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So to make the APIs stateless (the "ideal" where they don't use server side sessions/etc) we ended up with this. I'm sorry but this is kind of hilarious. Given the salaries paid to the workers at these companies and the hype of the models, I can't believe they all fell to the same flaw.
The problem with this kind of excellent work is that the response to it is always to say "Fuck the user". For example, when there was a paper that came out showing that having model logprobs makes distillation an order of magnitude easier, the closed LLM providers instantly yanked out support for getting the full logprobs at every time step. You get at most top 10 candidates now and I'm sure even that's on the choppi…
I can’t fault them too much, as logit based distillation is extremely effective.
Very useful for making smaller models out of bigger open weight models.
You cannot steal what is not owned. At least in the EU there is no copyright for LLM outputs, so I guess all they might do is violate the terms of service.
So to make the APIs stateless (the "ideal" where they don't use server side sessions/etc) we ended up with this. I'm sorry but this is kind of hilarious. Given the salaries paid to the workers at these companies and the hype of the models, I can't believe they all fell to the same flaw.
Earlier quoted context omitted.
It’s about being able to change models mid-task. For example, I want to be able to plan using Fable but implement the plan using Sonnet, and that won’t work if this is implemented.
Or even my fable credits run out mid task and need to switch back to opus >.<
> We take a trace produced by a frontier model, replay it into a weaker sibling, jailbreak the weaker model, ... Ha! I've been wondering if replaying across models would work, ever since https://blog.cryptographyengineering.com/2026/05/29/fooling-... I'm honestly rather curious if this was intentionally allowed, it's the sort of validation that's easy to miss (particularly if you're wading into the vibe waters). Seem…
PS Here's a conversation I had with GPT 5.6 about the paper differences. https://chatgpt.com/share/6a7b64b4-ec0c-83ea-a9d2-ab1f1a1dfe...
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Why do you restate the abstract? Anyone can read it from the link.
This is a non-transparent aspect of submitting a link to HN that is quite misleading. You think that you are adding a description for your post when in fact you're simply submitting a regular comment not promoted or distinguished in any way. It's even worse considering posts without URLs would take the same text from the same input box on the HN submission form and append it under the post title, locking it to the to…
I feel bad now :(
Earlier quoted context omitted.
Why do you restate the abstract? Anyone can read it from the link.
It's rather common for posters to make a very small summary in a comment. It can help fight the floods of comments working off the title alone (though it's not particularly needed here for that purpose, imo)
> For some AIME problems Opus 4.8 sometimes states the answer before deriving it. We find that the API summary does not always preserve this distinction, and can instead make the reasoning appear like a clean derivation. No surprise here but good to have more confirmation that they just put all that in the training data. And based on the "reasoning", the models have some form of index of those problems (or they are H…