Global Neural Network
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The base year for the analysis is 2025. Historical data has been considered for the period from 2022 to 2025. The year 2026 is considered as the estimated base for forecasting, with projections covering the period from 2026 to 2034. When we deliver the report that time we updated report data till the purchase date.
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| Data Timeline | Historical Data: 2022-2025 | Base Year: 2025 | Forecast Period: 2026-2034 |
|---|---|
| Component Segment Analysis | Software, Services |
| Industry Vertical Segment Analysis | BFSI, IT & Telecom, Aerospace & Defense, Public Sector, Retail, Healthcare, Manufacturing, Energy & Utilities, Others |
| Regions & Countries Analysis |
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According to Cognitive Market Research, the global Neural Network market size was USD 15214.20 million in 2024. It will expand at a compound annual growth rate (CAGR) of 27.20% from 2024 to 2031.
Market Drivers:
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Market Restrains:
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Market Trends:
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| Market Size | 2021 (A) | 2025 (A) | 2033 (P) | CAGR |
|---|---|---|---|---|
| Global Neural Network Market Sales Revenue | xxxx | xxxx | xxxx | 27.2% |
| North America Neural Network Market Sales Revenue | xxxx | xxxx | xxxx | 25.4% |
| United States Neural Network Market Sales Revenue | xxxx | xxxx | xxxx | 25.2% |
| Canada Neural Network Market Sales Revenue | xxxx | xxxx | xxxx | 26.2% |
| Mexico Neural Network Market Sales Revenue | xxxx | xxxx | xxxx | 25.9% |
| Europe Neural Network Market Sales Revenue | xxxx | xxxx | xxxx | 25.7% |
| United Kingdom Neural Network Market Sales Revenue | xxxx | xxxx | xxxx | 26.5% |
| France Neural Network Market Sales Revenue | xxxx | xxxx | xxxx | 24.9% |
| Germany Neural Network Market Sales Revenue | xxxx | xxxx | xxxx | 25.9% |
| Italy Neural Network Market Sales Revenue | xxxx | xxxx | xxxx | 25.1% |
| Russia Neural Network Market Sales Revenue | xxxx | xxxx | xxxx | 24.7% |
| Spain Neural Network Market Sales Revenue | xxxx | xxxx | xxxx | 24.8% |
| Rest of Europe Neural Network Market Sales Revenue | xxxx | xxxx | xxxx | 24.4% |
| Asia Pacific Neural Network Market Sales Revenue | xxxx | xxxx | xxxx | 29.2% |
| China Neural Network Market Sales Revenue | xxxx | xxxx | xxxx | 28.7% |
| Japan Neural Network Market Sales Revenue | xxxx | xxxx | xxxx | 27.7% |
| India Neural Network Market Sales Revenue | xxxx | xxxx | xxxx | 31% |
| South Korea Neural Network Market Sales Revenue | xxxx | xxxx | xxxx | 28.3% |
| Australia Neural Network Market Sales Revenue | xxxx | xxxx | xxxx | 28.9% |
| Rest of APAC Neural Network Market Sales Revenue | xxxx | xxxx | xxxx | 29% |
| South America Neural Network Market Sales Revenue | xxxx | xxxx | xxxx | 26.6% |
| Brazil Neural Network Market Sales Revenue | xxxx | xxxx | xxxx | 27.2% |
| Argentina Neural Network Market Sales Revenue | xxxx | xxxx | xxxx | 27.5% |
| Colombia Neural Network Market Sales Revenue | xxxx | xxxx | xxxx | 26.4% |
| Peru Neural Network Market Sales Revenue | xxxx | xxxx | xxxx | 26.8% |
| Chile Neural Network Market Sales Revenue | xxxx | xxxx | xxxx | 26.9% |
| Rest of South America Neural Network Market Sales Revenue | xxxx | xxxx | xxxx | 25.7% |
| Middle East Neural Network Market Sales Revenue | xxxx | xxxx | xxxx | 26.9% |
| Egypt Neural Network Market Sales Revenue | xxxx | xxxx | xxxx | 27.2% |
| Turkey Neural Network Market Sales Revenue | xxxx | xxxx | xxxx | 26.4% |
| Rest of Middle East Neural Network Market Sales Revenue | xxxx | xxxx | xxxx | 25.9% |
Neural Network Market is Segmented as below. Particular segment of your interest can be provided without any additional cost. Download the Sample Pages!
The neural network market is rapidly evolving, driven by advancements in artificial intelligence and machine learning technologies. Key drivers include increasing data availability, rising computational power, and growing adoption across various industries such as healthcare, finance, and autonomous vehicles. Neural networks excel in complex data analysis, pattern recognition, and predictive modeling, leading to widespread implementation in real-time applications. Key trends include the rise of deep learning models, increased investment in AI research, and the development of more efficient algorithms. The integration of neural networks into edge computing and IoT devices is also gaining traction. Despite challenges such as high computational costs and data privacy concerns, the market continues to expand, fueled by ongoing innovation and the increasing need for intelligent, data-driven solutions.
In August 2022, NVIDIA's NeuralVDB integrates artificial intelligence (AI) with GPU optimization to enhance interactions with large and complex volumetric data, benefiting professionals in scientific computing, visualization, and related fields. NeuralVDB enables real-time processing and reduces the memory footprint of sparse volumetric data, like smoke and clouds, by a factor of 100. (Source: https://blogs.nvidia.com/blog/neuralvdb-ai/ )
Rising investments in AI research and development are significantly driving the neural network market by accelerating advancements in technology and expanding applications. Increased funding from both public and private sectors fuels innovation, enabling the development of more sophisticated and efficient neural network models. This investment supports breakthroughs in areas such as deep learning, natural language processing, and computer vision. Enhanced research efforts lead to improved algorithms, reduced training times, and greater accuracy in neural networks. Additionally, increased R&D funding helps address current limitations, such as interpretability and scalability, further boosting market growth. As more resources are allocated to AI research, the capabilities and adoption of neural networks continue to expand, driving the overall market forward. For instance, Google AI has introduced GraphWorld, a tool designed to enhance performance benchmarking for graph neural networks (GNNs). This tool enables AI engineers and researchers to evaluate new GNN architectures using larger graph datasets, facilitating innovative approaches to testing and designing GNN architectures.
The growing interest in artificial intelligence (AI) is driving the neural network market as organizations across various sectors recognize the transformative potential of AI technologies. Neural networks, a core component of AI, offer powerful solutions for complex data analysis, pattern recognition, and decision-making. The increasing demand for AI-driven innovations in fields such as healthcare, finance, and autonomous systems fuels the need for advanced neural network applications. As businesses and governments invest in AI to gain competitive advantages, enhance efficiency, and create personalized experiences, the adoption of neural networks rises. This heightened focus on AI encourages continuous development and refinement of neural network technologies, contributing to market growth and expanding their applications in solving real-world challenges.
High computational costs are a significant restraint on the neural network market due to the substantial resources required for training and deploying complex models. Neural networks, especially deep learning models, demand powerful hardware such as GPUs and TPUs, which incurs high expenses. The energy consumption associated with running these models also adds to operational costs. For many organizations, particularly startups and small enterprises, these costs can be prohibitive, limiting their ability to invest in advanced neural network technologies. Additionally, the need for specialized infrastructure and maintenance further escalates expenses. As a result, high computational costs can hinder the widespread adoption and development of neural networks, impacting the overall growth of the market.
The COVID-19 pandemic has had a dual impact on the neural network market. On one hand, the crisis accelerated the adoption of AI and neural network technologies as organizations sought solutions for remote work, healthcare diagnostics, and supply chain management. The increased demand for AI-driven tools and automation during the pandemic drove market growth. On the other hand, the pandemic disrupted research and development activities and delayed projects due to lockdowns and resource constraints. Additionally, financial uncertainties led some companies to defer or scale back their AI investments. Overall, while the pandemic highlighted the critical role of neural networks in addressing urgent challenges, it also posed temporary challenges to market expansion and innovation.
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The neural network market is highly competitive, featuring major players like NVIDIA, Google, and IBM who lead in innovation and technology development. Companies compete through advancements in AI algorithms, hardware optimization, and cloud-based solutions. Strategic partnerships, mergers, and acquisitions are common as firms aim to enhance their technological capabilities and market reach. Emerging startups also contribute by introducing novel applications and specialized solutions, intensifying competition and driving rapid advancements in the neural network sector.
In August 2022, Amazon has introduced new machine learning software designed to analyze patient medical records, aiming to improve treatment outcomes and reduce overall healthcare costs. (Source:https://aws.amazon.com/comprehend/medical/#:~:text=Amazon%20Comprehend%20Medical%20is%20a,prescriptions%2C%20procedures%2C%20or%20diagnoses. ) In May 2022, Intel has unveiled its second-generation Habana AI deep learning processors to enhance efficiency and performance. This launch highlights Intel’s commitment to its AI strategy, offering customers diverse solutions from cloud to edge to meet the increasing demands and complexity of AI workloads. (Source: https://www.intel.com/content/www/us/en/cloud-computing/cloud-technology.html?cid=sem&source=sa360&campid=2024_ao_cbu_in_gmocoma_gmocrbu_awa_text-link_brand_broad_cd_HQ-dcai-cloud_3500231769_google_b2b_is_non-pbm_intel&ad_group=DCAI_Brand_Cloud_Cloud_Broad&intel_term=Intel+Cloud+computing&sa360id=43700079954016837&gad_source=1&gclid=CjwKCAjw3P-2BhAEEiwA3yPhwDerKnGmWu4Ka33TYgsZdgWmBHdrIWeDpQQJZoti3pVBQiq90rSf2hoC4h8QAvD_BwE&gclsrc=aw.ds ) In September 2023, Amazon and Anthropic have formed a strategic partnership to combine their technology and expertise in generative artificial intelligence (AI). This collaboration aims to advance Anthropic’s foundation models and enhance their availability to AWS customers. (Source: https://press.aboutamazon.com/2023/9/amazon-and-anthropic-announce-strategic-collaboration-to-advance-generative-ai )
Top Companies Market Share in Neural Network Industry: (In no particular order of Rank)
| Companies | 2022 (A) | 2023 (A) | 2024 (A) | 2025 (A) |
|---|---|---|---|---|
| NVIDIA Corporation | xxxx | xxxx | xxxx | xxxx |
| Google LLC | xxxx | xxxx | xxxx | xxxx |
| IBM Corporation | xxxx | xxxx | xxxx | xxxx |
| Microsoft Corporation | xxxx | xxxx | xxxx | xxxx |
| Amazon Web Services | xxxx | xxxx | xxxx | xxxx |
| Inc. | xxxx | xxxx | xxxx | xxxx |
| Intel Corporation | xxxx | xxxx | xxxx | xxxx |
| xxxx | xxxx | xxxx | xxxx | |
| Inc | xxxx | xxxx | xxxx | xxxx |
| Salesforce.com | xxxx | xxxx | xxxx | xxxx |
| Inc. | xxxx | xxxx | xxxx | xxxx |
| Baidu | xxxx | xxxx | xxxx | xxxx |
| Inc. | xxxx | xxxx | xxxx | xxxx |
| Amazon Web Services | xxxx | xxxx | xxxx | xxxx |
| Alibaba Group | xxxx | xxxx | xxxx | xxxx |
| SAP SE | xxxx | xxxx | xxxx | xxxx |
| Oracle Corporation | xxxx | xxxx | xxxx | xxxx |
| Hewlett Packard Enterprise | xxxx | xxxx | xxxx | xxxx |
| Qualcomm Incorporated | xxxx | xxxx | xxxx | xxxx |
*List of Second Tier Companies, List of Third Tier/ Start-up Companies (Inquire with sales executive)
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According to Cognitive Market Research, North America holds the largest market share in the neural network market due to its advanced technological infrastructure, high investment in AI research and development, and the presence of major technology companies. The region's strong emphasis on innovation and early adoption of cutting-edge technologies drives significant growth. Additionally, extensive funding for AI projects, a skilled workforce, and robust support for startups and established firms contribute to North America's dominant position in the market.
The Asia Pacific region is growing at the fastest CAGR in the neural network market due to rapid advancements in technology, increasing investments in AI research, and a large, expanding base of tech-savvy users. The region benefits from a growing number of startups and technology firms driving innovation, coupled with supportive government policies and rising demand for AI applications in sectors like healthcare and finance. Additionally, the increasing adoption of digital technologies across various industries fuels the market's rapid growth.
The current report Scope analyzes Neural Network Market on 6 major region Split (In case you wish to acquire a specific region edition (more granular data) or any country Edition data then please write us on info@cognitivemarketresearch.com
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According to Cognitive Market Research, the global Neural Network market size was estimated at USD 15214.20 Million, out of which North America held the major market share of more than 40% of the global revenue with a market size of USD 6085.68 million in 2024 and will grow at a compound annual growth rate (CAGR) of 25.4% from 2024 to 2031.
According to Cognitive Market Research, the global Neural Network market size was estimated at USD 15214.20 Million, out of which Europe held the market share of more than 30% of the global revenue with a market size of USD 4564.26 million in 2024 and will grow at a compound annual growth rate (CAGR) of 25.7% from 2024 to 2031.
According to Cognitive Market Research, the global Neural Network market size was estimated at USD 15214.20 Million, out of which Asia Pacific held the market share of around 23% of the global revenue with a market size of USD 3499.27 million in 2024 and will grow at a compound annual growth rate (CAGR) of 29.2% from 2024 to 2031.
According to Cognitive Market Research, the global Neural Network market size was estimated at USD 15214.20 Million, out of which the Latin America held the market share of around 5% of the global revenue with a market size of USD 760.71 million in 2024 and will grow at a compound annual growth rate (CAGR) of 26.6% from 2024 to 2031.
According to Cognitive Market Research, the global Neural Network market size was estimated at USD 15214.20 Million, out of which the Middle East and Africa held the major market share of around 2% of the global revenue with a market size of USD 304.28 million in 2024 and will grow at a compound annual growth rate (CAGR) of 26.9% from 2024 to 2031..
Conclusion
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I am Aarti Bagekari, worked as a research associate with strong passion for transforming complex information into strategic insights. My strong analytical skills, coupled with a deep understanding of market dynamics and consumer behavior, empower me to identify hidden opportunities and proactively mitigate risks for clients. As a part of team, I possess a skills in data analysis, segmentation, competitive landscape.
Global Neural Network Market Report 2025 Edition talks about crucial market insights with the help of segments and sub-segments analysis. In this section, we reveal an in-depth analysis of the key factors influencing Neural Network Industry growth. Neural Network market has been segmented with the help of its Component, Industry Vertical , and others. Neural Network market analysis helps to understand key industry segments, and their global, regional, and country-level insights. Furthermore, this analysis also provides information pertaining to segments that are going to be most lucrative in the near future and their expected growth rate and future market opportunities. The report also provides detailed insights into factors responsible for the positive or negative growth of each industry segment.
According to Cognitive Market Research, Software Neural Networks are likely to dominate the Neural Network Market over the forecast period. The software component captured the largest market share in the neural network market due to its essential role in developing and deploying neural network models. Software solutions, including frameworks, libraries, and platforms, provide the tools necessary for building, training, and optimizing neural networks. The rapid advancement and wide adoption of these software tools across industries such as healthcare, finance, and technology drive their dominance. Additionally, continuous innovation and updates in software enhance performance and scalability, further solidifying its market leadership.
The services component is growing at the highest CAGR in the neural network market due to increasing demand for specialized support, consulting, and managed services. Organizations seek expert assistance for developing, implementing, and optimizing neural network solutions, as well as for integrating AI technologies into existing systems. The growing complexity of neural network applications and the need for ongoing maintenance and updates drive demand for these services. Additionally, the rise in custom solutions and cloud-based AI services contributes to this rapid growth.
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According to Cognitive Market Research, the BFSI segment holds the largest share of the market. The BFSI (Banking, Financial Services, and Insurance) industry captured the largest market share in the neural network market due to its extensive use of AI for fraud detection, risk management, and customer service. Neural networks enhance capabilities in analyzing large datasets, identifying patterns, and automating complex financial processes. The industry’s high demand for advanced analytics, predictive modeling, and personalized financial services drives significant adoption of neural network technologies, solidifying its dominant market position.
The IT & Telecom industry is growing at the highest CAGR in the neural network market due to the sector's increasing reliance on advanced AI for network optimization, customer experience enhancement, and data management. Neural networks are utilized for improving network performance, predictive maintenance, and personalized services. The rapid expansion of 5G technology and the need for efficient handling of massive data volumes further drive the adoption of neural network solutions, accelerating growth in this vertical.
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Disclaimer:
| Component | Software, Services |
| Industry Vertical | BFSI, IT & Telecom, Aerospace & Defense, Public Sector, Retail, Healthcare, Manufacturing, Energy & Utilities, Others |
| List of Competitors | NVIDIA Corporation, Google LLC, IBM Corporation, Microsoft Corporation, Amazon Web Services, Inc., Intel Corporation, Facebook, Inc, Salesforce.com, Inc., Baidu, Inc., Amazon Web Services, Alibaba Group, SAP SE, Oracle Corporation, Hewlett Packard Enterprise, Qualcomm Incorporated |
Chapter 1 2026 Geopolitical Outlook - Neural Network Market Detailed Analysis
This chapter isn't just about technology; it’s about certainty. We show you how AI is being used in leading industries so you can apply those same 'High-Speed' and 'High-Accuracy' principles to your own market strategy
Chapter 2 AI's Impact on Market - Detailed Qualitative Analysis
This chapter will help you gain GLOBAL Market Analysis of Neural Network. Further deep in this chapter, you will be able to review Global Neural Network Market Split by various segments and Geographical Split.
Chapter 3 Global Market Analysis
Global Market has been segmented on the basis 5 major regions such as North America, Europe, Asia-Pacific, Middle East & Africa, and Latin America.
You can purchase only the Executive Summary of Global Market (2019 vs 2024 vs 2031)
Global Market Dynamics, Trends, Drivers, Restraints, Opportunities, Only Pointers will be deliverable
This chapter will help you gain North America Market Analysis of Neural Network. Further deep in this chapter, you will be able to review North America Neural Network Market Split by various segments and Country Split.
Chapter 4 North America Market Analysis
This chapter will help you gain Europe Market Analysis of Neural Network. Further deep in this chapter, you will be able to review Europe Neural Network Market Split by various segments and Country Split.
Chapter 5 Europe Market Analysis
This chapter will help you gain Asia Pacific Market Analysis of Neural Network. Further deep in this chapter, you will be able to review Asia Pacific Neural Network Market Split by various segments and Country Split.
Chapter 6 Asia Pacific Market Analysis
This chapter will help you gain South America Market Analysis of Neural Network. Further deep in this chapter, you will be able to review South America Neural Network Market Split by various segments and Country Split.
Chapter 7 South America Market Analysis
This chapter will help you gain Middle East Market Analysis of Neural Network. Further deep in this chapter, you will be able to review Middle East Neural Network Market Split by various segments and Country Split.
Chapter 8 Middle East Market Analysis
This chapter will help you gain Middle East Market Analysis of Neural Network. Further deep in this chapter, you will be able to review Middle East Neural Network Market Split by various segments and Country Split.
Chapter 9 Africa Market Analysis
This chapter provides an in-depth analysis of the market share among key competitors of Neural Network. The analysis highlights each competitor's position in the market, growth trends, and financial performance, offering insights into competitive dynamics, and emerging players.
Chapter 10 Competitor Analysis (Subject to Data Availability (Private Players))
(Subject to Data Availability (Private Players))
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
This chapter would comprehensively cover market drivers, trends, restraints, opportunities, and various in-depth analyses like industrial chain, PESTEL, Porter’s Five Forces, and ESG, among others. It would also include product life cycle, technological advancements, and patent insights.
Chapter 11 Qualitative Analysis (Subject to Data Availability)
Segmentation Component Analysis 2019 -2031, will provide market size split by Component. This Information is provided at Global Level, Regional Level and Top Countries Level The report with the segmentation perspective mentioned under this chapters will be delivered to you On Demand. So please let us know if you would like to receive this additional data as well. No additional cost will be applicable for the same.
Chapter 12 Market Split by Component Analysis 2022 - 2034
The report with the segmentation perspective mentioned under this chapters will be delivered to you On Demand. So please let us know if you would like to receive this additional data as well. No additional cost will be applicable for the same.
Chapter 13 Market Split by Industry Vertical Analysis 2022 - 2034
Chapter 14 Neural Network Price Trend Analysis
Chapter 15 Neural Network Import/Export Analysis
Chapter 16 Neural Network Production Analysis
Chapter 17 Gap Analysis
Chapter 18 Strategy Analysis
Chapter 19 Profitability and Gross Margin Analysis
Chapter 20 TAM Analysis
This chapter helps you understand the Key Takeaways and Analyst Point of View of the global Neural Network market
Chapter 21 Research Findings
Here the analyst will summarize the content of entire report and will share his view point on the current industry scenario and how the market is expected to perform in the near future. The points shared by the analyst are based on his/her detailed in-depth understanding of the market during the course of this report study. You will be provided exclusive rights to interact with the concerned analyst for unlimited time pre purchase as well as post purchase of the report.
Chapter 22 Research Methodology and Sources
1 Data Gathering
2 Data Validation
3 Data Presentation
To maintain the integrity of our proprietary methodology and protect our elite expert network, specific source disclosures are reserved for our full-access partners. Our research framework is anchored by a 70:30 primary-to-secondary ratio, ensuring your strategy is driven by real-time market intelligence rather than recycled, publicly available, or AI-generated data. Every deliverable includes an exhaustive source directory and grants your team direct access to our lead analysts for bespoke strategic consultation.
Johns Hopkins researchers have developed a deep learning-based model using lung ultrasonography images to identify COVID-19 infection. The automated detection method could improve emergency department physicians' efficiency in diagnosing patients. The tool was trained using a range of datasets, including 40,000 simulated images, 174 in vivo photos, 958 hand-picked images, and a mix of datasets. The model was tasked with identifying B-lines, bright, vertical picture anomalies that suggest inflammation in individuals with pulmonary problems. The model performed admirably in detecting anomalies connected to COVID-19. The tool's diagnostic potential suggests it could be useful for other illnesses, such as heart failure. Wearable ultrasonography patches that track fluid accumulation and alert patients to medication adjustments or doctor visits could be ideal use cases. However, the application of AI in medical imaging analytics is still somewhat risky, as research from Stanford University, Harvard Medical School, and the Massachusetts Institute of Technology has revealed unpredictable effects on clinical performance.