I will give an overview and key lessons from building up a customer service chat automation platform with built-in natural language understanding system from ground zero. I will outline the challenges involved in interpreting language, which is just a surface representation of the vastly complex conceptual model every human carries around in their brain. I will address the real world limitations imposed by the chat interface, scarcity of training data and dynamic content of the customer service.
- Human-level language understanding is much more complicated than matching token patterns
- Training data is scarce
- Customization is the key to good user experience
- Automation pays off when volumes are large