| ▲ | dcow 2 hours ago |
| I can understand why the author feels bitter but it still feels juvenile to me. Certainly both Jev and Laya are based on the research of countless prior papers and academics. Diogo decided to build a product out of the concept. The author didn't. Publishing research papers and model weights is probably part of the problem--it feels academic. If you look at the author's profile they focus on applying AI to healthcare. Not selling general AI type safety to AI pilled companies and devs. There's a big difference there. Whether that's good or bad you can argue all day. But for the author to expect otherwise is pretty weird. I do applaud them for not stewing too much on it and trying to do something about it, though. |
|
| ▲ | operaopera 2 hours ago | parent | next [-] |
| 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. |
| |
| ▲ | prodigycorp 2 hours ago | parent [-] | | 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 | | |
| ▲ | nandakishor_ml an hour ago | parent | next [-] | | The paper is one year old. https://arxiv.org/abs/2510.01237
https://pypi.org/project/hallunox/ | | |
| ▲ | dcow an hour ago | parent | next [-] | | By releasing a paper you are specifically telling the world, “hey look I did this thing for no comp, pomp or circumstance and I thought it was interesting enough to share with the world”. You get academic interest and credit when your paper is cited. It’s not “prior art” in any negative use of the term when a company takes the ideas in an academic paper and builds a product around them. This is a standard and well understood cycle where academic research happens and then gets applied to industry. Have you heard of a company called Google? And are you sure Jev is based on your work, or did you just do something similar? Ideas are cheap… | | |
| ▲ | jeremyjh 36 minutes ago | parent | next [-] | | Generally they do credit the papers and/or people who developed the theory behind their product. | |
| ▲ | charcircuit 34 minutes ago | parent | prev [-] | | Researchers definitely do get paid for research. That Google company you mention funds research which can be integrated into their products. | | |
| ▲ | Matticus_Rex 20 minutes ago | parent [-] | | 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. |
|
| |
| ▲ | prodigycorp an hour ago | parent | prev [-] | | Excuse me, but calibrating language models to accurately reflect probabilities did not start with you. | | |
| |
| ▲ | prometheus1992 an hour ago | parent | prev [-] | | @prodigycorp - reading your comments here on this post - you seem pretty hurt by this post. | | |
| ▲ | prodigycorp an hour ago | parent [-] | | 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 | | |
| ▲ | prometheus1992 43 minutes ago | parent | next [-] | | 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. | | |
| ▲ | prodigycorp 40 minutes ago | parent [-] | | 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. |
| |
| ▲ | verdverm 16 minutes ago | parent | prev [-] | | 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. |
|
|
|
|
|
| ▲ | vessenes an hour ago | parent | prev | next [-] |
| Agreed. Another difficulty here is there are not good benchmarks for this new architecture yet, so it’s easy to potshot and snipe, where jev seems to be pretty broadly intelligent/at least have had a lot of rl in different domains. We haven’t seen any of these copy cats play doom or street fighter for instance; just categorize email. I imagine once the author cools down and evaluates on a broad harness of tasks he may find that his new thing has a lot of engineering work ahead. |
| |
| ▲ | hirako2000 38 minutes ago | parent [-] | | The doom demo would have to be reproduced to confirm what their model is capable of. Oh but it's all closed source, so who knows. It reminds. Me of Devin. Took a while to debunk. Not saying Jev is a fraud , but the gap between structuring typed output and playing a game involving logical interpretation of frames made of pixels, screams unstructured interpretation they made and forgot to mention. | | |
| ▲ | derac 18 minutes ago | parent [-] | | They mention in their blog post that the model is working on text rather than pixels in the Doom demo. |
|
|
|
| ▲ | tomsyouruncle an hour ago | parent | prev [-] |
| I’m not filled with confidence when the author’s first paper takes an RL approach but then doesn’t use it to change the action taken in the next turn. Seems like simple classification would achieve the same end. And this quote from the paper isn’t overly reassuring: “I personally found that this sequential approach captured
sales dynamics much more effectively than traditional classification models.” https://arxiv.org/pdf/2503.23303 |
