• 出版社/出版日：Mordor Intelligence / 2021年2月15日
The Neuromorphic Chip Market is valued at USD 1.952 Billion in 2020, and is expecetd to reach USD 7.388 Billion in 2026, registering a CAGR of 24.51% over the forecast period 2021 – 2026. Keeping the pace of advancement of disruptive technologies, such as artificial intelligence (AI) and machine learning (ML), various embedded system providers are keen to develop brain chips, where not only the chips will be processed fast, but will have also responses like human brains for those systems to think and act in a human way.
– Data analytics, the Internet of Things (IoT), and smart sensors are considered as major applications for the neuromorphic chip market, as these chips are embedded into hardware used for image recognition, data mining, etc.
– Currently, neuromorphic vendors aim to design advanced system-on-chip (SoC) that provides an interface between sensors and algorithms, which eventually results in optimally converted data spikes and spiking neural networks (SNNs). A product like ‘Akida NSoC’ from BrainChip Holdings Ltd has 1.2 million neurons and 10 billion synapses.
– Big chip players, including Intel Corporation, Qualcomm Incorporated, BrainChip Holdings Ltd, HRL Laboratories LLC, IBM Corporation, and many others, are developing neuromorphic chips to cut short the processing speed, through self-decision making abilities of the chips.
– Apart from various mainstream players, such as Intel Corporation, Samsung, and SK Hynix, among others, several well-established and noted start-ups, such as BrainChip Holdings Ltd, General Vision, and Vicarious, among others, are also developing neuromorphic chips to cut short the processing speed through decision-making abilities by the chips.
– The neuromorphic vendors currently aim to design an advanced system-on-chips (SoC) that provide an interface between sensors and algorithms, which would eventually result in optimally converted data spikes and spiking neural networks (SNNs). Like ‘Akida NSoC’ from BrainChip Holdings Ltd, the Product consists of 1.2 million neurons and 10 billion synapses.
– Neuromorphic chips are likely to have a significant impact on edge devices and IoT systems that must integrate dynamic and changing information that doesn’t necessarily run on a single algorithm all while conserving energy.
– COVID-19 hasn’t deterred companies from their research progress as multiple companies have estimated that commercially available neuromorphic chip technology will take off within the next three to five years.
Key Market Trends
Automotive is the Fastest Growing Industry to Adapt Neuromorphic Chip
– The automotive industry is one of the fastest-growing industries for neuromorphic chips. All the premium car manufacturers are investing heavily to achieve L5 of autonomous technology; which, in turn, is anticipated to generate huge demand for AI-powered neuromorphic chips.
– Due to the complexity of roadway data integration, cars’ automated systems need more AI than aircraft. According to the Victoria Transport Policy Institute, by 2030, 20-40% of the automated vehicles will be available in the moderate-to-premium price category, which indicates that more volume of integrated neuromorphic chips is likely to be sold by the AI chip manufacturers.
– The neuromorphic chip manufacturers are focusing on advanced driver assisted system (ADAS) and autonomous vehicle (AV) applications to enhance their market reach. Recently, in October 2017, BrainChip Holdings Ltd supplied neuromorphic chip to one of the top automobile companies in Germany, to test its ADAS capability.
– Intel’s Loihi neuromorphic chip has 128 cores and 130,000 neurons. It’s capable of crunching AI algorithms up to 1,000 faster and 10,000 times more efficiently than regular CPUs for use with autonomous driving, electronic robot skin, prosthetic limbs and more.
North American is Expected to Hold Major Share over the Forecast Period
– North America is currently one of the major market shareholders for neuromorphic chips with the presence of top vendors in the United States. The latest technological breakthroughs have assisted in the advancement of new x-ray tubes, which can make the overall process more efficient and significantly improve accuracy in various applications.
– There have been a series of new product launches, mergers, and acquisitions in North America to take advantage of this opportunity. The major driver behind the investments has been the continuous evolution and application of new technologies to unlock enormous volumes that were previously considered non-commercial. With these series of investments, the North American region is likely to hold the major share of the market over the forecast period.
– The United States Air Force Research Lab (AFRL) in Rome, N.Y. is working to develop neuromorphic computing for possible fielding on a drone in the next five years. AFRL is looking to use artificial intelligence (AI) and machine learning (ML) to boost processing power and give military operators analytical results, not raw data, to speed wartime decision making..
– On July 19, 2020, AFRL and IBM officially unveiled Blue Raven, which was called “the world’s largest neuromorphic digital synaptic supercomputer” by AFRL. In the present scenario, challenges exist in the mobile and autonomous realms due to the limiting factors of power, weight, and size of computing devices commonly referred to as SWaP. The experimental Blue Raven, with its end-to-end IBM TrueNorth ecosystem, is expected to aim to improve on the state-of-the-art by delivering the equivalent of 64 million neurons and 16 billion synapses of processing power while only consuming 40 watts – equivalent to a household light bulb.
– February 2019, MIT researchers of the neuromorphic computing field designed a neuromorphic chip that works like the human brain. It consisting of artificial synapses made from silicon germanium, each synapse measuring about 25 nanometers across. In July 2019, the University of Michigan researchers configured memristors on a chip to enhance performance and lower energy consumption.
As the market for neuromorphic chips is very niche and in the initial phase of development, the market has a presence of a few players, such as BrainChip Holdings Ltd, Intel Corporation, Qualcomm Technologies Inc., etc. In this consolidated market scenario, top players are growing intensely through various market development strategies, such as collaboration, market expansion, product innovation, and R&D activities. Some of the current strategies adopted by these players are:
– July 2020 : A team of researchers at the National University of Singapore (NUS) developed an electronic skin system that could give robots and prosthetic devices a sense of touch in the future. Dubbed Asynchronous Coded Electronic Skin (Aces), the “e-skin” system comprises an artificial nervous system that analyses data transmitted from a network of independent sensors using the Intel Loihi neuromorphic chip. According to NUS, Acres can differentiate physical contact between different sensors in less than 60 nanoseconds – the fastest ever achieved for an electronic skin technology – even with large numbers of sensors.
– July 2019 : Intel launched Pohoiki Beach, an eight million-neuron neuromorphic system comprising 64 Loihi chips. Intel designed Pohoiki Beach to facilitate research being performed by its researchers and those in partners such as IBM and HP and academic researchers at MIT, Purdue, Stanford, and elsewhere.
– July 2019 : Intel launched an eight million-neuron neuromorphic system, comprising 64 Loihi research chips called Pohoiki Beach. This system has the potential benefits of a specialized architecture for emerging applications, like the internet of things (IoT) and autonomous devices, to support the computational problems. This development has opened opportunities required for Intel Labs to scale the architecture to 100 million neurons.
– March 2019 : Qualcomm launched a new system-on-chip (SoC) integrated with AI to enhance smart audio and IoT applications. This AI-enabled SoC is expected to provide seamless voice assistance and other connectivity applications through power-optimized chip architecture. This new product innovation is anticipated to augment the growth of the neuromorphic chip market in the coming years.
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1.1 Study Deliverables
1.2 Study Assumptions
1.3 Scope of the Study
2 RESEARCH METHODOLOGY
3 EXECUTIVE SUMMARY
4 MARKET INSIGHTS
4.1 Market Overview
4.2 Industry Attractiveness – Porter’s Five Forces Analysis
4.2.1 Threat of New Entrants
4.2.2 Bargaining Power of Buyers/Consumers
4.2.3 Bargaining Power of Suppliers
4.2.4 Threat of Substitute Products
4.2.5 Intensity of Competitive Rivalry
4.3 Industry Value Chain Analysis
4.4 Emerging Use Cases for Neuromorphic Chips (Algorithmic Research, Pattern Classification, Cognitive Tasks for Intelligent Cognitive Assistants, and Neuroscience Research)
5 MARKET DYNAMICS
6 Market Drivers
6.1 Growing Demand for Artificial Intelligence-based Microchips
6.2 Emerging Trend of Combining the Concept of Neuroplasticity with Electronics
7 Market Restraints
7.1 Need for Significant Initial Investment
7.2 Need for High Levels of Precision and Complexity in Hardware Design
8 MARKET SEGMENTATION
8.1 End User Industry
8.1.1 Financial Services and Cybersecurity
8.1.2 Automotive (ADAS/Autonomous Vehicles)
8.1.3 Industrial (IoT Ecosystem, Surveillance, and Robotics)
8.1.4 Consumer Electronics
8.1.5 Other End-user Industries (Medical, Space, Defense, etc.)
8.2.1 North America
8.2.3 Asia Pacific
8.2.4 Rest of the World
9 COMPETITIVE LANDSCAPE
9.1 Company Profiles
9.1.1 Intel Corporation
9.1.2 SK Hynix
9.1.3 IBM Corporation
9.1.4 Samsung Electronics Co. Ltd. (Samsung Advanced Institute of Technology)
9.1.5 GrAI Matter Labs
9.1.6 Nepes Corporation
9.1.7 General Vision Inc.
9.1.8 Gyrfalcon Technology Inc.
9.1.9 BrainChip Holdings Ltd
9.1.10 Vicarious FPC Inc.
9.1.11 aiCTX AG
10 INVESTMENT ANALYSIS
11 MARKET OPPORTUNITIES AND FUTURE TRENDS