Lex, the bot building platform in which Amazon has invested a great deal of money, can be drastically improved. Lex’s understanding accuracy has the potential to go from 40% to over 90% thanks to the artificial training data automatically generated by Bitext. Building a well performing bot with Lex is now possible!
Customers are using channels such as Facebook Messenger as the place where to complain when their online order is delivered late. Therefore, companies have started to trust in chatbots for handling these issues. Can you see the potential of applying sentiment analysis to chatbot conversations?
Bots built upon machine learning need long training processes to have the ability to hold a meaningful conversation with real people. Training data becomes, therefore, a diamond in the rough; all companies need such input for their bots. Until now, this data was generated in a slow manual way. However, speeding up your bot training can now come true with artificially generated data.
A need for chatbots is spreading at full speed in the business world. These days, firms are generally counting on consulting companies for the integration of bots in their websites. It ends up in a challenge for integrators to choose vendors to give high quality conversational bot that suits their customers.
Companies who have been running a bot for a while will realize that the main reason a bot doesn’t get what users mean is their use of spelling. They usually make typos and also mix languages. To be honest, users don’t make it easy to be understood. This is the one of the biggest challenges a bot developer must face.