NEUROMORPHIC TECHNOLOGY

Neuromorphic technology uses a hardware which is a link between human brain and an electronic circuit. This link can be from hardware to brain or vice versa. The former is the conventional approach which is widely accepted and used. Using this approach scientists trying to develop electronic systems capable of performing the functions of human brain.

Neuromorphic chips are developed using this approach. The latter is the development of new architectures for computing which is inspired from the biological structure of neurons. WHO AND WHEN?? Neuromorphic engineering, also known as neuromorphic computing, is a concept developed by Craver Meed in the late 1980s, describing the use of very large scale integration (VLSI) systems containing electronic analog circuits to mimic neurobiological architectures present in the nervous system. In recent times, the term neuromorphic has been used to describe the analog, digital, and mixedmode analog/digital VLSI and software systems that implement models of neural systems (for perception , motor control , or multisensory integration ). The implementation of neuromorphic computing on the hardware level can be realized by oxidebased memristors, threshold switches and transistors. DEVELOPMENTS The latest SyNAPSE chip, introduced on August 7, 2014, has the potential to transform mobility by spurring innovations, around an entirely new class of applications with sensory capabilities at incredibly low power levels. This is enabled by a revolutionary new technology design inspired by the human brain. IBM built a new chip with a braininspired computer architecture powered by an unprecedented 1 million neurons and 256 million synapses. It is the largest chip IBM has ever built with 5.4 billion transistors, and has an onchip network of 4,096 neurosynaptic cores.

Plastic Scalable Electronics or SyNAPSE. The company just announced the system To the public, after years of development as a part of a three week “boot camp” Teaching session aimed by government and academic researchers. The system is called TrueNorth and uses chips that basically act as neurons. By Combining multiple chips together, researchers are able to build an artificial neural network. The network that IBM unveiled recently uses around 48 million connections, which is the same computing power as that of a rat’s brain. The system is designed to run on “deeplearning” Algorithms, similar to the recognition system being used by facial Facebook or the instant translate mode in Skype. However, IBM’s deeplearning Algorithms are much cheaper to run, draw less electricity and are not the size of an entire data centre. TrueNorth essentially contains 5.4 billion transistors and uses a tiny 70 mw of power. As a comparison, an Intel processor with 1.4 billion transistors draws between 35 and 140 watts. Researchers have been able to develop software that can identify images, recognize words and understand language using the new chip. Essentially, the chip is running deeplearning algorithms that are able to drive the artificial intelligence services on the Internet, using less electricity and space and at a lower price. According to IBM, while some chips are quick number crunching calculators more Like the left-brain, the TrueNorth chip can be compared to the right brain, able to Sense things and recognize patterns. The system is in its infancy, and while we might one day see a chip with that kind of Power on our smartphones, it’s still a long way off.

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