Between 2013 and 2017, machine learning patents grew at a Compound Annual Growth Rate of thirty-four percent and had featured as the third faster-growing category of all patents granted. A forecast by International Data Corporation (IDC) indicates that spending on artificial intelligent (AI) and machine learning (ML) will grow from twelve billion dollars in 2017 to about fifty-eight billion dollars in 2021. A prediction by Deloitte Global also shows that the number of machine learning pilot and implementations will double in 2018 compared to 2017, and double again by 2020.
Coupled with a lot of other fascinating insights are the latest series of machine learning market forecasts, project ions, and market estimates. Machine learning’s potential impact across many of the world’s most data-prolific industries continue to fuel venture capital investment, private equity funding mergers and acquisitions all focused on winning the race of Intellectual Property and patent in this niche.
The development of custom chipsets is one of the fastest growing areas of the machine learning Intellectual Property (IP). There is a prediction that up to eight hundred thousand machine learning chips will be in use across global data centers this year. A lot of enterprises are increasing their investments, research, and projections of the machine learning program in 2018. Market estimates, forecasts, and projections all reflect how machine learning is improving the acuteness and insights of companies on how to grow faster and more profitably while the methodologies across these many sources.
Here are some key facts from the collection of machine learning market forecasts, market estimates, and projections.
Predictions of the growth of machine learning by Business Intelligence (BI) and analytics market and Data Science platforms that support learning.
Within the Business Intelligence and analytics market, Data Science platforms that support machine learning are predicting that the patents will grow at a Compound Annual Growth Rate (CAGR) of thirteen percent through 2021. Data Science platforms will outperform the broader Business Intelligence and analytics markets, which is predicted to grow at the eight percent CAGR in the same period. It shows that Data Science platforms will rise in value from three billion dollars in 2017 to about five billion dollars in 2021.
Machine learning is the third fastest growing category of all patents granted
Between 2013 and 2017, machine learning patents grew at a thirty-four percent CAGR making it one of the fastest growing category of all patents granted. Facebook, Google, IBM, Microsoft, Fujitsu, Intel and LinkedIn (not in ranking order) were of the seven biggest machine learning patent producers in 2017.
Most companies now use machine learning and artificial intelligence.
About sixty-one percent of organizations most frequently pick machine learning and artificial intelligence as their company’s most significant data intuitive for next year. More than half of these companies indicating that they actively use machine learning and artificial intelligence stated they ran models in production.
Top tech market leaders in machine learning and artificial intelligence
Companies like Apple, Tesla, Google, Amazon, and Microsoft are the leading in the sector of machine learning and artificial intelligence by an extensive margin in investment. Each is designing machine learning into future generation products using machine learning and artificial intelligence to improve customers’ experience and also improve the efficiency of selling channels.
Machine learning and artificial intelligence are attracting more investments
An estimate made by McKinsey shows an annual external investment in artificial intelligence increased from eight billion dollars to twelve billion dollars in 2016 alone and machine learning alone attracting sixty percent of that investment. Robotics and speech recognition are two main areas where most investments are made in machine learning. A lot of investors favor machine learning startups due to quickness code-based start-ups have at scaling up to include new features fast. A lot of software-based machine learning are preferred over their more cost-intensive machine based robotic counterparts.
Amazon relies on machine learning to improve customer experience
Amazon relies on machine learning to improve customer experience in key areas of their business including the recommendation of products, substituting the prediction of products, the detection of fraud, the validation of meta-data and the acquisition of knowledge.
Increase use of data chips in the days ahead
Machine learning (ML) chips used in data centers will grow from the one hundred thousand to two thousands chips run rate in 201 to about eight hundred thousand this year as predicted by Deloitte Global. Field Programmable Gate Arrays (FPGA) and Application Specific integrated Circuits (ASICs) will make up at least twenty five percent. They also found out that Total Available Market (TAM) for machine learning accelerator technologies could potentially reach about twenty six billion dollars by 2020.
Ease in data analysis and insights
About half of the sixty percent of enterprises at varying stage of machine learning adoption say that the machine learning technology has led to more extensive data analysis and insights. A third of them can complete faster data analysis and increased the speed of insight, delivering greater acuteness to the establishment. About thirty-five percent also finds that machine learning is enhancing their R&D capabilities for next-generation products.
Source: https://www.forbes.com/sites/louiscolumbus/2018/02/18/roundup-of-machine-learning-forecasts-and-market-estimates-2018/#74390f702225
Asif Razzaq is the CEO of Marktechpost Media Inc.. As a visionary entrepreneur and engineer, Asif is committed to harnessing the potential of Artificial Intelligence for social good. His most recent endeavor is the launch of an Artificial Intelligence Media Platform, Marktechpost, which stands out for its in-depth coverage of machine learning and deep learning news that is both technically sound and easily understandable by a wide audience. The platform boasts of over 2 million monthly views, illustrating its popularity among audiences.
