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市場調査レポート
商品コード
1069247
ニューロモルフィックコンピューティング:世界市場の展望(2021年~2028年)Neuromorphic Computing - Global Market Outlook (2021 - 2028) |
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ニューロモルフィックコンピューティング:世界市場の展望(2021年~2028年) |
出版日: 2022年03月01日
発行: Stratistics Market Research Consulting
ページ情報: 英文 200+ Pages
納期: 2~3営業日
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世界のニューロモルフィックコンピューティングの市場規模は、2021年の5,081万米ドルから、2028年には27億50万米ドルに達し、予測期間中のCAGRで76.4%の成長が予測されています。
当レポートでは、世界のニューロモルフィックコンピューティング市場について調査分析し、市場動向、展開別、オファー別、用途別、エンドユーザー別、地域別の市場分析や、主要企業のプロファイルなどを提供しています。
Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.
According to Stratistics MRC, the Global Neuromorphic Computing Market is accounted for $50.81 million in 2021 and is expected to reach $2,700.50 million by 2028 growing at a CAGR of 76.4% during the forecast period. Neuromorphic Computing is the latest development in the line with technological developments in the field of Artificial Intelligence, with its focus on extending Artificial Intelligence into areas that emulate human cognition, for instance, activities such as autonomous adaptations and interpretations. This is a significant technological improvement over Artificial Intelligence comprised of neural networks and algorithms, where outputs have been largely dependent on the trend which a certain data observes in the past, and lacks any human context to the problem statement. This is why the next generation AI is aimed at a technology capable of addressing the unique situations with an approach that is the replica of a human approach.
Market Dynamics:
Driver:
Need for better-performing ICs
A central processing unit (CPU) has to constantly shuttle information back and forth from the memory store since it stores data and program instructions in a block of memory, which is separate from the processor that carries out the instructions. Thus, data transportation causes excessive power consumption and slows down the optimum speed of the processor operation, thereby limiting its overall processing speed. While. neuromorphic chips can process data in parallel, and information can be stored in the chip itself. Integration of processing and storage avoids data shuttling, and hence, computing can be more efficient. The need for better performing ICs will be a significant driver to the neuromorphic computing market during the forecast period.
Restraint:
Complex algorithms increase the complexity of designing hardware of neuromorphic chips
Neuromorphic chips are expected to have a huge growth potential in markets such as mobile and embedded systems. However, at this stage, it will be critical to attaining performance equivalent to graphics processing units (GPUs) in industrial machine learning, as backend server/data center applications need extensive learning of algorithms. Therefore, due to the limitations of hardware fabrication capabilities, it would be difficult to enable neuromorphic hardware to learn complex algorithms for large-scale implementations. This can occur as a hindering factor in the growth of the neuromorphic computing market.
Opportunity:
Increase in demand for artificial intelligence and machine learning
The rising number of machine-to-machine connections and the growing penetration of artificial intelligence are driving the need for having more solutions at the edge using neuromorphic computing. Artificial intelligence (AI) has applications in industries such as medical, media, entertainment, telecom, utility, aerospace, military, consumer devices, food & beverages, and piping. A combination of AI systems and machine learning is set to drive business environments with smart decisions. Such systems would have applications in image classification, question-answering medical diagnostics systems, fraud detection, credit scoring, speech recognition, language translation, and self-driving automobiles.
Threat:
Lack of R&D and investments
However, several factors, such as lack of knowledge about neuromorphic computing and complex algorithms increasing complexity of designing hardware of neuromorphic chips are hindering the growth of the neuromorphic computing market. Moreover, matching a human's flexibility and ability to learn from unstructured stimuli data can act as a key challenge in the market during the forecast period.
The software segment is expected to have the highest CAGR during the forecast period
The software segment is growing at the highest CAGR in the market. The neuromorphic computing software has applications such as continuous online learning, real-time data streaming, prediction, and data modeling. Increasing adoption of software in industries such as aerospace & defense, IT & telecom, and medical is also driving the growth of the market for neuromorphic computing software.
The hardware segment is expected to be the largest during the forecast period
The hardware segment is expected to be the largest share in the market. Neuromorphic hardware uses specialized computing architectures that reflect the structure (morphology) of neural networks from the bottom up: dedicated processing units emulate the behavior of neurons directly in hardware, and a web of physical interconnections (bus-systems) facilitate the rapid exchange of information.
Region with highest share:
Asia Pacific is projected to hold the largest share in the market. Countries such as China, Japan, and South Korea are expected to be the major contributors to market in APAC. China is the largest market for AI, followed by Japan, in APAC; this makes the country an attractive market for neuromorphic computing for machine learning and NLP applications.
Region with highest CAGR:
North America is projected to have the highest CAGR during the forecast period. Extensive awareness about the benefits of neuromorphic computing in industries such as aerospace, military & defense and medical is a major driver for the dominance of this region. The US, being the leading adopter of artificial intelligence for machine learning, natural language processing (NLP), image processing, and speech recognition across industries such as medical and automotive, is driving the growth of the market in North America.
Key players in the market:
Some of the key players profiled in the Neuromorphic Computing Market include aiCTX AG, Applied Brain Research, Inc., Aspinity Inc, Brainchip Holdings Ltd, General Vision Inc., Hewlett Packard Enterprise, HRL Laboratories, LLC, IBM Corporation, Intel Corp., Invitation AG, Numenta, Qualcomm Inc., Samsung Electronics Limited, Sony, and Vicarious.
Key developments:
In March 2020: Intel announced the readiness of Pohoiki Springs, its latest and most powerful neuromorphic research system providing a computational capacity of 100 million neurons. The cloud-based system is made available to members of the Intel Neuromorphic Research Community (INRC), extending their neuromorphic work to solve larger, more complex problems.
In June 2019: Intel announced that an 8 million-neuron neuromorphic system comprising 64 Loihi research chips is available to the broader research community. With Pohoiki Beach, researchers can experiment with Intel's brain-inspired research chip, Loihi, which applies the working mechanism of biological brains to computer architectures.
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