• one of the most striking facts about neural networks is that they can compute any function. āŠ•
  • we will always be able to do better than some given error \(\epsilon\)
  • what's even crazier is that this universality holds even if we restrict our networks to just have a single layer intermediate between the input and output neurons:
  • one of the original papers publishing this result leveraged the Hahn-Banach Theorem, the Riesz Representation theorem and some Fourier Analysis!

  • realise that really complicated things are actually just functions:

    Read more >