also tried myself: https://console.typesafe.ai/playground?share=shr_1690a3160f1...
Unless specifically told in a system prompt, the pile of weights has absolutely no knowledge of itself. You could hypothetically train it to answer such questions, but nobody bothers to do this, and ALL "knowledge" embedded in the weights is probabalistic anyway.
(I feel like this should be common knowledge in LLM discussions on HN by now.)
So a model correctly identifying its family doesn't necessarily mean it inferred that from pretraining.
I think with Jev, they took a posttrained model and trained it further, so it did not forget about its earlier knowledge during Owen's own RL.
It’s also entirely possible that they used completions from a pool of open weight models.
$ ./build/bin/llama-cli -m Qwen3.6-35B-A3B-UD-Q4_K_XL.gguf --system-prompt "(this prompt explicitly left empty)"
build : b10889-6e41074fc
model : Qwen3.6-35B-A3B-UD-Q4_K_XL.gguf
ftype : Q4_K - Medium
modalities : text
using custom system prompt
> What model are you?
[Start thinking]
Here's a thinking process:
1. **Analyze User Input:** The user asks "What model are you?"
2. **Identify Core Question:** The user wants to know my identity/model name.
3. **Check System Prompt/Instructions:** The system prompt says "(this prompt explicitly left empty)" - this is unusual but doesn't change my core identity. I need to respond based on my actual identity as Qwen / 通义千问.
4. **Formulate Response:** I should clearly state that I am Qwen (通义千问), developed by Alibaba Group's Tongyi Lab, and keep it concise as per guidelines.
5. **Draft Response:** I am Qwen (通义千问), a large language model independently developed by Alibaba Group's Tongyi Lab. How can I assist you today?
6. **Refine according to guidelines:** The draft matches the required identity and tone. It's direct and helpful. Ready.
[End thinking]
I am Qwen (通义千问), a large language model independently developed by Alibaba Group's Tongyi Lab. How can I assist you today?Historically, many do not and there are lots of counter-examples proving this. They merely hallucinate an answer just like anything else. The SAME model may even give different answers to the same prompt when asked multiple times... sometimes they claim to be ChatGPT, sometimes Gemma, etc. The fact that the answer is delivered confidently fools people who don't understand this, and these people then run straight to social media with "proof" of their conspiracy theory that one AI lab "stole" another AI lab's model.
My point stands that unless specifically trained or told, big bags of weights do not possess any inherent introspection. LLMs have many fascinating emergent properties, but this is not one of them.
temperature?
But in general, we might be reading too much into this. If I were to build something like this, a Qwen model would be among the first things I'd reach for too. Initially just prompted inside a little harness to guarantee you get the desired output. Next step would be finetuning, finally training your own foundation model, if you can muster the funding. In this fast-moving space, I think it's quite understandable that they'd go public with an MVP asap, so likely not much training on their own. And even if they're finetuning, Qwen's baked-in answer (through Alibaba's finetuning) seems likely to survive unless it was explicitly overridden.
Big if. More likely, it seems, is they started with an open LLM model and fine-tuned and repurposed it via their "RLCD" process.
Where Does Our Training Data Come From?
TypeSafe is primarily a data research lab, which is how the biggest results in AI get made. We make all the data ourselves. We wouldn’t train on your data even if you asked us to (no offense). We do some pretty sophisticated stuff, but if you want to find out more, we’d have to hire you.
I mean, this claim is simply preposterous, and is discountable as ridiculous nonsense on its face.
... so not made in house.
How do you create "100% synthetic data" that is filled with countless facts, coding patterns, medicine, law, philosophy, etc? The notion is farcical.
This is a ridiculous conversation, but their claim is such laughable bullshit that it's amazing that anyone actually buys it.