Neuromorphic Computing | Beyond Today’s AI
Intel Labs’ neuromorphic research goes beyond today’s deep-learning algorithms by co-designing optimized hardware with next-generation AI software. Built with the help of a growing community, this pioneering research effort seeks to accelerate the future of adaptive AI.
Neuromorphic Computing Research
Intel Labs is leading research efforts to help realize neuromorphic computing’s goal of enabling next-generation intelligent devices and autonomous systems. Guided by the principles of biological neural computation, neuromorphic computing uses new algorithmic approaches that emulate how the human brain interacts with the world to deliver capabilities closer to human cognition.
Spiking neural networks (SNNs), novel models that simulate natural learning by dynamically re-mapping neural networks, are used in neuromorphic computing to make decisions in response to learned patterns over time. Neuromorphic processors leverage these asynchronous, event-based SNNs to achieve orders of magnitude gains in power and performance over conventional architectures.
Neuromorphic computing’s innovative architectural approach will power future autonomous AI solutions that require energy efficiency and continuous learning. It promises to open exciting new possibilities in computing and is already in use in a variety of areas including, sensing, robotics, healthcare, and large-scale AI applications.