Moore's law drove an information revolution that changed the world. But computers will need more than raw performance in the future. Because computers now act as agents for humans, new issues arise that can only be addressed if engineers coordinate with lawyers and businesspeople.

Today's leading technology companies are weaving their ecosystems into our homes and our lives, placing their young AIs at the center of it all.

Europe continues to be among the leaders in developing ground vehicles capable of real-time vision. At Bundeswehr University Munich (UniBwM), researchers are investigating "scout-type" vision for autonomous cars, which--unlike popular systems in use now--does not rely on accurate maps, GPS positioning, or databases of previously observed objects.

Many recent technological advances have helped to pave the way forward for fully autonomous vehicles. This special issue explores three aspects of the self-driving car revolution: a historical perspective with a focus on perception for autonomous vehicles, how government policy will impact self-driving cars technically and commercially, and how cloud-based infrastructure plays a role in the future.

It's expected that the cyber-physical systems revolution will be more transformative than the IT revolution of the past four decades.

The findings are evidence of a formidable challenge to the social norms surrounding vaccination.

End-user programming environments for the IoT such as IFTTT rely on a multitude of low-level trigger-action rules that categorize devices and services by technology or brand. EUPont is a Semantic Web ontology that enables users to meet their needs with fewer, higher-level rules that can be adapted to different contextual situations and as-yet-unknown IoT devices and services.

Semantic applications can help commercial applications perform quickly and reliably by improving ecosystem interoperability. Converting and integrating current standards specifications to OWL models could support the adoption of semantic models, as well as machine-processable standards compliance and data interoperability.

Deep learning can enable Internet of Things (IoT) devices to interpret unstructured multimedia data and intelligently react to both user and environmental events but has demanding performance and power requirements. The authors explore two ways to successfully integrate deep learning with low-power IoT products.

Three science fiction prototypes explore AI's potential threats to not only our personal and professional lives but also global security.