LOS ANGELES, Feb. 05, 2020 (GLOBE NEWSWIRE) -- The global machine learning market is anticipated to grow at a CAGR of around 40.1% over the forecast period 2019 to 2026 and reach the market value of around US$ 76.8 Bn by 2026.
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North America accounted for the maximum share of the market in 2018. This can be attributed to the presence of the number of banking organizations, investment in machine learning-based firms, and high adoption of next-generation technologies in the region. About 2900 companies are operating in the machine learning market in the U.S. However, the Asia Pacific is anticipated to observe the fastest growth during the forecast period. Increasing adoption of machine learning technology in emerging and developed countries in the region such as India, China, and Singapore, government support for next-generation technologies, and investment by service providers due to the presence of talent base are anticipated to boost the market growth in the coming years. In May 2018, NITI Aayog, a policy think tank of the Government of India, collaborated with Google LLC, a multinational technology company. Through this collaboration, the former company will incubate and train start-ups based on AI in India.
Based on the component, the market has been divided into hardware, software, and services. The software segment accounted for the significant share of the market in 2018 due to the high adoption of cloud-based software. This can be attributed to improved cloud infrastructure and hosting parameters. However, the hardware segment is anticipated to observe the fastest growth rate during the forecast period. This is due to the growing demand for hardware optimized for machine learning, an increasing number of hardware providers, and technological development such as customized silicon chips with machine learning and artificial intelligence capabilities.
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Based on the enterprise size, the global machine learning market is segmented into Small & Medium-sized Enterprises (SMEs) and large enterprises. In 2018, the large machine learning enterprise segment accounted for the largest share of the market. This can be attributed to the capability of investment and focus of large enterprises on connecting machine learning, deep learning, and optimization of decisions to deliver high business value. However, the adoption of machine learning is rapidly growing across small and medium-sized enterprises. This is majorly due to the cost-effective and easy deployment offered by service providers. Furthermore, the availability of options for deployment methods such as on-premise, cloud-based, or hybrid to easily scale-up pilot projects of small and medium-sized enterprises is likely to increase the demand for machine learning from SMEs.
Based on the end-use, the market is divided into healthcare, law, BFSI, advertising & media, retail, agriculture, automotive & transportation, manufacturing, and others. Advertising and media held the largest share of the market in 2018. However, healthcare is anticipated to observe significant growth and is expected to surpass advertising & media during the forecast period. This is due to broadening the application of machine learning technology in the healthcare industry such as the use of technology for better diagnosis and predicts the probability of death of the person. The law segment is witnessing the fastest growth in the coming years.
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Key players operating in the machine learning market are Baidu Inc.; Amazon Web Services, Inc.; FICO, Google Inc.; H2O.ai; International Business Machines Corporation; Intel Corporation; Hewlett Packard Enterprise Development LP; SAS Institute Inc.; Microsoft Corporation; Predictron Labs Ltd., and SAP SE.Some of the start-ups in the machine learning industry are DataRobot (Predictive analytics), Benevolent AI (Pharmaceuticals), Pony.ai (Autonomous vehicles), and SenseTime (Facial recognition). Partnerships or collaborations of service providers with end-use industries and focus on launching innovative products are the key strategies adopted by market players to expand their geographical reach or customer base.
Some of the key observations regarding the machine leaning industry include:
- In January 2020, the New York Institute of Finance and Google Cloud launched new machine learning for Trading Specialization. The Specialization is suited for analysts, those involved in investment management or portfolio management, day traders, and anyone interested in constructing effective trading strategies using machine learning. A new trading specialization available exclusively on the Coursera platform.
- In January 2020, Udacity launched a new Nanodegree program called Intro to machine learning with TensorFlow. The course includes advanced areas such as supervised and unsupervised learning, manipulating data, and deep learning and introduces learners to fundamentals of machine learning. TensorFlow is a deep learning framework, developed by Google, which is widely used for creating machine learning models.
- In May 2019, Microsoft launched three new services to simplify the machine learning process. This range of interface completely automates the process of creating models, training and deploying models, and to a new no-code visual interface for building to host Jupyter-style notebooks for advanced users.
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