Machine based interaction has become commonplace with the proliferation of technology. The global Chatbot market is projected to fetch $1,250 million by 2025. This is leaps and bounds ahead of its $190.8 million figure from 2016. From virtual assistants like Siri and Alexa to automated Customer Support Chatbots, AI Chatbots are rapidly transforming the way we interact with technology. But what exactly is an AI Chatbot, and how does it work? Fret not, for the following blog will list down everything you need to know about AI Chatbots.
Understanding what is an AI Chatbot
Simply put, an Artificial Intelligence Chatbot is a program that simulates conversations with human users. This can range from simple rule-based bots programmed to respond to specific keywords to sophisticated AI-powered bots that leverage Natural Language Processing (NLP) and Machine Learning to understand and respond to complex inquiries in a natural, human-like way.
An AI Chatbot has the ability to read, understand, derive insights, and answer questions pertaining to different topics. Bear in mind that a Chatbot usually responds to questions belonging to a particular topic rather than a bunch of topics. If you train a Chatbot to answer questions on Customer Support, then the Chatbot will answer queries pertaining to Customer Support only. It will not respond to queries regarding any other field or discipline.
Exploring the types of Chatbots
Just like every other piece of technology, Chatbots come in different shapes and sizes, each equipped to handle different tasks. Here’s a list of types based on their complexity and capabilities:
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Rule-based Chatbots: These bots rely on predefined rules and keywords to trigger pre-written responses. While limited in adaptability, they are simple to create and ideal for basic tasks like answering FAQs.
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Retrieval-based Chatbots: These bots access and retrieve relevant information from databases and knowledge bases to respond to user queries. While more interactive than rule-based bots, they struggle with understanding context and nuance.
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Generative Chatbots: Powered by Natural Language Generation (NLG) techniques, these bots can create unique and coherent responses based on their understanding of the conversation. They offer a more natural conversational experience but may lack factual accuracy.
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AI-powered Chatbots: These are the most advanced, leveraging Machine Learning and NLP to understand user intent, sentiment, and context. They can personalize responses, learn from interactions, and offer genuinely engaging conversations.
How does an AI Chatbot work?
Before learning how an AI Chatbot works, we need to look at what constitutes a Chatbot in the first place. The inner workings of an AI Chatbot involve a blend of technologies, namely:
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Natural Language Processing: This technology enables the Chatbot to decipher the meaning and intent behind user input by analyzing grammar, semantics, and context.
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Machine Learning: This allows the Chatbot to learn and improve over time. By analyzing large datasets of conversations, it can identify patterns, refine its understanding of language, and generate more natural responses.
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Dialogue management: This module manages the flow of conversation, determining what information to retrieve, what actions to take, and how to respond based on the context of the conversation.
Now, with that understood, let’s understand how exactly an AI Chatbot works:
Pattern matching
As the name suggests, pattern matching is a technique in which an identifier is defined and then given to the system to be trained upon. Once trained, the system develops the ability to look for this identifier and information associated with the said identifier. For example, you can train a system on something like “Who was George Washington?” and create patterns revolving around phrases such as “Who is George Washington?” “Do you know who George Washington is/was?”
Once the system is trained enough, it will browse through the available data sets and come up with the answer “George Washington was the first President of the United States of America.” The system was only able to come up with this answer due to its training on the name “George Washington.” This process is simple compared to algorithmic training and creating neural networks. But it isn’t the most accurate as it can be tricked into giving multiple or contradicting answers.
Algorithms
An algorithm is a set of instructions based on which operations are performed. Think of an algorithm as a blueprint of a system that encompasses every detail and workflow. Primarily, algorithms are quite heavily used in the creation of Chatbots as they have the ability to incorporate a number of variables. The more diverse your variables are, the more accurate answers your Chatbot will come up with.
Scientists and engineers usually take a reductionist approach towards creating AI Chatbots today. They create a hierarchy of patterns; the most prominent ones are listed at the top, while the less relevant ones are at the bottom. This helps in reducing the number of steps when learning.
For example, let’s assume that a system has been trained on a class called “Salutations” with messages such as “Hi there!” “Hello, how are you?” “Greetings, how is it going?” And then you give the system a prompt such as “How are you doing today?” The system will then try to map every word in the statement for a match in the class “Salutations”. It’ll find the words “how”, “are”, “you” and then assign a score to every match found.
On multiple iterations, it’ll learn how to respond to queries from different classes as well. The example mentioned above used Multinational Naive Bayes in its algorithm. Similarly, you can use a number of algorithms to create more nuanced systems.
Artificial Neural Networks
Neural Networks are layered structures with layers and weights. Different weights are assigned to different layers and are amended with every iteration. Once enough iterations are done, the results are compared and the better approach is given a go. Usually the more iterations a system is trained on, the more accurate answers it comes up with.
Neural Networks are often joined by classification algorithms, pattern matching techniques and other methods to give the most accurate answers. It is a highly complex process as it requires blending a lot of concepts together, but it gives the most accurate answers of the three methodologies discussed.
Unveiling the potential of AI Chatbots
AI Chatbots are no longer just about answering questions. They are transforming various industries by:
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Customer Service: Offering 24/7 support, and resolving inquiries, improving efficiency and customer satisfaction. A whopping 84% of companies believe that AI Chatbots will be better at handling customer interactions and solving queries in the upcoming years.
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Marketing & sales: Engaging leads, qualifying prospects, scheduling appointments, and providing product information, leading to higher conversion rates and improved sales cycles.
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Healthcare: Answering patient questions, providing health information, scheduling appointments, and offering basic symptom assessment, making healthcare more accessible and personalized.
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Education: Delivering personalized learning experiences, providing feedback, and answering student questions, improving learning outcomes and engagement.
Can you build your own Chatbot?
With the growing popularity of AI Chatbots, numerous platforms and development tools are available for businesses and individuals to build their own. But we’ll cut you the research part and give you the best solution there is on Chatbot development.
At Purro, we provide businesses of all shapes and sizes the ability to create personalized GPT-powered Customer Support Chatbots. Purro can help you improve conversions, boost efficiency, save time and money through easy implementation. All you have to do is:
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Import your data by letting Purro crawl through your website. You can also add files to increase the data set.
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Embed it onto your website through a simple code snippet.
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And let it handle customer queries on its own.
You can set the tone, add prompts that generate instant responses, and do a lot more to create a 24x7 Customer Support Chatbot with ease.
Conclusion
We hope that you’ve read and understood the nuances that come with Chatbots. AI Chatbots offer immense potential to improve communication, streamline processes, and enhance customer experiences. These days they’re absolutely necessary to handle your business needs and goals. All you need is a reliable and robust platform like Purro to build an equally reliable and 24x7 available Customer Support Chatbot for your needs.