Machine Learning and Artificial Intelligence Applications of the Next Generation

Our developmental stage is very high in progressing towards machine learning and Artificial Intelligence. Many people don’t know how to operate it on a daily basis and it is spreading across every sector and industry.

Many devices such as Siri on iPhone and Google on Android have been the first steps towards this, moving to automated results on Netflix, and many of us don’t know that machine learning Powers up all these systems.

How do Artificial Intelligence and Machine Learning differ?

How do Artificial Intelligence and Machine Learning differ?

Machine learning is a way too advanced, as it gives a computer the ability to learn, and also teaches it how to learn. Whereas AI allows computers to generate the data in large amounts in order to provide conclusions and focuses to copy human behaviour. But both on their own paths turning the faces of human living and also businesses.

What increases as we move forward with AI and ML? 

Imagine walking into a high-end store, with a glass of drink offered by a robot, and getting recommendations on your style without even explaining. If it sounds good, then yes! It’no farther.

Many retailers are planning to move towards the support of Machine Learning and Artificial Intelligence so that it can recognize the face of their clients and clothing sense so that they could suggest.

In Hong Kong, high-end fashion retailer ‘Guess’ has opened up a concept shop based on Fashion based AI at the Hong Kong Polytechnic University. With the help of consumers and designers, the machines will be able to learn and automate.

Customers checked into the store with Face Recognition technology. RFID-enabled mirror offered suggestions.

Credit Card Frauds may decrease. 

Credit Card Frauds may decrease

As consumers lost nearly $6.4 billion in credit card frauds in the past year, it seems like the new tech can recognize a transaction’s fraud or real terminology. AI and ML will enable businesses’ recognition of the ethnicity of the transaction when it’s punched in the machine before it’s completed, which will tend to reduce frauds.

The only fear as of now is that these applications may detect ‘false positives’ while payments. MIT’s Laboratory of Information and Decision Systems is working on it and has currently developed an approach that may help in reducing these false positives by 54 per cent.

The key is that they may be able to find such characteristics that may lead to detecting whether it’s fraud or not.

There could be Smart Data Management taking place in Seconds

Smart Data Management taking place in Seconds

Talking about Data Management it’s duplicate entries have been a task for all kinds of businesses for years now.

When we shop online, we log in and avail a few first-time offers, we purchase items and you’re done. The next time we use the site and don’t find any offers, we just tend to make a new account! It might not be a big deal for us as users. But so many account entries scrambling the minds of data handlers, just imagine the pain!

As per new reports, out of 30 million users, only 3 million seem to be unique users and the rest left have created new accounts, just imagine the amount of headache for them!

With AI and ML this will be possible to leave behind. Background scanning and duplicate entries will help in blocking new accounts from the same users. Automatic matching of user’s data will be happening such as matching the usernames, date of birth, ID proofs, etc.

So far there has only been the same number and email tracing, soon it seems like there will be more. This time taking task will not require human capital.


A new and less costly version is coming in all sectors of the market, the AI and ML-based applications. The next generation will have more efficient operations and better customer satisfaction will be seen. Technology and innovation will lead our paths towards fast functioning.

Disclaimer: This information is covered based on the latest research and development available. However, it may not fully reflect all current aspects of the subject matter.

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