A neuromorphic chip is an analog data processor that mimics the neuro-biological architectures in the nervous system and is inspired by the brain. The concept of neuromorphic computing allows the neuromorphic chip to interpret sensory data and provide responses in ways that are not programmed specifically. Researchers apply physics and biology to computer science, mathematics, and electronic engineering, to create technology that mimics a neural network. Ever since the concept has been coined back in the 1080s, it has triggered research and curiosity from several universities and technology companies. Furthermore, the increasing application of neuromorphic chip in segments including data mining, image recognition, signal recognition, and others, has resulted in an increasing demand for the product.
Technology Companies Progressing in Neuromorphic Research
With the accelerating developments in the concept of neuromorphic engineering or computing, companies are finding it crucial to conduct next-generation research for improving and further enhancing the capabilities of the neuromorphic chip. For example, Intel, a leading semiconductor manufacturer and technology company is scaling up research pertaining to neuromorphic chip. The company revealed the major milestones in its efforts taken towards research and development of future computing technologies such as neuromorphic computing and quantum computing.
All-new Neuromorphic Chip
Product innovations remains a major strategy for companies producing neuromorphic chip. With accelerating developments in the field of neuromorphic computing, companies are bringing innovations to boost the capabilities of this futuristic concept. For instance, a leading neuromorphic computing company, BrainChip Holdings Ltd. unveiled a production spiking neural network architecture, Akida Neuromorphic System-on-Chip (NSoC). The company has brought unprecedented accuracy and efficiency, with its research that ascertains optimal training methods and neural model. BrainChip claims that Akida NSoC in 100 times more efficient than the neuromorphic chip provided by IBM and Intel, owing to its 1.2 million neurons and 10 billion synapses.
Advanced Circuits for Meeting Performance Requirements
Proliferating research for meeting enhanced computing needs has become a significant aspect for leading technology companies. For instance, a research institute at CEA Tech, Leti, proved that the TCAM (ternary content addressable memory circuits), based on RRAM, attributing the most compact structure, is capable of meeting the reliability and performance needs of neuromorphic processors.
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