Data Lake Market Analysis 2024-2033: Size, Trends

The Deep Learning  by The Business Research Company provides market overview across 60+ geographies in the seven regions – Asia-Pacific, Western Europe, Eastern Europe, North America, South America, the Middle East, and Africa, encompassing 27 major global industries. The report presents a comprehensive analysis over a ten-year historic period (2010-2021) and extends its insights into a ten-year forecast period (2023-2033).

Learn More On The Deep Learning  Market:

https://www.thebusinessresearchcompany.com/report/deep-learning-global-market-report

According to The Business Research Company’s Deep Learning , The deep learning market size has grown exponentially in recent years. It will grow from $17.97 billion in 2023 to $25.15 billion in 2024 at a compound annual growth rate (CAGR) of 40.0%.  The  growth in the historic period can be attributed to global investments and funding, adoption in autonomous systems, focus on explainability and interpretability, emergence of generative models, growth of edge computing..

The deep learning market size is expected to see exponential growth in the next few years. It will grow to $100.02 billion in 2028 at a compound annual growth rate (CAGR) of 41.2%.  The growth in the forecast period can be attributed to global economic and geopolitical factors, security and robustness improvements, hybrid and federated learning approaches, expansion into new industry verticals, increasing adoption in healthcare.. Major trends in the forecast period include augmentation of human abilities, quantum computing for deep learning, cross-industry collaborations and open source contributions, hybrid cloud and multi-cloud deployments, enhanced computer vision applications, responsible ai and ethical considerations..

Increasing adoption of cloud-based services is significantly contributing to the growth of the deep learning market. Cloud-based services have advanced significantly, to the point that they can now provide enterprises with the ability to run their whole business through their cloud-based platforms. As a result, businesses are increasingly convinced that transferring their tasks from on-premises to cloud-based frameworks. For instance, according to a report by Harvard Business Review Analytic Services on cloud computing, over 74% of organizations believe that cloud computing gives them a competitive advantage over their competitors. Therefore, the increasing adoption of cloud-based services is expected to increase the demand for the deep learning market during the forecast period.

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The deep learning market covered in this report is segmented –

1) By Product: Hardware, Software, Services

2) By Application: Image Recognition, Signal Recognition, Data Mining

3) By End User: BFSI, Automotive, Telecom and Media, Retail, Manufacturing, Healthcare, Other End Users

Increased use of edge intelligence has emerged as a popular trend in the deep learning market. Edge intelligence, also known as edge Artificial Intelligence (AI), is a blend of AI and edge computing that allows machine learning algorithms to be deployed to the edge device where data is generated. Edge intelligence could give AI to any person or organization, at any time and in any location. For instance, according to the Swiss-based AI tech company, viso.ai by 2025, 80 billion IoT devices and sensors will be online, with over 50 billion connected to the internet, and according to Cisco’s Global Cloud Index by 2021, approximately 850 Zettabytes (ZB) of data will be generated annually outside the cloud, compared to only 20.6 ZB for worldwide data center traffic.

The deep learning market report table of contents includes:

 

1. Executive Summary
2. Deep Learning Market Characteristics
3. Deep Learning Market Trends And Strategies
4. Deep Learning Market – Macro Economic Scenario
5. Global Deep Learning Market Size and Growth

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31. Global Deep Learning Market Competitive Benchmarking
32. Global Deep Learning Market Competitive Dashboard
33. Key Mergers And Acquisitions In The Deep Learning Market
34. Deep Learning Market Future Outlook and Potential Analysis
35. Appendix

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