Open-source rival Laya launches; creator accuses TypeSafe of uncredited copying
5 Sep 19 6:46 AM · 4d ago · 7 articles · 15 posts · 55 comments · 6 sources · development 5 of 6
Developer nandakishor_ml released Laya, an open-weight 'System 1' decision model he says runs 6-8x faster than Jev, while publicly stating that he had published the same non-autoregressive decision-model concept, with papers, open weights and datasets, a year before TypeSafe's launch and was never credited.
“They proposed the exact same non-autoregressive decision concept as if it was a brand-new scientific breakthrough. Except they launched without technical papers, without open weights, and with zero open training datasets.”
nandakishor_mlDiogo Almeida Founder, TypeSafe AInandakishor_ml Creator of Laya (open-source rival)Simon Willison Independent AI commentatorflorianstandhar Creator of JevBench
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Reported in the same hours no headline names this development itself — these 3 claims were published in its stretch
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first by AIModels.fyi, 3d ago · also Arize AI, MarkTechPost
2 more headlines
- TypeSafe's Jev: Can decision models replace LLM judges? Arize AI · 3d ago
- TypeSafe AI Releases Jev: A System One Model That Returns Typed, Calibrated Decisions Instead of Text MarkTechPost · 3d ago
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first by Vercel, 3d ago
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first by Forbes, 3d ago
What people said 24 voices · best of 64 · verbatim
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🚀 Next Tool Tech Roundup · Sep 20 Jev (TypeSafe AI) is a non-LLM transformer that outputs probabilities, not text. Built by an OpenAI RLHF co-inventor. Can't hallucinate. Vercel reports 5–18× faster than OpenAI for classification.
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The unfortunate true is that getting even the best work in front of an audience is often much harder than solving the problem. Is uploading a paper to arXiv enough to expect the work to be recognized and cited? Unfortunately, it rather is not. arXiv is an open repository which includes plenty of not reviewed and not officially published papers. In…
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Jev is the AI model for the token-pinching era. — Instead of generating text, it makes decisions: yes/no, where to route this request, whether to escalate this issue, etc. — The key idea is that not every AI task needs an LLM generating text. Nearly 13% of Vercel's paid AI teams tried it in 24 hours. …
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Jev was adopted faster than any other model in AI Gateway history. In the first day, @typesafeai reached ~13% of teams, 2x the GPT-5.6 family and 6x Fable 5.1.
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OP's was leaky slop from day one [0][1], as is his article [2]It is arrogant and entitled for the author to take credit for the concept of RL over sequence embeddings, and none of the work that went into pretraining, not to mention the egregious target leakage [1][0]: Author fails to grasp the concept of virtual environments…
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Some jev-like alternative server benchmarks (many run local)
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Jev is not open-source and only available via API. Here's an open version called Nimble which performs just as well.
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I think their problem is more not being cited by the team at typesafe, as in general academic politeness. On the one hand you have the charitable assumption that they developed it independently. On the other hand, my opinion is that it is naive to expect companies to do that even if they took inspo from it, especially when this is a core product…
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I think the biggest lesson with Jev was the one of communication and understanding for the broader audience, sometimes a lot about innovating involves repeating yourself and translating your own thoughts to an intended audience.Classical machine learning has been, for the most part, and just by the nature of science, behind academic terms and…
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This is also a really common thing in ML specifically. We joke about getting Schmidthuber'd, which is when Jurgen Schmidthuber (sometimes correctly) announces that he or one of his colleagues actually proposed your thing 37 years ago in a Japanese linguists journal.Statistical modeling, from simple classical stuff up to modern deep learning, just…
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I think the main gripe that people had with Jev and Typesafe was the language used when they launched. To me personally it seemed like a parody/con/shady at first."Breakthrough", "our research went in another direction" , "Two years in stealth", "System One thinking model", "Jev can't hallucinate", "RLCD","We are doing very cool stuff, but we will…
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Jev claims to be frontier intelligence. Laya, while claiming to be "the open source version of Jev", is using a tiny open weight model with a tiny context window. Anyone who has experimented with tiny models knows that they are far from "frontier intelligence". It's not plausible that Laya could be "the open source version of Jev", with "frontier…
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It’s a tale as old as time — people don’t understand that marketing and branding are just as important, if not more so, than the product. Jev is exceptionally-well branded. Anyone can look at the webpage and understand it, and the implications, instantly.OPs “marketing” is a single post on Reddit titled “ Predicting sales conversion probability…
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Idk, your limitations section sure makes it seem less drop in and less general than Jev. Like the point here isn't your ML aptitude it's how easy is it for developers to drop this into a product and use it.I'm more than capable of training a bert classifier in fact in 2019 I had trained many custom berts and was running them on hundreds of…
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It is really interesting to see this claim, because i thought the current theory was that typesafe actually repackaged the work from GLiNER[1] - which does seem to be a closer match, and their original paper[2] predates yours by several years. Curious if you had heard of it before? It is also open source[3] and I think also has some good usage.[1]
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You're right but it's not the full picture. It's much easier to market when you have a name brand behind you. Not sure the author would've done much better even if he messaged it better. It's like the difference between someone random saying something smart on Twitter and no one gives a shit and Karapthy saying the same thing and everyone talks…
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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…
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Hi I want to explain that arxiv is not "publishing a paper" - it's a step up perhaps from putting it on your own website, but this is not what is meant by professional academics when they talk about "publishing" (even when they work for big AI companies).Your "papers" have only a single author and no current citations. It is not clear you are able…
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I generated an guide for a project I'm working on. The structure and appearance were pretty much what I wanted, but I'm going to have to go through and rewrite all of the text and cut out all of the simple tautological statements that are there just because it felt like it had to say something but had nothing to say.It's useful but any sense of…
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I played around with Jev last night and did it for classification tasks that I used Gemini 2.5 flash lite with.It’s a bit faster and bit cheaper, but this is compared to LLM. The consistency was nice to see, BUT, as someone who trained NLP models prior to LLMs, it’s just BERT with more data. I can see why people would want ready made one shot…
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I am not sure for how long the output will stay absolutely free. But apart from the pricing advantage of Jev itself, I just love the simplicity of having only an input price. Input is pretty easy to estimate and calculate upfront, which makes the cost of running something at scale much more predictable.With LLMs, even with JSON schema constraints…
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This 100%. Engineers really lack understanding in marketing and branding.No one cares if you are "first". They only care if your product is known by as many people as possible and is better than all the other alternatives at solving a problem that is worth paying for.If you don't market, then no-one will care that you exist even if you solved a…
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"But to me it seems like they were able to trick the VCs with "can't hallucinate" etc."I don't understand why we lept to accusatory and personal, nor do I understand where this connects with the article, nor do I understand the assertions if I ignore either of those two things.The article claims non-hallucination, it makes sense, then there's just…
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There have been other "universal"/general classifiers like GLiNER, GLiFormer, etc based on BERTs (Laya itself is based on ModernBERT!), but I do think there's something underrated about slapping classification on a "big" model like I've seen post-Jev announcement, lots of Qwen stuff, but the most interesting to me so far is razorback16/openjev…
All 6 developments of TypeSafe AI's Jev sparks priority fight with open-source… →
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