I speculate high quality data can be compared to be similar via embeddings comparisons. By organizing the dataset using features, grouping the vectors by them,

I speculate high quality data can be compared to be similar via embeddings comparisons. By organizing the dataset using features, grouping the vectors by them, and ensuring the dataset relates to itself in a given domain by quality tags, we can speculate the data becomes better as we are more specific with our queries to it. I need to train more models to see if this is an accurate claim, but I've been finishing up the storage layer and haven't gotten to that yet.