Increasing use of technology and automation aids drive the growth of Machine Learning Industry 2023 – 2030

 Machine Learning Industry| Forecast 2030

Machine Learning Industry Data Book - Machine Learning, Deep Learning, Natural Language Processing Market Size, Share, Trends Analysis, And Segment Forecasts, 2023 – 2030

 

The machine learning market was valued at 25.58 billion in 2021 with a CAGR of 35.6% during 2022-2030. Deep learning market and natural language processing market are also expanding with a CAGR of 34.3% and 41.3% respectively. 

 

Access the Global Machine Learning Industry Data Book, 2023 to 2030, compiled with details like market sizing information & forecasts, competitive benchmarking analyses, macro-environmental analyses, and regulatory & technological framework studies

 

Deep Learning Market Growth & Trends

The global deep learning market size is expected to reach USD 526.7 billion by 2030, expanding at a CAGR of 33.5% from 2023 to 2030, according to a new report by Grand View Research, Inc. Deep learning is expected to gain sustainable momentum in the coming years owing to its high computational ability and improved complex data-driven applications. The growing emphasis on big data analytics and the adoption of Artificial Intelligence (AI) in customer-centric services is expected to propel the growth of the deep learning industry over the forecast period.

 

AI has evolved rapidly in recent years, enabling machines to perform cognitive tasks effectively. The adoption of AI across various sectors has unlocked numerous potential opportunities for machine learning and deep learning applications. Furthermore, AI-as-a-service such as virtual assistants has allowed smaller organizations to implement AI algorithms required for deep learning applications without a large capital investment. Moreover, the availability of a large amount of data and the need for high computing power encourage SMEs and large enterprises to invest significantly in deep learning technology.

 

Deep learning allows the machine to solve complex problems even if the data is not well organized. A deep learning algorithm performs a task repeatedly, every time tweaking it to improve the outcomes. Thus, the more the task performed by the machines, the better will be the outcome. As a result, large amounts of unstructured data can be analyzed using deep learning algorithms and further deployed to obtain relevant insights for a more reliable decision-making process. For instance, organizations may use deep learning technology to unveil any data pointers between industry insights, social media conversation, and a stock price of a given organization.

 

Image and voice recognition are some of the leading applications in the deep learning industry. Several online and offline services such as Alexa virtual assistant by Amazon, Microsoft Cortana, and Siri use deep learning to acquire language skills while interacting with people. Facebook and Google have implemented deep learning technology for cognitive image analysis in their image classification application. It helps companies provide relevant results and automatic descriptions related to images.

 

Besides, deep learning algorithms can recreate a black-and-white image in color, offering impressive and accurate results in image colorization applications. For instance, In June 2019, Amazon introduced a new deep learning model called Alexa Conversations to create natural voice experiences on Alexa.

 

Deep learning offers lucrative investment opportunities for vendors due to the technology's high adoption rate. As a result, the companies consider product development as one of the strategic initiatives to capture the deep learning industry share. Recently, in February 2020, Google Inc. announced the launch of Reformer, an updated version of the transformer deep-learning model. In February 2020, Concentrix Corporation launched the deep learning algorithm tool for cybersecurity applications.

 

Order your copy of the Free Sample of “Machine Learning Industry Data Book - Machine Learning, Deep Learning, Natural Language Processing Market Size, Share, Trends Analysis, And Segment Forecasts, 2023 – 2030” Data Book, published by Grand View Research

 

Natural Language Processing Market Growth & Trends

The global natural language processing market size is estimated to reach USD 439.85 billion by 2030, expanding at a CAGR of 40.4% from 2023 to 2030, according to a new study by Grand View Research, Inc. Machine learning is predicted to play a critical role in natural language processing (NLP) techniques, mostly in text analytics, as AI advances. In the future, unsupervised and supervised learning will enable machine-learning engines to undertake more in-depth assessments. According to their ongoing evolution, social media platforms are expected to play a superior role in business decisions. A company, for instance, can rely on several NLP tools to track customer evaluations, feedback, and comments about their business on social media platforms and in the news around the time of a quarterly report.

 

Factors such as increased usage of smart devices to facilitate smart environments boost market growth. Additionally, the demand for NLP technologies is expanding owing to the rising demand for sophisticated text analytics and increasing internet and connected device usage. In addition, NLP-based apps are increasingly being used across industries to enhance customer experience. Additional profitable market expansion potentials are anticipated due to rising healthcare sector investments. However, constraints in the development of NLP technology utilizing neural networks and complexity associated with the use of code-mixed language during the implementation of NLP solutions constrain the use of cloud-based services, which can create hindrances for market growth.

 

Companies with huge amounts of spoken or unstructured text data can effectively discover, collect, and analyze dark data issues to the growing pragmatic application of NLP. The usage of NLP is anticipated to increase in areas like semantic search and intelligent chatbots that need to comprehend user intent. The abundance of natural language technologies is expected to endure to shape the communication capability of cognitive computing and the expanding utilization of deep learning and unsupervised and supervised machine learning. Intelligent data for businesses to develop plans, NLP is essential for tracking and monitoring market intelligence reports.

 

Natural language processing is gaining popularity in the healthcare sector due to the search, analysis, and understanding of massive volumes of patient data. Machine learning in healthcare and NLP technology services can extract pertinent concepts and insights from data previously thought to be buried in text form using advanced medical algorithms. In healthcare media, NLP can effectively give voice to unstructured data, providing great insight into understanding quality, enhancing processes, and increasing patient outcomes. For Instance, In July 2022, Google released a free tool called AutoML Entity Extraction for Healthcare, which is also low-code for healthcare professionals with limited coding expertise. Moreover, it is used to develop Healthcare Natural Language models customized to derive more specific information from medical data, which helps understand more essential details in medical records.

 

North America is one of the most important marketplaces for natural language processing owing to the early adoption of advanced technologies in the countries from the region. The U.S. has an advantage in innovation because it is home to the majority of the key vendors in the industry. Additionally, the regional governments are promoting AI, ML, and NLP technologies, creating a favorable environment for market vendors to increase their presence in the region.


Competitive Landscape

Key players operating in the machine learning industry are –

  • Advanced Micro Devices, Inc.
  • Amazon Web Services, Inc.
  • Apple Inc.
  • ARM Ltd
  • Atomwise Inc.
  • Baidu Inc.
  • Clarifai Inc.
  • Enlitic Inc.
  • Google LLC
  • AI

 

Grand View Research’s machine learning Industry data book is a collection of market sizing information & forecasts, regulatory data, reimbursement structure, competitive benchmarking analyses, macro-environmental analyses, and regulatory & technological framework studies. Within the purview of the database, all such information is systematically analyzed and provided in the form of presentations and detailed outlook reports on individual areas of research.

 

 

Check out more Industry Data Books, published by Grand View Research

 

About Grand View Research

Grand View Research, U.S.-based market research and consulting company, provides syndicated as well as customized research reports and consulting services. Registered in California and headquartered in San Francisco, the company comprises over 425 analysts and consultants, adding more than 1200 market research reports to its vast database each year. These reports offer in-depth analysis on 46 industries across 25 major countries worldwide. With the help of an interactive market intelligence platform, Grand View Research helps Fortune 500 companies and renowned academic institutes understand the global and regional business environment and gauge the opportunities that lie ahead.

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