How Disruptive Technologies Like AI and NLP are Transforming Customer-Oriented Forecasting?

How Disruptive Technologies Like AI and NLP are Transforming Customer-Oriented Forecasting?

Have you ever wondered how the ape who became the first man felt? The feeling probably had been the same as what we feel right now. Sitting in front of black and white CRT technology, our generation wouldn't have thought of living in a world of online streaming media with extremely personalized content. But as they say, "Humanity is about transitions and evolutions by intelligent means", it has become a reality.

Does it ever hammer your brain that how Facebook, YouTube and others know our preferences so well? How come these brands are able to provide us with such personalized original content?

Beyond the build-up, the answer is unpretentious – It's all possible by virtue of Artificial Intelligence (AI). The intimations of AI and the acceleration of algorithms have never been too relevant, too crucial, or too complex yet interesting.

Artificial Intelligence in alliance with speech recognition and weighed outcomes, identify customer's preferences and even senses the subscriber's behavior and time coordination. The technology of AI/ML is well versed in learning from patterns that subscribers show in their behavior over time and offering personalized contents recommendations accordingly.

Also, Natural Language Processing (NLP) and Semantics Analytics have taken this adventure to a whole next level. NLP is a form of AI that analyses human language. The core of its technology helps machine understand and even communicate with human speech. For example, Alexa and Google Assistant using Hidden Markov Model (HMM) system translate our words into text which then becomes usable by the NLP system. Precisely, HMM listens to 10 to 20-millisecond clips of voice and looks for phonemes to compare with a pre-recorded speech.

If we are breaking down NLP and HMM, it would be really unfair to leave semantics analysis unnoticed. This branch of analytics is closely related to NLP and helps in forming the spunk of it. Semantics analysis aids the logical interpretation of human sentences using NLP AI. After HMM breaks down the speech into simplest form semantic analysis helps in integrating the pieces and add logical meaning to the content.

Here, quoting an example of one of the leading online streaming media, we can say that, Netflix is not just a trade of entertainment and media but an AI-driven success story of planet comprising of clicks, views and ratings.

In other words, we can say that Netflix is launching original content as it is well aware of what people want before they do. Tracing the timeline of Netflix content, it took them more than five years to get into the analytics of customer data to device a presentation like 'House of Cards' that earned worldwide success. Algorithms, big data, and gut instincts combined with AI are the secret ingredients of the prosperity of Netflix.

Likewise, Amazon as a leader in user experience innovation has reshuffled the organization in orbit of AI and machine learning technologies. Amazon's secret sauce in its approach to AI is flywheel. Technically, flywheel is a mechanical device specifically designed to efficiently store rotational energy aiming at the time when a machine isn't working at a constant level.

With the advancement of AI and analytics, landing up with firm decisions and performing tasks requiring human intelligence, has become more efficient. AI and ML are the core of Amazon's customer-oriented forecasting on steroids and tabloids and its kick to prune minutes and seconds in rush of demand and supply practice.

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