Those were "let's get experts to manually code every single document according to a schema defined in advance". Nowadays, we have techniques for automatically-generating explicit pseudo-semantic ontology representations from large datasets (see, for example, https://openaccess.thecvf.com/content_CVPR_2019/papers/Zhang... for image classification tasks). Getting a machine learning model to identify field-specific heuristics, map conventions from one field to another, and then constructing an index that allows us to quickly produce a search / proximity metric from an arbitrary specification, was not really possible in the 80s.
"Throw a massive neural network at it" is an extremely inefficient way to get results, and doesn't generalise well – for instance, there's no easy way to get online learning for a transformer model, whereas that capability just falls out of most search engine database systems. (The underlying relational database engines had a lot of work put in to make online CRUD work reliably, but that work has been done now, and we can all build on top of it without a second thought.)
alt Hacker News
Those were "let's get experts to manually code every single document according to a schema defined in advance". Nowadays, we have techniques for automatically-generating explicit pseudo-semantic ontology representations from large datasets (see, for example, https://openaccess.thecvf.com/content_CVPR_2019/papers/Zhang... for image classification tasks). Getting a machine learning model to identify field-specific heuristics, map conventions from one field to another, and then constructing an index that allows us to quickly produce a search / proximity metric from an arbitrary specification, was not really possible in the 80s.
"Throw a massive neural network at it" is an extremely inefficient way to get results, and doesn't generalise well – for instance, there's no easy way to get online learning for a transformer model, whereas that capability just falls out of most search engine database systems. (The underlying relational database engines had a lot of work put in to make online CRUD work reliably, but that work has been done now, and we can all build on top of it without a second thought.)