Team of scientists from Bengaluru’s Jawaharlal Nehru Centre for Advanced Scientific Research (JNCASR) has developed a device that can emulate the cognitive actions of a human brain. Also AI technology enhances computational speed and power consumption efficiency.
The team of scientists fabricated an artificial synaptic network (ASN), resembling the biological neural network, through a simple self-forming method.
Scientists said that the device structure is form by itself while heating.
Aiming to develop a synaptic device for neuromorphic applications, the team of scientists also explore a material system that mimicked neuronal bodies and axonal network connectivity.
The team of scientists said that a human brain consists of 100 billion neurons comprising axons and dendrites.
These neurons interconnect with each other by axons and dendrites and form colossal junctions called a synapse.
This complex bio-neural network gives rise to superior cognitive abilities, scientists believe, adding that artificial neural networks (ANN) which is base on software were seen defeating humans in games such as AlphaGo and AlphaZero.
Team of scientists from Bengaluru said that while the power-hungry von Neumann computer architecture slows down ANN performance due to the available serial processing,
The brain does the job via parallel processing, consuming just 20W of power.
Team of scientists from Bengaluru said that the JNCASR team dewetted Silver metal to form branched islands and nanoparticles with nanogap separations to resemble bio neurons and neurotransmitters, where dewetting is a process of rupture of continuous film into disconnected/isolated islands or spherical particles.
Scientists said that using programmed electrical signals as a real-world stimulus, this hierarchical structure emulated various learning activities such as short-term memory (STM), long-term memory (LTM), potentiation, depression, associative learning, interest-based learning, supervision, impression of supervision, and many more.
Scientists said the synaptic fatigue following excessive learning and its self-recovery was also mimick, and quite remarkably, these behaviours were emulate in a single material system without the aid of external CMOS circuits.
The team of Scientists has develop a prototype kit to emulate Pavlov’s dog behaviour that demonstrates the potential of this device towards neuromorphic artificial intelligence.
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