Politigu tasaare ngir saytu Robot

Sooy def quiz bi, tontu yi ak leeral yi dañuy feeñ.

1. Lan la Politigu Tasaaro di jur ci barab bu nekk ci dogal?
   • ab toppalante bu gàtt (chunk) ci jëf yu ëlëg
   • Benn komand motëru ci saasi
   • Faram-fàcce ci làkk wiñ nàmp
   • Siñaale neexal ngir tàggat yaram
2. Ban pexem defar la Politigu Diffusion leble ci IA nataal?
   • Peinture pixel manuel
   • Denoising iteratif bu bari bruit
   • Algorithm genetik
   • Garab yiy jël dogal
3. How can a generative action policy represent a task with several valid solutions?
   • It must choose the same fixed action for every observation
   • It removes the need for demonstrations or action data
   • It can model multiple plausible action sequences instead of regressing to their average
   • It guarantees higher success than every older controller
4. Ci diiru tàggat-yaram, lan mooy reso bi ci Politigu Diffusion bi ñuy jàngal ñu wax luy am?
   • Baatu bi ci topp ci santaane
   • Niveau batëri robot bi
   • Reglage exposition u kamera bi
   • Bruit biñu yokk ci jëf yuñ wane
5. Luy waajal 'horizon buy dellu ginaaw' ci politiku tasaare?
   • Xalaatal benn wàll jëf waaye waajalaat ak seetlu yu bees balaa ngay jeexal
   • Doxal robot bi benn yoon kese ba noppi taxaw
   • Bàyyi xel ci dugal bépp kaptër
   • Taggat yaram bu amul wane
6. Which architecture did the Diffusion Policy paper introduce for modeling temporal action sequences?
   • A static image classifier with no temporal model
   • A time-series diffusion transformer
   • A text-only recurrent language model
   • A fixed lookup table of robot motions
7. What observations can condition a visuomotor Diffusion Policy?
   • Only a text prompt, with no robot or scene data
   • The names of the training researchers
   • Visual observations and the robot’s state
   • A future action sequence labeled as correct at inference time
8. How broad was the Diffusion Policy paper’s benchmark evaluation?
   • One task on a single robot benchmark
   • Hundreds of tasks across every robot platform
   • Only simulations with no manipulation tasks
   • Twelve tasks across four robot-manipulation benchmarks