I believe his qualms were with the "hype" in Jev's announcement: specifically calling this kind of model a breakthrough, without crediting previous art, and keeping everything closed source.
I believe his qualms were with the "hype" in Jev's announcement: specifically calling this kind of model a breakthrough, without crediting previous art, and keeping everything closed source.
The hype is kinda nuts; I use X for ML/LLM stuff, and I just can't get away from Jev - even in my Following feed. Even days later 75% of posts are about "how I use typesafe for cooking breakfast!" or Jev clones.
So many different theories on why this is.
First, I think comprehensibility is a major part of why certain products grab the interest of the mainstream portions of the market. The 75% of posts in your feed are not from people who evaluate products based on underlying technology. They typically value signal from social reinforcement higher than anything else. This is the same reason why we see people mentioning products instead of technologies, i.e. PlanetScale versus Postgres & Tailscale versus WireGuard. The consumers understand the value proposition, but would have never discovered it without relatable messaging. This isn't a new phenomenon in computer software either; jQuery is probably one of the first examples that I can remember with this sort of texture.
The other side is a perception of expertise in a specialty. Software development, especially in AI, has become an incredibly desirable profession, and there are more people than ever racing to be included in it. In my own professional experience I find an excessive amount of entry level talent leveraging the same comprehension of product, but not comprehension of technology to get their foot in the door. A vast majority of the "thought leaders" occupying our feeds are not as well practiced as they claim to be, they're just trying to get a job or raise funding.
And finally, AI has brought out a certain amount of desperation in practitioners, for lack of a better term, materializing as an anecdotal, but certainly observable need to remain on the very tip of the news cycle in order to feel well informed. And so, using the dynamics above and many other human social dynamics, we find certain concepts spreading across cohorts that would not normally have a need or a want for these particular techniques, or products, or solutions, but because they feel pressured to remain relevant.
if is closed source, how does he know there isn't some breakthrough he doesn't know?
If it's closed source, how do you know it's not technology given by aliens from the 43rd dimension running on quantum computers enabled by discovering that P=NP and finding a linear time reduction from NP to P?
Occam's razor is that it's probably not all that different unless there is some specific reason to believe otherwise.
And how is laya previous art? The project was vibecoded and posted yesterday.
https://github.com/NandhaKishorM/laya/commits/main/
https://huggingface.co/convaiinnovations/laya/commits/main
The paper is one year old. https://arxiv.org/abs/2510.01237 https://pypi.org/project/hallunox/
Excuse me, but calibrating language models to accurately reflect probabilities did not start with you.
I didn't claimed it bro it was first. Just shared the findings here.
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just not these jev guys not opensourcing their work
You used a number of not open source projects in your paper, are you equally upset with them for this reason?
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Generally they do credit the papers and/or people who developed the theory behind their product.
Ideas are cheap. But the ideas are cheap coming from anyone. The reason some ideas (like JEV's) are taking up our attention (as opposed to Laya's) is not because of their execution ability, but because venture funding now is subbing filling in for execution ability. I do understand your argument to this would be - "welcome to the world!" or "that's just how the world works" - but that does not mean we do not recognize the ideas that came well before "venture funding made it happen".
I'd like to remind us all that there is a reason Joseph Liouville took the time to painstakingly review Galois’s chaotic manuscripts to credit him. It matters who did what before everyone else - if you do want to say "ideas are cheap" - we'd need to control for other variables before drawing conclusions.
Researchers definitely do get paid for research. That Google company you mention funds research which can be integrated into their products.
Sure, researchers get paid when they either do the research under contract or productize the research and sell it themselves. But they don't usually do the latter because that's quite difficult.
Are you grouping academic research funded by grants under the contract category?
To me, there is a meaningful difference and I'd add a third category, but I can also see the contract angle
@prodigycorp - reading your comments here on this post - you seem pretty hurt by this post.
Yeah, the reason why I am annoyed by it is because a person (who felt like a burner account of the laya creator) yesterday was haranguing me for saying that projects like this were vibe coded, posting the link to this project.
I evaluated this project yesterday and found its claims un-credible. It's literally nothing like jev. That's some context behind why, a day later, I find it annoying that this is somehow the top story on HN.
https://news.ycombinator.com/item?id=49752902
I don't really see the breakthrough in Jev. Classification, scoring, routing and returning probabilities over predefined choices are all established problems. We implemented category routing in our own retrieval system in a slightly different way: embed the incoming query, compare it against category profiles and route to the highest cosine-similarity. Obviously Jev isn't similarity based, but the underlying task of making a constrained decision from predefined choices isn't novel. TypeSafe says Jev has a new architecture and RLCD training, but Jev's actual architecture, weights and training details aren't public. So we can't even claim Jev is specifically a BERT classifier, but also don't see enough public technical evidence yet to call the underlying idea a breakthrough. Atleast they should publish a technical paper to prove their idea is breakthrough.
What is jev like? Did they release any research paper? I really think typesafe hired someone to boost their post because there was nothing "Breakthrough" about their product. At least this post has some touch with the reality that this functionality was available a year ago and was well known among ML people.
> At least this post has some touch with the reality that this functionality was available a year ago and was well known among ML people.
When you market a product you make exciting claims relative to the audience you’re engaging with. When was the last time you saw a product marketing page reverently lost all the academic research and prior art that came together to make a product possible?
If Layla’s functionality was available in a SaaS form in a way that could be used by all the people who are excited about and using Jev, wouldn’t this research have won hearts and minds last year when it landed? I would have a lot more empathy for the author if they’d taken a product to market and nobody cared. But even then maybe the market wasn’t ready. There are still reasonable explanations why sometimes ideas take off. We’re on a venture capital forum this shouldn’t need an explanation.
I can't believe you say in another post that you have experience with bert and yet you don't understand the value of a generalist classifier.
Good models take time and effort. There wasn't a good option for satisficers until a few days ago.
I agree with your analysis based on my own last night (on another HN post to this same gripe on reddit, before this blog post). OP received a lot of echo chamber support in the subreddit, and recommended to post to HN, so here we are.
The work is very amateurish, the "paper" would be a strong reject if I were still peer reviewing.
https://www.reddit.com/r/LocalLLaMA/comments/1wijo3e/i_liter...