I am not sure how this is JEV, but just a llm following the JEV api, as it is using standard LLMS. The main contribution of JEV is not the API but the model itself. Can someone please explain ?
I'm not sure anybody but people inside the company know if the model itself is a contribution. There's no publication and no architectural details. There's no benchmarks or comparisons published. You can do all of the things they claim with an LLM, not that I think that's what they did.
Likely they have some encoder (eg ModernBERT) trained to do late interaction or latent states along the lines of ColBERT, Perceiver IO or poly-encoders.
mukundesh · · focus · HN ↗
cmrdporcupine · · focus · HN ↗
deepsquirrelnet · · focus · HN ↗
Likely they have some encoder (eg ModernBERT) trained to do late interaction or latent states along the lines of ColBERT, Perceiver IO or poly-encoders.