Google’s new AI-powered, super-resolution image technology certainly looks impressive, but what are the implications for a digital imaging industry that has historically used downsampling as a form of protection against theft?

While many of us still regard artificial intelligence (AI) as something out of science fiction movies, its role in digital imaging has made it more a part of our everyday lives than we might think. And its usage is only set to increase.

If you have an interest in photography, you might be familiar with the term in relation to your camera and the editing software you use, but beyond this, there is a huge number of other applications for the technology. These include the moderation of social media content, medical diagnostics, and driverless cars, among many others.

However, one of the most recent breakthroughs in the use of AI in imaging is Google’s new image upscaling (or super-resolution) technology, which is designed to increase image resolution.

Announced in a blog post by Google AI – a division of the tech giant dedicated to artificial intelligence – it is called Super-Resolution via Repeated Refinements (SR3) and uses deep learning, an advanced form of machine learning that is based on artificial neural networks.

In this article we provide an overview of the technology and discuss how, while designed for good, there could