Left-pad strings with TypeSafe AI's Jev. For reasons. - f/jev-leftpad

234 points•fka•10 days ago•87 comments•

87 comments

sethaurus10 days ago
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.
preommr10 days ago
> its confidence scores

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] https://docs.typesafe.ai/confidence

wongarsu9 days ago
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
danieltanfh9510 days ago
Man we're going full 2015 ML, telling normies that confidence scores mean NOTHING to alleviate false negatives/positives.
bbor10 days ago
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!

ckastner10 days ago
Can't believe it's already been 10 years...

https://joelgrus.com/2016/05/23/fizz-buzz-in-tensorflow/

BenoitP10 days ago
What an eerie feeling reading this, or was it prescient?:

"""

    def fizz_buzz_encode(i):
        if   i % 15 == 0: return np.array([0, 0, 0, 1])
        elif i % 5  == 0: return np.array([0, 0, 1, 0])
        elif i % 3  == 0: return np.array([0, 1, 0, 0])
        else:             return np.array([1, 0, 0, 0])
interviewer: OK, that's probably enough.

me: That's enough setup, you're exactly right. [<--- !!] [...]

"""

Damn, Claude was there all along

ckastner10 days ago
oh, I missed that. Brilliant!
kevinrineer9 days ago
> me: That's enough setup, you're exactly right.

So that's where in the training set current models get that phrase! /j

kmoser9 days ago
This comes just in time. My app has been using Amazon Mechanical Turk for left-pad queries, and that service is shutting down in less than two weeks.
mawadev9 days ago
I should have know that beforehand, I have terraform ready for quickly moving off of mechanical turk into agentic AI left padding, this load-bearing workload has to be clowd powered
hanspagel10 days ago
This is funny, because I just implemented the same feature, but mine is calling OpenAI’s Astra on High (very capable for this kind of feature).

It works great, but maybe your implementation could save me some money. I’ll test it and report back.

gandreani10 days ago
I can't tell if this comment is satire or not lol
silviot10 days ago
I can. It is indeed satire.
fwlr10 days ago

    The tests mock Jev. 
10/10 no notes
slowmovintarget9 days ago
I posted the same observation, then saw yours. Yours is better (at 0.92 certainty) so I deleted my post.
marcus_cemes9 days ago
Reading this, I got excited that there may be be a hidden Easter egg, making fun of Jev. I was disappointed to find actual tests.

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