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상품코드
2015374

뉴로모픽 칩 시장(-2040년) : 업계 동향과 세계 예측

Neuromorphic Chip Market, Till 2040: Industry Trends and Global Forecasts

발행일: | 리서치사: 구분자 Roots Analysis | 페이지 정보: 영문 199 Pages | 배송안내 : 7-10일 (영업일 기준)

    
    
    



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뉴로모픽 칩 시장 전망

세계의 뉴로모픽 칩 시장 규모는 현재 23억 9,000만 달러에서 2040년까지 186억 1,000만 달러에 달할 것으로 추정되며, 2040년까지 CAGR로 15.79%의 확대가 전망되고 있습니다.

뉴로모픽 칩은 인간 뇌의 구조와 기능을 모방하도록 설계된 새로운 첨단 프로세서의 일종으로, 컴퓨팅에 대한 혁신적인 접근 방식을 제공합니다. 폰노이만 병목현상에 제약이 있는 기존 아키텍처와 달리 뉴로모픽 시스템은 인공 뉴런과 시냅스 내에 연산과 메모리를 통합하여 고도로 병렬화된 이벤트 기반 처리를 가능하게 합니다.

이 아키텍처의 혁신은 기존 GPU 및 CPU에 비해 전력 소비를 크게 줄여 에너지 효율을 획기적으로 향상시킵니다. 이러한 진화는 전 세계 AI 에너지 수요의 급증으로 더욱 가속화되고 있으며, 전력망의 안정성을 해치지 않는 고성능 추론 솔루션에 대한 절실한 요구가 발생하고 있습니다. 역동적인 실제 환경을 관리하기 위한 저전력 지능형 컴퓨팅과 엣지 AI 프레임워크와의 원활한 통합이 점점 더 중요해지면서 뉴로모픽 칩 시장은 당분간 계속 성장세를 이어갈 것으로 보입니다.

Neuromorphic Chip Market-IMG1

경영진을 위한 전략적 인사이트

뉴로모픽 칩 시장의 주요 성장 촉진요인

뉴로모픽 칩 시장은 주로 각 산업 분야에서 에너지 절약형 고성능 AI 처리에 대한 수요가 급증하면서 주도하고 있습니다. 스마트 카메라 및 IoT 센서와 같은 엣지 애플리케이션에서 실시간 및 온디바이스 인텔리전스에 대한 요구가 증가함에 따라 채택이 가속화되고 있습니다. 뉴로모픽 아키텍처는 클라우드 인프라에 의존하지 않고 뇌에서 영감을 얻은 저지연 연산을 실현하기 때문입니다. 국방 및 로봇공학 분야에서의 노력 확대는 시장 성장을 더욱 촉진하고 있으며, 각국 정부는 역동적인 환경에서 작동하는 자율 드론 및 로봇 플랫폼에 대한 적응형 인텔리전스 시스템에 투자하고 있습니다. 또한 데이터센터의 에너지 소비가 증가함에 따라 기업은 기존 프로세서를 대체할 수 있는 전력 효율적인 대안을 찾고 있으며, 뉴로모픽 칩은 대규모 비용 절감을 실현할 수 있는 유력한 솔루션으로 여겨지고 있습니다. 또한 신경과학 연구의 발전은 칩 설계 능력을 강화하여 보다 진보된 인지 시스템의 상용화를 촉진하고 있습니다. 또한 자율주행차의 급속한 보급도 시장 성장에 기여하고 있으며, 뉴로모픽 프로세서는 보다 안전한 주행을 위해 인지, 센서 융합, 실시간 의사결정을 향상시킵니다.

뉴로모픽 칩 시장: 업계내 기업 간 경쟁 상황

뉴로모픽 칩 시장에는 전통 있는 다국적 기업과 신생 전문 기술 기업이 모두 진출해 치열한 경쟁이 벌어지고 있습니다. 각 기업은 기술 혁신, 전략적 자금 조달, 투자, 협력적 파트너십을 적극적으로 활용하여 제품 포트폴리오를 강화하고 시장 입지를 확대하기 위해 노력하고 있습니다. 예를 들어 최근 인텔은 Loihi 2 프로세서를 탑재한 세계 최대 규모의 뉴로모픽 시스템인 Hala Point를 발표하여 샌디아 국립연구소에 배치했습니다. 이는 이전 세대 포호이키 스프링스 대비 뉴런 용량이 약 10배, 성능이 12배 향상되어 뇌에서 영감을 얻은 지속가능한 AI 연구를 촉진하고 있습니다.

마찬가지로 IBM은 초저전력 감각 처리를 위해 설계된 TrueNorth와 기존 GPU에 비해 속도와 에너지 효율을 크게 향상시키고 거대 언어 모델의 추론을 크게 가속화하도록 설계된 NorthPole을 통해 듀얼 뉴로모픽 전략을 추진하고 있습니다. 있습니다. 이 노력은 DARPA의 지원을 받은 연구로 지원되고 있으며, 2026년까지 상업적 규모의 5nm 테이프 아웃을 목표로 하고 있습니다.

세계의 뉴로모픽 칩 시장에 대해 조사했으며, 시장 규모 추정과 기회 분석, 경쟁 상황, 기업 개요 등의 정보를 전해드립니다.

목차

제1장 프로젝트 개요

제2장 조사 방법

제3장 시장 역학

제4장 거시경제 지표

제5장 개요

제6장 서론

제7장 규제 시나리오

제8장 주요 기업의 종합적 데이터베이스

제9장 경쟁 구도

제10장 화이트 스페이스 분석

제11장 기업 경쟁력 분석

제12장 스타트업 에코시스템 분석

제13장 기업 개요

제14장 메가트렌드 분석

제15장 미충족 수요 분석

제16장 특허 분석

제17장 최근 발전

제18장 세계의 뉴로모픽 칩 시장

제19장 시장 기회 : 컴포넌트별

제20장 시장 기회 : 뉴로모픽 칩 유형별

제21장 시장 기회 : 아키텍처 유형별

제22장 시장 기회 : 배포 방식별

제23장 시장 기회 : 가역성 기구 유형별

제24장 시장 기회 : 통합 유형별

제25장 시장 기회 : 싱글 도메인 아키텍처 유형별

제26장 시장 기회 : 응용 분야별

제27장 시장 기회 : 최종 용도 산업별

제28장 북미의 뉴로모픽 칩의 시장 기회

제29장 유럽의 뉴로모픽 칩의 시장 기회

제30장 아시아태평양의 뉴로모픽 칩의 시장 기회

제31장 라틴아메리카의 뉴로모픽 칩의 시장 기회

제32장 중동 및 아프리카의 뉴로모픽 칩의 시장 기회

제33장 시장 집중도 분석 : 주요 기업별

제34장 인접 시장 분석

제35장 주요 성공 전략

제36장 Porter's Five Forces 분석

제37장 SWOT 분석

제38장 밸류체인의 분석

제39장 Roots의 전략적 제안

제40장 1차 조사로부터의 인사이트

제41장 리포트 결론

제42장 표형식 데이터

제43장 기업과 조직 리스트

KSA

Neuromorphic Chip Market Outlook

As per Roots Analysis, the global neuromorphic chip market size is estimated to grow from USD 2.39 billion in current year to USD 18.61 billion by 2040, at a CAGR of 15.79% during the forecast period, till 2040.

Neuromorphic chips are an emerging class of advanced processors designed to emulate the structure and functioning of the human brain, offering a transformative approach to computing. Unlike conventional architectures constrained by the von Neumann bottleneck, neuromorphic systems integrate computation and memory within artificial neurons and synapses, enabling highly parallel, event-driven processing.

This architectural innovation significantly reduces power consumption compared to traditional GPUs and CPUs, delivering orders-of-magnitude improvements in energy efficiency. This evolution has been further accelerated by the sharp rise in global AI energy demand, which has created an urgent requirement for high-performance inference solutions that do not compromise power grid stability. With increasing emphasis on low-power intelligent computing and seamless integration with edge AI frameworks to manage dynamic, real-world environments, the neuromorphic chip market continues to gain momentum throughout the foreseeable future.

Neuromorphic Chip Market - IMG1

Strategic Insights for Senior Leaders

Key Drivers Propelling Growth of Neuromorphic Chip Market

The neuromorphic chip market is primarily driven by the surging demand for energy-efficient and high-performance AI processing across industries. The growing need for real-time, on-device intelligence in edge applications (such as smart cameras and IoT sensors), is accelerating adoption, as neuromorphic architectures enable low-latency, brain-inspired computing without reliance on cloud infrastructure. Expanding defense and robotics initiatives are further supporting market growth, with governments investing in adaptive intelligence systems for autonomous drones and robotic platforms operating in dynamic environments. Additionally, rising energy consumption in data centers is prompting enterprises to seek power-efficient alternatives to conventional processors, positioning neuromorphic chips as a viable solution for large-scale cost savings. Additionally, advances in neuroscience research are also strengthening chip design capabilities, facilitating the commercialization of more sophisticated cognitive systems. Moreover, the rapid expansion of autonomous vehicles is contributing to market momentum, as neuromorphic processors enhance perception, sensor fusion, and real-time decision-making for safer navigation.

Neuromorphic Chip Market: Competitive Landscape of Companies in this Industry

The neuromorphic chip market is characterized by intense competition, marked by the presence of both established multinational corporations and emerging specialized technology firms. Companies are actively leveraging technological innovation, strategic funding, investments, and collaborative partnerships to strengthen their product portfolios and expand market presence. For instance, recently, Intel introduced Hala Point, the world's largest neuromorphic system powered by Loihi 2 processors and deployed at Sandia National Laboratories. This is delivering nearly ten times greater neuron capacity and twelve times higher performance than its predecessor, Pohoiki Springs, to advance sustainable brain-inspired AI research.

Similarly, IBM is advancing a dual neuromorphic strategy through TrueNorth, which is designed for ultra-low-power sensory processing, and NorthPole, which is engineered to significantly accelerate large language model inference with substantial improvements in speed and energy efficiency over conventional GPUs. This initiative is supported by DARPA-backed research and is targeting a commercial-scale 5nm tape-out by 2026.

Key Technological Advancements and Emerging Trends in the Industry

The neuromorphic chip market is witnessing several transformative trends driven by advancements in connectivity, healthcare innovation, next-generation computing, and global manufacturing expansion. The rapid rollout of 5G networks is accelerating Edge AI deployment, enabling neuromorphic processors to power smart city infrastructure (such as traffic monitoring systems and connected wearables), thereby capturing opportunities within the rapidly expanding edge computing ecosystem.

Simultaneously, the development of neuro-inspired microcontrollers is supporting biometric monitoring in wearable devices, creating new avenues for personalized healthcare solutions, particularly for aging populations. Emerging research into quantum-hybrid architectures is gaining significant attention. Integrating neuromorphic systems with quantum computing platforms has the potential to solve highly complex simulations in areas such as drug discovery, thereby attracting pharmaceutical companies seeking to accelerate research and development timelines.

Regional Analysis of Neuromorphic Chip Market

In the evolving neuromorphic chip market, Europe holds a significant market share, largely driven by strong adoption across the industrial and automotive sectors. Regional growth is supported by stringent Vision Zero autonomous vehicle initiatives and the accelerating implementation of Industry 4.0 strategies. Meanwhile, the Middle East and Africa account for 10.70% of the market, positioning themselves as a strategic infrastructure-driven growth region. This expansion is underpinned by large-scale smart city developments, including Saudi Arabia's NEOM and major urban transformation initiatives in the UAE, where neuromorphic chips are deployed for grid optimization, intelligent surveillance, and sustainability-focused infrastructure management. In contrast, Latin America currently represents a smaller share but is projected to expand at a robust CAGR, emerging as a growing data and innovation hub.

Key Challenges in Neuromorphic Chip Market

The neuromorphic chip market faces several structural and technological challenges that may constrain its growth trajectory. High research and development costs associated with designing brain-inspired architectures limit broader participation. This enables only well-capitalized corporations to compete effectively while smaller firms struggle with commercialization and scalability. Additionally, existing semiconductor fabrication infrastructure remains inadequately optimized for neuromorphic designs, resulting in low production yields and operational inefficiencies that delay large-scale deployment. The market is further hindered by a limited software ecosystem, as the shortage of developers skilled in programming spiking neural networks restricts application development and slows adoption in comparison to established GPU-supported AI frameworks.

Neuromorphic Chip Market: Key Market Segmentation

Market Share by Component

  • Hardware
  • Processors
  • Memory
  • Sensors
  • Software
  • Development Frameworks & SDKs
  • Mapping & Simulation Tools
  • Algorithms & Libraries
  • Services
  • Consulting & Integration
  • Support & Maintenance

Market Share by Type of Neuromorphic Chip

  • Analog Neuromorphic Chips
  • Digital Neuromorphic Chips
  • Mixed-Signal Neuromorphic Chips

Market Share by Type of Architecture

  • ASIC-based Neuromorphic Chips
  • Deep Neural Networks (DNN) Accelerators
  • FPGA-based Neuromorphic Chips
  • Memristor-based Chips
  • Spiking Neural Networks (SNN)

Market Share by Deployment Mode

  • Edge Computing / Devices
  • Cloud Computing / Data Center Nodes

Market Share by Type of Plasticity Mechanism

  • Inference-Only Chips
  • On-Chip Learning / Adaptive Chips

Market Share by Type of Integration

  • Embedded Neuromorphic IP Cores
  • Neuromorphic Sensing Units
  • Standalone Neuromorphic Accelerators

Market Share by Type of Single Domain Architecture

  • Hybrid Mixed-Signal
  • Pure Digital (SNN)
  • Sub-Threshold Analog

Market Share by Application Area

  • Audio & Signal Processing
  • Cybersecurity & Pattern Recognition
  • Data Mining & Analytics
  • Edge AI and IoT Devices
  • Healthcare & Wearable
  • Image & Video Processing
  • Natural Language Processing (NLP)
  • Object Detection & Recognition
  • Sensor Fusion

Market Share by End Use Industry

  • Automotive
  • Aerospace & Defense
  • Consumer Electronics
  • Healthcare
  • Industrial Automation
  • IT & Telecommunications

Market Share by Geographical Regions

  • North America
  • US
  • Canada
  • Mexico
  • Rest of North America
  • Europe
  • Austria
  • Belgium
  • Denmark
  • France
  • Germany
  • Ireland
  • Italy
  • Netherlands
  • Norway
  • Russia
  • Spain
  • Sweden
  • Switzerland
  • UK
  • Rest of Europe
  • Asia-Pacific
  • Australia
  • China
  • India
  • Japan
  • New-Zealand
  • Singapore
  • South Korea
  • Rest of Asia-Pacific
  • Latin America
  • Brazil
  • Chile
  • Colombia
  • Venezuela
  • Rest of Latin America
  • Middle East and Africa (MEA)
  • Egypt
  • Iran
  • Iraq
  • Israel
  • Kuwait
  • Saudi Arabia
  • UAE
  • Rest of MEA

Example Players in Neuromorphic Chip Market

  • Applied Brain Research
  • BrainChip Holdings
  • CEA-Leti
  • Cerebras Systems
  • Ceryx Medical
  • General Vision
  • Gyrfalcon Technology
  • Hewlett Packard Labs (HPE)
  • HRL Laboratories
  • IBM
  • Innatera Nanosystems
  • Intel
  • Knowm
  • Koniku
  • Lockheed Martin
  • MemComputing
  • Micron Technology
  • Nepes
  • Numenta
  • NVIDIA
  • Qualcomm
  • Samsung Electronics
  • SK Hynix

neuromorphic Chip Market: Report Coverage

The report on the neuromorphic chip market features insights on various sections, including:

  • Market Sizing and Opportunity Analysis: An in-depth analysis of the neuromorphic chip market, focusing on key market segments, including [A] component, [B] type of neuromorphic chip, [C] type of architecture, [D] type of plasticity mechanism, [E] type of integration, [F] type of single domain architecture, [G] deployment mode, [H] application area, [I] end use industry, [J] geographical regions, and [K] leading players.
  • Competitive Landscape: A comprehensive analysis of the companies engaged in the neuromorphic chip market, based on several relevant parameters, such as [A] year of establishment, [B] company size, [C] location of headquarters and [D] ownership structure.
  • Company Profiles: Elaborate profiles of prominent players engaged in the neuromorphic chip market, providing details on [A] location of headquarters, [B] company size, [C] company mission, [D] company footprint, [E] management team, [F] contact details, [G] financial information, [H] operating business segments, [I] product / technology portfolio, [J] recent developments, and an informed future outlook.
  • Megatrends: An evaluation of ongoing megatrends in the neuromorphic chip industry.
  • Patent Analysis: An insightful analysis of patents filed / granted in the neuromorphic chip domain, based on relevant parameters, including [A] type of patent, [B] patent publication year, [C] patent age and [D] leading players.
  • Recent Developments: An overview of the recent developments made in the neuromorphic chip market, along with analysis based on relevant parameters, including [A] year of initiative, [B] type of initiative, [C] geographical distribution and [D] most active players.
  • Porter's Five Forces Analysis: An analysis of five competitive forces prevailing in the neuromorphic chip market, including threats of new entrants, bargaining power of buyers, bargaining power of suppliers, threats of substitute products and rivalry among existing competitors.
  • SWOT Analysis: An insightful SWOT framework, highlighting the strengths, weaknesses, opportunities and threats in the domain. Additionally, it provides Harvey ball analysis, highlighting the relative impact of each SWOT parameter.

Key Questions Answered in this Report

  • What is the current and future market size?
  • Who are the leading companies in this market?
  • What are the growth drivers that are likely to influence the evolution of this market?
  • What are the key partnership and funding trends shaping this industry?
  • Which region is likely to grow at higher CAGR till 2040?
  • How is the current and future market opportunity likely to be distributed across key market segments?

Reasons to Buy this Report

  • Detailed Market Analysis: The report provides a comprehensive market analysis, offering detailed revenue projections of the overall market and its specific sub-segments. This information is valuable to both established market leaders and emerging entrants.
  • In-depth Analysis of Trends: Stakeholders can leverage the report to gain a deeper understanding of the competitive dynamics within the market. Each report maps ecosystem activity across partnerships, funding, and patent landscapes to reveal growth hotspots and white spaces in the industry.
  • Opinion of Industry Experts: The report features extensive interviews and surveys with key opinion leaders and industry experts to validate market trends mentioned in the report.
  • Decision-ready Deliverables: The report offers stakeholders with strategic frameworks (Porter's Five Forces, value chain, SWOT), and complimentary Excel / slide packs with customization support.

Additional Benefits

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TABLE OF CONTENTS

1. PROJECT OVERVIEW

  • 1.1. Context
  • 1.2. Project Objectives

2. RESEARCH METHODOLOGY

  • 2.1. Chapter Overview
  • 2.2. Research Assumptions
  • 2.3. Database Building
    • 2.3.1. Data Collection
    • 2.3.2. Data Validation
    • 2.3.3. Data Analysis
  • 2.4. Project Methodology
    • 2.4.1. Secondary Research
      • 2.4.1.1. Annual Reports
      • 2.4.1.2. Academic Research Papers
      • 2.4.1.3. Company Websites
      • 2.4.1.4. Investor Presentations
      • 2.4.1.5. Regulatory Filings
      • 2.4.1.6. White Papers
      • 2.4.1.7. Industry Publications
      • 2.4.1.8. Conferences and Seminars
      • 2.4.1.9. Government Portals
      • 2.4.1.10. Media and Press Releases
      • 2.4.1.11. Newsletters
      • 2.4.1.12. Industry Databases
      • 2.4.1.13. Roots Proprietary Databases
      • 2.4.1.14. Paid Databases and Sources
      • 2.4.1.15. Social Media Portals
      • 2.4.1.16. Other Secondary Sources
    • 2.4.2. Primary Research
      • 2.4.2.1. Introduction
      • 2.4.2.2. Types
        • 2.4.2.2.1. Qualitative
        • 2.4.2.2.2. Quantitative
      • 2.4.2.3. Advantages
      • 2.4.2.4. Techniques
        • 2.4.2.4.1. Interviews
        • 2.4.2.4.2. Surveys
        • 2.4.2.4.3. Focus Groups
        • 2.4.2.4.4. Observational Research
        • 2.4.2.4.5. Social Media Interactions
      • 2.4.2.5. Stakeholders
        • 2.4.2.5.1. Company Executives (CXOs)
        • 2.4.2.5.2. Board of Directors
        • 2.4.2.5.3. Company Presidents and Vice Presidents
        • 2.4.2.5.4. Key Opinion Leaders
        • 2.4.2.5.5. Research and Development Heads
        • 2.4.2.5.6. Technical Experts
        • 2.4.2.5.7. Subject Matter Experts
        • 2.4.2.5.8. Scientists
        • 2.4.2.5.9. Doctors and Other Healthcare Providers
      • 2.4.2.6. Ethics and Integrity
        • 2.4.2.6.1. Research Ethics
        • 2.4.2.6.2. Data Integrity
    • 2.4.3. Analytical Tools and Databases

3. MARKET DYNAMICS

  • 3.1. Forecast Methodology
    • 3.1.1. Top-Down Approach
    • 3.1.2. Bottom-Up Approach
    • 3.1.3. Hybrid Approach
  • 3.2. Market Assessment Framework
    • 3.2.1. Total Addressable Market (TAM)
    • 3.2.2. Serviceable Addressable Market (SAM)
    • 3.2.3. Serviceable Obtainable Market (SOM)
    • 3.2.4. Currently Acquired Market (CAM)
  • 3.3. Forecasting Tools and Techniques
    • 3.3.1. Qualitative Forecasting
    • 3.3.2. Correlation
    • 3.3.3. Regression
    • 3.3.4. Time Series Analysis
    • 3.3.5. Extrapolation
    • 3.3.6. Convergence
    • 3.3.7. Forecast Error Analysis
    • 3.3.8. Data Visualization
    • 3.3.9. Scenario Planning
    • 3.3.10. Sensitivity Analysis
  • 3.4. Key Considerations
    • 3.4.1. Demographics
    • 3.4.2. Market Access
    • 3.4.3. Reimbursement Scenarios
    • 3.4.4. Industry Consolidation
  • 3.5. Robust Quality Control
  • 3.6. Key Market Segmentations
  • 3.7. Limitations

4. MACRO-ECONOMIC INDICATORS

  • 4.1. Chapter Overview
  • 4.2. Market Dynamics
    • 4.2.1. Time Period
      • 4.2.1.1. Historical Trends
      • 4.2.1.2. Current and Forecasted Estimates
    • 4.2.2. Currency Coverage
      • 4.2.2.1. Overview of Major Currencies Affecting the Market
      • 4.2.2.2. Impact of Currency Fluctuations on the Industry
    • 4.2.3. Foreign Exchange Impact
      • 4.2.3.1. Evaluation of Foreign Exchange Rates and Their Impact on Market
      • 4.2.3.2. Strategies for Mitigating Foreign Exchange Risk
    • 4.2.4. Recession
      • 4.2.4.1. Historical Analysis of Past Recessions and Lessons Learnt
      • 4.2.4.2. Assessment of Current Economic Conditions and Potential Impact on the Market
    • 4.2.5. Inflation
      • 4.2.5.1. Measurement and Analysis of Inflationary Pressures in the Economy
      • 4.2.5.2. Potential Impact of Inflation on the Market Evolution
    • 4.2.6. Interest Rates
      • 4.2.6.1. Overview of Interest Rates and Their Impact on the Market
      • 4.2.6.2. Strategies for Managing Interest Rate Risk
    • 4.2.7. Commodity Flow Analysis
      • 4.2.7.1. Type of Commodity
      • 4.2.7.2. Origins and Destinations
      • 4.2.7.3. Values and Weights
      • 4.2.7.4. Modes of Transportation
    • 4.2.8. Global Trade Dynamics
      • 4.2.8.1. Import Scenario
      • 4.2.8.2. Export Scenario
    • 4.2.9. War Impact Analysis
      • 4.2.9.1. Russian-Ukraine War
      • 4.2.9.2. Israel-Hamas War
    • 4.2.10. COVID Impact / Related Factors
      • 4.2.10.1. Global Economic Impact
      • 4.2.10.2. Industry-specific Impact
      • 4.2.10.3. Government Response and Stimulus Measures
      • 4.2.10.4. Future Outlook and Adaptation Strategies
    • 4.2.11. Other Indicators
      • 4.2.11.1. Fiscal Policy
      • 4.2.11.2. Consumer Spending
      • 4.2.11.3. Gross Domestic Product (GDP)
      • 4.2.11.4. Employment
      • 4.2.11.5. Taxes
      • 4.2.11.6. R&D Innovation
      • 4.2.11.7. Stock Market Performance
      • 4.2.11.8. Supply Chain
      • 4.2.11.9. Cross-Border Dynamics
  • 4.3. Concluding Remarks

5. EXECUTIVE SUMMARY

6. INTRODUCTION

  • 6.1. Chapter Overview
  • 6.2. Overview of Neuromorphic Chip Market
    • 6.2.1. Type of Component
    • 6.2.2. Type of Neuromorphic Chip
    • 6.2.3. Type of Architecture
    • 6.2.4. Type of Deployment
    • 6.2.5. Type of Plasticity Mechanism
    • 6.2.6. Type of Integration
    • 6.2.7. Type of Single Domain Architecture
    • 6.2.8. Application Area
    • 6.2.9. End Use Industry
  • 6.3. Future Perspective

7. REGULATORY SCENARIO

8. COMPREHENSIVE DATABASE OF LEADING PLAYERS

9. COMPETITIVE LANDSCAPE

  • 9.1. Chapter Overview
  • 9.2. Neuromorphic Chip Market: Overall Market Landscape
    • 9.2.1. Analysis by Year of Establishment
    • 9.2.2. Analysis by Company Size
    • 9.2.3. Analysis by Location of Headquarters
    • 9.2.4. Analysis by Type of Company
  • 9.3. Key Findings

10. WHITE SPACE ANALYSIS

11. COMPANY COMPETITIVENESS ANALYSIS

12. STARTUP ECOSYSTEM ANALYSIS

  • 12.1. Neuromorphic Chip Market: Startup Ecosystem Analysis
    • 12.1.1. Analysis by Year of Establishment
    • 12.1.2. Analysis by Company Size
    • 12.1.3. Analysis by Location of Headquarters
    • 12.1.4. Analysis by Ownership Type
  • 12.2. Key Findings

13. COMPANY PROFILES

  • 13.1. Chapter Overview
  • 13.2. Applied Brain Research
    • 13.2.1. Company Overview
    • 13.2.2. Company Mission
    • 13.2.3. Company Footprint
    • 13.2.4. Management Team
    • 13.2.5. Contact Details
    • 13.2.6. Financial Performance
    • 13.2.7. Operating Business Segments
    • 13.2.8. Service / Product Portfolio (project specific)
    • 13.2.9. MOAT Analysis
    • 13.2.10. Recent Developments and Future Outlook
  • Similar details are presented for other companies mentioned below (based on information in the public domain)
  • 13.3. BrainChip Holdings
  • 13.4. CEA-Leti
  • 13.5. Cerebras Systems
  • 13.6. Ceryx Medical
  • 13.7. General Vision
  • 13.8. Gyrfalcon Technology
  • 13.9. Hewlett Packard Labs (HPE)
  • 13.10. HRL Laboratories
  • 13.11. IBM
  • 13.12. Innatera Nanosystems
  • 13.13. Intel
  • 13.14. Knowm
  • 13.15. Koniku
  • 13.16. Lockheed Martin
  • 13.17. MemComputing
  • 13.18. Micron Technology
  • 13.19. Nepes
  • 13.20. Numenta
  • 13.21. NVIDIA
  • 13.22. Qualcomm
  • 13.23. Samsung Electronics
  • 13.24. SK Hynix

14. MEGA TRENDS ANALYSIS

15. UNMET NEED ANALYSIS

16. PATENT ANALYSIS

17. RECENT DEVELOPMENTS

  • 17.1. Chapter Overview
  • 17.2. Recent Funding
  • 17.3. Recent Partnerships
  • 17.4. Other Recent Initiatives

18. GLOBAL NEUROMORPHIC CHIP MARKET

  • 18.1. Chapter Overview
  • 18.2. Key Assumptions and Methodology
  • 18.3. Trends Disruption Impacting Market
  • 18.4. Demand Side Trends
  • 18.5. Supply Side Trends
  • 18.6. Global Neuromorphic Chip Market: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 18.7. Multivariate Scenario Analysis
    • 18.7.1. Conservative Scenario
    • 18.7.2. Optimistic Scenario
  • 18.8. Investment Feasibility Index
  • 18.9. Key Market Segmentations

19. MARKET OPPORTUNITIES BASED ON COMPONENT

  • 19.1. Chapter Overview
  • 19.2. Key Assumptions and Methodology
  • 19.3. Revenue Shift Analysis
  • 19.4. Market Movement Analysis
  • 19.5. Penetration-Growth (P-G) Matrix
  • 19.6. Neuromorphic Chip Market for Hardware: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 19.6.1. Neuromorphic Chip Hardware Market for Processors: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 19.6.2. Neuromorphic Chip Hardware Market for Memory: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 19.6.3. Neuromorphic Chip Hardware Market for Sensors: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 19.7. Neuromorphic Chip Market for Software: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 19.7.1. Neuromorphic Chip Software Market for Development Frameworks & SDKs: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 19.7.2. Neuromorphic Chip Software Market for Mapping & Simulation Tools: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 19.7.3. Neuromorphic Chip Software Market for Algorithms & Libraries: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 19.8. Neuromorphic Chip Market for Services: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 19.8.1. Neuromorphic Chip Services Market for Consulting & Integration: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 19.8.2. Neuromorphic Chip Services Market for Support & Maintenance: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 19.9. Data Triangulation and Validation
    • 19.9.1. Secondary Sources
    • 19.9.2. Primary Sources
    • 19.9.3. Statistical Modeling

20. MARKET OPPORTUNITIES BASED ON TYPE OF NEUROMORPHIC CHIP

  • 20.1. Chapter Overview
  • 20.2. Key Assumptions and Methodology
  • 20.3. Revenue Shift Analysis
  • 20.4. Market Movement Analysis
  • 20.5. Penetration-Growth (P-G) Matrix
  • 20.6. Neuromorphic Chip Market for Analog Neuromorphic Chips: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 20.7. Neuromorphic Chip Market for Digital Neuromorphic Chips: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 20.8. Neuromorphic Chip Market for Mixed-Signal Neuromorphic Chips: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 20.9. Data Triangulation and Validation
    • 20.9.1. Secondary Sources
    • 20.9.2. Primary Sources
    • 20.9.3. Statistical Modeling

21. MARKET OPPORTUNITIES BASED ON TYPE OF ARCHITECTURE

  • 21.1. Chapter Overview
  • 21.2. Key Assumptions and Methodology
  • 21.3. Revenue Shift Analysis
  • 21.4. Market Movement Analysis
  • 21.5. Penetration-Growth (P-G) Matrix
  • 21.6. Neuromorphic Chip Market for ASIC-based Neuromorphic Chips: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 21.7. Neuromorphic Chip Market for Deep Neural Networks (DNN) Accelerators: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 21.8. Neuromorphic Chip Market for FPGA-based Neuromorphic Chips: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 21.9. Neuromorphic Chip Market for Memristor-based Chips: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 21.10. Neuromorphic Chip Market for Spiking Neural Networks (SNN): Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 21.11. Data Triangulation and Validation
    • 21.11.1. Secondary Sources
    • 21.11.2. Primary Sources
    • 21.11.3. Statistical Modeling

22. MARKET OPPORTUNITIES BASED ON DEPLOYMENT MODE

  • 22.1. Chapter Overview
  • 22.2. Key Assumptions and Methodology
  • 22.3. Revenue Shift Analysis
  • 22.4. Market Movement Analysis
  • 22.5. Penetration-Growth (P-G) Matrix
  • 22.6. Neuromorphic Chip Market for Edge Computing / Devices: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 22.7. Neuromorphic Chip Market for Cloud Computing / Data Center Nodes: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 22.8. Data Triangulation and Validation
    • 22.8.1. Secondary Sources
    • 22.8.2. Primary Sources
    • 22.8.3. Statistical Modeling

23. MARKET OPPORTUNITIES BASED ON TYPE OF PLASTICITY MECHANISM

  • 23.1. Chapter Overview
  • 23.2. Key Assumptions and Methodology
  • 23.3. Revenue Shift Analysis
  • 23.4. Market Movement Analysis
  • 23.5. Penetration-Growth (P-G) Matrix
  • 23.6. Neuromorphic Chip Market for Inference-Only Chips: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 23.7. Neuromorphic Chip Market for On-Chip Learning / Adaptive Chips: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 23.8. Data Triangulation and Validation
    • 23.8.1. Secondary Sources
    • 23.8.2. Primary Sources
    • 23.8.3. Statistical Modeling

24. MARKET OPPORTUNITIES BASED ON TYPE OF INTEGRATION

  • 24.1. Chapter Overview
  • 24.2. Key Assumptions and Methodology
  • 24.3. Revenue Shift Analysis
  • 24.4. Market Movement Analysis
  • 24.5. Penetration-Growth (P-G) Matrix
  • 24.6. Neuromorphic Chip Market for Embedded Neuromorphic IP Cores: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 24.7. Neuromorphic Chip Market for Neuromorphic Sensing Units: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 24.8. Neuromorphic Chip Market for Standalone Neuromorphic Accelerators: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 24.9. Data Triangulation and Validation
    • 24.9.1. Secondary Sources
    • 24.9.2. Primary Sources
    • 24.9.3. Statistical Modeling

25. MARKET OPPORTUNITIES BASED ON TYPE OF SINGLE DOMAIN ARCHITECTURE

  • 25.1. Chapter Overview
  • 25.2. Key Assumptions and Methodology
  • 25.3. Revenue Shift Analysis
  • 25.4. Market Movement Analysis
  • 25.5. Penetration-Growth (P-G) Matrix
  • 25.6. Neuromorphic Chip Market for Hybrid Mixed-Signal: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 25.7. Neuromorphic Chip Market for Pure Digital (SNN): Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 25.8. Neuromorphic Chip Market for Sub-Threshold Analog: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 25.9. Data Triangulation and Validation
    • 25.9.1. Secondary Sources
    • 25.9.2. Primary Sources
    • 25.9.3. Statistical Modeling

26. MARKET OPPORTUNITIES BASED ON APPLICATION AREA

  • 26.1. Chapter Overview
  • 26.2. Key Assumptions and Methodology
  • 26.3. Revenue Shift Analysis
  • 26.4. Market Movement Analysis
  • 26.5. Penetration-Growth (P-G) Matrix
  • 26.6. Neuromorphic Chip Market for Audio & Signal Processing: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 26.7. Neuromorphic Chip Market for Cybersecurity & Pattern Recognition: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 26.8. Neuromorphic Chip Market for Data Mining & Analytics: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 26.9. Neuromorphic Chip Market for Edge AI and IoT Devices: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 26.10. Neuromorphic Chip Market for Healthcare & Wearable: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 26.11. Neuromorphic Chip Market for Image & Video Processing: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 26.12. Neuromorphic Chip Market for Natural Language Processing (NLP): Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 26.13. Neuromorphic Chip Market for Object Detection & Recognition: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 26.14. Neuromorphic Chip Market for Sensor Fusion: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 26.15. Data Triangulation and Validation
    • 26.15.1. Secondary Sources
    • 26.15.2. Primary Sources
    • 26.15.3. Statistical Modeling

27. MARKET OPPORTUNITIES BASED ON END USE INDUSTRY

  • 27.1. Chapter Overview
  • 27.2. Key Assumptions and Methodology
  • 27.3. Revenue Shift Analysis
  • 27.4. Market Movement Analysis
  • 27.5. Penetration-Growth (P-G) Matrix
  • 27.6. Neuromorphic Chip Market for Automotive: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 27.7. Neuromorphic Chip Market for Aerospace & Defense: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 27.8. Neuromorphic Chip Market for Consumer Electronics: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 27.9. Neuromorphic Chip Market for Healthcare: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 27.9. Neuromorphic Chip Market for Industrial Automation: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 27.10. Neuromorphic Chip Market for IT & Telecommunications: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 26.11. Data Triangulation and Validation
    • 26.11.1. Secondary Sources
    • 26.11.2. Primary Sources
    • 26.11.3. Statistical Modeling

28. MARKET OPPORTUNITIES FOR NEUROMORPHIC CHIP IN NORTH AMERICA

  • 28.1. Chapter Overview
  • 28.2. Key Assumptions and Methodology
  • 28.3. Revenue Shift Analysis
  • 28.4. Market Movement Analysis
  • 28.5. Penetration-Growth (P-G) Matrix
  • 28.6. Neuromorphic Chip Market in North America: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 28.6.1. Neuromorphic Chip Market in the US: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 28.6.2. Neuromorphic Chip Market in Canada: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 28.6.3. Neuromorphic Chip Market in Mexico: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 28.6.4. Neuromorphic Chip Market in Other North American Countries: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 28.7. Data Triangulation and Validation

29. MARKET OPPORTUNITIES FOR NEUROMORPHIC CHIP IN EUROPE

  • 29.1. Chapter Overview
  • 29.2. Key Assumptions and Methodology
  • 29.3. Revenue Shift Analysis
  • 29.4. Market Movement Analysis
  • 29.5. Penetration-Growth (P-G) Matrix
  • 29.6. Neuromorphic Chip Market in Europe: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 29.6.1. Neuromorphic Chip Market in Austria: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 29.6.2. Neuromorphic Chip Market in Belgium: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 29.6.3. Neuromorphic Chip Market in Denmark: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 29.6.4. Neuromorphic Chip Market in France: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 29.6.5. Neuromorphic Chip Market in Germany: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 29.6.6. Neuromorphic Chip Market in Ireland: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 29.6.7. Neuromorphic Chip Market in Italy: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 29.6.8. Neuromorphic Chip Market in the Netherlands: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 29.6.9. Neuromorphic Chip Market in Norway: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 29.6.10. Neuromorphic Chip Market in Russia: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 29.6.11. Neuromorphic Chip Market in Spain: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 29.6.12. Neuromorphic Chip Market in Sweden: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 29.6.13. Neuromorphic Chip Market in Switzerland: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 29.6.14. Neuromorphic Chip Market in the UK: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 29.6.15. Neuromorphic Chip Market in Other European Countries: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 29.7. Data Triangulation and Validation

30. MARKET OPPORTUNITIES FOR NEUROMORPHIC CHIP IN ASIA-PACIFIC

  • 30.1. Chapter Overview
  • 30.2. Key Assumptions and Methodology
  • 30.3. Revenue Shift Analysis
  • 30.4. Market Movement Analysis
  • 30.5. Penetration-Growth (P-G) Matrix
  • 30.6. Neuromorphic Chip Market in Asia-Pacific: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 30.6.1. Neuromorphic Chip Market in China: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 30.6.2. Neuromorphic Chip Market in India: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 30.6.3. Neuromorphic Chip Market in Japan: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 30.6.4. Neuromorphic Chip Market in Singapore: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 30.6.5. Neuromorphic Chip Market in South Korea: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 30.6.6. Neuromorphic Chip Market in Other Asian Countries: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 30.7. Data Triangulation and Validation

31. MARKET OPPORTUNITIES FOR NEUROMORPHIC CHIP IN LATIN AMERICA

  • 31.1. Chapter Overview
  • 31.2. Key Assumptions and Methodology
  • 31.3. Revenue Shift Analysis
  • 31.4. Market Movement Analysis
  • 31.5. Penetration-Growth (P-G) Matrix
  • 31.6. Neuromorphic Chip Market in Latin America: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 31.6.1. Neuromorphic Chip Market in Argentina: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 31.6.2. Neuromorphic Chip Market in Brazil: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 31.6.3. Neuromorphic Chip Market in Chile: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 31.6.4. Neuromorphic Chip Market in Colombia Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 31.6.5. Neuromorphic Chip Market in Venezuela: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 31.6.6. Neuromorphic Chip Market in Other Latin American Countries: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 31.7. Data Triangulation and Validation

32. MARKET OPPORTUNITIES FOR NEUROMORPHIC CHIP IN MIDDLE EAST AND AFRICA (MEA)

  • 32.1. Chapter Overview
  • 32.2. Key Assumptions and Methodology
  • 32.3. Revenue Shift Analysis
  • 32.4. Market Movement Analysis
  • 32.5. Penetration-Growth (P-G) Matrix
  • 32.6. Neuromorphic Chip Market in Middle East and Africa (MEA): Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 32.6.1. Neuromorphic Chip Market in Egypt: Historical Trends (Since 2022) and Forecasted Estimates (Till 205)
    • 32.6.2. Neuromorphic Chip Market in Iran: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 32.6.3. Neuromorphic Chip Market in Iraq: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 32.6.4. Neuromorphic Chip Market in Israel: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 32.6.5. Neuromorphic Chip Market in Kuwait: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 32.6.6. Neuromorphic Chip Market in Saudi Arabia: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 32.6.7. Neuromorphic Chip Market in United Arab Emirates (UAE): Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
    • 32.6.8. Neuromorphic Chip Market in Other MEA Countries: Historical Trends (Since 2022) and Forecasted Estimates (Till 2040)
  • 32.7. Data Triangulation and Validation

33. MARKET CONCENTRATION ANALYSIS: DISTRIBUTION BY LEADING PLAYERS

34. ADJACENT MARKET ANALYSIS

35. KEY WINNING STRATEGIES

36. PORTER'S FIVE FORCES ANALYSIS

37. SWOT ANALYSIS

38. VALUE CHAIN ANALYSIS

39. ROOTS STRATEGIC RECOMMENDATIONS

  • 39.1. Chapter Overview
  • 39.2. Key Business-related Strategies
    • 39.2.1. Research & Development
    • 39.2.2. Product Manufacturing
    • 39.2.3. Commercialization / Go-to-Market
    • 39.2.4. Sales and Marketing
  • 39.3. Key Operations-related Strategies
    • 39.3.1. Risk Management
    • 39.3.2. Workforce
    • 39.3.3. Finance
    • 39.3.4. Others

40. INSIGHTS FROM PRIMARY RESEARCH

41. REPORT CONCLUSION

42. TABULATED DATA

43. LIST OF COMPANIES AND ORGANIZATIONS

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