this post was submitted on 17 May 2024
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Honestly I feel people are using them completely wrong.
Their real power is their ability to understand language and context.
Turning natural language input into commands that can be executed by a traditional software system is a huge deal.
Microsoft released an AI powered auto complete text box and it's genius.
Currently you have to type an exact text match in an auto complete box. So if you type cats but the item is called pets you'll get no results. Now the ai can find context based matches in the auto complete list.
This is their real power.
Also they're amazing at generating non factual based things. Stories, poems etc.
Searching with synonym matching is almost.decades old at this point. I worked on it as an undergrad in the early 2000s.and it wasn't new then, just complicated. Google's version improved over other search algorithms for a long time.and then trashed it by letting AI take over.
Google's algorithm has pretty much always used AI techniques.
It doesn't have to be a synonym. That's just an example.
Typing diabetes and getting medical services as a result wouldn't be possible with that technique unless you had a database of every disease to search against for all queries.
The point is AI means you don't have to have a giant lookup of linked items as it's trained into it already.
Yes, synonym searching doesn't strictly mean the thesaurus. There are a lot of different ways to connect related terms and some variation in how they are handled from one system to the next. Letting machine learning into the mix is a very new step in a process that Library and Information Sci has been working on for decades.