Towards Extensively Using Conversational AI

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Conversational AI is actually a group of technologies that allow computers to mimic, process, and behave appropriately in natural speaking, or real-world situations, and is generally used in conjunction with artificial intelligence or intelligent artificial agents (IAIs). These are generally described as natural-language understanding (NLA), or as “artificial intelligence” (IA). NLA refers to a system which can recognize and describe a natural language, as opposed to a machine or program which mimics or interprets something from a source language. On the other hand, artificial intelligence deals more with applications in intelligence research and includes databases, software, and systems which work on previously established principles. These include Deep Learning, Voice Recognition, Natural Language Processing, and Search Engine Optimization.

NLP refers to the process of studying language patterns, learning structures, and syntax. This methodology originated from the study of how humans interact with one another and with language. One of the key elements to all is the notion of “matching” or “comparison” –a concept which is at the heart of all language learning. For instance, if you are trying to teach a dog to sit, it would be more effective to show the dog two similar options, rather than two different options. Similarly, it would be more effective to provide the learner with an example of a particular situation (like sitting on a couch) rather than repeating the same phrase (sit).

Conversational AI refers to the integration of NLP techniques with existing commercial dialog management systems. NLP is based on the idea that we can apply our knowledge and skills to effectively predict and handle the intent behind a user’s words or actions. This is done using the natural language of the user and through the use of heuristics and rules. For instance, if a person were to say, “I’d like a cup of coffee,” and then request me to put the coffee down, I’d expect the person to understand that they want a cup of coffee. Using NLP, we’d then attempt to predict what that person intended by analyzing the underlying grammatical structure of the sentence. If we found that the sentence was grammatically correct, but the meaning was ambiguous (the person being requested to sit didn’t actually mean “sit”), we could simply modify the request so it made more sense.

This is important because it underlines the importance of using conversational AI tools (which are usually based on natural language processing technology) in tandem with existing commercial tools such as appointment books, appointment reminders, voice mail, IM and text messaging programs. These tools enable enterprises to better serve their customers by taking advantage of their natural curiosity and desire to be entertained. If customers feel that the service they are getting is efficient and easy to use, it increases the likelihood that they’ll return. This is especially true when it comes to small businesses that don’t have a large customer base and thus may not rely heavily on traditional channels to promote their business. However, we do see this approach being used for very large enterprises that have a very strong customer base. For instance, Amazon has created its own interactive television channel and has integrated conversational ai into its chat application.

In this case, what happens is that a bot (a pre-trained sales representative or agent) responds to a customer’s inquiry by using the appropriate language technologies. For example, if the customer says they’re looking for a pizza parlor, the bot will use the appropriate natural language technologies such as speech recognition, image recognition and video chat to find a matching business. Then it’ll prompt the user to choose a menu from several options and provide them with the details. The chat experience can be highly customized and tailored to each customer, since it controls the level of interaction a customer has with an agent. In fact, some businesses are able to set up a virtual customer service center where live agents can handle calls and provide answers to customers’ queries remotely. In this instance, it’s much like having a call center for live agents that work from an iPad or iPhone.

However, even these artificially intelligent chats can’t replace the human element of a conversational ai system. Conversational AI will only be able to carry out basic functions such as asking questions. It will never be able to think on its own or provide personalized responses to customer inquiries. Thus, enterprises will need to invest in their own in-house research and development teams to create custom solutions to their customer care needs. They should also incorporate speech recognition technologies to help robots provide more personalized customer service experiences.

What’s also important to an enterprise setting is the question of how conversational commerce at work will affect the way employees and managers communicate with one another. Naturally, businesses want their employees to be efficient, but they also want them to be engaged with the organization. Through NLP, an artificial intelligence system that captures and stores customer information will be able to adapt its behavior to the way people are speaking to it. NLP and other technologies are being used for many purposes in business, from making sales to scheduling meetings. By applying natural language processing to conversational AI systems, businesses will be able to create a more cohesive and professional workforce.

For the foreseeable future, conversational ai applications will continue to evolve and take the technology beyond its current set of uses. Enterprises that implement conversational AI will be able to address business requests using natural language queries that provide relevant and tailored answers. This will provide a great deal of flexibility to businesses while also providing a greater degree of control over how conversations are conducted within their own teams. When conversational as systems become more widely available, they will prove to be a tremendous asset for companies looking to empower their staff members, no matter what the intent of the conversation.

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