As enterprises increasingly adopt IoT-based technologies and solutions, more companies are leveraging machine learning technologies for data analytics. With major cloud-infrastructure providers, like Amazon, Google, IBM, and Microsoft, heavily investing in the technologies, ABI Research estimates machine learning-based data analytics tools and services revenues to hit nearly $20 billionin 2021 as Machine-Learning-as-a-Service (MLaaS) models take off.
“The emergence of the Machine-Learning-as-a-Service (MLaaS) model is good news for the market, as it cuts down the complexity and time required to implement machine learning and thus opens the doors to an increase in its adoption level, especially in the small-to-medium business sector,” says Eugenio Pasqua, Research Analyst at ABI Research. “Most companies also offer a free trial period to allow customers to test the functionalities before fully committing.”
Machine learning is the method of choice for developing software for disciplines like natural language processing, speech recognition, computer vision, and robot control. While in the past, businesses used it to tackle application-specific problems, it is thought to be a building block of a larger system, with many companies developing more ‘general purpose’ tools that can be leveraged across an array of different industries and use cases.
Major cloud-infrastructure providers are investing in the technologies to either acquire or build upon their own machine learning expertise. These providers can provide these capabilities in a cloud-based delivery model, exploiting their own cloud infrastructures to offer APIs that developers can use to quickly and easily embed machine learning capabilities into their applications.
“Solutions built on machine learning automate the IoT data modeling process, removing the labor-intensive and circuitous activities of model selection, coding, and validation,” concludes Ryan Martin, Senior Analyst at ABI Research. “This ‘write once, run anywhere’ mentality has already seen big buy-in from companies like Amazon, Google, IBM, and Microsoft to make advanced analytics more accessible to a broader and more evenly-distributed workforce. This will open the road for widespread adoption of machine learning.”
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