NEWARK, DE / ACCESSWIRE / November 17, 2022 / The global Natural Language Processing (NLP) market stands at US$ 14 Mn as of now and is expected to reach US$ 45 Bn at a staggering CAGR of 23% between 2022 and 2032.
With growing inclination towards digital technology-based software throughout, the demand for Natural Language Processing (NLP) is expected to skyrocket in the forecast period. Along these lines, Apple Inc. plans launching next-gen 5G infrastructure. It has, in fact, announced investing close to US$ 430 Bn for developing 5G for the US economy until the year 2026.
Also, Startup One AI, in May 2022, launched the novel Natural Language Processing technology business. Venture capitalists like Tech Aviv, Ariel Maislos, SentinelOne Inc., and many others have raised close to US$ 8 MN for establishing the company. Future Market Insights has included these facts with future perspectives in its latest market study entitled ‘Natural Language Processing (NLP) Market’.
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Key Takeaways from the Natural Language Processing (NLP) Market
North America holds more than 50% of the market share due to the US being home to the majority of key players.
Europe comes in second with close to 40% of the market share with enterprises increasingly adopting cloud-based services.
The Asia-Pacific is expected to grow at the fastest rate in the Natural Language Processing (NLP) market with countries like Japan being at the forefront regarding the adoption of NLP.
LATAM is expected to grow in Natural Language Processing (NLP) market on the back of Brazil, where more than 20% of the large enterprises are into adoption of ML and AI.
The GCC governments have also seen to it that close to 25% of the companies use NLP for improving the experience of customers.
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SAP SE, in July 2022, did acquire Askdata. The major objective is that of assisting the clientele in making proper choices through AI-driven ‘natural language searches’.
SAP SE, in July 2021, entered into a strategic collaboration with Google Cloud for helping the end-customers in the transfer of critical systems to the cloud, thereby catalyzing the existing systems. ML and Ai are deployed over here.
Inbenta, in June 2021, began a partner ecosystem for working jointly with the enterprise partners who show interest in automation of business processes and reshape the customer service using Artificial Intelligence.
Inbenta, in October 2020, partnered with IntelePeer for providing intelligent workflows to the clients.
Apple Inc., in May 2020, acquired Inductiv Inc. (ML start-up) for enhancing the performance of Siri.
Intel Corporation, in 2020, entered into partnership with China-based Alibaba Group Holding Ltd. and came up with advanced tracking technology backed by AI platform to cater to Tokyo Olympics 2021.
Expert.ai, in November 2020, tabled advanced tools that work towards Advanced Edge AI and application development. It facilitates smoother deployment of AI technology on private, hybrid, or on-premise cloud.
Baidu, in December 2021, launched PCL-BAIDU Wenxin (ERNIE 3.0 Titan). It comes across as the very first knowledge-enhanced multi-hundred-billion model (a pre-training language model having 260 Bn parameters). This model excels at NLG as well as NLU. Apple, in June 2022, announced plans for providing open-source reference PyTorch implementation of Transformer architecture.
“With Google Search, Alexa, Siri, and various others into operation coupled with many technologies on the anvil, the global Natural Language Processing (NLP) market is likely to grow by leaps and bounds in the near future”, says an analyst from Future Market Insights.
How does the report unfold?
The research study is based on technology (auto coding, text analytics, OCR (Optical Character Recognition), Interactive Voice Response, pattern & image recognition, and speech analytics), by type (Rule Based Natural Language Processing, Statistical Natural Language Processing, and Hybrid Natural Language Processing), by service (Integration Services, Consulting Services, and Maintenance Services), by deployment model (on-demand and on-premise), by application (sentiment analysis, data extraction, risk and threat detection, automatic summarization, content management, language scoring, portfolio monitoring, branding and advertising, and HR and recruiting, and by vertical (healthcare, public sector, retail sector, media & entertainment, manufacturing, and others).
With deep learning architectures along with algorithms making noteworthy advances in the field of speech processing and image recognition, the global Natural Language Processing (NLP) market is bound to witness an exuberance in the forecast period.
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Table of Contents
1. Executive Summary
1.1. Global Market Outlook
1.2. Demand Side Trends
1.3. Supply Side Trends
1.4. Analysis and Recommendations
1.5. Global Market: Long-term Strategies for Lucrative Growth
1.6. Global Market Analysis – Key Conclusions
1.7. Key Success Factors
2. Market Introduction
2.1. Market Coverage/Taxonomy
2.2. Market Definition/Scope/Limitations
3. Market Background
3.1. Macro-Economic Factors
3.1.1. Overall Economic Outlook
3.1.2. Global Population Overview
3.1.3. Real GDP Growth
3.1.4. Industry-Value Added Growth
3.1.5. Global GDP by Region
3.1.6. Global Construction Industry Snapshot
3.1.7. Global Automotive Production, by Region
3.1.8. Global Energy Consumption
3.2. Truck and Trailer Production Outlook
3.3. Global Capacity of Refrigerated Warehouses: Overview
3.4. Consumer Spending and Refrigerated Warehouses: Overview
3.5. Global Manufacturing Output Analysis
3.6. Demographic Outlook
3.7. Urban Population Growth Outlook
3.8. India Market Analysis – Key Growth Region
3.9. Forecast Factors: Relevance and Impact
3.10. Value Chain
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