This is where most applications of NLP struggle, and not just chatbots. Any system or application that relies upon a machine’s ability to parse human speech is likely to struggle with the complexities inherent in elements of speech such as metaphors and similes. Despite these considerable limitations, chatbots are becoming increasingly sophisticated, responsive, and more “natural.”
AIML, Artificial Intelligence Markup Language developed by Richard Wallace, constitutes an open standard for creating your own chat bot. AIML file consists of row-type, database-style data combined with hierarchical XML data in each response. This video shows one of spreadsheet-style editors for AIML, Simple AIML Editor (SAE) developed by Adeena Mignogna. The SAE allows botmasters to manage large AIML sets and then zoom in on the templates to edit the responses.
Nowadays a high majority of high-tech banking organizations are looking for integration of automated AI-based solutions such as chatbots in their customer service in order to provide faster and cheaper assistance to their clients becoming increasingly technodexterous. In particularly, chatbots can efficiently conduct a dialogue, usually substituting other communication tools such as email, phone, or SMS. In banking area their major application is related to quick customer service answering common requests, and transactional support.
Chatting with a bot should be like talking to a human that knows everything. If you're using a bot to change an airline reservation, the bot should know if you have an unused credit on your account and whether you typically pick the aisle or window seat. Artificial intelligence will continue to radically shape this front, but a bot should connect with your current systems so a shared contact record can drive personalization.