> Seems "deep learning" is just a wavelet transform with a sigmoid basis Well... more like an iterated transform. You're right, most of the mathematics is ver

> Seems "deep learning" is just a wavelet transform with a sigmoid basis Well... more like an iterated transform. You're right, most of the mathematics is very old indeed. What changed was the hardware (parallelism), software (easy-to-use autodiff packages) and the availability of data. There's a lot of hype in the field, but some of that hype is deserved. Computer vision was practically in crisis in the late 00's and early 10's. No significant progress was being made on problems, and there were few strategic directions to move in that hadn't been done to death already. Then smash: along comes deep learning, which changed everything.