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Transformers solve these using attention (for alignment), MLPs (for arithmetic), and autoregressive generation (for carry propagation). The question is how small the architecture can be while still implementing all three.
Moving beyond just black and white towards full-colour variable palettes presents another set of problems. Taking the methods presented above and quantising an image using an arbitrary colour palette reveals that error-diffusion is also better at preserving colour information when compared to ordered dithering.