Benefits that MNC’s are getting from AI/ML

What is Artificial Intelligence?

Artificial Intelligence is the simulation of human intelligence to the machine that is programmed to act and think like a human mind and copy the behaviour of humankind. Human have some limitations like a human can’t do certain things after a certain limit, can't do calculations as fast as a machine, etc., but using human mind we can overcome this limitation with the help of the machine. Artificial intelligence relies on Machine learning, Deep learning, natural language processing and more.

What is Machine Learning?

Machine Learning (ML) is an application of Artificial Intelligence (AI) that provides systems to learn and predict like humans. The process is very simple, find the pattern in historical data and apply that pattern. ML focuses on the development of computer programs that can access data and use it to learn for themselves.

Machine Learning in Industry

Machine Learning has proved to be a game-changer for many industries. ML techniques have plunged into almost all major industry verticals. Machine Learning with its incredible potential has completely revolutionized the business space.

The machine learning market is expected to grow from USD 1.03 Billion in 2016 to USD 8.81 Billion by 2022, at a Compound Annual Growth Rate (CAGR) of 44.1% during the forecast period, says a report.

Businesses worldwide are leveraging advanced ML techniques and algorithms for scaling their growth and profits. Even big names such as Amazon, Microsoft, Google have begun investing in Machine Learning models.

APPLICATIONS OF MACHINE LEARNING

Here are some applications of ML in business that are being used to solve problems and deliver evident business benefits:

1. Real-time chatbot agents -

One of the earliest forms of automation are chatbots, which have bridged the communication gap between people and technology by allowing people to essentially converse with machines that can then take actions based on the requests or requirements by humans. By offloading mundane tasks to bots, employees can invest their time in doing other value-driven tasks.

Early generations of chatbots followed scripted rules that told the bots what actions to take based on keywords. However, Machine Learning and Natural Language Processing (NLP) ,another member of the AI technology family, enable chatbots to be more interactive and productive. These newer chatbots better respond to user's needs and converse increasingly more like real humans. 

Digital assistants such as Siri, Google Assistant and Alexa, are based on machine learning algorithms, and this technology may find its ways in new customer service and engagement platforms that replace traditional chatbots. Example,

• FACEBOOK CHATBOTS :

Facebook is one of the top ML companies. It is one of the most important aspects of social media platforms. Machine learning Facebook Messenger chatbots have become indistinguishable from humans when chatting via text because they have access to an immeasurable number of customer-related data points and can detect repetitive problems, patterns, and predict user issues. It means that they are perfectly equipped for customer service agent roles and are an invaluable addition to modern business. Facebook's also enabling SME to avail of the advantages by allowing third-party developers to submit a chatbot inclusion in Messenger. So, even if our resources are limited, we can still provide an excellent customer service level leveraging chatbots.

2. Customer recommendation engines -

Machine learning powers the customer recommendation engines designed to enhance the customer experience and provide personalized experiences. In this use case, algorithms process data points about an individual customer, such as the customer's past purchases, as well as other data sets such as a company's current inventory, demographic trends and other customers' buying histories to determine what products and services to recommend to each individual customer.

Here are a few examples of companies whose business models rely on recommendation engines:

• NETFLIX :

A well-known deployer of this machine learning application is Netflix, the streaming entertainment service, which uses a customer's viewing history, the viewing history of customers with similar entertainment interests, information about individual shows and other data points to deliver personalized recommendations to its customers.

• YOUTUBE :

Online video platform YouTube uses recommendation engine technology to help users quickly find videos that fit their tastes and their searches. The machine leaning algorithm of YouTube will match our term with the Meta data created by audio and video content

• PINTEREST :

Pinterest has attracted a large number of people surfing for the preferences. It is a machine learning automated system of a commercial application that allows specific content searching and recommendations. The main function of Pinterest is to curate the content. Thus, Machine Learning is the best technology that the company can opt for in order to make the process more effective.

3. Image classification and image recognition -

Businesses are also taking the help of Machine Learning, Deep Learning and Neural Networks (sets of algorithms designed to recognize patterns) to make sense out of images. This machine learning technology has wide application, from Facebook's desire to tag photos posted on its site, to security teams' drive to identify criminal behavior in real time, to automated cars' need to see the road.

Retailers also have a number of applications for image classification and image recognition, including the following:

• Equipping robots with computer vision and machine learning to scan shelves to determine what items are less, out of stock or misplaced.
• Using image recognition to ensure all items are removed from shopping carts and scanned for purchase, thereby limiting unintentional loss of sales.
• Combating unsafe conditions by analyzing visuals to detect workplace safety violations, such as unauthorized use of dangerous equipment.

With its endless advantages, Machine Learning is surely here to stay. Leverage ML benefits in businesses to enhance sales profits. The power of ML helps the business work in a more smarter and efficient way.

“We are entering a new world. The technologies of machine learning, speech recognition, and natural language understanding are reaching a nexus of capability. The end result is that we’ll soon have artificially intelligent assistants to help us in every aspect of our lives.” -Amy Stapleton.

Hope this article was useful and helps you understand the widespread scope of Machine Learning in these industries!

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