In higher dimensional vector space, yes it can.

Dimensionality gets bizarre in 1000-D space. Similarity and orthogonality express themselves in strange ways and each dimension codes different semantic meaning.

Therefore, if the training data is highly consistent you are by definition reducing some complexity and/or encoding better similarity.

In Go the statement

    result, err := Storage.write(...)

    if err != nil { ... }

   try { Storage.write() } catch (error) { ... }