Hard to take you seriously, fam. The distance between these two things is trivial. The author of the paper implemented the "generalized" version of same in less than 24 hours. It's not novel, it is a continuation of what already existed in a boring way
The comment I was responding to describes Jev's significance as being specifically about embeddings:
> Jev is basically the embeddings side of an LLM
This is how the paper you are referencing is describing the "key contribution" as it relates to embeddings:
> Novel state representation techniques using Azure OpenAI embeddings (3072 dimensions) with sales-specific features
And now you are claiming that the author of the paper created:
> "generalized" version of same
It's a bit hard to guess what you are trying to say, but if I were to steelman your argument, I would guess that you mean: training a model with a vocabulary that has some tokens representing things like "OPTION_A", "OPTION_B" is in your mind the same thing as "generalized version of sales-specific features in embeddings"? Is this what you were trying to say?
Hard to take you seriously, fam. The distance between these two things is trivial. The author of the paper implemented the "generalized" version of same in less than 24 hours. It's not novel, it is a continuation of what already existed in a boring way
The comment I was responding to describes Jev's significance as being specifically about embeddings:
> Jev is basically the embeddings side of an LLM
This is how the paper you are referencing is describing the "key contribution" as it relates to embeddings:
> Novel state representation techniques using Azure OpenAI embeddings (3072 dimensions) with sales-specific features
And now you are claiming that the author of the paper created:
> "generalized" version of same
It's a bit hard to guess what you are trying to say, but if I were to steelman your argument, I would guess that you mean: training a model with a vocabulary that has some tokens representing things like "OPTION_A", "OPTION_B" is in your mind the same thing as "generalized version of sales-specific features in embeddings"? Is this what you were trying to say?