What is my purpose?

You pad the text.

Oh, my god.

Now that's a rare GitHub Username!

Though, again, a yet another project for a yet another "AI" to make someone else more dependent on it...

Related:

    https://en.wikipedia.org/wiki/Jev_(AI_model)  
    https://typesafe.ai/

It did one thing that you could write in one line of code. But it wasted space as a packaged dependency instead.

Jev is a new type of model that just makes decisions based on given options. It's small and really really fast.

Leftpad is a npm package that chooses if it should or shouldn't pad the left side of a string. It was famous for bringing down everyone's npm installs a few years ago.

This combination is a double joke. Put something stupid in something stupid.

funny

Please don't use this in production. Or anything important.

5 to 10 years from now, after this has worked itself deep into the npm dependency chain, we'll be lamenting how Jev-Leftpad is causing outages in critical services.

On the npm doomsday thing, the scarier version is someone vendoring it and the padding silently drifting between runs.

Make sure to vendor this package if you want reliable operation.

    it('trusts Jev when it chooses the wrong amount', async () => {
    answer('space_2');
    await expect(leftPad('jev', 8)).resolves.toBe('  jev');
    });

Since the potential error increases with N, I suggest spawning N different models and let them fight it out instead.

Aren't we all. Aren't we all.

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

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!

It's surely on the Pareto Frontier of something

wait.. is it just me or are we going overboard? I am waiting for jev assistance to exit vim, no wait.. a decision if we should exit vim or not.

You need to get the Pro version, please contact sales.

Done: https://github.com/freakynit/jev-test-runner

This needs an SBOM and a SonarQube Qualitygate pass to be considered production grade code

    The tests mock Jev. 

10/10 no notes

i maintained a system where for .. reasons (like other systems) from early days have users with id: null "null" "" and some i do not even know how to write here

so probably early bird

His oldest repository was updated in 2011. Looks like he's been there a long time.

GitHub clearly didn’t use his left pad

Jev mania at its peak? HN is full of Jev like today.

I already have Jev fatigue.

Terrorist

Instead of using Choice with criteria "space_0", "space_1"..., it could be even more elegant to use criteria names like "", " "... which could be directly inserted into response.

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

MIT Licensed

Would have been funnier if it used the GLWTPL: https://spdx.org/licenses/GLWTPL.html

github.com/f is more impressive to me than jev-leftpad lol

I’d be curious to see how reliable it is in practice, it sounds like a cheap and (hopefully) easy benchmark

JEV seems similar to BERT. Where would it be useful?

I use it mainly to check whether this code fits the rules I defined, just a yes or no. But I'm not sure if that's the right way to use it.

Is this package vibe coded with Jev or just old school with an LLM?

Jev-in-the-Loop. Makes sense.

I can't tell if this comment is satire or not lol

Next: jev-is-even

This makes about as much sense to me as AI-powered air traffic control

poor implementation

jev should only have the choice of space_0 or space_1, then recurse on n-1

this extends the implementation to infinite padding and is cleaner code

Is there a local model that can run this?

Subtlety in a joke is a beautiful art. BUT AT WHAT COST.

It's fun so far seeing the new trend from the sidelines, never bothered and never will bother learning what JEV is, but I'll see the occasional meme.

I feel for the people whose 'AI strategy' is keeping up with every vibecoded vibecoding junk that releases

I'm afraid the performance won't be great. Definitely needs a caching layer.