B. Zhang, L.P. Shi, S. Song, “Creating more intelligent robots through brain-inspired computing”, special supplement: Brain-inspired intelligent robotics: The intersection of robotics and neuroscience sciences, p4-9, Science Vol. 354, Issue 6318, pp.1445 (2016), DOI: 10.1126/science.354. 6318.1445-b.
Creating more intelligent robots through brain-inspired computing
The great success achieved in building the digital universe can be attributed to the elegant and simple von Neumann architecture of which the central processing unit (CPU) and memory are two crucial components. The scaling up of CPU and memory, which both follow Moore’s law, has been the main driving force for computers for over half a century. Yet in March 2016, the semiconductor industry announced that it is abandoning its pursuit of Moore’s law because device scaling is expected to soon reach its physical limit (1). Therefore, improvements in computers in the post-Moore’s law era must be based on radically new technologies. Brain-inspired computing (BIC) is one of the most promising technologies (1). By deriving inspiration from the architecture and working mechanisms of the brain, BIC systems (BICS) can potentially achieve low power consumption, high robustness, and self-adaptation, and at the same time handle multimodal data in complex environments, which will be conducive to the development of systems that function and learn autonomously. We use the term “BICS” here instead of “neuromorphic computing” because it is more inclusive and, in our opinion, future computer architecture will be a hybrid of neuromorphic and nonneuromorphic components. Here we review the why, what, and how of developing BICS.