Mark Huang: belief

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…Multi-value, multi-query. Yeah, yeah. Multi-value, multi-query. That's the ablation. There's also a variable tracking one where you go, hey, if X equals this, Y equals this, Y equals Z, like what is this variable? And you have to track it through all of that context. And then finally, there's one that is more of like creating a summary statistic. So like the common words one, where you choose a word that goes across the entire context, and then you have to count it. So it's a lot more holistic and a little bit more difficult that way. And then there's a few other ones that escaped me at this moment. But ruler really pushes you. If I think about the progression of the evaluations, it start to force the model to actually understand like the totality of the context. Like everybody argues to say, couldn't I just use like a retrieval to like just grab that variable rather than pay $10 for one shot or something? Although it's not as expensive. The main thing that I struggled with, with even some of our use cases, were like when the context is scattered across multiple documents, and you have like really delicate plumbing for the retrieval step. But it only works for that one, that really specific instance, right? And then you throw in other documents and you're like, oh, great, my retrieval doesn't grab the relevant context anymore. So that's the dream, right? Of getting a model that can generalize really well that way. Yeah, totally. And I think that probably is what Greg mentioned when saying that he has to move beyond Needle and Haystack. You also mentioned you extended from 1 million to 4 million token context recently. And you saw some degradation in the benchmarks too. Like you want to discuss that?…

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