Not long ago I was at a company that was rushing to get their AI "chat with our documentation" bot out the door as fast as possible. But prior to AI hype, 'improve documentation search' was not even remotely a priority, or even a concern. It's not like they had an okay chatbot for docs that was previously important but not high enough quality. Why was a documentation chatbot suddenly important?

I was talking to a neighbor the other day and he said he was tasked with using AI to help solve scheduling problems in his hospital! This was particularly bizarre, because if "solve scheduling issues" was a real problem, there are plenty of existing approaches to this (and have been for decades) and further more LLMs are not a particularly good way to solve this.

There are plenty of tricky NLP problems that AI/LLMs can unblock, and it makes sense that if you've been trying to solve a tricky NLP problem you might think AI can help you. There are numerous old problems I've had that I just couldn't get quite performant enough to work years ago that I would love to revisit with LLMs.

Funnily enough, when I chat with former coworkers about progress they've made solving these old problems they tell me leadership isn't interested and instead they're building something like a chatbot for documentation.

>(b) The term “artificial intelligence” or “AI” has the meaning set forth in 15 U.S.C. 9401(3): a machine-based system that can, for a given set of human-defined objectives, make predictions, recommendations, or decisions influencing real or virtual environments. Artificial intelligence systems use machine- and human-based inputs to perceive real and virtual environments; abstract such perceptions into models through analysis in an automated manner; and use model inference to formulate options for information or action.

1. https://www.whitehouse.gov/briefing-room/presidential-action...