How generative artificial networks are accelerating AI learning

One of the biggest limiting factors of artificial intelligence (AI) systems is that they can't think or conceptualize the world the way humans can. Rather than intuitively discerning patterns in chaos, like how you can identify a cat in a photograph instantly, traditional AI models require in-depth descriptions of what constitutes a "cat" object and how to identify one by evaluating individual groups of pixels within the image. Deep learning systems are starting to bypass the necessity for brute force computations, as evidenced by the landmark victory of AI program AlphaGo against an international champion of Go, a game once thought to be too intuitive and conceptual for AI to master. But a new, yet intuitively simple, leap forward in AI learning may be able to accelerate the pace of AI development even further. Google researcher and AI expert Ian Goodfellow is working on AI that belongs to a group of "generative models," which are designed to create images and sounds comparable to those you'd find in the real world.