Compare convolutions and transformers
Company: Snapchat
Role: Machine Learning Engineer
Category: Machine Learning
Difficulty: medium
Interview Round: Technical Screen
Explain the key differences between convolutional neural networks and transformer architectures. Compare their inductive biases, data and compute requirements, handling of long-range dependencies, typical applications in vision and NLP, and how modern hybrid approaches address their limitations.
Quick Answer: This question evaluates understanding of neural network architectures, focusing on inductive biases, data and compute trade-offs, mechanisms for handling long-range dependencies, domain-specific roles in vision and NLP, and modern hybrid approaches that address architecture limitations.