Rule-based systems that understand pre-programmed keywords and respond with fixed answers.
Uses Machine Learning that continuously learns and improves, based on data and user interactions.
Follow rigid, pre-defined scripts, leading to frustratingly repetitive or irrelevant responses. Restricted navigation within the scripts.
Engage in more natural and fluid conversations, able to understand and respond to follow-up questions, change topics and even humor.
Offer generic responses with limited personalization, lacking tailored recommendations or relevant information
from user data.
Leverage user data and conversation history to personalize responses, tailor recommendations, and provide relevant information.
Struggles with typos, slang, or unexpected questions, often resorting to error messages or ending the conversation, unable to understand user intent.
Can handle diverse language styles and unexpected inputs, attempting to understand the user's intent and provide helpful responses even with errors.
Fixed and inflexible, requiring manual updates to respond to new information or changing needs.
Continuously learn and adapt based on new data and user feedback, improving it's abilities over time.