Machine learning is now able to create data structures on its own, adapting to the needs of each task. This means quicker, more efficient data searches tailored to how information is arranged. For example, it’s like organizing books by how often you read them instead of alphabetically. This research could make data retrieval way faster and smarter across different fields.
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There is also the vectorization of these databases which means we are seeing something is completely new.
Databases are quicker and better able to connect data. This means we are going to see the output of the models getting better over time.
Vector databases improve as more is entered simply by the way they are designed.
I remember you schooled me on that a couple of days ago when I made a mess on threads explaining context in terms of data used to train the models.
Thanks for that.