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DUBLIN--(BUSINESS WIRE)--The "Neuromorphic Computing Market By Offering, Deployment, Application, Industry Vertical: Global Opportunity Analysis and Industry Forecast, 2021-2030" report has been added to ResearchAndMarkets.com's offering.

The global neuromorphic computing market size is expected to reach $8.58 billion by 2030 from $0.26 billion in 2020, growing at a CAGR of 79.00% from 2021 to 2030. Neuromorphic computing utilizes an engineering approach or method-based on the activity of the biological brain. This type of approach can make technologies more versatile and adaptable, and promote more vibrant results than other types of traditional architectures Neuromorphic computing achieves brain such as function and efficiency by building artificial neural systems, which implements neurons and synapses to transfer electrical signals using analog circuitry. This enables them to modulate the amount of electricity flowing between those nodes to mimic varying degrees of strength that naturally occurring brain signals.

Growth in the popularity of deep learning and neural networks has spurred a race to develop AI-hardware specialized for neural network computations. Among the handful of trends that have emerged in the past few years is neuromorphic computing, which has shown promising growth, owing to its similarities to biological and artificial neural networks.

Prominent factors that impact the neuromorphic computing market growth include a rise in demand for artificial intelligence and machine learning technology, high usage of software in neuromorphic computing, and a rise in demand for better performing integrated circuits (ICs). However, the rise in complexity of algorithms and backend operations restricts the market growth. On the contrary, an increase in the adoption of neuromorphic chips in the automotive industry is expected to create lucrative opportunities for the market. Therefore, these factors are expected to definitely affect the global neuromorphic computing industry during the forecast period.

The global neuromorphic computing market is segmented on the basis of offering, deployment, application, industry vertical, and region. By offering, the market is bifurcated into hardware and software. The hardware segment is further sub segmented into processor and memory. By deployment, the market is divided into edge computing and cloud computing. By application, it is fragmented into image recognition, signal recognition, data mining, and others. Depending on industry vertical, it is separated into consumer electronics, automotive, IT & telecom, aerospace & defense, industrial, healthcare, and others.

Region-wise, the neuromorphic computing market trends are analyzed across North America (U.S., Canada, and Mexico), Europe (Germany, UK, France, Italy, and Rest of Europe), Asia-Pacific (China, Japan, India, South Korea, and Rest of Asia-Pacific), and LAMEA (Latin America, the Middle East, and Africa). North America is dominating the market, owing to rise in awareness regarding benefits of neuromorphic computing in industries such as aerospace, military & defense, and healthcare.

Key Market Segments

By Offering

By Deployment

By Application

By Industry Vertical

By Region

Key Players

Key Topics Covered:

CHAPTER 1: INTRODUCTION

1.1. Report description

1.2. Key benefits for stakeholders

1.3. Key market segments

1.4. Research methodology

CHAPTER 2: EXECUTIVE SUMMARY

2.1. Key findings

2.2. CXO perspective

CHAPTER 3: MARKET OVERVIEW

3.1. Market definition and scope

3.2. Key forces shaping the neuromorphic computing

3.3. Patent analysis

3.3.1. By region, 2012-2020

3.3.2. By applicant, 2012-2020

3.4. COVID-19 impact analysis

3.4.1. COVID-19 outbreak

3.4.2. Impact on market size

3.4.3. End user trends, preferences, and budget impact

3.5. Market dynamics

3.5.1. Drivers

3.5.1.1. Rising demand for artificial intelligence and machine learning technology

3.5.1.2. High usage of software in neuromorphic computing

3.5.1.3. Increasing demand for better performing integrated circuits (ICs)

3.5.2. Restraint

3.5.2.1. Increasing complexity of algorithms and backend operations

3.5.3. Opportunity

3.5.3.1. Rising adoption of neuromorphic chips in the automotive industry

CHAPTER 4: NEUROMORPHIC COMPUTING MARKET, BY OFFERING

4.1. Overview

4.2. Hardware

4.3. Software

CHAPTER 5: NEUROMORPHIC COMPUTING MARKET, BY DEPLOYMENT

5.1. Overview

5.2. Edge Computing

5.3. Cloud Computing

CHAPTER 6: NEUROMORPHIC COMPUTING MARKET, BY APPLICATION

6.1. Overview

6.2. Image Recognition

6.3. Signal Recognition

6.4. Data Mining

6.5. Others

CHAPTER 7: NEUROMORPHIC COMPUTING MARKET, BY INDUSTRY VERTICAL

7.1. Overview

7.2. Consumer electronics

7.3. Automotive

7.4. IT & Telecom

7.5. Aerospace & Defense

7.6. Industrial

7.7. Healthcare

7.8. Others

CHAPTER 8: NEUROMORPHIC COMPUTING MARKET, BY REGION

8.1. Overview

8.2. North America

8.3. Europe

8.4. Asia-Pacific

8.5. LAMEA

CHAPTER 9: COMPETITIVE LANDSCAPE

9.1. Introduction

9.1.1. Market player positioning, 2020

9.2. Top winning strategies

9.3. Competitive dashboard

9.4. Competitive heatmap

CHAPTER 10: COMPANY PROFILES

For more information about this report visit https://www.researchandmarkets.com/r/3bxxqs

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