Natural language is a fundamental element of bot technologies. As a result, there has been a direct correlation between the evolution of bot platforms and natural language processing platforms. While the evolution of bot technologies has been driven by the messaging platform vendors such as Facebook or WeChat, the main advancements in natural language processing technologies is coming from cloud platform and service providers like Microsoft, Google and IBM.
As a result, most bot developers spend time integrating their frontend bot applications with natural language processing services provided by a different platform.
During this Meetup we will discuss the two main natural language programming techniques that have become popular with bot technologies as well as the key differences between a rule-based bot and AI bot.
Answer 1: Chabot utilize data of existing web application or data sources. So client has 100% ownership of data.
Answer 2: Whatever the data is accessed by Chatbot is encrypted in secured fashion and can be authenticated by Chatbot only. However only thing we need to consider is where this information is stored, how long it’s stored, how it’s used, and who has access to it.
Answer 3: For static or repetitive tasks - clients are looking for Rule-based bots. e.g., bots that provide production information, order status, after sales customer support, IT-Support, etc.
For usecases that need bots to understand intend and context of user; client are looking for integration of bots with NLP and bots that require to provide intelligent insights based on historic data; client are looking for integration of Bots with ML.
Answer 4: - Botpress, BotLibre, etc.
Answer 5: Accuracy of AI Based bots depends broadly on three factors:
-Machine Learning Model
-Training of NLP
Answer 6: That may vary from bot framework to framework. Certain NLP like wit.ai, api,ai, etc. do provide support to multi lingual.
The main difference in a conversational interface is complex language input by the user that needs to be handled by an NLP engine. So, translating a chatbot is not just translating the output message, but also training an NLP model for the new language.