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Showing posts from December 29, 2016

Machine learning, as the method of choice for natural language processing, speech recognition, computer vision and more

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For many analysts, Machine learning is the method of choice for developing software for disciplines like natural language processing, speech recognition, computer vision, and robot control. 


The technologies is now billed as 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.

The emergence of the Machine-Learning-as-a-Service (MLaaS) model

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One can easily observe that, the emergence of the Machine-Learning-as-a-Service (MLaaS) model is good news for the entire Machine-Learning 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.
Free trial period to allow users to test the functionalities before fully committing is generally available to streamline experiences.

Machine learning technologies for data analytics

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It is steadily clear that, as enterprises increasingly adopt IoT-based technologies and solutions; more companies are leveraging machine learning technologies for data analytics. 

I can also observe that, with major cloud-infrastructure providers, like Amazon, Google, IBM, and Microsoft, heavily investing in the Machine learning technologies, ABI Research estimates machine learning-based data analytics tools and services revenues to hit nearly $20 billion in 2021 as Machine-Learning-as-a-Service (MLaaS) models take off.

The time for sophisticated modems on smartphones or mobile devices

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In an indispensable dynamic to avoid a negative impact on network performance and function, I can recall that, Operators need to push their handset OEMs to increase adoption of next-generation modems in mobile devices.
As mobile operators rapidly transition subscribers to LTE-Advanced and LTE-Advanced Pro, ABI Research suggests that failure to do this will have a negative impact on network performance and function.


I can also observe that, devices supporting LTE-Advanced networks are more widespread, with almost one in every four LTE smartphones shipped in 2016 expected to be powered by a modem supporting a down link speed higher than 200 Mbps.

According to ABI Research, now that LTE-Advanced services are maturing, the prospects of LTE-Advanced Pro are becoming more pronounced to industry members; notably the use of higher carrier aggregation combinations exceeding three channels, the use of advanced MIMO features and elevation beamforming, as well as the deployment of higher modulation …