Neural Network Software Market Set to Reach USD 152.3 Billion by 2031 Driven by Growing Demand for AI Applications

The SNS Insider report estimates that the global Neural Network Software Market size reached USD 25.7 Billion in 2023. Driven by the aforementioned factors, the market is projected to reach a staggering USD 152.3 Billion by 2031, reflecting a robust CAGR of 24.9% throughout the forecast period 2024-2031.

Growing Demand for Neural Network Software

The exponential growth of spatial data generated from various sources, including satellite imagery and IoT devices, necessitates efficient processing, analysis, and visualization. Neural network software offers a powerful toolset for handling such complex data sets, ultimately driving market expansion. Neural network software plays a crucial role in predictive solutions by leveraging historical data to forecast future outcomes. This capability empowers businesses to make data-driven decisions, mitigate risks, and optimize resource allocation, contributing to market growth.

The burgeoning adoption of cloud-based neural network software offers substantial advantages, including scalability, flexibility, cost-effectiveness, and improved performance compared to traditional on-premise deployments. This shift towards cloud solutions is expected to create significant growth opportunities. Neural network software encompasses a wide range of tools and frameworks designed to streamline the development, training, and deployment of neural networks, a core component of deep learning. These software solutions are categorized by functionality and purpose, including data mining and archiving, optimization, analytics, visualization, and machine learning.

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Major The Key Players of Neural Network Software Market

Qualcomm Technologies Inc., IBM, Intel Corporation, Google Inc., Ward Systems Group Inc., Microsoft Corporation, Neuralware, SAP SE, Oracle Corporation, Alyuda Research LLC, Neural Technologies Ltd., Starmind International AG, Slagkryssaren AB, Afiniti, GMDH LLC

Segmentation Analysis

The neural network software segment holds the dominant market share. This segment offers frameworks and libraries equipped with pre-designed functions and tools for constructing, training, and deploying neural networks. These tools provide researchers and developers with a platform to create and execute complex neural network structures. Additionally, they offer APIs that allow users to define layers, set parameters, and manage the overall network topology. Neural network software also encompasses algorithms and functions that facilitate the training process, enabling models to fine-tune their parameters and achieve optimal performance.

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Key Market Segments

By Type

• Data Mining and Archiving
• Analytical Software
• Optimization Software
• Visualization Software

By Application

• Fraud Detection
• Hardware Diagnostics
• Financial Forecasting
• Image Optimization
• Others

By Component

• Neural Network Software
• Services
• Platform and Other Enabling Services

By Vertical

• BFSI
• Government and Defense
• Energy and Utilities
• Healthcare
• Industrial Manufacturing
• Media
• Telecom and IT
• Transportation and Logistics
• Retail and eCommerce
• Others

Impact of Global Events

The ongoing Russia-Ukraine war presents potential challenges to the neural network software market. Disruptions in the global supply chain, sanctions on certain countries, and fluctuations in energy prices can impede the development and deployment of neural network technologies. However, the long-term impact of the war remains uncertain, and the market’s inherent growth potential could mitigate these challenges.

An economic slowdown has the potential to dampen market growth. Reduced investments in research and development, coupled with budget constraints faced by businesses, could limit the adoption of neural network software. However, the long-term benefits of neural networks, such as increased efficiency and cost savings, could encourage continued investment even during economic downturns.

Key Regional Developments

North America currently holds the most significant share of the global neural network software market and is expected to maintain its leadership position throughout the forecast period. This dominance is attributed to superior technological advancements, a thriving innovation ecosystem, and the presence of prominent players like Google, IBM, Microsoft, and Intel. Furthermore, the extensive implementation of neural network technology by major companies in the region is expected to fuel market expansion.

Recent Developments

In January 2024: Tesla initiated the rollout of its FSD Beta v12 upgrade, signifying a critical step towards achieving autonomous driving capabilities. This update leverages a unified neural network trained on a vast dataset of video clips, replacing over 300,000 lines of C++ code. This demonstrates the power of neural networks in automating complex tasks.

In November 2023: Broadcom Inc. introduced NetGNT, a novel on-chip neural network inference engine within its Trident 5-X12 processor. This hardware innovation, coupled with programmable software, facilitates efficient neural network execution.

Future Growth

The neural network software market exhibits immense potential for future growth, driven by advancements in artificial intelligence and the increasing demand for data-driven solutions. Emerging fields like autonomous vehicles, robotics, and personalized medicine will continue to fuel this expansion.

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Key Takeaways

• The surging demand for data processing, analysis, and predictive solutions is propelling the neural network software market towards significant growth.
• Cloud-based deployments, offering scalability and cost-effectiveness, are expected to be a major growth driver.
• North America is likely to retain its dominance due to a strong technological infrastructure and established industry leaders.
• The development of next-generation applications in autonomous vehicles, robotics, and personalized medicine will create lucrative opportunities.
• Gain a comprehensive understanding of the neural network software market landscape, including current trends, growth drivers, and potential challenges.
• Analyze the competitive landscape and develop effective strategies to gain a competitive edge.
• Stay updated on the latest technological advancements and future growth prospects in the neural network software domain.

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