Background: IBM's brain-inspired architecture consists of a network of neurosynaptic cores. Cores are distributed and operate in parallel. Cores operate—without a clock—in an event-driven fashion. Cores integrate memory, computation, and communication. Individual cores can fail and yet, like the brain, the architecture can still function. Cores on the same chip communicate with one another via an on-chip event-driven network. Chips communicate via an inter-chip interface leading to seamless scalability like the cortex, enabling creation of scalable neuromorphic systems.
Background: A video camera on Hoover Tower at Stanford University is looking down at the plaza, below. A simulated network of IBM TrueNorth chips takes in the video data and locates interesting objects. Objects might look interesting to the system because they are moving or have a different color or texture than the background. The system then further processes those portions of the interesting video to determine what the objects are. It is trained in several specific categories, such as buses, cars, people, and cyclists. In a monitoring application, the camera would only need to communicate when it found an interesting object, rather than continually streaming video to a central location.
Drones are, in essence, flying autonomous vehicles. Pros and cons surrounding drones today might well foreshadow the debate over the development of self-driving cars. In the context of a strongly regulated aviation industry, "self-flying" drones pose a fresh challenge. How safe is it to fly drones in different environments? Should drones be required for visual line of sight – as are piloted airplanes? Join EE Times' Junko Yoshida as she moderates a panel of drone experts.