Neural Network Software Market

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.

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.

The Global Neural Network Software Market Industry experiences a notable surge in demand for artificial intelligence solutions across various sectors. Industries such as healthcare, finance, and automotive increasingly adopt neural network software to enhance decision-making processes and automate tasks. For instance, healthcare providers utilize neural networks for predictive analytics, improving patient outcomes. The market is projected to reach 32.4 USD Billion in 2024, with a robust growth trajectory anticipated as organizations recognize the potential of AI-driven insights. This trend indicates a broader acceptance of neural networks as essential tools for operational efficiency and innovation.

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, Market Research Future 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.

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.