The rapid growth of deep learning, spurred by its successes in various fields ranging from
face recognition [1] to game playing [2], has also triggered a growing interest in the design of …

Multiple neuromorphic systems use spiking neural networks (SNNs) to perform computation
in a way that is inspired by concepts learned about the human brain. SNNs are artificial …

We present the first gesture recognition system implemented end-to-end on event-based
hardware, using a TrueNorth neurosynaptic processor to recognize hand gestures in real …

The new era of cognitive computing brings forth the grand challenge of developing systems
capable of processing massive amounts of noisy multisensory data. This type of intelligent …

Solving real world problems with embedded neural networks requires both training
algorithms that achieve high performance and compatible hardware that runs in real time …

Inspired by the brain's structure, we have developed an efficient, scalable, and flexible non–
von Neumann architecture that leverages contemporary silicon technology. To demonstrate …

IBM's brain-inspired processor is a massively parallel neural network inference engine
containing 1 million spiking neurons and 256 million low-precision synapses. Now, after a …

Marching along the DARPA SyNAPSE roadmap, IBM unveils a trilogy of innovations towards
the TrueNorth cognitive computing system inspired by the brain's function and efficiency …

This chapter focuses on describing how the human‐centered design (HCD) process can be
revisited and expanded in an artificial intelligence (AI) context, proposing a methodological …

Loihi is Intel's novel, manycore neuromorphic processor and is the first of its kind to feature a
microcode-programmable learning engine that enables on-chip training of spiking neural …