I have to be honest. While this is obviously a smart and useful idea, it misses one of the core features of Jev: its confidence scores. Partial confidence could easily be mapped to fractional spaces, using unicode characters like U+2009: THIN SPACE. As it stands, this package is not harnessing the full power of Jev.
Yeah I keep getting this weird sense that Jev is kinda poorly reinventing ML. I guess the graphs don't lie and theoretically I can replace luna with it, but I don't really use luna anyway.
What is the use case for a classifier that works 90% of the time...? I feel like if I'm classifying something, I probably care enough that 90% ain't gonna cut it...
I guess the answer is just agential stuff that effectively gets double checked by the LLM in the driver seat, anyway? That tracks, though it means that jev is mostly just for the people making harnesses. Which is all of us but still!
I think the argument would be that the classifiers of classic ML can be very useful and that Jav is a geenral purpose classifier you can just use that doesn't need to be trained per-task.
sethaurus · · focus · HN ↗
danieltanfh95 · · focus · HN ↗
bbor · · focus · HN ↗
What is the use case for a classifier that works 90% of the time...? I feel like if I'm classifying something, I probably care enough that 90% ain't gonna cut it...
I guess the answer is just agential stuff that effectively gets double checked by the LLM in the driver seat, anyway? That tracks, though it means that jev is mostly just for the people making harnesses. Which is all of us but still!
serbuvlad · · focus · HN ↗