The Global Neural Processor Market size is expected to reach $798.2 million by 2031, rising at a market growth of 17.8% CAGR during the forecast period.
Neural processors power chatbots and virtual assistants’ banks and insurance companies use to handle customer inquiries, provide support, and offer personalized recommendations. Consequently, the BFSI segment would generate approximately 17.8% share of the market by 2030. By comprehending natural language and delivering pertinent responses, these systems enhance the consumer experience. Thus, these factors can assist in the growth of the segment.
Edge computing entails processing data in proximity to the point of generation, as opposed to centralized data centers. This approach reduces latency and bandwidth usage while enabling real-time data analysis and decision-making, making it crucial for applications requiring quick responses and efficient resource utilization. Thus, these factors can assist in the expansion of the market.
Additionally, Deep learning methods, distinguished by their multi-layered, sophisticated neural network architectures, have been extensively implemented in various fields, including computer vision, natural language processing (NLP), and autonomous systems. Therefore, owing to these factors, the market will witness increased demand in the coming years.
However, While neural processors exhibit superior performance in accelerating specialized AI tasks, they often struggle to match the versatility of general-purpose processors such as CPUs and GPUs. Developing neural processors that efficiently handle various AI workloads while maintaining scalability across various applications poses formidable engineering hurdles. Therefore, these factors can lead to reduced demand in the market.
Neural processors power chatbots and virtual assistants’ banks and insurance companies use to handle customer inquiries, provide support, and offer personalized recommendations. Consequently, the BFSI segment would generate approximately 17.8% share of the market by 2030. By comprehending natural language and delivering pertinent responses, these systems enhance the consumer experience. Thus, these factors can assist in the growth of the segment.
Edge computing entails processing data in proximity to the point of generation, as opposed to centralized data centers. This approach reduces latency and bandwidth usage while enabling real-time data analysis and decision-making, making it crucial for applications requiring quick responses and efficient resource utilization. Thus, these factors can assist in the expansion of the market.
Additionally, Deep learning methods, distinguished by their multi-layered, sophisticated neural network architectures, have been extensively implemented in various fields, including computer vision, natural language processing (NLP), and autonomous systems. Therefore, owing to these factors, the market will witness increased demand in the coming years.
However, While neural processors exhibit superior performance in accelerating specialized AI tasks, they often struggle to match the versatility of general-purpose processors such as CPUs and GPUs. Developing neural processors that efficiently handle various AI workloads while maintaining scalability across various applications poses formidable engineering hurdles. Therefore, these factors can lead to reduced demand in the market.
By End Use Analysis
On the basis of end user, the market is divided into BFSI, healthcare, retail, defense agencies, media, logistics, and others. The retail segment recorded a 24.21% revenue share in the market in 2023. As AI becomes more pervasive in consumer electronics, the demand for neural processors in retail products is expected to rise. Manufacturers are integrating AI capabilities into devices such as smartphones, cameras, smart speakers, and wearables, which drives the demand for efficient neural processing units (NPUs).
By Application Analysis
Based on application, the market is segmented into fraud detection, hardware diagnostics, financial forecasting, image optimization, and others. In 2023, the financial forecasting segment garnered a 14.9% revenue share in the market. Neural networks excel at capturing intricate patterns and relationships within financial data, leading to more accurate forecasting models. As neural processors become more powerful and specialized for financial applications, they contribute to further improvements in prediction accuracy. Thus, these aspects will propel the growth of the segment.By Regional Analysis
By region, the market is segmented into North America, Europe, Asia Pacific, and LAMEA. In 2023, the Europe segment acquired a 29.56% revenue share in the market. Europe has been actively investing in AI research and development, with countries like the UK, Germany, France, and Switzerland being prominent hubs for AI innovation. European companies and research institutions have been at the forefront of developing neural processors for various applications, including data centers, autonomous vehicles, healthcare, and consumer electronics. Hence, the segment will grow rapidly in the upcoming years.Recent Strategies Deployed in the Market
- Mar-2024: Hewlett Packard Enterprise company has partnered with NVIDIA Corporation to launch an end-to-end AI-native portfolio. This solution, powered by HPE ProLiant DL380a Gen11 servers, is pre-configured with NVIDIA GPUs, Spectrum-X Ethernet networking platform, and BlueField-3 DPUs. Enhanced by HPE's machine learning platform and analytics software, along with NVIDIA AI Enterprise 5.0 software, the solution offers businesses speed, scale, and control for deploying generative AI models within a hybrid cloud model.
- Jan-2024: BrainChip Holdings Ltd has partnered with MYWAI, a top AIoT solution provider in the EU, to deliver cutting-edge Edge AI solutions. These solutions will utilize BrainChip’s Akida™ for efficient sensor data processing and learning, along with MYWAI’s AIoT Platform for EaaS. The partnership aims to drive Edge AI adoption in industrial and robotic sectors, creating substantial value for both companies and their clients.
- Jan-2024: NVIDIA Corporation launched new GeForce RTX™ SUPER desktop GPUs for enhanced generative AI performance, alongside AI laptops from various leading manufacturers. They also introduced new NVIDIA RTX™-accelerated AI software and tools for developers and consumers, leveraging decades of PC expertise. These tools include NVIDIA TensorRT™ acceleration for text-to-image workflows, NVIDIA RTX Remix for AI-based texture creation, NVIDIA ACE microservices, and more games integrating DLSS 3 technology for Frame Generation.
- Dec-2023: Intel Corporation has unveiled the Core Ultra H and Core Ultra U series, part of their new mobile processors based on the Meteor Lake platform. The Ultra Core H series offers four SKUs, including 16-core and 14-core variants, with a base TDP of 28W and a maximum turbo TDP of up to 115W. These chips feature two Low Power Island cores for light workloads and include Neural Compute Engines for generative AI inferencing.
- Nov-2023: NVIDIA collaborates with Terra Quantum AG, a Swiss deep tech incubator focusing on quantum technology. The collaboration aimed to advance data analytics through hybrid computing. Together, they will accelerate the integration of hybrid quantum through GPUs. Terra Quantum seeks to leverage quantum computing's potential to overcome data processing limitations, enhancing speed, accuracy, and scalability. This collaboration with NVIDIA unlock new opportunities across sectors like finance, healthcare, logistics, and energy, enabling businesses to employ data-driven strategies for growth and competitiveness.
List of Key Companies Profiled
- Applied Brain Research, Inc.
- BrainChip Holdings Ltd
- Intel Corporation
- Samsung Electronics Co., Ltd.
- Hewlett Packard Enterprise Company
- NVIDIA Corporation
- Bit&Brain Technologies S.L
- BrainCo, Inc.
- General Vision Inc.
- Aspinity, Inc.
Market Report Segmentation
By Application- Hardware Diagnostics
- Image Optimization
- Fraud Detection
- Financial Forecasting
- Others
- Retail
- Defense Agencies
- Media
- BFSI
- Healthcare
- Logistics
- Others
- North America
- US
- Canada
- Mexico
- Rest of North America
- Europe
- Germany
- UK
- France
- Russia
- Spain
- Italy
- Rest of Europe
- Asia Pacific
- China
- Japan
- India
- South Korea
- Singapore
- Malaysia
- Rest of Asia Pacific
- LAMEA
- Brazil
- Argentina
- UAE
- Saudi Arabia
- South Africa
- Nigeria
- Rest of LAMEA
Table of Contents
Chapter 1. Market Scope & Methodology
Chapter 2. Market at a Glance
Chapter 3. Market Overview
Chapter 5. Global Neural Processor Market by Application
Chapter 6. Global Neural Processor Market by End User
Chapter 7. Global Neural Processor Market by Region
Chapter 8. Company Profiles
Companies Mentioned
- Applied Brain Research, Inc.
- BrainChip Holdings Ltd
- Intel Corporation
- Samsung Electronics Co., Ltd.
- Hewlett Packard Enterprise Company
- NVIDIA Corporation
- Bit&Brain Technologies S.L
- BrainCo, Inc.
- General Vision Inc.
- Aspinity, Inc.
Methodology
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