More and more businesses are beginning to appreciate chatbots. The ability of AI chatbots to mimic human conversations and provide instant digital connection has paved their way to success. Modern chatbots handle online requests 24/7, create brand engagement, reduce human errors, and save costs of customer service. Apart from that, chatbots particularly appeal to "speedy" Millennials by keeping them constantly "updated." Business giants such as Sephora and Marriott already see the benefits of using chatbots.

Artificial Intelligence has already proven to be able to change our lives in a better way by making things much easier for us. Businesses have taken notice and are constantly trying to leverage the latest technologies not only to increase their performance but also to stay competitive. Every business has a customer and practically every customer has a choice and in 100% of situations, they tend to choose what's easier for them. So when it comes to deciding about a company offering some service or a product, the one demanding fewer efforts from the customers will appear more tempting for them. Being there for the customer when the time's right is one of the most important key factors leading to the deal with a client.

Customer interaction and channels preferences have experienced significant changes over time and are constantly evolving and expanding across all industries, including banking. To consolidate customer satisfaction and cultivate customer advocacy, banks must endeavor to continue to meet these changing needs through use of innovative and progressive technology. Self-service banking interactions with technology were first introduced to customer's through implementation of ATMs, marking the advent of self-service banking. For staff, their introduction to the digital age began with some employees using text terminals that provided the first user experience with computing, though these character interfaces lacked intuitive design and required training. Channel options for customers experienced further expansion with availability of phone banking in the 1980s, while staff started using graphical windows screens.

At their core, internet forums like Reddit work because they are centered around a democratic ideal. The content that makes the front page is whatever is most liked by the community. In theory, each website user has one vote and majority rule decides what content wins and what content loses. However, as malcontents run bots on sites like Reddit (as well as Instagram, Facebook, and Twitter), the process that makes these websites great is being tested. As a single user votes 150 times or automates thousands of comments to shift public opinion, the democratic procedure becomes eroded.

The advancement in technology and evolution of artificial intelligence have developed what today is called Chatbot. Chatbots started to make an appearance in 2011 as artificial intelligence combined with messaging platforms as a way of supporting companies interacting with their customers. I have personally started using chatbot as a consumer and I absolutely love it! Such a quick and engaging dialogue that really sounds real. But what is a chatbot?

Chatbots can handle patient records as well as receptionist duties. A friend o mine, John, came over for dinner the other day. He is an osteopath: for those who don't know, an osteopath is a highly trained health professional who uses manual therapy to fix anything going wrong in your body. Think a hybrid of chiropractor, massage therapist and physio and you are nearly there. Over the spicy asparagus soup John said, 'I've read a couple of those articles you published about chatbots (We need a chat-a–bot healthcare, and, Cashbots; Chatbots are making interactions with banks a genuine pleasure), and they are interesting but chatbots are not relevant for a small business like mine, are they?' 'Well hang on,' I said. 'Do you employ a receptionist?

By "higher-level" they mean higher abstraction level, which is what we're after. So we have our 7 lines of code for a multi-layer neural net. This is magnificent -- 5 lines of code to define our neural net structure (input 2 hidden output regression), 2 lines to train it. Our notebook code is here. Let's go through this in detail, you'll notice that the data and learning intent is identical to our earlier example.

The chatbot represents a booming trend in online interaction, helping to provide information quickly to customers, and for users to get straight to the point without the need to hang on to a hold message or scour a FAQ page for information. While chatbots maybe a boom area for companies, they don't just pop into existence fully-formed, although it is possible that people can build a rough example in a few hours. Instead, the chatbot needs to be created and trained based on sets of data. The business will already have much of that data, but it is likely to stored in various unstructured forms. Different types of chatbots handle data in different ways, scripted bots can only offer a limited set of functions or questions and will only accept a narrow range of responses.

It's been said that nostalgia isn't what it used to be, and in the world of technology there's a lot to be nostalgic about! Just over twenty years ago client-server was all the rage, and then the internet arrived and suddenly browser-based systems became the new way to do everything. Then in the mid-2000's Apple coined the phrase, "there's an app for that", which then begat a mad rush to build phone-based apps for everything under the sun. And now, in 2018, all of those things have been usurped by a new UI that will change the technology landscape yet again: chatbots. And, for generation Z or millennials, this is the way they expect to be able to interact with everything.

The NLU component's only job is to extract meaning from user input. In the above example, the user intends to control heating, and 70 and bedroom are the entities required to complete the action suggested by the intent. The entities are dependent on the intent, for example, you would only want a location and a cuisine if the user intends to look up a restaurant, not if the user is asking to add a reminder. These sentences, which the user can express in different ways but have the same meaning for the bot, are called Expressions. Now how does the bot work with all these intricacies of the human language?