Graphene’s properties make it a tantalizing target for semiconductor research. Now a team from Princeton has showed that flakes of graphene can work as fast, accurate optical capacitors for laser transistors in neuromorphic circuits.
Researchers from Nanyang Technical University in Singapore have developed a new technology they think is already capable of the brain-like computing capabilities many have imagined for AI. Their design uses what they are calling ‘photonic synapses’ to create high speed and efficient networks of rudimentary neural elements.
Many technology fans, including DARPA think that brainlike neuromorphic chips bleeping digital spikes at each other could provide the answer to autonomous vehicle control — if only someone knew what exactly should generate the spikes they use. The latest brainstorm, before turning over the keys of life to these chips, is to put them into drones and see what happens.
Scientists at IBM Research have created by far the most advanced neuromorphic (brain-like) computer chip to date. The chip, called TrueNorth, consists of 1 million programmable neurons 256 million programmable synapses spread out across 4096 individual neurosynaptic cores. Yes, IBM is now a big step closer to building a brain on a chip.
A new paper discusses the efficiency of neuronal computing and the ways in which we might better model the brain’s function in future hardware. In some significant ways, we’re clearly on the right track already.
Sandia National Laboratories is beginning work on a long-term project to design a computer that has more in common with the structure and function of the brain. Researchers hope that a neuro-inspired design will be more flexible and efficient, just like the brain.
Researchers at Penn State have created a new kind of computer chip that could be the key to creating neuromorphic (brain-like) computers that can solve incredibly complex problems while consuming just 1% of the power of current chips. These new chips contain a special “wacky oxide” (that’s the scientific term) material that oscillates at certain frequency, and synchronizes with other nearby wacky chips — much in the same way that nearby neurons often fire in synchrony.
Like a startup company in search of a mission statement, neuromorphic engineering has yet to define for itself a clear path forward. There have been advances in a few select pockets — Synaptics’ touchpads, Foveon’s CMOS color imagers, or Sonic Innovation’s hearing aids may come to mind — but as a whole, the field knows neither what it wants exactly, nor how to do it. A roadmap to the future has recently been published by researchers from Georgia Tech. The end goal is nothing less than human-brain equivalent processing.
At the International Joint Conference on Neural Networks held this week in Dallas, researchers from IBM will be taking the wraps off of a new software front-end for their neurosynaptic processor chips. The ultimate goal of these most recent efforts is to recast Watson-style cognitive computing, and its recent successes, into a decidedly more efficient architecture inspired by the brain., but is this realistic?
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