I built non-autoregressive decision models with RL a year ago

Posted by nandakishor_ml 12 hours ago

I built non-autoregressive decision models with RL a year ago(laya.convaiinnovations.com)

993 points | 230 commentspage 3

adamisnotroman 3 hours ago|

It seems like in today's day and age, whoever comes to market with a new tech second is usually winning. It's kind of unfortunate, as Laya is actually pretty cool. I think it will catch on considering its open weight and self hostable. It's easy to host on a home lab compared to the 1T parameter behemoths.

sandos 6 hours ago||

How come its completely unable to understand when it does not understand the script? Why was this no in the training, or was it?

The routing feels like such a hack to me...

throwaway63467 8 hours ago||

Landing page full of AI fluff, discussion feels very fake here, I would assume this is some upvote bot, nothing makes sense.

prometheus1992 8 hours ago||

Did you see the carnage that typesafe's landing page was? every other post here is llm generated, every other poster here seems like a LLM.

prodigycorp 8 hours ago|||

It's an embarrassing showing for our community, seems like nobody has read anything. None of the claims of the blog post add up.

nandakishor_ml 8 hours ago||

It's property benchmarked btw. And do read the og paper at https://arxiv.org/abs/2510.01237 And btw pypi package also there which never mentioned https://pypi.org/project/hallunox/

nandakishor_ml 8 hours ago||

All the stuff are proper benchmarked. Feel free to read the paper, https://arxiv.org/abs/2510.01237

samayashar 6 hours ago||

Great work by the author. Both Laya and Jev showcase how a different class of models can be efficient on tasks that don't require a 'generated output artifact'. I believe the same is true for VLMs where you're not always generating an image, but rather trying to understand more about the input image.

Token consumptions are flying through the roof and optimisation is the way forward.

iamflimflam1 3 hours ago||

Probably important to call out this part of the post:

Zero-shot vs. Fine-tuning: Out-of-the-box base models score ~0.35 on the typed-decisions benchmark (near random). The 0.766 score is achieved by fine-tuning on the benchmark's train split. Treat Laya as a fast foundation model to specialize, not as an omniscient zero-shot oracle.

recroad 3 hours ago||

This is awesome OP - very impressive. I'm definitely going to be using it to classify customer support tickets and log error classification. Thank you!

nandakishor_ml 12 hours ago||

This project was built on the exact research on jev architecture research one year ago

whizzter 10 hours ago||

I'm reading your year old Reddit post and Typesafe's description, and while they probabably say that they can do what you do the main point is that it's different things really as far as I can tell?

Laya seems to be focused on sales/conversations?

Reading quickly about TypeSafe, it seems to be about creating _type-safe_ outputs from AI tools for downstream systems to consume, we actually have a system in production that's probably a glove-fit for that, it's for scanning receipts to be ingested into a system and we also have other systems in a sales-pipe that isn't too far off Laya but still sounds more pertient to TypeSafe.

You did a special case well, but just because they cover (perhaps badly) that case doesn't mean that it's the same thing.

woggy 11 hours ago|||

I don't understand this sentence, can you try again please? Are you saying Laya was built on research done by the Jev team?

klibertp 11 hours ago|||

Jev was built using the same architecture Laya's author proposed[1] in March 2025. Laya is an open-source system based on that research from a year ago. Whether Jev is also based on the OP's materials or independently invented is hard to say.

[1] https://arxiv.org/abs/2503.23303

verdverm 6 hours ago||

the paper does not describe a model architecture, it describes a system built on embeddings, rag, and orchestrators

they don't seem very similar to me

water-drummer 11 hours ago|||

No, OP thinks they independently discovered Jev's architecture a year ago and published a paper. I am not an expert but I don't think Typesafe has published Jev's architecture so OP's claims cannot be taken at face value.

cgio 11 hours ago|||

It’s the other way around for me. OP has published everything in the open, so I can take him at face value. A PR media release on the other hand, I can accept with some reservations. The objective and non-conspiratorial reading I could offer is, this is most probably two independent discoveries of the same idea, maybe with different implementation. I still think the Jev team should look at prior art before going so hard on the marketing.

verdverm 6 hours ago||

if you look at the paper on arxiv, you might see why academics would pass it by

another point of consideration might be if you are taking OP's local statements at face value over what the pre-Jev content actually contains

The reddit commentary around OP's gripe is cringe imo

https://www.reddit.com/r/LocalLLaMA/comments/1wijo3e/i_liter...

if you want more cringe from OP, there's this gem

https://news.ycombinator.com/item?id=49674396

cmrdporcupine 10 hours ago|||

Jev is only on people's mouths because they made friends with venture capitalists and used the publicity blowhorns that come with that.

Whereas the other guy went through the unglorious but formerly respectable path of publishing software and papers for other professionals to look at. A year ago.

We're in a bad place where the latter looks less reliable than the former.

(EDIT: I'm not saying the research here is in fact the same as what "Jev" is doing; and Jev is in fact more "product shaped." But I think it's important to temper the hype and back up and focus on the fact that this whole industry is built on research by both academics and enthusiasts ... first ... and gold rushes can often bulldoze over those people who are focused primarily on making-doing-researching instead of fundraising-hyping-promoting. That's not good.)

verdverm 6 hours ago||

posting to arxiv is not publishing, it's a preprint site, and what's there I would not call professional work of academic quality

This was a year ago, when we were all complaining about the arxiv slop, which led to the new vouching system. This paper would not make it to arxiv today, it would be a zenodo link since they have not instituted any gatekeeping

nandakishor_ml 8 hours ago||

I built a pypi for it called hallunox https://pypi.org/project/hallunox/

scottcodie 6 hours ago||

They're definitely not the only one. I've been building on relational transformers, which does prediction and classification over relational data (it handles numeric types better). It's validating to see that these small models that do prediction tasks are so useful to the community, but also stings a little that it was so hard for me to communicate how game changing they are.

julianozen 1 hour ago||

Distribution > Creation

bluegatty 4 hours ago|

Jev is mostly a cost optimization and some good plumbing, I don't think it's breakthrough of naything

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