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These models are trained on massive datasets of text, allowing them to learn patterns and relationships in language that can be used to generate human-like responses. They use fancy deep-learning techniques like neural networks. All in all, NLP is a subfield of AI that focuses on language processing and understanding, ML is a broader field that encompasses a wide range of algorithms and techniques used for machine learning and data analysis, and LLMs like Chat GPT are a type of machine learning model designed specifically for generating natural language responses.

Using an AI WhatsApp chatbot comes in handy in use cases when Phone Number List you need to handle more complex or unpredictable queries or when you need your bot to recognize context, not just input at its face value. For example, imagine a scenario where a hotel booking bot asks, “And how many people will be staying with us?” and the user responds, “just my husband and I”. A rule-based bot, if not specifically trained to recognize these keywords, will report this as an error and bid the user to rephrases so it can process the information. It is most likely expecting the user to answer “2” or “two”. On the other hand, a well-trained AI bot will be able to recognize the context and translate the user input correctly, responding, “Great, that will be 2 adults then.



Now, let’s look at the different ways you can use AI in your WhatsApp chatbot. Using NLU Tools likeadvantage of a natural language understanding platform like Dialog flow. Dialog flow is your typical NLU platform many companies use to design and integrate a conversational user interface into web applications, devices, mobile apps, interactive voice response systems, etc. Simply put, training an AI model is hard and time-consuming, so Dialog flow meets you half the way. It already boasts a pretty educated and well-trained database, so your developers just need to make a few tweaks.