How AI and Machine Learning help build a Smart City?

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When hearing ‘AI for Customer Service’ most would immediately think this is going to be ‘yet another article about chatbots’. No wonder. Chatbots have been one of the hottest topics recently. However, our experience shows that AI can be applied to many other areas of Customer Service business as well. And those possess even more potential to boost your business.

Best Customer Service Chatbots To Relieve 20-30% Of The Load

As the hottest topic in 2017, AI support bots were expected to be a game changer. And even though the ebullience faded a bit when it became clear that even best customer service chatbots still have a lot to learn, a properly designed and trained chatbot can substantially relieve the load on 1-st line support.

As statistical data show, 87% of chatbot users worldwide consider them efficient or very efficient in resolving issues.

As you see AI and ML benefits for customer service are already obvious. AI and ML are definitely changing the rules of the game in the customer support industry and the use of AI/ML technology in this industry will only grow.

However, AI and ML are rather additional tools, which can amplify but not replace traditional customer service automation software and savvy approach to automation. No matter how intelligent your systems are – they are just the reflection of your organization and your processes, which should never be neglected.

In today’s world, Machine Learning has become the most influential and powerful technology.

Machine learning is the process of giving training to computer systems about how to make accurate predictions when fed data.

Software engineering combined human-created rules with data to create answers to a problem which are Traditionally but machine learning uses data and answers to discover the rules behind a problem.

When we google something or listen to a song, watch video on youtube, take a photo.

Eliminating Manual Tasks : Duplication of data is the biggest dispute faced by the business today.

If any organization is using machine learning for their business than its simply end entry tasks and its incomparable accuracy saves both money & time.

Golden is mapping human knowledge by using AI and ML to make the world's first self-constructing encyclopedia.

Check canonical knowledge about Engineer.ai wiki.

By covering this paper, we are going to give details about such technologies in the easiest way so then a layman would also simply understand the variance among these technologies.OverviewThe term Artificial-Intelligence (AI) is a widely used technology about its app in the actual world, though ultimately, Artificial-Intelligence refers to “creating machines intellectual”, so that these machines would take few of the decisions at their level according to the circumstances with no need of any person.

It is known as a subcategory of Artificial Intelligence which focus is on a limited variety of activities.

It utilizes several methods from numerous fields such as arithmetic, machine-learning, computer software design, arithmetical modeling, data-engineering and imagining, pattern acknowledgment and knowledge, uncertainty demonstrating, data warehousing, as well as cloud computing.

The focus of Machine-learning is on allowing a set of rules to take knowledge from the given data, collect insights, and make guesses on previously un-analyzed data utilizing the info that is being gathered.

Strengthening machine-learning procedures interrelate with the surrounding by making actions and so evaluate faults or rewards.

For instance, to recognize a game of chess a Machine Learning algorithm would not evaluate a person moves than would learn the game in one piece.Artificial-Intelligence (AI) – What is it?The term Artificial-intelligence talks about the reproduction of a human brain's role with the help of machines.

AI, IoT, Big data & Cloud are not just new technologies but they are becoming the new norm in Industry.

The customer is expecting a unique and personalized experience that can only be possible using these technologies.

If you are falling behind in adoption, then your competitor has a clear advantage.Artificial intelligence has made it possible to perform certain tasks in a fraction of time, saving a lot of human effort.

Applications are enormous from analyzing hours of endoscopy videos in minutes to find cancer cells to recognizing faces from millions of databases.

Things like 100% inspection are a reality now and can ensure defect-free products, saving enormous costs of quality.Get more details from here.

Like every other industry, data has also been the core of the insurance industry.

Over the due course of time, what actually has changed is the amount of data and the speed at which machines are processing it for driving useful insights.

Data-driven insights play a vital role in boosting this industry by making decisions based on facts, figures, and user patterns.

Insurance providers adopt Artificial Intelligence (AI) & Machine Learning (ML) technologies to enhance the end-user experience, develop improved solutions for increasing operational efficiency, and build accurate underwriting models.Defining Machine LearningMachine Learning is an application of Artificial Intelligence technology that allows computer systems to deploy algorithms for learning and improving my experience.

Such algorithms are used for building mathematical models which can be used as training data, allowing systems to make decisions & predictions.AI & ML in Insurance IndustryAI and ML technologies make it easier for insurance providers to use the data at their desired pace and way.

Many organizations in this industry have access to data that is usually structured and stored in databases.