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 mostly been driven by messaging platform vendors such as Facebook or WeChat, the main advancements in natural language processing technologies seem to be coming from cloud platform and service providers like Google or IBM. Consequently, most bot developers spend time integrating their front-end bot applications with natural language processing services provided by a different platform.
From a conceptual standpoint, there are two main natural language programming techniques that have become popular with bot technologies: Natural language processing (NLP) and natural language understanding (NLU). Here’s a look at their basic features:
- Natural language processing: In the artificial intelligence (A.I.) context, NLP is the overarching umbrella that encompasses several disciplines that tackle the interaction between computer systems and human natural language. From this perspective, NLP includes several subdisciplines, such as discourse analysis, relationship extraction, natural language understanding and a few other language analysis areas.
- Natural language understanding: NLU is a subset of NLP that focuses on reading comprehension and semantic analysis.