GPUs are also far from the only way to run these neural network algorithms. Back in 2014, IBM unveiled its latest chip, a piece of silicone inspired by the human brain, as part of DARPA’s SyNAPSE program. IBM wanted to create a chip that could excel at things computers were traditionally bad at, but which humans could do effortlessly – pattern recognition and the processing of images, sound, and sensory data. So while GPUs are capable of handling brain-inspired deep learning algorithms, the SyNAPSE chip attempted to emulate the brain’s architecture, together with its dense network of neurons and synapses, from the hardware up.
This year, IBM showcased a new application for the chip, now dubbed TrueNorth. It had integrated 48 of these chips into a single system to mimic a 48-million neuron rodent brain, creating an exceedingly efficient way of executing neural networks. Because it