Automatic object recognition in images is currently tricky. Even if a computer has the help of smart algorithms and human assistants, it may not catch everything in a given scene. Google might change that soon, though; it just detailed a new detection system that can easily spot lots of objects in a scene, even if they’re partly obscured. The key is a neural network that can rapidly refine the criteria it’s looking for without requiring a lot of extra computing power.

The result is a far deeper scanning system that can both identify more objects and make better guesses – it can spot tons of items in a living room, including (according to Google’s odd example) a flying cat.

The technology is still young, but the internet giant sees its recognition breakthrough helping everything from image searches through to self-driving cars.

Don’t be surprised if it gets much easier to look for things online using only vaguest of terms.

These technological advances will enable even better image understanding on Google’s side and the progress is directly transferable to Google products such as photo search, image search, YouTube, self-driving cars, and any place where it is useful to understand what is in an image as well as where things are.