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1687061

神經型態晶片：市場佔有率分析、行業趨勢和統計數據、成長預測（2025-2030 年）

Neuromorphic Chip - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2025 - 2030)

出版日期: 2025年03月18日 | 出版商:

Mordor Intelligence | 英文 151 Pages | 商品交期: 2-3個工作天內

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簡介目錄

預計神經型態晶片市場規模在 2025 年將達到 3.3 億美元，到 2030 年將達到 117.7 億美元，預測期內（2025-2030 年）的複合年成長率為 104.7%。

生物識別和語音辨識的使用日益增多，推動了智慧型手機對神經形態晶片的需求。這些晶片用於處理雲端的語音資料並將其發送回行動電話。此外，由於人工智慧 (AI) 需要更多的運算能力，低能耗神經形態運算可以顯著推動目前在雲端運行的應用程式未來直接在智慧型手機上運行，而不會顯著消耗智慧型手機電池。

神經形態是一種受大腦啟發的特定 ASIC，可實現尖峰神經網路 (SNN)。平均而言，它們由能夠達到數十瓦大規模並行大腦處理能力的物體提供動力。記憶體和處理單元是單一抽象（記憶體內運算）。

這意味著在複雜環境中具有動態和自可程式設計行為的優勢。神經型態硬體並非採用傳統的位元精度計算，而是利用大腦的高度機率特性，從而形成簡單、可靠、穩健且資料高效的機率計算模型。神經形態硬體可以說比精確計算更適合認知應用。

未來十年，神經形態計算可能會改變廣泛的科學和非科學應用的性質和能力。這包括越來越需要強大處理能力和功能的行動應用程式。

神經型態晶片的設計遵循對生物神經系統部分建模的目標。目的是複製計算功能，特別是有效解決認知和感知任務的能力。為了實現這一點，需要建立一個在神經元和突觸連接數量方面足夠複雜的網路模型。大腦及其學習和適應特定問題的能力仍然是基礎神經科學研究的主題。

神經形態計算設備可能只使用很少的電量，導致能源需求顯著增加，使硬體攻擊更容易識別。這種成長可能透過側通道監控顯現出來。神經形態設備的設計者可能會使用大腦的功能作為藍圖，利用 3D 奈米結構、生醫材料、氧化還原憶阻器、磁性神經網路交叉陣列和其他技術來建構運算系統。

新冠疫情對醫療保健業務市場產生了正面影響。 IBM、惠普和高通等多家市場領導已將神經形態運算解決方案推廣至全球多家醫院和診所。他們的技術的計算能力可以緩解典型醫院生態系統中的各種困難。疫情推動了資本設備產業的發展，對下一代電子產品的需求強勁。

神經型態晶片市場趨勢

消費性電子領域佔較大市場佔有率

消費性電子產業已經認知到神經形態運算是實現這些目標的有前途的工具，可以實現高效能運算和超低功耗。例如，Alexa 和 Siri 等人工智慧服務依靠雲端運算和網際網路來解釋和回應口頭命令和問題。神經形態晶片有可能使各種感測器和設備無需網路連接就能智慧運作。

智慧型手機有望成為神經形態運算引入的催化劑。某些操作（例如生物識別）非常耗電且資料密集。例如，透過語音辨識，語音資料在雲端處理，然後發送回行動電話。

穿戴式裝置是一項快速發展的技術，它將對個人醫療保健、經濟和社會產生深遠的影響。隨著寬頻和分散式網路中感測器的激增，功耗、處理速度和系統適應性對於智慧穿戴式裝置的未來至關重要。此外，人工智慧領域正在進一步增強智慧穿戴感測系統的潛力。新興的高效能系統和智慧應用需要更大的複雜性，並需要能夠準確代表物理物件的感覺單元。

IBM 的 TrueNorth 等專用神經形態裝置正在為穿戴式裝置實現影像辨識和自然語言處理等高級功能。在緊急情況下，神經形態穿戴裝置可以通知相關人員、監測生命徵象、辨識異常並快速做出反應。

人們對神經型態工程的興趣日益濃厚，顯示硬體脈衝神經網路被認為是一項重要的未來技術，在邊緣運算和穿戴式裝置等重要應用方面具有巨大潛力。

預測期內，北美將佔據主要佔有率

北美有英特爾公司、IBM公司等主要供應商。由於政府舉措、投資活動和其他活動等因素，該地區的神經形態晶片市場正在成長。

例如，2023年9月，美國國家科學基金會宣布了24項研究和教育計劃，總額達4560萬美元，其中包括來自2022年《晶片與科學法案》的資助，旨在促進新半導體舉措的快速進步、製造和勞動力發展。 NSF 未來半導體 (FuSe) 計劃是公私合營，與三星、愛立信、IBM 和英特爾四家公司合作資助舉措。

同時，加拿大政府對人工智慧技術的關注也有望在未來幾年為神經形態運算創造成長空間。例如，2023年6月，加拿大政府提出新的《人工智慧和資料法案》（AIDA），以提案人工智慧帶來的潛在風險，建立對加拿大人工智慧產業的信任，並保護加拿大人免受各種傷害。 AIDA 將確保加拿大成為世界上最負責任和最值得信賴的人工智慧的發源地。

多個研究計劃正在尋求合作以推進神經型態技術。例如，2023年6月，洛斯阿拉莫斯國家實驗室宣布開發出一種新型介面憶阻裝置。結果表明，它們可用於構建下一代神經形態計算的人工突觸。

此外，各國國防支出的增加也可望推動北美對神經形態運算的需求。

神經形態晶片產業概況

神經形態晶片市場包括大型半導體供應商、架構開發新興企業以及具有強大產生收入能力的大學。市場正在整合，供應商擴大投入研發和合作活動來獲取和商業化技術力，使市場競爭更加激烈。

儘管神經型態晶片尚處於開發早期階段，但市場參與企業的專利申請活動已引起各大半導體公司、研發中心和大學的興趣，未來競爭對手之間的競爭可能會更加激烈。

2023 年 6 月，BrainChip Holdings Ltd. 和 Lorser Industries Inc. 宣布將利用 BrainChip 的 Akida 技術為軟體定義無線電 (SDR) 裝置提供神經形態運算解決方案。此次夥伴關係將利用 Lorser 在 SDR 設計和製造方面的專業知識以及 BrainChip 的尖端神經型態技術，實現創新、智慧的解決方案，使 SDR 設備更具適應性、可靠性和擴充性。

2024 年 4 月，晶片製造商英特爾宣布已建成世界上最大的神經型態系統“Hala Point”，以促進更永續的人工智慧 (AI)。這個大型神經形態系統首先在桑迪亞國家實驗室實施，將利用英特爾的 Loihi 2 CPU 支援未來受大腦啟發的人工智慧研究，並解決當前人工智慧的有效性和永續性問題。

其他福利

Excel 格式的市場預測 (ME) 表
3個月的分析師支持

The increasing use of biometrics and in-speech recognition drives the demand for neuromorphic chips in smartphones. These chips are used to process audio data in the cloud and then return it to the phone. In addition, Artificial Intelligence (AI) requires more computing power, but low-energy neuromorphic computing could significantly push applications that run presently in the cloud to run directly in the smartphone in the future without substantially draining the phone battery.

Neuromorphic is a specific brain-inspired ASIC that implements the Spiked Neural Networks (SNNs). On average, it has an object that can reach a massively parallel brain processing ability in tens of watts. The memory and the processing units are in single abstraction (in-memory computing).

This leads to the advantage of dynamic, self-programmable behavior in complex environments. Instead of traditional bit-precise computing, neuromorphic hardware leads to the probabilistic models of simple, reliable, robust, and data-efficient computing as the brain's highly stochastic nature. Neuromorphic hardware certainly suits more cognitive applications than precise computing.

During the next decade, neuromorphic computing will transform the nature and functionalities of a wide range of scientific and non-scientific applications. Some of them include mobile applications that are increasingly demanding powerful processing capacities and abilities.

The design of neuromorphic chips follows the goal of modeling parts of the biological nervous system. The aim is to reproduce its computational functionality, especially its ability to efficiently solve cognitive and perceptual tasks. Achieving this requires modeling networks of sufficient complexity regarding the number of neurons and synaptic connections. The brain and its ability to learn and adapt to specific problems are still subject to basic neuroscientific research.

The telltale spike in energy demand resulting from neuromorphic computing devices using potentially very small quantities of electricity makes hardware attacks much easier to identify. This increase would be visible through side-channel monitoring. Neuromorphic device designers may use brain functionality as a blueprint to create computing systems that use 3D nanostructures, biomaterials, redox memristors, magnetic neural network crossbar arrays, and other technologies.

The COVID-19 pandemic had a favorable influence on the medical business market. Several market leaders, including IBM, Hewlett Packard, and Qualcomm, pushed their neuromorphic computing solutions into several hospitals and clinics worldwide. Their technologies' computational skills were able to reduce various difficulties inside a normal hospital ecosystem. The pandemic kept the capital equipment sector humming with a strong demand for next-generation electronics.

Neuromorphic Chip Market Trends

Consumer Electronics Segment Holds Significant Market Share

The consumer electronics industry identifies neuromorphic computing as a promising tool for enabling high-performance computing and ultra-low power consumption to achieve these goals. For instance, AI services like Alexa and Siri rely on cloud computing and the internet to parse and respond to spoken commands and questions. Neuromorphic chips have the potential to allow several varieties of sensors and devices to perform intelligently without requiring an internet connection.

Smartphones are expected to be the trigger for the introduction of neuromorphic computing. Several operations, such as biometrics, are power-hungry and data-intensive. For instance, in speech recognition, audio data is processed in the cloud and then returned to the phone.

Wearable devices are a fast-growing technology with a considerable impact on personal healthcare for both the economy and society. Due to widespread sensors in pervasive and distributed networks, power consumption, processing speed, and system adaptation are vital in the future of smart wearable devices. Additionally, the field of artificial intelligence further boosts the possibility of smart wearable sensory systems. The emerging high-performance systems and intelligent applications need more complexity and demand sensory units to describe the physical object accurately.

Advanced functions like image identification and natural language processing are becoming possible for wearables due to dedicated neuromorphic devices like IBM's TrueNorth. In an emergency, neuromorphic wearables can notify medical personnel, monitor vital signs, identify abnormalities, and respond promptly.

The increasing interest in neuromorphic engineering shows that hardware-spiking neural networks are considered a critical future technology with high potential in crucial applications, such as edge computing and wearable devices.

North America to Hold Major Share over the Forecast Period

North America is home to some of the major market vendors, such as Intel Corporation and IBM Corporation. The market for neuromorphic chips is growing in the region due to factors such as government initiatives, investment activities, and others.

For instance, in September 2023, In order to facilitate quick advancements in novel semiconductor technologies and manufacturing as well as workforce development, the US National Science Foundation announced 24 research and education initiatives totaling USD 45.6 million, including financing from the "CHIPS and Science Act of 2022". The NSF Future of Semiconductors (FuSe) program funds the initiatives in conjunction with four companies, Samsung, Ericsson, IBM, and Intel, through a public-private collaboration.

On the other hand, the government of Canada is focusing on artificial intelligence technology, which is also expected to create a scope for growth in neuromorphic computing over the coming years. For instance, in June 2023, the government of Canada proposed a new Artificial Intelligence and Data Act (AIDA) to address the potential risks of AI, build trust in Canada's AI industry, and protect Canadians from a range of harms. AIDA will ensure that Canada is home to the world's most responsible and trusted AI.

Several research projects are attracting collaborations for advancements in neuromorphic technology. For instance, in June 2023, Los Alamos National Laboratory announced the development of the new interface-type memristive device, which their results suggest can be used to build artificial synapses for next-generation neuromorphic computing.

The increasing defense expenditure of various countries is also expected to drive the demand for neuromorphic computing in North America.

Neuromorphic Chip Industry Overview

The neuromorphic chip market has large-scale semiconductor vendors that command significant revenue generation capabilities, architecture-development start-ups, and universities. The market is consolidated, and vendors are increasingly spending on R&D and collaboration activities to gain technological capabilities and commercialize the market, making the market less competitive.

Despite neuromorphic chips being at an early stage of development, the patent filing activity by players in the market is gaining interest across key semiconductor companies, R&D centers, and universities, and competitive rivalry is poised to increase in the future.

In June 2023, BrainChip Holdings Ltd and Lorser Industries Inc. announced that they would use BrainChip's Akida technology to deliver neuromorphic computing solutions for software-defined radio (SDR) devices. The partnership will leverage Lorser's expertise in SDR design and manufacturing and BrainChip's cutting-edge neuromorphic technology to create innovative, intelligent solutions that enhance SDR devices' adaptability, reliability, and scale.

In April 2024, Chip maker Intel announced that to facilitate more sustainable artificial intelligence (AI), it has constructed the largest neuromorphic system in the world, known as "Hala Point." This massive neuromorphic system, which was first implemented at Sandia National Laboratories, makes use of Intel's "Loihi 2" CPU, supports research into future brain-inspired artificial intelligence, and addresses issues with the effectiveness and sustainability of current AI.

Additional Benefits:

The market estimate (ME) sheet in Excel format
3 months of analyst support

1 INTRODUCTION

1.1 Study Assumptions and Market Definition
1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET INSIGHTS

4.1 Market Overview
4.2 Industry Attractiveness - Porter Five Forces
- 4.2.1 Bargaining Power of Suppliers
- 4.2.2 Bargaining Power of Buyers
- 4.2.3 Threat of New Entrants
- 4.2.4 Threat of Substitute Products
- 4.2.5 Intensity of Competitive Rivalry
4.3 Industry Value Chain Analysis
4.4 Emerging Use Cases for Neuromorphic Chips
4.5 Assessment of the Impact of COVID-19 on the Market

5 MARKET INSIGHTS

5.1 Market Drivers
- 5.1.1 Increasing Demand for Artificial Intelligence-based Microchips
- 5.1.2 Emerging Trend of Combining the Concept of Neuroplasticity with Electronics
5.2 Market Challenges
- 5.2.1 Need for High Level of Precision and Complexity in Hardware Design

6 GLOBAL DEEP LEARNING MARKET ANALYSIS

6.1 Current market scenario
6.2 Global Deep Learning Market Segmentation
- 6.2.1 By Type
  - 6.2.1.1 CPU
  - 6.2.1.2 GPU
  - 6.2.1.3 FPGA
  - 6.2.1.4 ASIC
  - 6.2.1.5 SoC Accelerators
6.3 Coverage on the Current Trends in the Deep Learning Software and Service industry
6.4 Investment Scenario
6.5 List of Major Hardware Vendors
6.6 Future of the Market

7 MARKET SEGMENTATION

7.1 By End-User Industry
- 7.1.1 Financial Services and Cybersecurity
- 7.1.2 Automotive (ADAS/Autonomous Vehicles)
- 7.1.3 Industrial (IoT Ecosystem, Surveillance, and Robotics)
- 7.1.4 Consumer Electronics
- 7.1.5 Other End-user Industries (Medical, Space, Defense, Etc.)
7.2 By Geography
- 7.2.1 North America
- 7.2.2 Europe
- 7.2.3 Asia Pacific
- 7.2.4 Rest of the World

8 COMPETITIVE LANDSCAPE

8.1 Company Profiles
- 8.1.1 Intel Corporation
- 8.1.2 SK Hynix Inc.
- 8.1.3 IBM Corporation
- 8.1.4 Samsung Electronics Co. Ltd
- 8.1.5 GrAI Matter Labs
- 8.1.6 Nepes Corporation
- 8.1.7 General Vision Inc.
- 8.1.8 Gyrfalcon Technology Inc.
- 8.1.9 BrainChip Holdings Ltd
- 8.1.10 Vicarious FPC Inc.
- 8.1.11 SynSense AG