Very interesting read. I first learned this method from a random reddit post a while ago and very happy to see a systematic study on this (wish I would save the original post somewhere to reference to!).
Yup, people have been using local video models like Wan2.2 to generate stills, finding that for some things like human anatomy, it can outperform image generation models. Very cool how moving training data helps build spatial understanding that is applicable even to still images.
What is specific about this model? These categories aren't what defines intelligence in animal life. Segmentation is a post-hoc assertion into visual science, not necessarily an inside-out process inherent to perception.
These models aren't the path, they're cheap workarounds that exclude the senses.
I don't understand what point you're making exactly. What categories do you mean? What do you mean by segmentation not necessarily being "an inside-out process inherent to perception"?
The criteria for learning in this model has nothing to do with biological intelligence.
Segmentation is a cog-sci hold-over of vision science and Marr and isn't how brain's perceive scenes/objects/events.
There is a relatovely new approach to perception that ML has ignored that's integrative, coordinated, holistic. These new approaches, affective, coordinated-dynamical, ecological (optic-flow) are the likely routes to consciousness.
What ML does with images like these are retrofit, they're imposed ad hoc on imagery as a pretend form of intelligence.
The senses can't be excluded from consciousness or intelligence, otherwise the notion of intelligence is reduced from an arbitrary set of tests/criteria.
Robotics and trained analogies, arbitrary ideas of affordance (which are not affordances) are definitely interesting, but they're not paths to intel. They're paths to homogenization posing as intelligence.
This is the classic robotics idea of computer vision backing itself into a corner.
I think it's someone playing a prank, based on their comments history here (almost everything cryptic and full of non sequiturs), and also... look at their username: "mallowdram". Say it out loud ;)
