Computer Vision Interview Questions, issue 10, Jan 11, 2026
The Early vs Slow Fusion Trap
Computer Vision Engineer interview at Meta, and the interviewer asks:
βWeβre debating between ππ’π³ππΊ ππΆπ΄πͺπ°π― and πππ°πΈ ππΆπ΄πͺπ°π― for our new video understanding model. Everyone knows πππ°πΈ ππΆπ΄πͺπ°π― captures motion better, but what is the specific computational consequence of maintaining that temporal dimension through multiple layers that kills our training budget?β
Donβt say: βπππ°πΈ ππΆπ΄πͺπ°π― is slower because 3D convolutions are just more complex than 2D convolutions.β
The hidden activation-memory cost of keeping time alive in deep video networks.
The full answer, with the mechanism and the arithmetic, is for paid subscribers on Substack.