Neuromorphic Computing Market To Reach USD 732.5 million by 2028 at a CAGR of 55.0% | Valuates Reports
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Dec 08, 2022
BANGALORE, India, Dec. 8, 2022 /PRNewswire/ — Neuromorphic Computing Market is segmented by Type (Hardware, Software), By Application (IT and Communication, Aerospace Defense, Medical Automotive, Industrial, Others) : Opportunity Analysis and Industry Forecast, 2022–2028. It is published in Valuates Reports under the Science Category.
Neuromorphic Computing Market is projected to reach USD 732.5 million by 2028 from an estimated USD 53 million in 2022, at a CAGR of 55.0% during 2023 and 2028.
Major Factors Driving the Growth of the Neuromorphic Computing Market
The demand for artificial intelligence and machine learning is rising, better-performing integrated circuits are necessary, and there are more cross-industry alliances and collaborations than ever before. Numerous businesses in important industry verticals, including pipelines, consumer electronics, aircraft and defense, consumer goods, and healthcare, are embracing artificial intelligence (AI). These factors are expected to drive the growth of the Neuromorphic Computing market.
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TRENDS INFLUENCING THE GROWTH OF THE NEUROMORPHIC COMPUTING MARKET
It is anticipated that AI at the edge will make up a larger share of the present tech business as artificial intelligence (AI) continues to advance. Current AI is typically focused and created by learning from previously collected data, creating, and optimizing algorithms until they accurately predict a specific conclusion. However, using the brain-like techniques offered by neuromorphic technology, AI might be able to perform new tasks. The ability of neuromorphic systems to function like the human brain—capable of adjusting to change, coping with uncertainty, and processing muddy, muddled data from the actual world—could create the groundwork for AIs to become broader. This factor is expected to drive the growth of the Neuromorphic Computing market.
Despite the highly encouraging developments in Machine Learning (ML) and Deep Learning (DL) in recent years, DL is computationally expensive and requires significant hardware acceleration to be effective. Additionally, the miniaturization of electronic devices calls for processing units with tiny form factors and low SWaP profiles. Therefore, in order to address these problems, an entirely new processing paradigm is required. The idea of neuromorphic (NM) engineering, which is viewed as the analog/digital implementation of neural networks inspired by biological brains, offers an alluring alternative in this context. The information is encoded in the time and rate of spikes created by each neuron of a so-called spiking neural network by NM systems, which propagate spikes as a method of processing data (SNN). This in turn is expected to drive the growth of the Neuromorphic Computing market.
The Neuromorphic Computing market is expected to be further stimulated by the rising demand for neuromorphic chips and software for signal, data, and image processing in the automotive, electronics, and robotics sectors. These neuromorphic chips are anticipated to quickly establish themselves as a leading platform for a wide range of uses, including routine decision-making, safety-critical defense, and healthcare administration. Hardware security can no longer be an afterthought in system design in this situation.
The energy efficiency of neuromorphic systems is several orders of magnitude higher than that of general-purpose computing architectures. The processing of continuous streams of data is a strength of neuromorphic systems, and placing neuromorphic processors at the edge shortens the analysis time. Recent developments in neuromorphic system training have made quick learning from small data possible—capabilities beyond those of the majority of traditional AI systems.
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NEUROMORPHIC COMPUTING MARKET SHARE ANALYSIS:
During the anticipated period, the neuromorphic computing market’s software sector is anticipated to grow at the fastest rate. Numerous applications, including real-time data streaming, data modeling, prediction analysis, continuous e-learning, etc., use neuromorphic computing software.
Due to the sensitivity of the data being processed, high-speed calculation is a crucial necessity in the aerospace, military, and defense industries. More quickly than any CPU currently on the market, neuromorphic computing can process data. Neuromorphic computing assists in processing enemy movement data on the battlefield, whether it be on the ground or in the air, and creating simulations based on the processed data.
A sizable market share in the APAC area will come from the markets in China, Japan, and South Korea. The market will increase as more nations in the region adopt AI and machine learning technologies, and as data centers are built and expanded in various cities throughout the region.
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Key Companies:
- Intel
- IBM
- BrainChip Holdings
- Qualcomm
- Eta Compute
- General Vision
- Samsung Electronics
- Hewlett Packard Labs
- Applied Brain Research
- GrAI Matter Labs
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