Chatbots represent one of the first and most tangible results of the practical application of artificial intelligence. As relatively young intelligent systems, chatbots are constantly evolving to improve their performance. Studies in the field of AI have led experts to develop different types of chatbots, each with specific tasks and characteristics.
Generally speaking, chatbots are divided into two categories:
- Old-generation chatbots (rule-based bots or task-oriented chatbots).
- Conversational chatbots next generation (or data driven).
Old-generation chatbot vs. Next-generation chatbot
The fundamental distinction between these two categories of chatbots concerns the language they can process and the answers they are able to provide. Chatbots, by definition, communicate with human beings and provide relevant answers.
However, there are significant differences between the two groups. Old-generation chatbots, also known as rule-based chatbots, process human language using a predefined set of data. On the other hand, next-generation chatbots use Natural Language Processing and Machine Learning to understand human language and offer articulated and complex answers.
Other, even more specific types of chatbots belong to the two categories:
- Support chatbot,
- Skill chatbot,
for task-oriented chatbots or older generation chatbots, and
- Virtual assistants,
for the next-generation conversational chatbot category.
Let's see in detail what are the characteristics of each type of bot.
Support chatbot
These chatbots are designed to have extensive and specific knowledge on certain topics or sectors, allowing them to respond contextually to any question and to continue the conversation effectively. They are multi-shift conversational agents capable of maintaining an enriched conversation beyond a simple answer to a question. For example, a support chatbot could be used by a company to guide a customer through the process of resetting their account password or to answer common questions related to the service or product. The advantages for companies are many and obvious, such as the ability to offer a service available 24/7 to customers and to optimize business resources by moving staff to other strategic sectors.
Skill chatbots or skill chatbots
Unlike support chatbots, skill chatbots are not contextual, that is, they do not have specific skills but aim to provide quick answers to commands. They are often used to automate transactional processes and simplify user-application interactions. They are not necessarily oriented to assistance, but rather to performing specific tasks efficiently. For this reason, they are defined as mono-shift. An example of a skill chatbot is represented by virtual agents for spell checking, very useful when you are studying a new language. Skill chatbots can be used at the enterprise level in the field of human resources and training.
Virtual assistants
This is the new generation of chatbots, virtual assistants are multi-shift virtual agents that are expected to both manage a conversation and offer a quick and precise solution to a problem. They are powered by large amounts of data and use machine learning to improve their conversational skills.
These chatbots are able to understand natural language in a more advanced way, which means they can handle more complex conversations and adapt to user needs.
They are often used to improve customer experience and service. This type of bot must have in-depth knowledge in different sectors and be able to interact and understand with natural language. Examples of conversational chatbots such as virtual assistants are Siri, Alexa or Google Assistant. Virtual assistants differ from Support Chatbots and Skill Chatbots because they have widespread contextual knowledge, unlike support chatbots that are highly specific.
In addition, the virtual assistant is designed to have immediate reaction times, exactly as required of a chatbot of skill. However, if questioned repeatedly, it must also be able to delve into the topic in a specific way or to execute the linked commands. Let's take an example: if you ask the virtual assistant what the temperature is in the house, the chatbot, in addition to being able to provide the answer, must also be able to understand and execute the next command, which could be to turn on the air conditioning and turn it off when it reaches a certain temperature. Task-oriented chatbots aren't designed to do this type of task.
With the latest developments in the field of research and new innovations such as those of ChatGPT or GPT-4, virtual assistants can be equipped with models of generative artificial intelligence. In this way, advanced artificial intelligence models, such as deep neural networks, are used to generate more complex and “creative” answers. They can handle more natural conversations and are able to answer more complex or unexpected questions. These chatbots are especially useful for applications that require a deep understanding of the context.
In conclusion, chatbots can become valid allies for our business and daily life, contributing significantly to the automation of tasks that would otherwise require human intervention. Each type of chatbot offers specific functionalities, and in a business strategy that involves the use of chatbots to manage specific activities, it is essential to turn to solutions that adopt the most advanced language models.
Thanks to indigo.ai's cutting-edge approach and its Conversational AI technologies, companies can take full advantage of the potential of chatbots to improve customer experience, optimize resources, and gain a deeper understanding of conversations with their users.
