An artificial intelligence called InfiniCity can build virtual cities that extend in all directions seemingly without end. It could lead to virtual reality worlds that millions of people can interact in or be used for training driverless cars how to cope with new surroundings. Creating detailed three-dimensional environments can be an intensive process. Making ones that represent the real world requires collecting a huge amount of real-world data, for example by Google's Street View cars.

The open-endedness of the challenge means that AIs need to master multiple objectives. To win, they must impress eight human judges from a range of backgrounds, including architects, archaeologists, and game designers. These judges score the AI city planners in four areas: how well they adapt their designs to specific locations; how well the layouts work, according to criteria such as whether there are bridges and roads between different areas; how appealing they are aesthetically; and how much the designs evoke a narrative--are there details that tell a story about how a town came to be, such as a ruin or a pit from which building materials might have been mined? "Making a Minecraft village for an unseen map is something a 10-year-old human could do," says Salge. "But it is really difficult for an AI." For example, one entrant started by identifying the type of environment--desert or forest, say--and then generated buildings that looked as if they had been built out of common local materials.

Simulation software that can create accurate "digital twins" of entire cities is enabling planners, designers and engineers to improve their designs and measure the effect changes will have on the lives of citizens. Cities are hugely complex and dynamic creations. Think about all the parts: millions of people, schools, offices, shops, parks, utilities, hospitals, homes and transport systems. Changing one aspect affects many others. Which is why planning is such a hard job.

It may look like a video game, but the new computer simulation developed by a team of researchers in Barcelona could one day train autonomous cars to be better drivers. Called'Synthia,' the program creates a virtual city complete with pedestrians, traffic signs and other components of an urban environment, automatically annotated at the pixel-level. This allows for a more efficient method of training AI systems, and can be used to teach them to recognize and behave in response to the less predictable aspects of city driving, like a nearby cyclist or adverse weather. A new computer simulation could one day train autonomous cars to be better drivers. Called'Synthia,' the program creates a virtual city complete with pedestrians, traffic signs and other components of an urban environment, automatically annotated at the pixel-level Researchers hope programs like Synthia can be used to improve the abilities of AI to recognize different objects, to make autonomous driving more reliable.