Article

James Warner
James Warner 9 October 2017
Categories Technology

Machine Learning – On Its Way to Revolutionize Digital Transformations

According to the latest predictions, digital transformation is coming of age and becoming a part of major corporate strategies. AI has taken a step ahead and its algorithms are being set to allow machines to learn by reading data sets – without any special programming.

According to the latest predictions, digital transformation is coming of age and becoming a part of major corporate strategies. AI has taken a step ahead and its algorithms are being set to allow machines to learn by reading data sets – without any special programming. Machine learning has grown exponentially due to easy availability of structured and unstructured data, reduced cost of data storage, and the ability to access enormous calculation power using cloud computing. It opens us to a world of unlimited applications and java application development for automated machines from healthcare systems to video games and self-driving cars.

Digital Transformation In Customer Value And Internal Operating Model

The implementation of ML solutions is expected to change an enterprises view on customer value and their internal operating model in the digital arena. It is designed to connect people, business and things in a much planned and intelligent way. New interaction scenarios can be crafted to handle communication between customers and companies to build a modern business environment.

ML To Provide Extraordinary Business Benefits

Customers can use the ML technology to make their decisions faster and pick our best solutions for themselves. It is predicted to help businesses with innovative ideas and support in deriving the right kind of business products/services based on a business model. It has the ability to develop insights beyond human competences, which would enable companies to take timely actions and yield greater benefits out of sales opportunities. Optimized and automated operations will help the business accelerate at a much lesser cost. It will also reduce most of the human error and create a stronger cybersecurity.

ML Technology And Applications In Business

ML is currently divided into two general categories: supervised and unsupervised – both of which need a solid data foundation to work with. It is designed to provide an interactive experience for the users – adapting with the user requirement in the process. It can prove to very useful in providing completely customized health care, to give the patients what they need by anticipating the patients’ conditions. The usage for ML Technology and Applications are varied.

Businesses Should Understand The Distinction Between ML And AI

Machines that will surpass all humans’ cognitive functions and completely replicate them – are still sitting in far-fetched future. However, ML is a reality – where they can mimic human cognitive system functions and solves problems based on their learnings from data analysis. It has the ability to analyze data beyond human capabilities and can respond with human-like emotions.

Implementations of Machine Learning

ML is currently implemented to perform lengthy and repetitive tasks, along with predicting the outcome of new data. Businesses should learn the usage of ML and about its performance range. It can also be used to integrate data gathered from various sources, like customers, partners, and suppliers – creating a usable algorithm for the process. There are various other uses of ML in businesses in the current time, let’s have a look at some of them:

  • Cyber-Security: ML algorithms look for patterns of data access and report anomalies – this help in predicting security breaches.
  • Algorithmic Trading: It is playing an important role in making financial trading decisions at higher speed and accuracy for better profits.
  • Fraud Detection: ML can identify and predict frauds more accurately using its deep learning/artificial intelligence.
  • Chatbots: they help to recognize and understand specific phrases in customer written/spoken requests, and respond accordingly. They improve their accuracy using further information and customer requests, allowing for improved conversations.
  • Language Translation: The AI algorithms examine various translated sentences and provide accurate translations. They are adapting to identifying patterns of speech and analyze them to deliver a natural conversation.
  • Content Generation: ML can generate coherent content using structured and unstructured data.
  • Imaging Analytics: ML can identify in imaging scans quicker than doctors leading to timely and accurate diagnosis.
  • PdM Techniques: Heavy industrial machinery manufacturers are using MLs Predictive Maintenance techniques to predict the machine failures to improve efficiency and avoid costly downtime.

Machine learning is not a new concept but in the recent times, it is started to become the brain of digital transformation. It is expected to become an essential part of our lives in the near future with all its undertakings in the digital world.

 


 

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