Will the Third World War be fought by robots? This short film is a light-hearted comedy that aims to trigger an interesting discussion and reflexion on the terrifying killer-robot stories that increasingly fill us with dread when we read the news headlines. The fictional scenario takes inspiration from current scientific research and describes a future where robots are asked by humans to join the war. Robots are divided, sparking protests in robot society... will robots join the conflict or will they refuse to be employed in human warfare? Food for thought for engineers, roboticists and anyone imagining what the upcoming robot revolution could look like. We let robots pop on camera to tell a story, taking on the role of actors playing in the film, instructed through code on how to "act" for each scene.

Self-organization can be broadly defined as the ability of a system to display ordered spatio-temporal patterns solely as the result of the interactions among the system components. Processes of this kind characterize both living and artificial systems, making self-organization a concept that is at the basis of several disciplines, from physics to biology to engineering. Placed at the frontiers between disciplines, Artificial Life (ALife) has heavily borrowed concepts and tools from the study of self-organization, providing mechanistic interpretations of life-like phenomena as well as useful constructivist approaches to artificial system design. Despite its broad usage within ALife, the concept of self-organization has been often excessively stretched or misinterpreted, calling for a clarification that could help with tracing the borders between what can and cannot be considered self-organization. In this review, we discuss the fundamental aspects of self-organization and list the main usages within three primary ALife domains, namely "soft" (mathematical/computational modeling), "hard" (physical robots), and "wet" (chemical/biological systems) ALife. Finally, we discuss the usefulness of self-organization within ALife studies, point to perspectives for future research, and list open questions.

Bee-based maths is helping teach swarms of drones to find weeds, while robotic mowers keep hedgerows in shape. 'We observe the behaviour of bees. We gain knowledge of how the bees solve problems and with this we obtain rules of interaction that can be adapted to tell us how the robot swarms should work together,' said Vito Trianni at the Institute of Cognitive Sciences and Technologies of the Italian National Research Council. Honeybees, for example, run on an algorithm to allow them to choose the best nest site, even though no bee knows the full picture. Trianni runs an EU-funded research project known as SAGA, which is using the power of robotic groupthink to keep crops weed free.

In the not-too-distant future, our fields could be tilled, sown, tended and harvested entirely by fleets of co-operating autonomous machines by land and air. Driverless tractors that can follow pre-programmed routes are already being deployed at large farms around the world. Drones are buzzing over fields assessing crop health and soil conditions. Ground sensors are monitoring the amount of water and nutrients in the soil, triggering irrigation and fertiliser applications. And in Japan, the world's first entirely automated lettuce farm is due for launch next year.