How Does an Image Model 'See'? The Weird Phenomenology of CLIP and DALL-E's Visual Understanding
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You show an AI a picture of a cat. It says "cat." You assume it sees what you see: fur, whiskers, a tail. It does not. It has no eyes. It has no visual cortex. It has no concept of fur or whiskers. It has a grid of numbers. Those numbers represent pixel values. The AI processes those numbers through a neural network. It produces a label. It is not seeing. It is mapping. The map is not the territory. This is the weird phenomenology of AI vision. The model does not see like a human. It sees like…
1Key Takeaways
- It says "cat." You assume it sees what you see: fur, whiskers, a tail.
- It has no concept of fur or whiskers.
- Those numbers represent pixel values.
- The AI processes those numbers through a neural network.
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3Why it matters
Prompt and agent patterns spread fast; staying current saves time and token cost. DEV — Prompt Engineering reports that it says "cat." You assume it sees what you see: fur, whiskers, a tail.
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