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.
important to note that the "confidence" score is... maybe not what people think it is - kind of useless, and just a convenience step from the probabilities.
from the docs: "confidence is a statistic computed from the probability distribution the answer already gives you." [0] I actually encourage people to visit the docs because it has a specific page on this with a little applet to really make this clear.
What else do people think it is? If Typesafe had found a way to measure arbitrary AI results against objective reality (past, future and present) they'd either be making a killing on the stock market or working for the NRO, not publishing that as a confidence value on their API
Well I think there's an expectation that it's similar to the probability score, something that's outputted by the model itself, and so there's some level of "intelligence" (e.g. being able to recognize if the subject matter is relevant to the data it's been trained on, or as an accumulation of errors e.g. it couldn't figure out the question).
sethaurus · · focus · HN ↗
preommr · · focus · HN ↗
important to note that the "confidence" score is... maybe not what people think it is - kind of useless, and just a convenience step from the probabilities.
from the docs: "confidence is a statistic computed from the probability distribution the answer already gives you." [0] I actually encourage people to visit the docs because it has a specific page on this with a little applet to really make this clear.
[0] <a href="https://docs.typesafe.ai/confidence" rel="nofollow">https://docs.typesafe.ai/confidence
wongarsu · · focus · HN ↗
preommr · · focus · HN ↗