Couldn't agree more.
To give an example, to go beyond a simple "generic" search.
I have a company finding buyers for commercial real estate. One of the search features are the locations of the buyers (usually family offices etc, always companies they have headquarters, preferences on where to buy etc.). You can then for example calculate the distance to those locations.
LLMs are extremely useful in creating these features from unstructured info on the companies. But just throwing an embedding on this and hoping it works doesn't.
However, embeddings work super well in the parts of the search.
I have a company finding buyers for commercial real estate. One of the search features are the locations of the buyers (usually family offices etc, always companies they have headquarters, preferences on where to buy etc.). You can then for example calculate the distance to those locations.
LLMs are extremely useful in creating these features from unstructured info on the companies. But just throwing an embedding on this and hoping it works doesn't.
However, embeddings work super well in the parts of the search.