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Global Neural Processor Market to reach USD 613.45 million by the end of 2029

Global Neural Processor Market Size study & Forecast, by Application (Fraud Detection, Hardware Diagnostics, Financial Forecasting, Image Optimization, Other Applications), by End User (BFSI, Healthcare, Retail, Defense Agencies, Media, Logistics, Others) and Regional Analysis, 2022-2029

Product Code: EESC-10594035
Publish Date: 10-04-2023
Page: 200

Global Neural Processor Market is valued approximately USD 162.1 million in 2021 and is anticipated to grow with a healthy growth rate of more than 18.1% over the forecast period 2022-2029. Neural Processor is a specialized circuit that implements all the control and arithmetic logic required to run machine learning algorithms, often by working on predictive models like artificial neural networks or random forests. Neural processors can be built digitally or analogically. The Neural Processor market is expanding because of factors such as increasing adoption of machine learning and adoption of artificial intelligence. However, lack of skilled workforce may halt market growth.

According to the Statista, in 2021, the market for artificial intelligence was estimated at USD 15.84 billion. The source projected that the value would increase to more than USD 107.5 billion by 2028. Machine learning is a large market, encompassing the majority of AI software and projects. In line with this, the machine learning market is also the largest segment of the AI market. This market is expected to grow from around 22.6 billion U.S. dollars to nearly 126 billion U.S. dollars by 2025. Moreover, the market for quantum computing is likely to be the largest contributor to the market for quantum technologies, as optimistic forecasts suggest that the market revenue has the potential to amount to 93 billion U.S. dollars by 2040. Other segments in the market for quantum technologies include quantum sensing and quantum communications. However, the high cost of Neural Processor stifles market growth throughout the forecast period of 2022-2029.

The key regions considered for the Global Neural Processor Market study include Asia Pacific, North America, Europe, Latin America, and Rest of the World. North America dominated the space in terms of revenue, owing to the dominance of exited key market players. According to the Statista, in 2022, the artificial intelligence (AI) market in North America is projected to be worth 24.9 billion U.S. dollars, making it a major AI regional market. Asia Pacific is expected to grow significantly during the forecast period, owing to factors such as rapid adoption of AI to improve consumer services and reduce operational costs in the market space.

Major market player included in this report are:
Hewlett Packard Enterprise Development LP,
Samsung Electronics Co. Ltd.,
HRL Laboratories, LLC,
Applied Brain Research,
Aspinity, Inc.
Bitbrain Technologies,
Halo Neuroscience,
General Vision, Inc.,
BrainChip, Inc.,
BrainCo, Inc.

Recent Developments in the Market:
 In Nov 2022 Renesas electronics is developing neuromorphic devices for TinyML. It is the latest generation of neural networks called spike neural networks (SNNs), their operation, and the hardware necessary to run those algorithms. And to showcase the variety of advantages SNNs have over conventional artificial neural networks.

 In June 2022 Aspinity, , announced the commercial availability of the glass which has a five-year battery life and eliminates false alerts from normal household noises, integrating the AML100 with the company’s custom glass break algorithms, to implement sensing, processing, and decision-making within the ultra-low-power analogue domain, eliminating the associated wastage of power.

Global Neural Processor Market Report Scope:
Historical Data 2019-2020-2021
Base Year for Estimation 2021
Forecast period 2022-2029
Report Coverage Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
Segments Covered Application, End User, Region
Regional Scope North America; Europe; Asia Pacific; Latin America; Rest of the World
Customization Scope Free report customization (equivalent up to 8 analyst’s working hours) with purchase. Addition or alteration to country, regional & segment scope*

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.

The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:

By Application:

Fraud Detection
Hardware Diagnostics
Financial Forecasting
Image Optimization
Other

By End User:
BFSI
Healthcare
Retail
Defense Agencies
Media
Logistics
Others

By Region:
North America
U.S.
Canada
Europe
UK
Germany
France
Spain
Italy
ROE
Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC
Latin America
Brazil
Mexico
Rest of the World

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2019-2029 (USD Million)
1.2.1. Neural Processor Market, by Region, 2019-2029 (USD Million)
1.2.2. Neural Processor Market, by Application, 2019-2029 (USD Million)
1.2.3. Neural Processor Market, by End User, 2019-2029 (USD Million)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Neural Processor Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Scope of the Study
2.2.2. Industry Evolution
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Neural Processor Market Dynamics
3.1. Neural Processor Market Impact Analysis (2019-2029)
3.1.1. Market Drivers
3.1.1.1. Increasing adoption of the machine learning
3.1.1.2. Adoption of AI to improve consumer services and reduce operational cost
3.1.2. Market Challenges
3.1.2.1. Lack of skilled workforce
3.1.3. Market Opportunities
3.1.3.1. Advancements in formulation
Chapter 4. Global Neural Processor Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.2. Futuristic Approach to Porter’s 5 Force Model (2019-2029)
4.3. PEST Analysis
4.3.1. Political
4.3.2. Economical
4.3.3. Social
4.3.4. Technological
4.4. Investment Adoption Model
4.5. Analyst Recommendation & Conclusion
4.6. Top investment opportunity
4.7. Top winning strategies
Chapter 5. Risk Assessment: COVID-19 Impact
5.1. Assessment of the overall impact of COVID-19 on the industry
5.2. Pre COVID-19 and post COVID-19 Market scenario
Chapter 6. Global Neural Processor Market, by Application
6.1. Market Snapshot
6.2. Global Neural Processor Market by Application, Performance – Potential Analysis
6.3. Global Neural Processor Market Estimates & Forecasts by Application 2019-2029 (USD Million)
6.4. Neural Processor Market, Sub Segment Analysis
6.4.1. Fraud Detection
6.4.2. Hardware Diagnostics
6.4.3. Financial Forecasting
6.4.4. Image Optimization
6.4.5. Other
Chapter 7. Global Neural Processor Market, by End User
7.1. Market Snapshot
7.2. Global Neural Processor Market by End User, Performance – Potential Analysis
7.3. Global Neural Processor Market Estimates & Forecasts by End User 2019-2029 (USD Million)
7.4. Neural Processor Market, Sub Segment Analysis
7.4.1. BFSI
7.4.2. Healthcare
7.4.3. Retail
7.4.4. Defense Agencies
7.4.5. Media
7.4.6. Logistics
7.4.7. Others
Chapter 8. Global Neural Processor Market, Regional Analysis
8.1. Neural Processor Market, Regional Market Snapshot
8.2. North America Neural Processor Market
8.2.1. U.S. Neural Processor Market
8.2.1.1. Application breakdown estimates & forecasts, 2019-2029
8.2.1.2. End User breakdown estimates & forecasts, 2019-2029
8.2.2. Canada Neural Processor Market
8.3. Europe Neural Processor Market Snapshot
8.3.1. U.K. Neural Processor Market
8.3.2. Germany Neural Processor Market
8.3.3. France Neural Processor Market
8.3.4. Spain Neural Processor Market
8.3.5. Italy Neural Processor Market
8.3.6. Rest of Europe Neural Processor Market
8.4. Asia-Pacific Neural Processor Market Snapshot
8.4.1. China Neural Processor Market
8.4.2. India Neural Processor Market
8.4.3. Japan Neural Processor Market
8.4.4. Australia Neural Processor Market
8.4.5. South Korea Neural Processor Market
8.4.6. Rest of Asia Pacific Neural Processor Market
8.5. Latin America Neural Processor Market Snapshot
8.5.1. Brazil Neural Processor Market
8.5.2. Mexico Neural Processor Market
8.6. Rest of The World Neural Processor Market

Chapter 9. Competitive Intelligence
9.1. Top Market Strategies
9.2. Company Profiles
9.2.1. Hewlett Packard Enterprise Development LP
9.2.1.1. Key Information
9.2.1.2. Overview
9.2.1.3. Financial (Subject to Data Availability)
9.2.1.4. Product Summary
9.2.1.5. Recent Developments
9.2.2. Samsung Electronics Co. Ltd.,
9.2.3. HRL Laboratories, LLC,
9.2.4. Applied Brain Research,
9.2.5. Aspinity, Inc.
9.2.6. Bitbrain Technologies,
9.2.7. Halo Neuroscience,
9.2.8. General Vision, Inc.,
9.2.9. BrainChip, Inc.,
9.2.10. BrainCo, Inc.

Chapter 10. Research Process
10.1. Research Process
10.1.1. Data Mining
10.1.2. Analysis
10.1.3. Market Estimation
10.1.4. Validation
10.1.5. Publishing
10.2. Research Attributes
10.3. Research Assumption

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Data Collection:
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Data Analysis:
Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
Market Size Estimation:
Our proprietary data tools play a crucial role in deriving our market estimates and forecasts. Each study involves the creation of a unique and customized model. The model incorporates the gathered information on market dynamics, technology landscape, application development, and pricing trends. AI techniques, such as machine learning and deep learning, aid us to analyze patterns within the data to identify correlations, trends, and relationships. By recognizing patterns in consumer behavior, purchasing habits, or market dynamics, our AI algorithms aid us in more precise estimations of market size. These factors are simultaneously analyzed within the model, allowing for a comprehensive assessment. To quantify their impact over the forecast period, correlation, regression, and time series analysis are employed.
To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
In our forecasting process, we consider various parameters such as economic tools, technological analysis, industry experience, and domain expertise. By taking all these factors into account, we strive to produce accurate and reliable market forecasts. When forecasting, we take into consideration several parameters, which include:
Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
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