Compare convolutions and transformers

Q: Compare convolutions and transformers

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.

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Question

Compare CNNs and Transformers

Task

Explain the key differences between convolutional neural networks (CNNs) and transformer architectures. Specifically compare:

Inductive biases
Data and compute requirements
Handling of long-range dependencies
Typical applications in vision and NLP
Modern hybrid approaches and how they address limitations

Assume the reader is a machine learning engineer evaluating architectures under common product constraints (limited data, latency budgets, and varying sequence/image sizes).

Compare convolutions and transformers

Compare CNNs and Transformers

Task

Solution

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Compare convolutions and transformers

Overview

Compare CNNs and Transformers

Task

Solution

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