How does a chatbot work? How does it understand what I tell it? How does it know what to answer me? In fact, which technologies are in the base of conversational agents like the chatbots created with Virtual Agent Studio by Witivio? Here are some explanations.
What is a chatbot in the first place?
Let’s start from the beginning, what is a chatbot exactly? It’s simply this little robotic software that often appears in the bottom right corner when you need it. In a meeting on Teams, or directly on your company’s intranet, to ask your CPs or simply to find a form, all of a sudden, this little creature arrives and offers to lend you a hand.
In fact, behind its friendly interface, hides an algorithm set up to interact between the platform and the user. Often the chatbot makes us interact with it, asks us questions to understand our needs and give us the information we are looking for. Its goal is to give an adapted and quasi-immediate answer which is both useful and personalized. But not only that, a complex chatbot can process a large amount of data and perform operations, a bit like a personal assistant. But how does it do it?
Artificial intelligence, the brain of the chatbot
It is thanks to artificial intelligence (AI) that the chatbot comes as close as possible to the reasoning or behavior of a human. For it to understand you, to assimilate your needs, your requests, and to interpret your language, the chatbot relies on NLP (Natural Language Processing), one of the main engines of artificial intelligence. To be clearer, NLP is the automatic processing of natural language.
NLP works in three steps: first one is NLU (Natural Language Understanding). Actually, this alone is a very important part of the process: it allows the software to understand what is asked of it, i.e., it gives it as much competence as possible to communicate with a human brain.
Machine Learning or bot learning
Like a child learning to speak, the chatbot must then evolve, increase its understanding, and enrich its vocabulary. Step by step, by dint of talking with users, the bot learns from its successes as well as its mistakes. This training phase is called Machine Learning. It is a period of automatic learning, which exploits large volumes of data to build a reflection or establish conclusions and always polish the result.
Responding with NLG
Finally, the chatbot must formulate its answer clearly, appropriately, and personally. For this, it relies on NLG (Natural Language Generation). With this tool the bot generates coherent sentences and maintains a fluid conversation with you. Of course, NLG technology is not yet entirely sufficient, and often the bot also uses answers previously written by a human.
Wow the bot is a polyglot!
Another asset of chatbots is that they recognize the language in which they are addressed, and therefore answer directly in that same language. This is another branch of artificial intelligence that is activated at this time, the NMT (Neural Machine Translation). This makes our little bots geniuses of foreign languages, very adaptable to the global market (70 languages for the chatbots created with the Virtual Agent Studio by Witivio).
Your bot works for you
What if, in addition to communicating and transmitting information, the bot performed our most repetitive tasks for us? What if it could compile our data, put them in an Excel table, and send them every night to our N+1? This is possible by connecting an RPA (Robotic Process Automation) to our chatbot. Of course, it requires some configuration beforehand, but then what a pleasure it is to have someone do all those boresome reports for us!
That being said, we have exposed the very essence of the bot, capable of relieving us of the daily tasks we don’t enjoy that much. What could be more natural than to have a bot work for us thanks to artificial intelligence?
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