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Table of contents
1.
Introduction
2.
What are Chatbots?
3.
Types of Chatbots
3.1.
Rule-Based Chatbots
3.2.
AI Chatbots
3.3.
Feedback Chatbots
4.
Applications of Chatbots in AI
4.1.
E-Commerce
4.2.
Banking Customer Support
4.3.
Virtual Assistants
4.4.
Educational Chatbots
5.
Limitations of Chatbots in AI
5.1.
Lack of Creativity
5.2.
Lack of Emotions
5.3.
No Real-Time Learning
5.4.
Internet Dependency
5.5.
Dataset Dependent
5.6.
Inaccuracy
6.
Frequently Asked Questions
6.1.
What are the various techniques of training Chatbots?
6.2.
Is it possible to modify chatbots from interactions?
6.3.
How can we implement security measures in Chatbots?
7.
Conclusion
Last Updated: Mar 27, 2024
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Chatbots in AI

Author Aayush Sharma
0 upvote

Introduction

We all have used AI chatbots at least once in our life. It may be an assistant chatbot present on a banking website or a more complex one like Chat-GPT. AI has gained significant importance in the tech industry, and Chatbots have emerged as one of the most promising and impactful applications of Artificial Intelligence. These chatbots aim to bridge the gap between humans and technology by simulating human behavior.

chatbots in AI

In this blog, we will discuss Chatbots in AI (Artificial intelligence). We will discuss the working of Chatbots in AI and their most useful applications. We will also look at some of the upcoming limitations and challenges faced by Chatbots in the present scenario.

What are Chatbots?

Chatbots are AI (artificial intelligence) powered tools trained by developers to behave like humans and respond to human queries. Chatbots work on the principle of Natural Language Processing (NLP). With the help of NLP, the Chatbot can interpret the user queries, process them and then give a response in return.

NLP is a field of Artificial Intelligence that trains computers to understand, process, and respond to users. NLP techniques are used to process large amounts of text, images as well as video-based data and then respond to the user accordingly.

So now the question arises, How does the Chatbot know what I am saying?

Developers use Machine Learning algorithms to train Chatbots on large datasets. These datasets may include text, images, and videos depending on the Chatbot being developed. The main aim of this training is to make the Chatbot learn patterns and then generate appropriate results.

With the advancements in Machine Learning techniques and artificial intelligence, chatbots have become more accurate and are now capable of handling complex queries from users.

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Types of Chatbots

Chatbots can be classified on the basis of the technique used to train them. In this section, we will focus on some of the common types of methods used to train chatbots.

Rule-Based Chatbots

It is the simplest type of training method used to train chatbots based on predefined rules. In this method, the developer manually creates test cases and their respective responses. These types of chatbots are easy to train for simple interactions. However, more than rule-based training is needed for chatbots having complex interactions.

AI Chatbots

We are specifically discussing these types of chatbots in this blog. AI Chatbots are trained using various machine-learning algorithms and large datasets. These chatbots are trained to recognize and identify patterns and then respond to the user.

Feedback Chatbots

These types of chatbots are based on the principle of learning through feedback. Initially, these chatbots are trained like other chatbots. But as the Chatbot interacts with users, it gathers feedback from them. This feedback is then used for the improvement of the Chatbot.

Applications of Chatbots in AI

Nowadays, chatbots are used extensively on almost every website. Some of the most common applications of Chatbots are discussed below.

applications of chatbot in AI

E-Commerce

Nowadays, every online shopping website has a chatbot embedded in it. These chatbots reduce the need for a human for customer care. These chatbots are trained to respond to user queries like details regarding an order, canceling orders, etc.

Banking Customer Support

With the increase in the number of users in online banking, each bank has a dedicated chatbot section. These chatbots are trained to make the online banking experience easier for new users. These chatbots have the ability to guide users with step-by-step instructions for every feature.

Virtual Assistants

Every smart device comes with a built-in virtual assistant today, whether it is SIRI, Google Assistant, Bixby, and many more. Virtual Assistants are just chatbots having the ability to generate both audio as well as text. These chatbots are also trained to respond to user queries like music controlsopening and closing apps, etc.

Educational Chatbots

Many websites which provide educational content have developed chatbots. The user can enter their query into the Chatbot, which then responds with interactive solutions to the students.

Limitations of Chatbots in AI

Although Chatbots have numerous advantages, there is still much room for improvement and advancement.

limitations of chatbots

Lack of Creativity

Chatbots generally need more creativity. Although advancement is being made in developing AI, which can generate images and texts from text, it is still in the early stages.

Lack of Emotions

Chatbots are not able to show genuine emotional intelligence. Hence chatbots used in social media websites are not effective at generating user interest.

No Real-Time Learning

Unlike humans, chatbots cannot learn in real-time. Chatbots are trained on predefined datasets, whereas in the case of humans, they can rectify their mistakes and give correct responses in the future.

Internet Dependency

Most Chatbots require an internet connection to be functional. With the spread of the internet, this is not that big of an issue, but still, few places are deprived of the internet.

Dataset Dependent

Since the Chatbots are trained on datasets, it becomes necessary that the dataset is accurate. If the dataset is inaccurate, it can make the Chatbot identify wrong patterns and hence generate incorrect responses.

Inaccuracy

No Machine learning model is known to generate total accuracy. There are always cases of false positives and false negatives in every machine learning algorithm. As a result, Chatbots cannot always generate a hundred percent accurate responses.

Frequently Asked Questions

What are the various techniques of training Chatbots?

Depending on the complexity of the Chatbot, it can be trained using multiple techniques. Simple Chatbots with predefined responses can be developed using rule-based training. On the other hand, we use machine learning techniques for more complex chatbots.

Is it possible to modify chatbots from interactions?

Yes, we can modify the behavior and response of the chatbots with machine learning techniques. We can implement user feedback, use the previous data history, and re-train our Chatbot to modify its responses.

How can we implement security measures in Chatbots?

We can use methods like encryption for storing user data, implement robust authentication measures, regular security updates, etc. These methods ensure that our Chatbot remains secure and reliable.

Conclusion

In this article, we discussed Chatbots in AI. We discussed the working of Chatbots in AI. We also discussed the applications of Chatbots in the AI industry. In the end, we concluded by discussing some limitations of chatbots along with some frequently asked questions.

So now that you know about Chatbots in AI, you can refer to similar articles.
 

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