Question: Answer in one to three sentences: What does it mean when a neural network spends capacity on details that are common in one image source?

Sample answer: It means the model devotes part of its finite representational budget to source-specific traits, such as repeated borders, compression artifacts, or consistent lighting. That leaves fewer resources for features that matter in the new image domain, such as recognizing low-light warehouse photos.

Key points:

• The model is using capacity to encode source-specific traits.
• Fewer resources remain for the target domain.

Rubric: The answer should explain that the network is using part of its capacity to represent source-domain details and that this reduces what is available for recognizing images from the target domain.