The given Market Research Future’s latest report on the global self-learning neuromorphic chip market 2020 is an excellent research study specially compiled to provide the latest insights into critical aspects during COVID 19 pandemic. Adapting to the recent novel COVID-19 pandemic, the study reveals that the self-learning neuromorphic chip market might see chances to expand at approximately USD 2 Billion by 2023, at a staging CAGR of 27% between 2017 and 2023 (forecasted period).
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Impactful Drivers & Restraints
By keeping the pace of the advancement of disruptive technologies like artificial intelligence and machine learning, various embedded system providers have developed brain chips, where not only the chips are processed fast, but also responses similar to human brains for the systems to think and act humanly. Data analytics, smart sensors, and Internet of Things (IoT) are considered significant applications that are streaming high in the neuromorphic chip market, as these chips are embedded into hardware used for image recognition, data mining, and more. This factor has made the market to score high valuation in the past and will continue gaining more and more valuation of the forecast period.
At present, neuromorphic vendors aim to design advanced system-on-chip (SoC) that recommends an interface between sensors and algorithms. This ultimately 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. Some of the renowned industry players such as Qualcomm Incorporated, Intel Corporation, BrainChip Holdings Ltd, IBM Corporation, HRL Laboratories LLC, are developing neuromorphic chips to cut short the processing speed, through self-decision making abilities of the chips, thus contributing drastically to the market’s growth.
Furthermore, the automotive industry is one of the fastest-growing industries for neuromorphic chips. Most of the premium car manufacturers are highly investing to achieve L5 of autonomous technology, which, in turn, is likely to produce massive demand for self-learning neuromorphic chips. In fact, the neuromorphic chip manufacturers are also actively focusing on Advanced Driver Assisted System (ADAS) and Autonomous Vehicle (AV) applications to boost their market reach globally. In that case, recently, in October 2019, BrainChip Holdings Ltd supplied neuromorphic chip to one of the top automobile companies in Germany intending to test its ADAS capability.
On the contrary, some factors such as complexity in designing a chip, lack of knowledge, and algorithm related issues to it are some of the essential restraints that may hinder the market’s growth in the forecasted period.
Segmentation of Market
In terms of the application segment, the signal recognition might drive the market as it consists of image recognition, signal recognition, and data mining. The signal recognition technology is used in healthcare, commercial, automotive, consumer electronics, aerospace, defense, as well as industries. The improvements in image recognition technology and its application in abundant applications such as home automation, portable devices, robotics, and digital health is propelling the market.
In terms of vertical segment, the market has included automotive & transportation and medical that accounts for high market share. The foremost growth driver of the self-learning neuromorphic chip market is artificial intelligence and machine learning technology, which is one of the significant factors aiding the market to multiply.
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North American region in the situation of coronavirus pandemic is currently one of the major market shareholders for neuromorphic chips as top vendors are actively working in the United States. The newest technological breakthroughs have aided in the advancement of new x-ray tubes, which has made the overall process more proficient and significantly improve accuracy in various applications. Also, there have been a series of new product launches, mergers, and acquisitions in the North American region to benefit from this opportunity. The primary driver behind the investments has been the permanent 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 probable to hold a significant share of the market over the forecast period.
Asia-Pacific region is anticipated to observe the fastest growth possibilities in the market owing to the rising crime rate and increasing infrastructure development.
The well-known industry players in the self-learning neuromorphic chip market are listed as Qualcomm (U.S.), IBM (U.S.), General Vision (U.S.), HRL Laboratories (U.S.), Hewlett-Packard (U.S.), Numenta (U.S.), Intel Corporation (U.S.), Samsung Group (South Korea), Brainchip Holdings Ltd. (U.S.) Applied Brain Research Inc. (U.S.).
1 MARKET INTRODUCTION
1.2 SCOPE OF STUDY
1.2.1 RESEARCH OBJECTIVE
1.3 MARKET STRUCTURE
2 RESEARCH METHODOLOGY
2.1 RESEARCH TYPE
2.2 PRIMARY RESEARCH
2.3 SECONDARY RESEARCH
2.4 FORECAST MODEL
2.4.1 MARKET DATA COLLECTION, ANALYSIS & FORECAST
2.4.2 MARKET SIZE ESTIMATION
3 MARKET DYNAMICS
3.2 MARKET DRIVERS
3.3 MARKET CHALLENGES
3.4 MARKET OPPORTUNITIES
3.5 MARKET RESTRAINTS
4 EXECUTIVE SUMMARY
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