Evolution of Chatbots: From Rule-Based to AI-Powered

Chatbots are the new thing in the market. They are quick, fast and proficient in getting things done. We can see them on many websites and applications that will help you sort your complaints and queries.

On the other hand, we have AI chatbots, like Chatgpt which have taken the world by storm. They are smart, quick and efficient. They get things done quickly and it has instilled fear in people that it will take their jobs.

While people have mixed feelings and experiences, one thing is for sure Chatbots have come a long way since they were first created. And they are here to stay.

What is the first bot in history?

The first ever AI chatbot is Eliza, a Rogerian psychotherapist. You can still talk to it but it is largely improved now compared to its earliest version.

Weizenbaum created this chatbot because he was curious about what he get if he made a chatbot that could talk to humans in their day-to-day language like English. And this is how a chatbot was created which had the power of a Natural language Processor.

If you want you can talk to ELIZA.

(A warning: She is a sassy chatbot)

What Is The History Of Chatbots?

After learning about the history of chatbots. It is time to learn about its development and history. We'll demonstrate how a simple chatbot that couldn't handle a complex request may solve problems for people.

Looking at Bot history is like visiting a museum. It all started with the invention of computers. In the 1960s and 1970s, people began inventing modest computer programs to automate monotonous tasks. These early bots assisted with duties such as computer system administration and data handling.

As the internet expanded in popularity in the 1990s, bots became more useful. Some were created to search web pages and collect data. During this time, chatbots were introduced, allowing people to have simple conversations on websites.

In the 2000s, these Bots got better at solving complex problems. At this time, you can find that people were using chatbots on online platforms. This was the start of the earliest version of rule-based chatbots.

Facebook and Twitter saw the potential of these chatbots and took a level above the rest. Even though, these platforms were in their infant stage. These bots could help with jobs, games, and information gathering.

The gaming industry saw potential in bots and started to use them in their games which led to more improvement in the bots.

Bos in video games were seen as local participants. We have seen in old video games where we would fight with a Computer as an opponent. This helped in the advancement of more powerful AI systems.

In recent years, we have Alexa and Google Assistant have become popular. These bots use Artificial intelligence to respond in human language. Bots are seen as a tool which is used in a variety of areas, including healthcare and finance, to help with activities such as customer support and diagnostics.

Bots will continue to get better in the future, thanks to technologies such as OpenAI's GPT-3, which can generate text that sounds like it was told by humans. Bots are slowly and steadily getting into our lives and making them easier by supporting us with everything from answering queries to completing complex jobs.

The origin of chatbot started with curiosity and now it has evolved into smart and savvy assistants who can answer our questions in seconds.

Chatbots have come a long way in making our lives easier and more connected, whether it's answering queries, playing a role in video games, or making our houses smarter. They play every role to the best of their capabilities.

What is the difference between rule-based and AI-based chatbots?

In the previous section, we talked about how a simple chatbot born from the curiosity of a professor in the 1900s paved the way for the most significant AI advancement that humans have ever witnessed after the Internet boom.

At this point, we have two types of chatbots: Rule-based and AI-based. In this section, we will talk about how different they are from each other.

We will start with Rule-based chatbots.

Rule-Based Chatbots

These chatbots are similar to employees who follow a set of guidelines, almost like a road map, to understand and reply to what you say.

They excel at straightforward and predictable tasks such as answering precise questions or performing particular chores. However, if you ask them anything unexpected, they may become perplexed.

• Think of them as well-trained employees who are excellent at what they do, but may struggle if asked to do something for which they were not trained.

• To Set them up it is essential to provide them with a manual. There is a precise response written in that book for each query or assignment. So, if you anticipate all of the probable inquiries or duties, you can program these bots to handle them.

AI chatbots

These chatbots are like students. Rather than sticking to rigid guidelines, they make use of resources and tools they are provided at the moment like natural language processing (NLP) and machine learning.

Think of them as students or learners who, with each conversation, improve their skills and ability to respond to your questions. They are more adaptable since they can even understand the conversation's context.

They work well with more complex conversations. They're willing to take on new challenges and are available for detailed discussions or working with a range of activities. The more you converse with them, more smarter they get.

Because they learn and adapt. Just like how you grow better at a game the longer you play it. However, setting them up is a little more difficult.

Conclusion

In this blog, we have talked about how a professor’s curiosity set the foundation for today’s artificially intelligent chatbots. We got to know what was the first chatbot and how all this evolved into present-time chatbots.

After that, we discussed the two types of chatbots which are popularly used in the present time. These chatbots are Rule and AI-based chatbots, then we talked about their difference in capabilities and functions.

At the end of this blog, we can say that in 57 years. We have seen a drastic improvement in the field of Artificial intelligence and we are yet to see more.

That’s all for now. Thank you for reading till the end.