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Neuromorphic Computing Market - Forecasts from 2021 to 2026

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    Report

  • 117 Pages
  • October 2021
  • Region: Global
  • Knowledge Sourcing Intelligence LLP
  • ID: 5510662
The neuromorphic computing market is estimated to be valued at US$3.297 billion in 2019 and is projected to grow rapidly during the forecast period.

Neuromorphic computing is a branch of computer engineering where computer elements are modeled after the human brain and nervous system. The term encompasses both the hardware and software aspects of computer design. To keep up with the rapid advancement of disruptive technologies such as artificial intelligence (AI) and machine learning (ML), various embedded system providers are working on brain chips that will not only be quick to process but will also have responses similar to human brains, allowing systems to think and act like humans.

The need for better-performing Integrated circuits (IC), the rising demand for artificial intelligence and machine learning, and the growing number of cross-industry alliances and collaborations are propelling the market forward. 

In April 2021, Brainchip Research Institute in Perth and precision immunology company, Biotome Pty Ltd, engaged in a research agreement. According to this agreement, The Akida neuromorphic processor chip developed by Brainchip will decode sensor responses and determine which responses that are the most representative for protective antibodies for Biotome, which is working on developing highly accurate antibody tests for infections.

In March 2020, Intel showcased its latest and most powerful neuromorphic research center, Pohoiki Springs, with a computation capacity of 100 million neurons and is 1,000 times faster and 10,000 times more efficient than conventional processors.

Neuromorphic chips provide their users with various advantages, such as high speed, low power consumption, cognitive computing, and optimal memory utilization which will drive the market growth.

The major factors driving the growth of the market are the increasing use of artificial intelligence technology in various applications and its ability to improve the performance of integrated chips. Image recognition, aerial surveillance, signal recognition, audio and signal processing, data mining are major applications of Neuromorphic computing.

A combination of AI systems and machine learning is expected to revolutionize the business environment with smart decision-making. However, complex algorithms, lack of knowledge about neuromorphic computing, and increasing complexity of hardware design of neuromorphic chips pose a major challenge for the market.

Geographical Segmentation


The North American region is expected to hold the largest market share due to being home to some of the major market players such as Intel Corporation and IBM Corporation. The market for neuromorphic chips is growing in the region due to factors like government initiatives, investment activities, etc. 

Growth Factors


Need for better-performing Integrated Circuits (IC)


Neuromorphic computing is more efficient, faster, and less power-consuming. This advantage helps the military and defense industry in processing sensitive data, test and transmit signals securely, and hence reducing security threats.

Ethical concerns


Neuromorphic computing is relatively new and has a promising future but there are many ethical considerations to apply while reproducing to human-like machines and AI using neuromorphic systems. One of the most serious ethical issues that neuromorphic computing may face is public perception. According to a European Commission survey titled Special Eurobarometer 382: Public Attitudes Towards Robots, more than 60% of EU residents are uncomfortable with the idea of using robots to care for their children and elderly parents. Not to forget that AI still being at infancy can also be weaponized easily.

Impact of COVID-19 on the Neuromorphic Computing Market
The COVID-19 pandemic positively influenced the neuromorphic computing industry as in 2020, neuromorphic chips were utilized in medical devices for the first time. 

Segmentation:


By Application

  • Data Processing
  • Image Processing
  • Signal Processing
  • Object Processing

By Industry

  • IT & Telecom
  • Aerospace & Defense
  • Healthcare
  • Automotive
  • Others

By Geography

  • North America
  • United States
  • Canada
  • Mexico
  • South America
  • Brazil
  • Argentina
  • Others
  • Europe
  • Germany
  • France
  • United Kingdom
  • Spain
  • Others
  • Middle East and Africa
  • Saudi Arabia
  • UAE
  • Israel
  • Others
  • Asia Pacific
  • China
  • India
  • South Korea
  • Taiwan
  • Thailand
  • Indonesia
  • Japan
  • Others

Table of Contents

1. INTRODUCTION
1.1. Market Definition
1.2. Market Segmentation
2. RESEARCH METHODOLOGY
2.1. Research Data
2.2. Assumptions
3. EXECUTIVE SUMMARY
3.1. Research Highlights
4. MARKET DYNAMICS
4.1. Market Drivers
4.2. Market Restraints
4.3. Porters Five Forces Analysis
4.3.1. Bargaining Power of Suppliers
4.3.2. Bargaining Powers of Buyers
4.3.3. Threat of Substitutes
4.3.4. The threat of New Entrants
4.3.5. Competitive Rivalry in Industry
4.4. Industry Value Chain Analysis
5. GLOBAL NEUROMORPHIC COMPUTING MARKET, BY APPLICATION
5.1. Introduction
5.2. Data Processing
5.3. Image Processing
5.4. Signal Processing
5.5. Object Processing
6. GLOBAL NEUROMORPHIC COMPUTING MARKET, BY INDUSTRY
6.1. Introduction
6.2. IT & Telecom
6.3. Aerospace & Defense
6.4. Healthcare
6.5. Automotive
6.6. Others
7. GLOBAL NEUROMORPHIC COMPUTING MARKET, BY GEOGRAPHY
7.1. Introduction
7.2. North America
7.2.1. United States
7.2.2. Canada
7.2.3. Mexico
7.3. South America
7.3.1. Brazil
7.3.2. Argentina
7.3.3. Others
7.4. Europe
7.4.1. Germany
7.4.2. France
7.4.3. United Kingdom
7.4.4. Spain
7.4.5. Others
7.5. Middle East and Africa
7.5.1. Saudi Arabia
7.5.2. UAE
7.5.3. Israel
7.5.4. Others
7.6. Asia Pacific
7.6.1. China
7.6.2. India
7.6.3. South Korea
7.6.4. Taiwan
7.6.5. Thailand
7.6.6. Indonesia
7.6.7. Japan
7.6.8. Others
8. COMPETITIVE ENVIRONMENT AND ANALYSIS
8.1. Major Players and Strategy Analysis
8.2. Emerging Players and Market Lucrative
8.3. Mergers, Acquisition, Agreements, and Collaborations
8.4. Vendor Competitiveness Matrix
9. COMPANY PROFILES
9.1. Intel Corporation
9.2. IBM
9.3. Hewlett Packard Enterprise Development LP
9.4. General Vision
9.5. Knowm Inc.
9.6. BrainChip Holdings Ltd.

Companies Mentioned

  • Intel Corporation
  • IBM
  • Hewlett Packard Enterprise Development LP
  • General Vision
  • Knowm Inc.
  • BrainChip Holdings Ltd.

Methodology

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