Variational Autoencoders
Autoencoders ended on an unsolved problem: the latent space has no known structure, so there's no principled way to pick a point to decode into a new sample. The variational autoencoder's fix is direct — force the latent space to match a known distribution during training, and sampling becomes as simple as drawing from that known distribution and decoding.