Top 8 factors shaping the future of AI, ML, and Big data

“Future is Artificial Intelligence”, this word has a greater impact on technology. Day by day larger IT companies are showing keen interest in developing Artificial Intelligence, Machine learning, and big data technologies. However, these three technologies are interrelated because we generate a large number of data every second, to control this big data generation we have started developing Machine learning algorithms. Artificial intelligence is a subset of Machine learning. We feed data set to the machine that creates an intelligent machine to help human beings. Let us know the factors that are shaping big data, Machine learning, and Artificial Intelligence.

1) Data mining plays an important role:

As we know that we generate 1.7MB of data every second which’s huge. We should control data generation, so most of the tech experts have developed data mining and data cleaning methods. To control this, experts have developed many machine learning algorithms such as cluster, classification, regression, and many more.

2) Data platforms for business growth:

Digital marketing has already started using these platforms, but now a day other businesses also started working on this data platform. They know that using this platform can enable them to serve their customers better. Uber is a great example to serve their customer and grow their business.

3) Using 5G data has a greater impact on Machine Learning:

Data speed, connectivity, and usage are the major factors of using 5G data. This will help in the growth of business and along with the faster transmission of data using sensor IoT capabilities. Office work becomes less repetitive as machine learning picks up the slacks.

4) Unsupervised machine learning process:

Working with a supervised machine learning algorithm is quite normal in recent times. Supervised machine learning algorithms work on using labeled data and structure whereas unsupervised algorithm uses the same technique but with unlabeled data. While working with unsupervised algorithms accuracy level is less compare to supervised algorithms. But using the mapped application you can get accurate outcomes.

5) Internal data platforms have become essential for growth and innovation:

Companies like Lyft and BMW work on internal data platforms to create Machines that produce better results. All they need is a robust, hugely scalable platform that will provide all the workflows.

6) Next-generation computing architecture:

Computing Architecture is a prototype means a set of rules and methods that helps users to work on the functionality and implementation of the computer system. IBM has come up with developing cloud computing architecture to merge components and subcomponents to produce elastic machines.

7) Low-cost internet and data scientists’ method:

Many telecommunication companies provide a  large number of data plans for a lower cost. This is one of the major causes to generate a large number of data. We access data on FACEBOOK, GOOGLE, YOUTUBE, And INSTAGRAM. To control these many data generations, data scientists have come up with ideas like data cleaning and data mining methods.

8) Important of capturing and computing real-time data:

This is the process used to define, manipulate, retrieve and transfer data in the data management system. There is a large number of advantages of computing real-time data such as agility, improvement in policies, governances, and data security.

I hope this article may help a few of you, who are interested to learn more about AI, ML, and big data. I love writing, and help people to learn more about technologies.