Abstract
The terms “chatbot,” “AI chatbot,” and “virtual agent” are used in a way that often does not differentiate between them, which might lead to possible misunderstandings. Despite the fact that the technologies associated with these terms are inextricably linked to one another, the subtle differences that exist between them result in considerable differences in their unique capabilities. The term “chatbot” is often used to refer to a wide variety of artificial intelligence systems that are designed to carry on conversations. The development of artificial intelligence chatbot software has resulted in the creation of virtual agents, which constitutes a significant step forward. These agents participate in conversation via the use of AI methods known as conversational AI, and they make use of deep learning algorithms in order to improve their performance over time. This chapter discusses the differences between chatbots, AI chatbots and virtual assistants, and other related topics.
TopIntroduction
The phrases chatbot, AI chatbot, and virtual agent are often used in a manner that lacks distinction, leading to potential misunderstanding. Although the technologies associated with these phrases are intimately interconnected, nuanced variations result in significant disparities in their individual functionalities.
The word “chatbot” is widely used to include a broad range of conversational artificial intelligence systems. A chatbot may be defined as any program that emulates human communication, using either classic, inflexible decision tree-based menu navigation or advanced conversational AI technology. Chatbots are ubiquitously present in many communication channels, including phone trees, social media platforms, as well as dedicated applications and websites.
AI chatbots refer to chatbots that use a range of artificial intelligence (AI) technologies, including machine learning for improving answer optimization over time, as well as natural language processing (NLP) and natural language understanding (NLU) for effectively comprehending user inquiries and associating them with particular intentions. The use of deep learning techniques enhances the proficiency of AI chatbots, enabling them to progressively improve their accuracy. Consequently, this advancement facilitates more seamless and natural interactions between people and AI chatbots, minimizing the likelihood of misunderstandings.
Virtual agents represent a progressive advancement in the field of artificial intelligence chatbot software. These agents employ conversational AI techniques to engage in dialogue and utilize deep learning algorithms to enhance their performance over time. Additionally, virtual agents frequently integrate robotic process automation (RPA) within a unified interface, enabling them to directly respond to user intentions without requiring additional human involvement.
To illustrate the differentiations, consider a scenario where a user exhibits curiosity over the weather forecast for the next day. In the context of a conventional chatbot, the user has the capability to use the precise phrase “provide me with the meteorological forecast.” According to the chatbot's prediction, there is a forecast of precipitation in the form of rain. The user has the ability to inquire about the weather forecast for the next day using an artificial intelligence chatbot. The chatbot accurately predicts that there will be precipitation in the form of rain. By using a virtual agent, the user has the capability to inquire about the meteorological conditions for the next day by posing the question, “What is the anticipated weather forecast for tomorrow?”. The virtual agent has the capability to not only forecast precipitation for the next day, but also propose the adjustment of an earlier alarm time to accommodate any delays caused by rain during the morning commute.
Artificial Intelligence (AI) and Machine Learning (ML) have become crucial components inside several enterprises. By using an AI chatbot or AI virtual assistant, businesses have the potential to enhance their income, save expenses, and cultivate a superior customer support encounter. The increasing popularity of virtual assistants and chatbots is to be expected. These entities exhibit a high degree of similarity. The primary distinction between a chatbot and a virtual assistant is in their respective design and intended functions.
Virtual assistants are designed to handle a diverse range of demands, while chatbots tend to have a narrower focus in terms of the services they provide. Both contribute to the enhancement of personalized support. Assistance with daily duties, in addition to providing support in functioning as a secondary individual, liberates individuals from monotonous and repetitive responsibilities.
This chapter discusses the key differences between Chatbots, Virtual assistants, AI virtual assistants, and AI chatbots, and their features. Also, discussing how each type of them benefits businesses. The main topics to be covered in this chapter includes the following;
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Key Differences Between Chatbot and Virtual Assistant and intelligent virtual assistant and AI chatbot
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What Are the Features of a Chatbot?
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What Are the Features of Virtual Assistants?
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What are the features of AI chatbots and AI virtual assistants?
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Technologies behind AI chatbots
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The technologies behind AI virtual assistants and their types
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Components of chatbots and virtual assistants
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Systems used with Virtual assistants
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Most famous AI Chatbots
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Chatbot or Virtual Assistant or AI chatbot: Which one is suitable for a Business?
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Ethical issues related to Chatbots and Virtual assistants
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The Future of Service Support Industry
Key Terms in this Chapter
Robotic Process Automation (RPA): A software technology that makes it easy to build, deploy, and manage software robots that emulate humans’ actions interacting with digital systems and software.
Interactive Voice Response (IVR): An automated telephone system that combines pre-recorded messages or text-to-speech technology with a dual-tone multi-frequency (DTMF) interface to engage callers, allowing them to provide and access information without a live agent.
Analog-to-Digital Converter (ADC): Used to convert an analog signal such as voltage to a digital form so that it can be read and processed by a microcontroller.
Multilayer Perceptron (MLP): A misnomer for a modern feedforward artificial neural network. This network comprises fully connected neurons that use a non-linear activation function. It is structured with a minimum of three layers and is particularly noteworthy for its capability to discern non-linearly separable input.
Application Programming Interface (API): A set of defined rules that enable different applications to communicate with each other.
Natural Language Generation (NLG) Chatbots: When a user engages with a chatbot, the chatbot utilizes its natural language generation (NLG) model to provide a response that is pertinent to the user's inquiry.
Client Relationship Management (CRM): The amalgamation of methodologies, tactics, and technological tools used by organizations to efficiently manage and scrutinize client interactions and data throughout the whole customer journey.