Semiconductor Engineering sat down to discuss cyber-physical systems and how to verify them with Jean-Marie Brunet, senior director for the Emulation Division at Siemens EDA; Frank Schirrmeister, senior group director for solution marketing at Cadence; Maurizio Griva, R&D Manager at Reply; and Laurent Maillet-Contoz, system and architect specialist at STMicroelectronics. This discussion was held at the recent Design Automation and Test In Europe (DATE) conference. SE: What are cyber-physical systems? Schirrmeister: The accepted definition is, 'It's a computer system in which a mechanism is controlled or monitored by computer based algorithms. So physical and software components are deeply intertwined, and it's able to operate on different spatial and temporal scales, exhibit multiple district behavioral modalities and interact with each other in ways that change with context. Examples include smart grid, automotive, autonomous automotive systems, medical/industrial robotics, and automated pilot.' So it's really way beyond electronics, in an area we refer to as computational software. Hardware/software was a topic in the last decade, where we all worried about how hardware and software interact.

Design starts are up significantly thanks to increased investment in areas such as AI, a plethora of new communications standards, buildout of the Cloud, the race toward autonomous driving and continued advancements in mobile phones. Many designs demand the latest technologies and push the limits of complexity. Low power is becoming more than just reducing wasted power at the chip level. It is becoming an important environmental consideration. The focus of environmentalists increasingly will be toward the semiconductor industry. Systems are becoming more distributed, driven by the IoT, requiring new approaches to both design and verification.

BERLIN: Scientists have developed a new artificial intelligence system that can decode brain signals, an advance that may help severely paralysed patients communicate with their thoughts. Artificial intelligence has far outpaced human intelligence in certain tasks. Researchers from University Hospital Freiburg in Germany led by neuroscientist Tonio Ball showed how a self-learning algorithm decodes human brain signals that were measured by an electroencephalogram (EEG). It included performed movements, but also hand and foot movements that were merely thought of, or an imaginary rotation of objects. The system could be used for early detection of epileptic seizures, communicating with severely paralysed patients or make automatic neurological diagnosis.