Especially in times of ChatGPT Companies are using more and more chatbots and AIs to specifically address their customers' concerns and to efficiently support their employees in their work. The performance of many chatbots improves the longer they are in use, as smart assistants are constantly evolving. But how exactly do chatbots and voice assistants actually learn what they should do?
There are basically two methods by which chatbots and language assistants learn: A distinction is made between supervised learning and unsupervised learning.
Supervised learning: Clear rules for the chatbot
In supervised learning, the chatbot is programmed according to strict procedures and rules. The company specifies exactly which interactions are possible and how the chatbot should react to them. Every possible input must be entered and provided with possible outputs. In a flow chart, this creates a tree with many branches along which the chatbot moves.
This method is particularly suitable for narrowly limited fields of activity with clear input options, such as a change of address or a simple service request. However, the disadvantage of this method is obvious: The bots are very narrowly limited to their target area and can only respond to clear, predictable requests. If customers deviate even a little from this, the machine consultants often have to fit in.
Unsupervised learning or deep learning: flexible learning using neural networks
The second modern method of turning chatbots into valuable helpers is supported by artificial intelligence and the latest achievements in language processing. With the help of so-called natural language processing (NLP), machines can recognize not only individual words, but entire sentences and also the meaning behind them, which is often not expressly stated. Learning is not carried out using rigidly pre-programmed routines, but the bot improves itself with the help of neural networks. Each interaction results in feedback that improves future responses.
Unsupervised learning can only be found in a few chatbot solutions, but it is highly appreciated as it reduces the administrative and maintenance effort required to improve the customer experience by using the chatbot.
That's how Sally learns
Equipped with the ability to learn independently, chatbots can not only be controlled with natural language input instead of written texts, they also advance into completely new fields of activity: The chatbot sally For example, helps employees prepare appointments or guides them through processes using voice control. Since the program is constantly learning, its wealth of knowledge grows together with the company.
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