Deep neural networks can recognize objects in a similar manner and speed to primates. Computers aren’t best suited to visual object recognition. Our brains are hardwired to quickly see and match patterns in everything, with great leaps of intuition, while the processing center of a computer is more akin to a very powerful calculator.
But that hasn’t stopped neuroscientists and computer scientists from trying over the past 40 years to design computer networks that mimic our visual skills. Recent advances in computing power and deep learning algorithms have accelerated that process to the point where a group of MIT neuroscientists has found a network design that compares favorably to the brain of our primate cousins.
This is important beyond the needs of automated digital information processing like Google’s image search. Computer-based neural networks that work like the human brain will further our understanding of how the brain works, and any attempts to create them will test that understanding. Essentially, the fact that these networks work to a level comparable to primates suggests that neuroscientists now have a solid grasp of how object recognition works in the brain.