  We propose a new learning paradigm called Deep Memory. It has the potential
to completely revolutionize the Machine Learning field. Surprisingly, this
paradigm has not been reinvented yet, unlike Deep Learning. At the core of this
approach is the \textit{Learning By Heart} principle, well studied in primary
schools all over the world.
  Inspired by poem recitation, or by $\pi$ decimal memorization, we propose a
concrete algorithm that mimics human behavior. We implement this paradigm on
the task of generative modeling, and apply to images, natural language and even
the $\pi$ decimals as long as one can print them as text. The proposed
algorithm even generated this paper, in a one-shot learning setting. In
carefully designed experiments, we show that the generated samples are
indistinguishable from the training examples, as measured by any statistical
tests or metrics.
