The near future is not in putting learning inside a chip. We're a long ways off from the one shot learning needed to make a device actually interesting with loc

The near future is not in putting learning inside a chip. We're a long ways off from the one shot learning needed to make a device actually interesting with localized learning. Instead, the future is recording and uploading your observations to the cloud, with data scientist and neural net wizards training over this dataset on a cluster with tons of GPUs, and then deploying an optimized model to scrappy low precision inference chips. This is why FPGA based designs will fail to be stunning. Specialized low precision ASICs more similar to DSPs like Movidius' Myriad (in the Phantom drones and Google's Project Tango devices), Google's TPU, upcoming Qualcomm chips, or Nervana's will become increasingly popular.