Machine learning as a service (MLaaS) is an umbrella term for services providing machine learning tools using cloud computing services. The development of business models such as Platform as a service (PaaS), Infrastructure as a service (IaaS) and Software as a service (SaaS) owing to growth of cloud based full-fledged services has led to the advent of machine learning as a service (MLaaS). The global Machine Learning as a Service (MLaaS) Market is expected to grow at an impressive 40% of CAGR between 2016 and 2022.
The growing trend of cloud data storage, greater efficiency, lower cost, benefit of remote access from multiple distributed and connected devices, falling costs of data storage solutions such as disks, and others have created antecedents for the growth of the market. The generation of large amount of data owing to growing social networking, internet usage, bandwidth, internet media content and the growing capabilities of analytics to derive meaningful insights are technical drivers of the market. Outsourcing to third party service providers frees internal in-house resources leading to lean operations, greater returns on investment, relieves development of expertise not present in-house and others which add to the attraction of the market.
Growing data led complimentary industries such as software, business processing, economy of scale and scope allows for lower cost of servicing additional clients which has led to a scramble for cloud space and technologies. MLaaS benefit clients to avail machine learning technologies without incurring the development cost, time and risk of developing in house team. The high market equity of big data such as predictive analytics and deep learning, natural language processing, data visualization, are the added advantages of the market.
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The growing functionality of machine learning as a service such as data visualization, programming interfaces, facial recognition, natural language processing, predictive analytics and deep learning, coupled with growing customization, and growing integration involving mobile application, enterprise information, industrial automation and control, LiDar, and others are driving greater enthusiasm for the market.
High cost of maintenance and the scarcity of trained manpower coupled with the nascent stage of the technology is hampering the growth of the market.
January, 2018 – Google LLC, an American Multinational Technology Company launched a new service which aims at businesses by converting machine leaning as a practical tool. This service is called Cloud Auto ML which aims at enterprises lacking expertise in data science by providing machine learning or AI as service.
December, 2017 – Oracle Corporation, an American multinational computer technology corporation, is integrating machine learning across all of its services through the cloud platform. By offering through cloud it makes self-driving, repairing and securing which helps in saving operational costs. This will benefit Oracle by applying AI and machine learning through all of their services which will help customers by lowering cost, reducing risk and to help in making smarter decisions.
The prominent players in the machine learning as a service (MLaaS) Market are- Google (U.S.), BigML (U.S.), Microsoft (U.S.), IBM (U.S.), Amazon Web Services (U.S.), AT&T (U.S.), Fuzzy.ai (Canada), Yottamine Analytics (U.S.), Ersatz Labs, Inc. (U.S.), and Sift Science, Inc. (U.S.) among others
To generate a comprehensive understanding of the market necessitated by the complexity and the nascent stage of the market, the Machine learning as a Service (MLaaS) market has been segmented by
- Based on components, the market has been segmented by software tools, cloud based APIs, web based APIs, and others.
- Based on applications, the market has been segmented by network analytics, predictive maintenance, augmented reality, marketing and advertising, risk analytics and fraud detection, and others
- Based on organization size, the market has been segmented by SMBs, and large enterprises.
- Based on deployment type, the market has been segmented by cloud, and on premise.
- Based on end user, the market has been segmented by manufacturing, BFSI, healthcare, retail, transportation, government, telecom, and others.
- Based on regions, the market has been segmented by North America, Europe, Asia Pacific, Middle East and Africa.
North America led by the U.S. Accounts for the largest share of the global machine learning as a service (MLaaS) market followed by Europe owing to the rapid uptake of new technology, presence of global players and others. However the market is expected to shift towards the developing regions such as Asia Pacific led by Japan, China and India. The Middle East and Africa market is expected to be dominated by Gulf economies of Saudi Arabia, UAE, Kuwait, and Qatar.
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- Machine learning as a service (MLaaS) vendors
- Resellers and distributors
- Technology investors
- System Integrators
- Government Organizations
- Research/Consultancy firms
- Network solution providers
- Independent software vendors
- Managed Security Service Providers (MSSPs)
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