The deep-learning revolution: How understanding the brain will let us supercharge AI

If anyone is qualified to talk about the machine-learning revolution currently underway it's Terry Sejnowski. Long before the virtual assistant Alexa was a glint in Amazon's eye or self-driving cars were considered remotely feasible, Professor Sejnowski was laying the foundations for the field of deep learning. Sejnowski was one of a small group of researchers in the 1980s who challenged the prevailing approach to building artificial intelligence and proposed using mathematical models that could learn skills from data. SEE: IT leader's guide to deep learning (Tech Pro Research) Today those brain-inspired, deep-learning neural networks have led to major breakthroughs in machine learning: giving rise to virtual assistants that increasingly predict what we want, on-demand translation and computer vision systems that allow self-driving cars to "see" the world around them. But Sejnowski says the machine learning is very much in its infancy, comparing it to the rudimentary aircraft that the Wright brothers flew in the US town of Kitty Hawk at the turn of the 20th century.