How Machine Learning Is Boosting MNCs Growth

5 min readOct 20, 2020

We live in the world of big data, artificial intelligence and machine learning. Companies are now becoming curious about the application and benefits of machine learning in business. Many people have heard of ML, but they don’t really know what exactly it is, what business related problems it can solve, and value it can add to the business. A 2016 research shows that by 2020,at least 30% of companies globally will use AI in at least one fragment of their sales processes. And Today business across the globe are leveraging machine learning to optimize their process and boost their revenues and profits.

With Google, Amazon, and Microsoft Azure launching their Cloud Machine learning platforms, we have seen artificial intelligence and ML gaining prominence in the recent years. We all have witnessed ML without actually knowing it. Some of the most common instances are ‘,Gmail recognizes the selected words or the pattern to filter out spam, Facebook automatically tags uploaded images using face recognition technique.

Machine learning helps businesses to improve their performance in many ways.

  • It can help businesses by understanding natural human language.
  • Businesses can use ML to improve the efficiency of logistics and transportation networks.
  • With the help of machine learning, businesses can leverage consumer data to build useful customer profiles, increase sales and improve brand loyalty.
Image by Abdul Rahid

Here are companies that are using the power of machine learning in new and exciting ways

1. Pinterest

Pinterest Engineers use ML to process 150 million image searches per month, helping users to find content that looks like pictures they have already pinned. Also enabling the site to surface more personalized recommendations. It also looks at captions from the previously pinned content and which items get pinned to the same virtual boards. ML touches every aspect of Pinterest’s business operations , from spam moderation and content discovery to advertising monetization and reducing churn of email newsletter subscribers.

2. Twitter

Twitter is a social media platform with millions of monthly active users. Twitter’s in-house engineering team, has turned to the power of artificial intelligence (AI) to enhance the platform’s user experience. Cortex is a group of researchers ,engineer and scientist working together to build state of art machine learning technologies within twitter. In 2016, Twitter purchased Magic Pony Technology to bulk up Cortex, who wants to “build the most advanced AI platform in the world, to apply the most complex AI algorithms to our most challenging datasets, seamlessly.”

Twitter uses ML for tweet recommendations ,Twitter show its users tweet in reverse chronological order. Twitter’s machine learning tech makes those decisions based on our individual preferences, resulting in the algorithmically curated feeds.

3. IBM

IBM has recently launched a broad range of new AI-powered capabilities and services to help CIOs automate various aspects of IT development, infrastructure and operations, IBM Watson AIOps, and Accelerator for Application Moderation with AI.

IBM Watson is a cognitive computing platform originally developed by IBM to answer questions on the quiz show Jeopardy. Watson was built on the company’s DeepQA project, and its advanced question answering (QA) capabilities are now being utilized by IBM and enterprise customers in a variety of applications. Watson platform was developed to take in questions that are expressed in natural language and then utilize algorithms, AI and a wealth of data (Big data) to fully understand the questions and return as precise an answer as possible to the question. Watson has been deployed in several hospitals and medical centers in recent years, where it demonstrated its aptitude for making highly accurate recommendations in the treatment of certain types of cancers.

4. Yelp

Yelp, the platform that connects millions with business reviews and reservations. Since images are almost as vital to Yelp as user reviews themselves, it should come as little surprise that Yelp is always trying to improve how it handles image processing. Yelp’s machine learning algorithms help the company’s human staff to compile, categorize, and label images more efficiently — no small feat when you’re dealing with tens of millions of photos

5. Netflix

Netflix is the world leading television network with over 160 millions subscriber in over 190 countries. Here subscribers enjoy hundreds of millions of hours of content per day, including original series, documentaries and feature films. They invest heavily in machine learning to continually improve our member experience and optimize the Netflix service end-to-end.Netflix innovate using machine learning in many areas where they prototype, design, implement, evaluate, and productionize models and algorithms through both offline experiments and online A/B testing.

personalization has been the most well-known area, where machine learning powers Netflix recommendation algorithms. They are also using machine learning to help shape our catalog of movies and TV shows by learning characteristics that make content successful. Netflix research spans many different algorithmic approaches including causal modeling, bandits, reinforcement learning, ensembles, neural networks, probabilistic graphical models, and matrix factorization.


Machine learning is helping businesses to increase sales and plan for the future.AI-driven software is already being used by some companies to increase efficiency and boost sales. In addition, companies are working with data scientist to build custom software that analyzes consumer data to improve sales and increase customer loyalty.AI-driven personal assistants are already helping corporate employees save time and increase the quality of their work.

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