(Un)natural Language Processing
I'm planning for some of my posts to get into the technical details of AI, some will just be my thoughts and opinions, and others will try to explain an aspect of AI in teams easy for everyone to understand. This is one of those posts. Natural language processing (NLP) attempts to understand, interpret, and generate human language. In my observation, it does fine at "generate," okay (I guess) at "interpret," but does not really "understand." NLP is based on statistics. It tries to guess what's next based on what word (or words) most often follow what you've typed. That is, most often in the training data. If the training data is really generic, then you might get one response, but if it's contextualized then you might get a different one. Here's an example: If I were to write "I had several bats in my garage, which..." the next few words could be "I would bring to baseball practice." or "I had to get ...