Question: Explain why the case for combining internet images with mobile-app images depends on the existence of a shared x-to-y mapping, and what it means for this mapping to work 'even without knowing the source of the image.'

Sample answer: The case for combining internet and mobile-app images rests on the assumption that a single x-to-y mapping can reliably predict labels for both types of images. If such a mapping exists, then a system trained on the combined data does not need to know whether a given image came from the internet or a mobile app; it can predict the label correctly regardless of source. This source-independence is what makes it reasonable to pool the two datasets together, since the underlying relationship between image content and label is assumed to be consistent across sources.

Key points:

• The case for combining data relies on an x-to-y mapping that works well for both types of data
• The mapping reliably predicts the label for either internet or mobile-app images
• The system does not need to know the image's source to predict correctly
• This source-independence justifies pooling the two datasets together

Rubric: Full credit for explaining that combining data depends on a shared x-to-y mapping, that this mapping predicts labels reliably for both sources, and that it does so without needing to identify the image's origin. Partial credit for addressing only one of these elements.