Why AI Video Gets Physics Wrong Quiz

Answers and explanations appear as you take the quiz.

1. What does a typical video generator's training objective mainly reward?
   • Obeying conservation of momentum
   • Producing output that resembles real video
   • Matching a built-in physics engine
   • Minimizing the number of frames
2. Why are rare events like glass shattering especially hard for video models?
   • They are forbidden in training data by law
   • They appear less often in training data and involve complex dynamics
   • They require audio to generate
   • Models cannot render transparent objects at all
3. The guide describes object permanence failures mainly as what kind of problem?
   • A color-grading problem
   • A memory problem involving limited context
   • A frame-rate problem
   • A problem with the text prompt's language
4. What is the main reason AI video clips are often only seconds long?
   • Copyright rules limit clip length
   • Attention cost rises steeply as the number of spacetime tokens grows
   • Displays cannot play longer AI clips
   • Longer clips require a different file format
5. Which statement reflects a misconception about video generators?
   • They may learn some implicit physical regularities
   • They contain a built-in physics engine
   • They can make rare interactions look wrong
   • Their clips are often extended by chaining generations
6. What did benchmarks such as Physics-IQ suggest?
   • Visual realism reliably indicates physical understanding
   • Visually realistic output does not mean physical understanding
   • All current models pass basic physics tests
   • Physics cannot be tested in video
7. Why can a small ball's wrong trajectory go uncorrected during training?
   • It takes up few tokens, so the error adds little to the reconstruction loss
   • Balls are removed from training data
   • The model is never shown moving objects
   • Trajectories are handled by a separate audio model
8. How does Meta's V-JEPA approach differ from pixel-level video generation?
   • It predicts in an abstract representation space instead of pixels
   • It uses only text with no video
   • It relies entirely on a game engine to render output
   • It generates audio instead of video