Why there is a lot of hype about Artificial Intelligence?

Introduction

 

 

 

 

 

 

 

 

 

 

Artificial Intelligence is a technology that helps businesses effectively gain insights from raw data. AI helps businesses automate their daily tasks, gather sales and customer data, and perform many other operations. It takes the human error out of critical decision-making and helps users understand their data more thoroughly.

It can utilize consumer data to create effective client profiles and enhance revenue. Cost effective decisions based on speed and accuracy can be taken within moments with the help of data analytics, while being subjective and unbiased, and in this way can be utilized for cost reduction against the human resources otherwise would be required for the same effort.

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Machine learning is a branch of artificial intelligence that uses statistical models to make recommendations.

It is a data analytics approach that trains a computer to learn from experience in the same way that people and animals do. It is closely related to computer statistics where it frequently overlaps with it.

How Does Machine Learning Work?

A typical machine learning process involves

  1. Training
  2. Validation
  3. Testing

Several high-level developments continue to draw attention and interest for emerging technology.

Faster decision making: By allowing businesses to process and analyze data more quickly than ever before, machine learning enables rapid – even split-second – decision making. For example, machine-learning-based software trained to identify anomalies in a company’s security environment can automatically detect a data breach instantly and notify that organization’s tech team

Chatbots: When you chat with an AI-based assistant to resolve an issue online, a trained machine learning model is at work, providing automated responses based upon the most appropriate answer for your input. 

Customer retention: Service providers rely on machine learning models to identify customers who may be ready to take their business elsewhere. If you’ve stopped using a credit card and suddenly received an email offer for a lower APR, your credit card provider is likely attempting to boost customer retention with the help of a machine learning-based platform

Medical image processing: For health care companies, machine learning radiology platforms can be trained to identify potential issues in patient X-rays, flagging them as warranting further attention.

Boosting efficiency: The use of machine learning allows businesses to accelerate repetitive tasks and shift human resources to higher value activities. For example, machine learning technology can perform exhaustive document searches in a fraction of the time it takes people to perform scanning and the cross-referencing of tasks.

Video Processing & Analytics:   Video processing techniques will pull out and analyze information from videos, making it easy for people to use.

A video analytics solution can be used by Civil Authorities for Law Enforcement, e.g., Motorists not obeying traffic lights. Security teams monitoring site security, e.g., Notification of intruders.

Conclusion

Starting to think about the uses of machine learning for your enterprise?
The first step is making sure that your machine learning model will be consuming clean data sets – the quality of your data correlates directly with the quality of insight you gain.
Working with large amounts of enterprise data will always come with challenges, but to mobilize your business and outpace competitors, you need to unlock its full potential.
AI is a path to reduce cost, cost though human resources to be able to do the same work.
• Cost in terms of speed
• Decision making faster
• Cost in Directness of decision making

 

 

 

 

 

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Our expert team are proud to be leading the way in global big data consultancy. Get in touch today to find out more information.

Get in touch

Our expert team are proud to be leading the way in global big data consultancy. Get in touch today to find out more information.