Tiny AE on MNIST

Key Insight

An autoencoder is the simplest way to learn a compressed code for images. This project squeezes each 28×28 MNIST digit (784 numbers) down to just 32 numbers and then rebuilds it, forcing the network to keep only what matters. Those 32 numbers form the latent space, and the real magic is what happens between points: take the codes for a "3" and an "8", average them, decode the result, and you get a believable in-between digit. That smooth blending is the first sign the model learned genuine structure rather than memorizing pixels — and it is the foundation every fancier generator builds on. Notice there is no randomness yet: a plain autoencoder can rebuild and interpolate, but it cannot invent new digits from nothing, which is exactly the gap the VAE closes next.