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Neuromorphic Computing Market

Neuromorphic Computing Market

The market for Neuromorphic Computing was estimated at $3.6 billion in 2024; it is anticipated to increase to $13.3 billion by 2030, with projections indicating growth to around $39.7 billion by 2035.

Report ID:DS1101009
Author:Ranjana Pant - Research Analyst
Published Date:December 2024
Datatree
Information Technology
Hardware & Infrastructure
Neuromorphic Computing
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Report Summary
Table of Contents
Methodology
Market Data

Global Neuromorphic Computing Market Outlook

Revenue, 2024

$3.6B

Forecast, 2034

$31.9B

CAGR, 2024 - 2034

24.5%
The Neuromorphic Computing industry revenue is expected to be around $4.4 billion in 2025 and expected to showcase growth with 24.5% CAGR between 2025 and 2034. Its use and transformative abilities make it a game changer that could lead to major shifts not only in computing but also, in artificial intelligence and robotics. By enabling the development of machines that mimic thinking and learning processes this groundbreaking technology is expected to usher in a new era of progress driving remarkable advancements and transformations across various applications worldwide.

Neuromorphic Computings special power comes from its ability to imitate the neural structure and functions of the human brain to handle complex calculations effectively.

Neuromorphic Computing market outlook with forecast trends, drivers, opportunities, supply chain, and competition 2024-2034

Market Key Insights

  • The Neuromorphic Computing market is projected to grow from $3.6 billion in 2024 to $31.9 billion in 2034. This represents a CAGR of 24.5%, reflecting rising demand across Machine Vision, Real-Time Data Analysis and Autonomous Robots.
  • The market leaders in this sector include IBM and Intel Corporation and Qualcomm Incorporated which determine the competitive dynamics of the market.
  • U.S. and China are the top markets within the Neuromorphic Computing market and are expected to observe the growth CAGR of 23.5% to 34.3% between 2024 and 2030.
  • Emerging markets including Brazil, India and South Africa are expected to observe highest growth with CAGR ranging between 18.4% to 25.5%.
  • The market for Neuromorphic Computing will experience a $3.7 billion growth boost because of Transition like Artificial Intelligence Ascendancy until 2030.
  • The Neuromorphic Computing market is set to add $28.3 billion between 2024 and 2034, with industry players targeting Signal Recognition & Data Mining Application projected to gain a larger market share.
  • With Advancement in computing technology, and Dominance of ai and machine learning applications, Neuromorphic Computing market to expand 795% between 2024 and 2034.
neuromorphic computing market size with pie charts of major and emerging country share, CAGR, trends for 2025 and 2032

Opportunities in the Neuromorphic Computing

The increasing demand for energy data solutions has led to the rise of neuromorphic computing as a promising solution to this evolving issue. Its design inspired by the brain allows for power consumption and aligns with the current focus, on developing greener and more sustainable data centers.

Growth Opportunities in North America and Europe

North America Outlook

North America stands out as a hub for tech companies and is at the forefront of the Neuromorphic Computing market due to significant investments in research and development (R&D) emphasis, on artificial intelligence (AI) and machine learning (ML) technologies and a thriving startup community that drives innovation. Although facing competition the North American market offers considerable potential especially within the technology sector and defense industry.

Europe Outlook

In Europe's Neuromorphic Computing sector is experiencing growth due to various factors like government emphasis on innovative technologies and ample funding for research projects along with a robust industrial presence in nations like Germany and the UK which all contribute to this upward trend in the market segment. Interestingly the rising adoption in sectors such as automotive and healthcare indicates promising prospects, for advancement and expansion.

Market Dynamics and Supply Chain

01

Driver: Advancement in Computing Technology, and Scalability and Energy Efficiency

The rise in the need for computing power to handle various intricate tasks has also played a significant role in the expansion of the neuromorphic computing sectors growth trajectory. Chips ability to emulate human brain functions has also made them well suited for tasks like big data analysis and pattern recognition. This has also led to an increase in their popularity and demand for applications such, as analytics and other sophisticated computing activities. The demand, for increased scalability and energy saving computing solutions to align with sustainability goals and improve efficiency is also propelling the growth of the neuromorphic computing sector.
The growth of AI and machine learning connected to the progress in computing technology is also a factor pushing forward the neuromorphic computing markets development. Its importance lies in its capability to learn and evolve with time which makes it suitable, for complex artificial intelligence tasks.
02

Restraint: High Implementation Cost

A major hurdle in the realm of computing is the steep implementation costs involved in creating neuromorphic chips necessitating a considerable investment, in research and development funds which could hinder market expansion as many interested parties might find it hard to finance such substantial ventures This obstacle is especially daunting in underdeveloped markets where resources are limited and the technological framework may not be sufficiently advanced to accommodate neuromorphic computing.
03

Opportunity: Enhanced IoT Devices and AI-driven Healthcare Applications

Given the growth of the Internet of Things (IoT) neuromorphic computing has the potential to bring about significant changes in this field. With the increasing need for efficient IoT devices that can respond quickly to inputs and data processing requirements comes an opening for neuromorphic computing to shine with its real time processing capabilities. The incorporation of chips, into IoT devices could usher in a new era characterized by highly responsive and intelligent devices operating autonomously and thereby reshaping the competitive landscape of the market.
Neuromorphic computing aims to replicate the processing power of the human brain and holds great promise in the realm of healthcare applications that remain largely unexplored. With its capacity to handle volumes of data rapidly and effectively in tow harnessing AI driven healthcare has the potential to enhance accessibility and precision making predictive diagnoses and advanced patient monitoring a reality.
04

Challenge: Limited Technological Understanding

The growth of computing faces a significant obstacle due to the lack of widespread knowledge and awareness about this technology, among non experts despite its promising advantages and intricate nature.

Supply Chain Landscape

1
Research & Development

Intel

HP Labs

2
Component Manufacturing

IBM

Qualcomm

Toshiba

3
System Integration

BrainChip Inc

HRL Laboratories

4
End Users

Aerospace & Defense Industries

Healthcare Industries

Consumer Electronics Industries

*The illustration highlights the key stakeholders within the supply chain ecosystem.

Applications of Neuromorphic Computing in Machine Vision, Real-Time Data Analysis & Autonomous Robots

Machine Vision

Neuromorphic computing is widely used in machine vision to help machines interpret and comprehend the environment they encounter in real time. This technology allows for fast image analysis which aids in making decisions accurately. Intel is a player in this field, with its research chip called Loihi that leverages neuromorphic capabilities.

Real-Time Data Analysis

Neuromorphic computing is widely used for real time data analysis due to its ability to quickly and effectively process datasets and provide immediate insights essential for time sensitive situations like high frequency trading activities. The TrueNorth neuromorphic chip from IBM is a player, in this field of technology.

Autonomous Robots

Neuromorphic computing plays a role in empowering autonomous robots to learn and adjust to their surroundings instantly—an ability reminiscent of the human brains functioning style. This advancement offers robots autonomy and performance levels in intricate environments while also lowering power consumption and computing demands. Qualcomm stands out as a player, in this field by enhancing robotics through their Snapdragon neuromorphic processor.

Recent Developments

December 2024

Intel has revealed its cutting edge neuromorphic computing chip called Loih 2. This new chip boasts an efficiency that is ten times greater, than its predecessor.

November 2024

IBM has effectively combined its neuromorphic computing technology with cloud storage platforms to significantly enhance data processing speeds.

September 2024

Hewlett Packard Enterprises (known as HPE in the tech world) entered the field of computing by introducing a cutting edge prototype that is highly energy efficient.

Neuromorphic Computing is an evolving area of computer science that focuses on image and pattern recognition and is experiencing notable advancements at present. These technologies imitate the architecture of the human brain to execute intricate calculations, with greater speed and efficiency.

Impact of Industry Transitions on the Neuromorphic Computing Market

As a core segment of the Hardware & Infrastructure industry, the Neuromorphic Computing market develops in line with broader industry shifts. Over recent years, transitions such as Artificial Intelligence Ascendancy and Shift Towards Edge Computing have redefined priorities across the Hardware & Infrastructure sector, influencing how the Neuromorphic Computing market evolves in terms of demand, applications and competitive dynamics. These transitions highlight the structural changes shaping long-term growth opportunities.
01

Artificial Intelligence Ascendancy

The rapid growth in the Neuromorphic Computing industry is driven by the adoption of artificial intelligence (AI). These systems that emulate the structure of the human brain are playing a crucial role in advancing AI technologies. The rising need for processing speeds and more efficient data management with lower energy consumption is fueling the integration of AI, into neuromorphic computing systems. This industry transition is expected to add $3.7 billion in the industry revenue between 2024 and 2030.
02

Shift Towards Edge Computing

During this journey of transformation in the field of computing industry stands out the significant move towards edge computing as a pivotal transition. Edge computing boosts the effectiveness of chips by handling data closer, to its origin point.

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