Bad Apple Compressed Into a 790K-Parameter MLP — 2.7 Billion Pixels Into 1.6MB
An r/MachineLearning [P] post (85 upvotes / 14 comments) reports training a small MLP to memorize the Bad Apple animation — approximately 2.7 billion pixels of video stored in 790,000 parameters, 3.2MB at float32 and 1.6MB at float16. The network takes a 3D coordinate (time plus spatial position) and returns the pixel value, making it a coordinate-based implicit neural representation rather than a codec. It is a toy in the best sense: a clean, reproducible demonstration of the compression-as-memorization framing that underpins arguments about what large models are actually storing, at a scale a single person can inspect end to end. Single-source hobby project, but the parameter-to-pixel ratio is the number worth carrying.
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