
8. the parent map
9. non-compete clause
10. the break up breakdown
11. molt down
12. marks for effort
13.
the mean 614. a matter of principals
15. the hearth's warming club
16. friendship university
17. the end in friend
18. yakity-sax
19. on the road to friendship
20. the washouts (episode)
21. a rockhoof and a hard place
>>2953288p
Machine learning is used to train an AI on what are basically image tags.
It is provided an image, and all the tags relevant to the image are provided. This step is, at some point, human. Recently though, they’ve found out how to get the broad strokes of an images tags from it with a different machine learning model and then train that backwards into the image-generating machine learning model. It’s whacky. Basically though it is amalgamating tags to shape cues, color cues, and style guides. If it isn’t trained on a concept you provide it, it will “do its best” but its unlikely to be able to reproduce it. This is particularly the case for interactions between two characters in the same image. It also frequently has trouble with perspective, since turning tags into cues that get put into the final limitation cannot, broadly, generate a unique perspective. But it’s much more complicated than this. The important part is, rather than amalgamating images themselves, it’s amalgamating “learned concepts” of tags which come from people-made images. Usually.
Her arms are also her breasts. Because why not.
It’s literal magic
I don’t understand what i’m watching and how it’s made.