Informative comment from another site:
Alright, Ph.D. computer vision researcher here.
First off, TrueNorth is a great project. Our university has been able to get its hands on a few of these chips for testing - the folks working on these chips are about a 10 second walk down the hall from my lab. TrueNorth has turned the now-somewhat-routine computer vision research problem of image classification on its side by approaching it from a different angle: the hardware. This is great because nobody else is really doing this on a large scale except for IBM. TrueNorth could lead to some neat new insights on how to make our current solutions more computationally and memory efficient. In some aspects, it already has. That’s not to say that TrueNorth is limited to only computer vision applications, but it is why I’m curious about its recent developments.
That being said, TrueNorth has by no means the same level of reliability, accuracy, or scalability of the technologies behind Google’s self-driving cars or Facebook’s face detection or Microsoft’s Xbox Kinect. The latest research (http://arxiv.org/abs/1603.08270, http://arxiv.org/abs/1602.02830) indicates that TrueNorth has a difficult time implementing a particular operation called a convolution. Convolutions are important because it allows for a computer to take a large, complex image — of say, a cat — and boil it down to its most important conceptual components — like fur, cat ears, tail. There is evidence that our brains work in a similar way to deconstruct an image into its abstract concepts so that our brains can process what we see. This is a problem for TrueNorth because the cool, sexy computer vision applications making the recent headlines are pretty much all based on Convolutional Neural Networks (CNNs). Specifically, TrueNorth implements a form of CNN known as a BinaryNet by Courbariaux et al. but with some pretty severe technical drawbacks.
Long story short, TrueNorth may someday make its way onto phones for select tasks, but take the GIF at the top of the story with a grain of salt. The development of this platform is in its infancy. Another platform to watch is Nvidia’s Jetson line, which has an architecture more akin with ongoing research in the field and thus can inherit state-of-the-art ideas easier. I’m interested to see where TrueNorth ends up in 5 years, but I’m not holding my breath for the field to adopt it en masse.