YHK - yet another hacker news clone

contrary to what i feel is extreme negativity of the author, to me it seems Jev is one of the only novel releases that lived up to the hype and has staying power. Not only that it jump started a whole new "classifier" war, leading to now things like cloudflare's clairic for extraction.

really early to call it "the fall of jev"

The rise and fall of something that majority of people never heard of

Did Jev take off briefly and stopped getting talked about a few days later? Yes.

But that doesn't make it a failure. In the era where we have:

a) an AI hype cycle where the benchmark of "successful product" is ChatGPT, Claude Code, etc. b) a social media environment that only rewards the most-engaged content

It's easy to declare something "fell off" because it didn't immediately revolutionize how everyone does their daily work.

But by that measure, nearly everything is a failure, even if it creates great businesses. That's especially true for infrastructure that runs in the background.

> I really don’t want to bash Jev

Sure. And yet...

Doomerism + Wishful thinking. We are what ~3 years into mass adoption of llm tech? Every couple of months it improves. Jev came out a couple of months ago and there is nothing that makes me believe that it will not improve over time as people fine tune small models to work better over time.

Jev is still extremely useful for its intended purpose, not the mildly interesting hype on social media.

Jev feels like what happens when people that have had no serious statistics get a glimpse of what statistics makes possible. I'm not talking about the developers of Jev, I'm talking about the uninformed that went all hype cycle on it. It's well designed and the advanced system a good statistical programmer would write.

I think there seems to be extremes in both ends and in my opinion neither of these extremes are the ICP. If you're using AI to finish your work, you're not the ICP. If you're building a product and want to implement AI in your product, you're the ICP.

The article says that other models are better at performance or cost. But whaz is not mentioned? Models that are _better_. From my testing, most models are much worse. And if you do an analysis on quality/performance/cost no one is beating Jev. Heck, no one is beating it at performance and cost at the same time.

There‘s a lot of hype with many releasing their decision models the past weeks. But all are worse. So maybe the years they spent in stealth is something you cant replicate in two weeks?

rise ???? it didn't even take off in the first place

What a low quality hit piece.

In the digital age, the "fall" of anything just means you, and the people in your bubble, stop using it. It could be something that enough people get value out of it that they can afford to pay for the domain name, and a bunch of other stuff, and you'd never even know. So to claim anything falls, well. There's Yahoo, AOL, Kodak, Snapchat, Facebook, Twitter, and Zombo.com. And they ain't going away.

I use Jev in production. Hype or no hype it’s working.

HN has a funny was of bubbling up low value article such as this. Jev is far from being a fallen software. It works and it works well. Just because no one is talking about it does not make it a failure.

Seems to be doing fine as per Openrouter rankings: https://openrouter.ai/rankings#leaderboard-table

It's the top model for classification.

did author used jev by any chance?

this actually very useful where you can rely your classical programming logic with coefficients provided by jev decision model results if (jevResponseJudge < 0.3) doSomething() else doNothing()

how would u code with LLM in such cases? parse responses for keywords? xd

no, they provide very useful interface. Just try it before writing posts about "hype".

After reading the article I can see that the comments here are a bit off. For example see this quote from the article:

> It’s not dead. Some companies use it while I believe the majority of use cases are addressed by open-weight rivals.

The point the article is making is the incredible way Jev specifically caused insane hysteria and hype, and just as suddently faded away. Not that it's dead or that the concept is severely flawed.

> It’s not dead. Some companies use it while I believe the majority of use cases are addressed by open-weight rivals.

The quality of the answers on my datasets are in another league compared to the benchmarks. I have a mixed language dataset, Jev answers only lack some accuracy, the open weight rivals output just look like random noise

Typesafe over-hyped their useful product and successfully got it in front of AI devs. So to be assholingly snarkily reductive I can sum this up as "founder did founder shit well"

If this is Jev’s trough of disillusionment, I’ll happily trade them for my plateau of productivity.

Seems to me most of the comments here miss the main point of the article about the pattern of hyped marketing (name dropping and jargon, ambiguity and inflated expectations, drama).

The author is obviously informed, but just as clearly biased.

Accused Dario of being part of Ilya’s coup against Sam Altman (now retracted), stated “ It’s an open secret that the training data wasn’t legally obtained anyway” when fair use has very clearly been established, and panders to the anti-AI doomer crowd with talk about how AI won’t be useful economically until we can get to the energy efficiency of the human brain while still invoking the boogeyman of killer drones and cyberterrorism.

Jev was overhyped, and the marketing was clearly looking to coin a few buzzwords, but the author seems to be intentionally ignoring the pace of development, the erosion of traditional intellectual property assumptions, and the realities of the technology. It can be overhyped, but this is very clearly the telos of all technology.

I've said it before, but the most surprising thing about Jev was that no one thought of doing it before. And second to that, that so many people didn't realise how useful classifiers were...

It seems a lot of the stuff people have using LLMs for in recent years were things that would be better suited to a classifier model.

Classifiers are not particularly difficult to train, but they also not as easy as just throwing an expensive LLM at the problem. That's really only the problem Jev solved. They've not done anything particularly technically impressive (imo), but they noticed the market for lazy/poorly informed people misusing LLMs for classification tasks and built a better solution.

I see no moat in that, but good on them for building something that is clearly useful and solves a real problem. The only thing I personally dislike about Jev is their Reddit-speak cringe posts and all the marketing nonsense about AGI. Although I'd be willing to believe that could be deliberate and they know their target audience are nerds with AI-psychosis.