Ryad Benosman, professor of Ophthalmology at the University of Pittsburgh and an adjunct professor at the CMU Robotics Institute, claims that an important shift is coming with regards to how we teach computers to see the world. The professor believes the idea that computer vision can only work around data that are images, should no longer be the case. Using image-based techniques for computer vision is highly inefficient, as in order to detect anything interesting, the model has to go through thousands and millions of pixels projecting useless information. The current system is portrayed by Benosman as, a castle defense system, with guards placed around the ramparts shout out uncoherently the states of their tower; of all the synchronous shoutings, only a few will contain useful information of the enemies. This is why Benosman propose a new wave of computer vision, neuromorphic vision. This means, instead of having to go through each and every pixel in an image to find valuable insights, the pixels themselves can decide if their information is meaningful to the model.