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The neural network software market patterns are gradually beginning to conform to the growing demand for state-of the-art AI (ML) and computer based intelligence solutions driven by various industries. Whilst organizations continually explore the utility of neural networks for productivity enhancement through innovation, the market for neural network software is experiencing amazing growth and transformation.
A noteworthy feature observed in the neural network software market is the growing acceptance of deep learning systems. These systems include TensorFlow, PyTorch, and Keras, which are gaining enough ground for their ability to treat complicated neural network models that work with more massive datasets. Companies are adopting these systems to develop use cases for image and speech recognition, natural language processing, and predictive analysis which have resulted in surging demand for neural network software.
The other key pattern could be the design of neural network software for edge processing and IoT devices. Consequently, as the deployment of intelligent systems at the edge increases, demand for smart and economical neural network software is increasing. This progression is stimulated by the necessity for continuous correction and active improvements in areas like self-driving vehicles, smart devices, and industrial automation, which foster growth in the neural network software market.
The market, on the other hand, is experiencing a surge of specifically designed neural network software to perform specific tasks. Organizations are hence shifting towards sector-specific partnerships such as healthcare diagnostics, financial fraud detection, and robotics which cater to the particular needs of different sectors. It implies the growing recognition of the possible implications of artificial neural network software in addressing industry-specific problems and opportunities.
In addition, coordination of neural network software with distributed computing innovations is a very important pattern contributing to this market. Cloud-based neural network stages and services are becoming more popular by the day, providing businesses with a way to access mobile computing resources, for training and deploying neural networks. This behavior is basically due to the increasing popularity of intelligence software as a requirement and the growth of the market for neural network software solutions.
Covered Aspects:
| Report Attribute/Metric | Details |
|---|---|
| Segment Outlook | Type, Component, and Region |
Neural Network Software Market Highlights:
Neural Network Software Market Overview
The Neural Network Software Market is projected to grow from USD 32.39 billion in 2024 to USD 152.75 billion by 2032, exhibiting a compound annual growth rate (CAGR) of 21.39% during the forecast period (2024 - 2032). Additionally, the market size for neural network software was valued at USD 25.95 billion in 2023.
The development of data archiving technologies to organize the massive volume of unorganized data produced by various end users is the main factor driving the growth of the neural network industry. Additionally, a growing acceptance of digital technologies and a rise in the need for predictive solutions are both factors propelling the market for neural network software. Predictive solutions are increasingly in demand due to several key variables, including an exponential increase in data volume, increased digitalization, strict laws, and financial losses brought on by a surge in fraudulent practices, which are the key market drivers enhancing market growth.
Figure 1: Neural Network Software Market Size, 2023-2032 (USD Billion)
Source: Secondary Research, Primary Research, MRFR Database and Analyst Review
Neural Network Software Market Trends
Advancement in the artificial intelligence (AI) sector is driving the market growth.
Market CAGR is driven by artificial intelligence (AI) market advancements. Artificial intelligence (AI) systems use neural networks to support learning, reasoning, and self-correction. Expert systems, machine vision, and speech recognition, are specific uses of AI. AI's current rise in popularity is due to difficult projects involving cloud computing and large data infrastructure. Leading businesses across a range of industries, including Software & IT (Google, Microsoft, and Amazon), Financial Services (Bloomberg and American Express), and Automotive (Tesla and Ford), have identified AI as a key strategic driver and begun investing in neural networks to create effective systems that will be more sophisticated.
These leading businesses have also helped young startups by offering funding to develop fresh, creative neural search systems. For instance, the open-source firm Jina.ai, located in Berlin, earned $30 million in a series A funding round in November 2021. Canaan Partners led a fundraising round that helps its customers uncover knowledge in their unstructured data.
Furthermore, there is a rise in cloud disruption in the modern industry. One of the most potent computer paradigms is cloud computing. The ability to use SaaS (Security as a Service), PaaS, and IaaS innovations, together with competition among the main IT providers and users, has made cloud computing successful in recent years. New services like "Backend as a Service" and "Function as a Service" have been incorporated to boost company profitability. Additionally, most cloud computing platforms still employ primitive Core Processing Unit (CPU) scheduling algorithms that lack the sophistication required for such an advanced computing architecture. Thus, driving the neural network software market revenue.
Neural Network Software Market Segment Insights
Neural Network Software Type Insights
Based on type, the global neural network software market segmentation includes data mining & archiving, analytical software, optimization software, and visualization software. In terms of revenue share, the analytical software segment dominates the market. Still, the data mining and archiving software segment is anticipated to grow at the quickest CAGR throughout the forecast period. The vast influx of unstructured and geographical data, as well as the requirement to categorize this data to carry out analytical and predictive operations, are the main drivers of the expansion of the data mining and archiving software market.
Neural Network Software Component Insights
Based on components, the global neural network software market segment includes neural network software, services, and platform. The rise of neural network software has been one of the most transformative developments in artificial intelligence (AI) and machine learning (ML). Neural networks are a class of algorithms inspired by the human brain's structure and functioning, allowing them to learn patterns and relationships from data. Deep learning, an area of AI that focuses on training multi-layered neural networks, is built on top of neural networks. Convolutional neural networks (CNNs) and recurrent neural networks (RNNs), two recent deep learning innovations, have significantly improved a variety of AI applications like computer vision, natural language processing, and speech recognition.
Figure 2: Neural Network Software Market, by Component, 2022 & 2032 (USD Billion)
Source: Secondary Research, Primary Research, MRFR Database and Analyst Review
Neural Network Software Regional Insights
By region, the study provides market insights into North America, Europe, Asia-Pacific and Rest of the World. As a result of the extensive use of neural network technology by tech giants, North America is anticipated to experience considerable expansion in the market for neural network software during the projected period. For instance, Intel made history in August 2019 when it unveiled two new CPUs for massive data centers powered by Al technology. The chips are the initial products in the Nervana Neural Network Processor (NPP) family; the Nervana NNP-T trains Al systems, while the Nervana NNP-1 handles inference. Such advancements are expected to fuel market expansion in the area.
Further, the major countries studied in the market report are The US, Canada, German, France, the UK, Italy, Spain, China, Japan, India, Australia, South Korea, and Brazil.
Figure 3: NEURAL NETWORK SOFTWARE MARKET SHARE BY REGION 2022 (USD Billion)
Source: Secondary Research, Primary Research, MRFR Database and Analyst Review
Europe's neural network software market accounts for the second-largest market share due to the acceptance of developments in the aviation sector and the incorporation of cutting-edge technology into the autopilot system. Europe is predicted to grow considerably in the neural network software market. Further, the German neural network software market held the largest market share, and the UK neural network software market was the fastest-growing market in the European region.
The Asia-Pacific Neural Network Software Market is expected to grow at the fastest CAGR from 2023 to 2032. Due to the expanding firms in the area embracing innovative technologies to quickly train deep learning models, Asia-Pacific is predicted to grow at an accelerated rate in the neural network software market during the forecast period. Moreover, China’s neural network software market held the largest market share, and the Indian neural network software market was the fastest-growing market in the Asia-Pacific region.
Neural Network Software Key Market Players & Competitive Insights
Leading market players are investing heavily in research and development to expand their product lines, which will help the advanced authentication market, grow even more. Market participants are also engaging in various strategic measures to grow their businesses, and global footprint, with important market developments including contractual agreements, new product launches, mergers and acquisitions, higher investments, and collaboration with other organizations. The neural network software industry must offer cost-effective items to expand and survive in a more competitive and rising market climate.
Manufacturing locally to minimize operational costs is one of the key business tactics manufacturers use in the global neural network software industry to benefit clients and increase the market sector. In recent years, the neural network software industry has offered some of the most significant medical advantages. Major players in the advanced authentication market, including Oracle Corporation, Qualcomm Technologies, SAP SE, IBM Corporation, Microsoft Corporation, Intel Corporation, Google, Alyuda Research LLC, Neural Technologies Ltd., Starmind International AG, Neuralware, Ward Systems Group Inc., and others, are attempting to increase market demand by investing in research and development operations.
Qualcomm's Neural Processing Engine (NPE) is a key component that enables AI and ML capabilities on their Snapdragon processors, which are widely used in smartphones, tablets, IoT devices, and other consumer electronics. The NPE is a software framework that provides a set of APIs (Application Programming Interfaces) to efficiently run neural network models on Qualcomm's hardware, such as the Adreno GPU or Hexagon DSP (Digital Signal Processor), which are designed to accelerate AI workloads. For instance, in June 2022, to further its leadership in AI and connected intelligent edge, Qualcomm Technologies integrated its existing best-in-class AI software products into a single package, the Qualcomm AI Stack. This will enable OEM clients of Qualcomm Technologies and developers to fully use the Qualcomm AI Engine's performance while developing, improving, and deploying their AI applications on Qualcomm Technologies' hardware.
Google's AI and neural network software offerings are part of a broader AI ecosystem, and the company actively contributes to open-source projects and supports AI research and development across various domains. As AI technology continues to evolve, Google is likely to keep innovating and expanding its neural network software tools to empower developers and researchers in the AI community. For instance, in May 2022, to speed up performance testing in graph neural networks (GNNs), Google AI launched GraphWorld. It offers a novel GNN architectural testing and design method by enabling artificial intelligence (AI) developers and researchers to test new GNN architectures on bigger graph datasets.
Key Companies in the neural network software market include
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Oracle Corporation
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Qualcomm Technologies
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SAP SE
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IBM Corporation
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Microsoft Corporation
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Intel Corporation
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Google
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Alyuda Research LLC
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Neural Technologies Ltd.
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Starmind International AG
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Neuralware
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Ward Systems Group Inc.
Neural Network Software Industry Developments
August 2022: To assist experts in scientific computing, visualization, and other fields that deal with huge and complicated volumetric data in real time, the famous OpenVDB merged artificial intelligence (AI) with general processing unit (GPU) optimization. This was done with the launch of NVIDIA's NeuralVDB. For sparse volumetric data, including smoke and clouds, NeuralVDB delivers a 100x memory footprint decrease.
October 2022: IBM announced the addition of three new libraries to its portfolio of embeddable AI software. With the help of these libraries, IBM Ecosystem partners, customers, and developers should find it easier, quicker, and more economical to build and sell their AI-powered products.
Neural Network Software Market Segmentation
Neural Network Software Component Outlook
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Data Mining & Archiving
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Analytical Software
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Optimization Software
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Visualization Software
Neural Network Software Deployment Outlook
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Neural Network Software
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Services
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Platform
Neural Network Software Regional Outlook
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North America
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US
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Canada
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Europe
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Germany
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France
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UK
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Italy
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Spain
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Rest of Europe
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Asia-Pacific
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China
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Japan
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India
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Australia
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South Korea
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Australia
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Rest of Asia-Pacific
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Rest of the World
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Middle East
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Africa
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