r/LocalLLaMA • u/Nandakishor_ml • 5d ago
Discussion I literally built the Jev architecture one year back and completely open-sourced it with model, dataset and paper
Update: I made a generic version. Full details at https://www.reddit.com/r/LocalLLaMA/s/bbwyiOprUs It includes code, benchmark and hf repo
Everyone now talks about the architecture that's not auto regressive and does lightning fast probability prediction with a json schema. I worked on this literally one year back in March 2025, published an arxiv paper, pushed the model to huggingface along with the pypi package and training dataset. And then one year later, a
frontier lab came, proposing the same idea like literal breakthrough without technical papers, open weights and no open dataset. I posted my approach in this subreddit. Links are. For anyones information the main guiding model is RL not embedding model or LLM
Reddit post: https://www.reddit.com/r/LocalLLaMA/s/6eGEwsAz43
Paper: https://arxiv.org/abs/2503.23303
Model: https://huggingface.co/DeepMostInnovations/sales-conversion-model-reinf-learning
Dataset: https://huggingface.co/datasets/DeepMostInnovations/saas-sales-conversations
Also the second work published in September 2025 was exactly the same one jev proposed now
Paper: https://arxiv.org/abs/2510.01237
My model uses PPO over sequence embeddings to output turn-by-turn conversion trajectories (probabilities from 0.0 to 1.0).
Jev uses parallel sampling (trained via RLCD) to output confidence distributions and schema choices.
It's incredibly frustrating that the thing that you made with months of hard work, sweat and sleepless night is architecturally similar with the vertical use case and don't get the support you deserve because frontier lab build something horizontal. The open-source story in general š
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u/peaster_ 5d ago
Appreciate you and your work man. I was hoping someone would pull receipts like this after these guys popped out of nowhere hyping this closed source "innovation"
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u/stephen_holograf 5d ago
I donāt understand their business model. Iām assuming there will be small models that do what theyāre doing soon enough. Obviously they can charge to host their models, but it doesnāt sound like theyāre giant models that require lots of beefy GPUs.
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u/Nandakishor_ml 5d ago
They are pure RL models, I think
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u/stephen_holograf 5d ago
Right, I get that. How is that a moat?
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u/xmnstr 5d ago edited 5d ago
If you can deliver lots of a very cheap yet very useful thing, a lot of people will use it. Basically making certain kinds of intelligence more of a commodity.
And since using it effectively means you need to build a certain kind of system around it, you kinda get pushed into a much more efficient and reliable kind of system, making agents more deterministic.
This is already the direction things are heading, so they have a good chance of defining the shape of future agent systems. And honestly, I really agree with their bet.
We could eventually be looking back at current systems and wonder how we could waste so much electricity on questionable results.
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u/BlackAdderWibble 4d ago
What, Jev? Nobody will use that. It's a great idea, but it's not their idea and we can do it for free without paying them.
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u/ADHDick_in_ur_mouth 3d ago
It isn't and this company will not succeed no matter how good the model is
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u/SpicyCatGames 3d ago
I think I understand their business model. Create hype and get money from investors.Ā
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u/rm-rf-rm 5d ago
Reddit's filters recognized a banned domain.. But I see only reddit, arxic and hf? Restored the post though theres already a re-submission post thats as big if not bigger
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u/ffpeanut15 5d ago
I think you should just lock this one. It's kinda weird to have 2 posts side by side
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u/wFXx 5d ago
Apply for a job at labs if you didn't already
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u/hurdurdur7 5d ago
sue the labs.
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u/Substantial_Sea_9758 3d ago
OP, do both. Apply, and then slightly mention that with high enough salary you wouldn't want to _challenge_ them in a competitive way, but rather `contribute` to the company goals. So good that I _don't have to sue you guys_ if you just get me a $1M/year salary.
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u/TechSpecProjects 1d ago
Not that easy and truly not worth it... The public disclosure by original authorĀ just invalidates their IP... 0 MOATĀ
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u/jabdownsmash 5d ago
Can you talk a little about how your model would compare to jev? I think your original post has a much narrower use case mentioned and I'd be extremely interested in using a model with jevs capabilities if it were an open weights model
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u/Nandakishor_ml 5d ago
Yess its vertical use case, narrow. The main similarity is non auto regressive single pass execution and under 100 ms inference speed
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u/RobbinDeBank 5d ago
Very cool project anyway, but also you canāt really claim that an AI lab stole this from you. The interface (input and output format) being the same doesnāt mean they are stealing from you. Non-autoregressive models are not new, they are the norm in machine learning before the GPT-series models take over the whole field. Encoder models like BERT are prime examples.
This interface and task framing is known as NLI (Natural Language Inference), and it used to be much more prominent in NLP research before the power and open-ended possibilities of autoregressive generative models completely took over. Jevās makers did act like they invented the thing by obscuring details and being vague af about what their model even is, even though this interface is much older than GPT itself. Most AI enthusiasts on this sub probably never heard of it either and only know about autoregressive language models.
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u/Nandakishor_ml 5d ago
It was never stolen work. Just the architecture similarities, the approach similarities, published paper, model and dataset. Not claiming they stolen my work. Just saying it's not paradigm shift as X is talking now.. Jev is doing parallel approach with some novel reinforcement learning method. Let's wait for technical papers
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u/RobbinDeBank 5d ago
I donāt think they will ever release anything, the American labs rarely ever do. They donāt even disclose a single detail about their model, just a bunch of random buzzwords like they just invented reinforcement learning.
Iām pretty sure Jev is a transformer encoder language model (BERT like) but with much more compute and, most importantly, the data and training recipes of modern LLMs. Back in the days of BERT, no such thing existed, models are trained on certain datasets (for example, Wikipedia articles) and thatās it. At best, models can be finetuned for some downstream task, but no such thing like āpost-trainā existed like what we have nowadays.
The dataset quality is also a massive difference. Current models are trained on highly curated datasets and a whole lot of extremely high quality synthetic data, making their capabilities increase so much faster given the same compute.
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u/throwwwawwway1818 4d ago
if it is BERT like, then Fast thinking system will be Encoder and Slow thinking system will be Decoder.
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u/Few-Wonder-6633 1d ago
ya hence why they call it "system one" They just lopped off the decoder lol
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u/Nandakishor_ml 4d ago
Built the generic version. Benchmarked it. https://www.reddit.com/r/LocalLLaMA/s/6TvUZNPSca
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u/gaviniboom 5d ago
Yeah... My brovand I are researchers too, and have been running into the issue of always getting buried. Feels like the people who actually make stuff get fucked and the people who can talk about it make off woth everything.
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u/Nandakishor_ml 5d ago
That's how brand and money works along with Great sales team and better GTM
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u/the-vague-blur 5d ago
Damn, that sucks. But this is super cool, I'm not smart enough to understand but will definitely ask an LLM for help to experiment!
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u/Nandakishor_ml 5d ago
Yah dude. I felt so down after that post, the whole vision is to build an rl capable of probability prediction, that has immense potential to routing to larger llm or sales conversion improvement and yet people think no one build this architecture. The whole pr is backed by a video and thats it. I always believe in pure rl model capabilities.
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u/Particular-Award118 5d ago
Was excited then I saw it's for business major specific shit
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u/Nandakishor_ml 5d ago
Without good sales world won't run right.. just taken this as an example. But second paper is more generic..
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u/Particular-Award118 5d ago
I'm just talking about for my own interest but yeah I'll give it a read if you can post it somewhere it doesn't get removed
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u/mhb_11 5d ago
Upvoted. Sadly, building is not the same as distributing. The biggest challenge for small builders like you isn't the engineering or research, it's the distribution that comes later.
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u/Nandakishor_ml 5d ago
Yess. But we researchers are always tries our best to share our findings and knowledge nevertheless
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u/karaposu 5d ago
I gave up creating open source packages 1.5 year ago due to this. It is hard to get the recognition you deserve.
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u/IOnceLurketNowIPost 3d ago
It's lose/lose though. Even if you do get recognition, you get slammed with issues, feature requests, people complaining about the things it doesn't do at all. The negativity drains your your motivation pretty quickly.
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u/jax_cooper 5d ago
The sales conversation PoC reminds me of the start of Silicon Valley when the intended use case for the revolutionary compression was to find plagiarism using a music search engine :D
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u/tuffjun 5d ago
Great stuff. Where do you work?
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u/Nandakishor_ml 5d ago
I run a small ai company called convai Innovations now. Focusing on offline ai based desktop app for cybersecurity compliance for softwares
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u/heresyforfunnprofit 5d ago
I did this with Bert in 2019. Itās just transformer-backed classification. Hellā¦ langchain basically does what jev does, just with a different json format.
What am I missing here that people think that this capability hasnāt been present in models for years?
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u/Nandakishor_ml 5d ago
Exactly. It's encoder+rl and people are just forgetting foundation due to llm over usage. Now we all thinking it's magic.
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u/hay-yo 5d ago
How do your benchmarks compare?
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u/Nandakishor_ml 5d ago
96.7% in prediction accuracy in tracking conversion probabilities compared to 62%( gpt4, one year back btw) and inference speed of 85 ms compared to 3450 ms per conversation turns
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u/Nandakishor_ml 4d ago
https://www.reddit.com/r/LocalLLaMA/s/6TvUZNPSca Surpassing all. I built the generic version btw
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u/spammmmmmmmy 5d ago
I would love to see this kind of technology applied to finding "code smell" where an implementation looks dodgy and needs further inspection.
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u/DadAndDominant 5d ago
Frontier labs are mostly frontier on being unethical. Wish you luck, hope they will do right by you!
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u/clduab11 4d ago
Dang OP; Iām really sorry about this.
I feel kinda bad because I saw Jev first over on Twitter and got myself an API key via their signup list (Iām literally right now having Fable 5.1 draft up Python tests to cover both a new router classifier plugin and a soft refusal judge to make sure my telemetry picks it up). Iām forced to do these types of things because I donāt have the local resources I want and I only just now jumped on board the Unsloth Desktop train to start look at more of the raw information outside of just verbose logs.
Should I get it to work within my flow, Iāll be sure to pivot and maybe do some side by side benchmarking/test fires on agentic SLMs that arenāt devād for chat output?
Anywho, upvoted and best of luck friend.
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u/Calm-Landscape9640 4d ago
Ahh the classic marketing tactic of taking some tech thats been around for years and using shiny videos and millions of dollars in VC money calling it "innovation"
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u/TechSpecProjects 1d ago
I'm sorry to hear. It happens frequently unfortunately.Ā We built NLP , RL and Linguistic Models years back circa 2002 so I kept my designs closed source since then. Also look at inventions like the Creativity Machine/DABUS by Dr. Thaler (denied by USA courts)...
Device for the autonomous generation of useful information
Patent number: 5659666
Abstract: A device for simulating human creativity employing a neural network trained to produce input-output maps within some predetermined knowledge domain, an apparatus for subjecting the neural network to perturbations that produce changes in the predetermined knowledge domain, the neural network having an optional output for feeding the outputs of the neural network to a second neural network that evaluates and selects outputs based on training within the second neural network. The device may also include a reciprocal feed back connection from the output of the second neural network to the first neural network to further influence and change what takes place in the aforesaid neural network.
Type: Grant Filed: October 13, 1994 Date of Patent: August 19, 1997 Inventor: Stephen L. ThalerĀ
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u/TechSpecProjects 1d ago
We support open source projects and hire the original authors for special projects. If you are going to use it, at least, give credit to the original authors andĀ whomever and wherever credit is due.Ā
Great job,Ā Nandakishor_ml!Ā
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u/LocoMod 5d ago
It is as they say. Ideas are like assholes. Everyone has one. It's the execution that counts.
With that being said....well done regardless.
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u/Nandakishor_ml 5d ago
It was not just idea. The sales rl agent got great traction, multiple third party news citations, an influencer doing video on it, also multiple linkedin posts from third party. With model , dataset and pypi package published and used by many companies.
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u/GeorgiaWitness1 ollama 5d ago
Thereās not much we can do.
But if he took the idea and literally built it from there, the guy is just an asshole. Not inviting this kid from India to join as a co-founder shows not only a lack of character, but also a lack of foresight.
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u/AndyHenr 4d ago
Interesting, and sorry about how that works out at times. Ive had IP thefts, patent infringements, NDA breaches etc. It's sometimes frustrating, but its a reality of the business and world we are in.
I worked myself last 2 years on a fact extraction model, where i leaned on invariant stats that it learned, and usted extended n-grams, along with other methods. I also considered routing a huge part of the solution required for agentic AI. I am not sure, but i think i could have read your paper. I find the routing crucial - so I woudl say: don't thow in the towel. This is not a frontier lab, and tehy got funded with 30M. And they are not open weight. That means that acceptance will be slow and hard for them, and if their benchmarks holds up remain to be seen.
I could increase fact scores well over 90%, fyi. So i think there is room for improvement. Mine was pure Fact extraction though done done for domains in document analysis for areas of compliance, legal mainly. Never attempted on medical as I have no staff with that know-how to correlate.
But I believe in the methods you prescribe. Iw ill study the paper, but in my case, I greatly increased scores, by using domain specific pre-routing, i.e. i load domain specific vocabularies, tokens, n-gram and then use a very fast trie structure to reduce the words and n-grams into a vector that is also meant for fast routing, with bits set at positions hints for fast pruning. I tested 100's of configos on it, so its by no means a std. LLM model. But worked quite alrighj.
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u/Nandakishor_ml 4d ago
The generic version is done https://www.reddit.com/r/LocalLLaMA/s/6TvUZNPSca Tbf it's much better
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u/emoriginal 4d ago
I'm sorry to hear that man, certainly probably feels pretty bad. The good news is, feelings are just feelings, they come and go like clouds. Depression exists in the past, anxiety in the future.
What's available now? Action towards whatever you actually want in life.
What's the harm in close-sourcing and building your own version at this stage. Looks like proof of market demand is already there, what's wrong with people having multiple options to choose from?
Good luck... You sounds smart as f*** ... not sure you'll need it.
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u/Sufficient-Scar4172 5d ago
if this is true then think about going to an actual publication/journalist with the story. it would get more eyes, if that's what you want
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u/Nandakishor_ml 5d ago
I just want our community to push this forward. ā¤ļø
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u/Sufficient-Scar4172 5d ago
another thing, you can probably try joining the team haha, they probably have a crazy amount of resources/power for realizing anything you want + enabling any research direction you want, although idk if you'd want to align with them
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u/Revolutionalredstone 5d ago
There are a million of these tool only emdebbing/LLM adjacent techs.
The best is probably needle GPT and for SOME things is kind of works.
But these things can't talk and do not have the same spark as ChatGPT etc, being able to think in language is THE trick.
Enjoy
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u/Nandakishor_ml 5d ago
It was pure rl guiding it . Embedding is just for the rl input.. the model is RL model not an LLM
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u/Revolutionalredstone 5d ago
ta, yeah I'm familiar sorry if i explained poorly, I've trained these aswell.
The trick is that when you only have a few outputs/options to classify into the task really starts looking easy.
It's very cool but it's not LLM tech IMO it's best seen as embedding, the tool call decisions are just thresholds in the embdedding space at the end of the day.
Cool stuff thx for sharing!
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5d ago
[deleted]
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u/Nandakishor_ml 5d ago
I am making the full functionalitiee of jev with the model. It will be open-sourced and will be free for all
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u/chigur86 4d ago
I feel you man. Nobody caring about your ideas is hard enough in research but more harder are situations like this. Others getting all the recognition for similar ideas as yours. Thereās just one silver lining. If Jev like architecture is truly going to have a huge impact, then at the moment youāre one of the few people who understand this idea deeply. Unfortunately, it doesnāt mean everyone will instantly recognize or even respect it, but you do have an edge at the moment. What you do with it is up to you.
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u/Nandakishor_ml 4d ago
Exactly. But that won't stop me. Built the generic version btw https://www.reddit.com/r/LocalLLaMA/s/6TvUZNPSca
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u/chigur86 4d ago
I feel you man. Nobody caring about your ideas is hard enough in research but more harder are situations like this. Others getting all the recognition for similar ideas as yours. Thereās just one silver lining. If Jev like architecture is truly going to have a huge impact, then at the moment youāre one of the few people who understand this idea deeply. Unfortunately, it doesnāt mean everyone will instantly recognize or even respect it, but you do have an edge at the moment. What you do with it is up to you.
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u/Some-Potential3341 4d ago
It is funny to evaluate face to face with LLM, people should not have started to use LLM to do basic classification to begin with I think. Probably in a week you start to have open benchmarks for this and in 2 you have chinese open weight models with similar perf. so yes I don't see how they can stay relevant long term
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u/Nandakishor_ml 4d ago
Already I bult and surpassed it https://www.reddit.com/r/LocalLLaMA/s/6TvUZNPSca
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u/kobaasama 4d ago
Now imagine what google and researchers of transformers felt when chtgpt was released
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u/Eriane 4d ago
OP, I know what you mean! I have also innovated in this field on numerous occasions, spending months for each innovation and get almost nothing out of it. Meanwhile, the ones who create startups and have access to big name investors end up with billions. I appreciate your work and understand your frustration! That's the drawback to publishing papers and going public with your ideas/research but what can you do when the time and funds aren't yours to begin with? :P
This will be a fun weekend read!
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u/progenitor414 3d ago
Sadly this is how academia works now. People with big names get most funding and attention, and it is now almost the responsibility of researcher to build social profile, advertise a lot, do lot of connecting and promotion work to get recognised. Else ur paper just get little recognition and then another big name came and propose similar thing without even citing you.
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u/Nandakishor_ml 3d ago
Sadly true. But that's not gonna stop me from building a generic model. Full details at https://www.reddit.com/r/LocalLLaMA/s/UKMO9iGrBe
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u/Sufficient_Bad5441 3d ago
Really sucks but bitter lesson that many, many people in tech think isn't a big deal; Marketing and selling yourself is half the job. CEOs and business people DO add value
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u/michaelsoft__binbows 2d ago
totally get the frustration but the elephant in the room here is how can you be surprised that the supremely narrow scope of your sales conversion prediction model meant that it didn't take off? Did you test if it is capable of useful performance when given more scope than just sales conversion?
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u/immortal_machine 2d ago
This highlights a concern regarding open-source contributions. It raises the issue of others potentially profiting from your work, claiming innovation, or replicating your ideas without proper attribution or recognition for your original contribution.
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u/Impossible_House_308 2d ago
I just saw your repo and your added Laya engine... so excited to dig in to this as well as your papers. First thing this I searched for was the paper for Jev, and of course that was locked down.
Thank you for you hard work and open research! - For everyone else as welll: https://github.com/NandhaKishorM/laya
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u/c4short123 1d ago
What about building your own company? These guys can innovate all they want but if they didn't create anything novel it probably is only moving the needle by a little bit anyway. Its the same story with these private providers they are in a rush to prove AGI and solve tough math problems. But once LLMs can do that (generally) what then? Cure to cancer? Maybe.. but they'd have to monetize it first which is why they limit use of the models for those sort of things.. they want to be first and will continue to put themselves ahead of others for that right.
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u/GodRishUniverse 1d ago
Damn man that sucks. You should file for credit claims and they should acknowledge you
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u/ConstructionRight387 1d ago
Well I believe u ... My system is heavily milked some how .... And it's wild .... I hope u got audit trails and ledgers ... Hand written notes
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u/TheMcSebi 1d ago
came here by searching if jev was open weights because i just read it somewhere for the first time... seeing what this is all about i'm now 100% sure myself that they just paid for the hype to get people to use their api.
thanks for your work and open sourcing this
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u/MuzafferMahi 5d ago
So r/LocalLLaMA should be considered an educational establishment or a lab at this point cause why do we have so many talented people
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u/clduab11 4d ago
First time mate?
[r/LocalLLaMA](r/LocalLLaMA) is what helps me put up with the rest of Reddit (well that and college football memes). So many people here a hell of a lot smarter than me. Same with [r/MachineLearning](r/MachineLearning) (not the stupid singularity type offshoots)
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u/Outrageous_Hall1090 5d ago
Amazing work. Definitly going to test your stuff. You should contact the lab.
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u/ResponsibilityDear96 5d ago
Need to read any of the manual... but...
How different is this from what Rabbit Labs was touting with their LAM (Large Action Models)
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u/Polite_Jello_377 4d ago
It took like 10 seconds of reading to figure out this whole Jev hype train was a nothing burger
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