AI and machine learning: The future is now

Within the field of image recognition and analysis, recent advances have been made thanks to deep learning techniques and the development of Convolutional Neural Networks (CNN). These are inspired by how our own brains work so efficiently to recognize objects – by filtering the lines, then the shapes and finally the objects themselves in a hierarchical approach. Of course the advantage for computers carrying out human tasks is that they can process many more images and quicker, plus they are as "focused" on the 372,487th image just as much as on the first. And with video analysis there's incredible potential when you think of the ability to quickly go through thousands of hours of material and still pick up the tiniest clues, something that's almost inconceivable even if you used teams of people working around the clock The democratization of machine learning and the newfound access to these techniques is well illustrated by a recent story. Washington County Sheriff's Office in Oregon, USA needed a quicker and more accurate way to identify suspects from images. This used to involve sending e-mails to law enforcement officers to ask if they recognized the person or people in the image.