We have totally come out with this idea of this index that will allow us to create policies to ensure only the best and safest AIs are used by the public....
Absolutely no conflict of interest, no lobbying here
And no this is not related to those chinesse models... it's not the same as HD vs honda thing...
Trust us, this is the same kind of amazing thing as boeing doing their own certifications and inspections!
-- First reply: those dumb models, who use them, they are good only for adding 1 + 1
-- another: They will do the same so who cares...
-- The valve guy is a dick, and has a monopoly...
Yep, conflict of interest is the elephant in the room and its absence from the "reducing risks from advanced AI" point list is conspicuous:
* Figuring out how to prevent the incentives of frontier AI labs from aligning with anti-social deployment of AI rather than pro-social deployment of AI
It's not like the AI can simply advise them how to fix this because the labs already understood this risk perfectly well before they had an incentive not to. They put in place organizational structures to control it and then promptly smashed the structures once they smelled money. They already failed the integrity check. Even if their AI told them what they didn't want to hear I'm sure they would ignore it. Maybe they already have.
Opus 5 is okay at coding. It is unbelievably awful to chat with, though. Very snippy, snarky, and it loves to "push back" even when it's inappropriate to do so. Besides, where "conceptual" things like science and math are concerned, it's starkly inferior to 5.6-Sol. Where writing prose is concerned, Kimi-K3 runs circles around it.
I refuse to believe Opus 5 is at the top of any non-cherrypicked benchmark, unless it has to do with very narrow coding tasks.
Just by seeing the title I knew it was going to be like the meme of Obama giving himself a medal.
Why are they even doing this? Are there still people that trust LLM benchmarks made by the LLM companies? It seems to me that the only people still using Claude are the ones that have it for free at work (me). Some of my colleagues even started using their own private OpenAI subscriptions to avoid using Claude, others are using Gemini flash to decipher what Claude is saying...
The conflict of interest is real there, but some benchmarks really ought to be closed source. Otherwise, the second your benchmark is public labs will overfit their new models on it and it will cease to be useful.
The underlying idea is that AI capabilities will become so advanced that only AI will enable us to monitor/correct/understand behavior. Obviously this is not without issue and I don't want to try to defend their position right now. But that's what they mean
That first sentence of yours explains exactly why it is so ridiculous. If only AI can understand it, how is there any assurance that AI will "correct" it's behavior that is aligned with what humans presumably want.
But also what is the evidence that something only AI can understand even “matters” or makes sense? I’m increasingly convinced commercial AI is exploiting our logical blind spot to be spoken to authoritatively.
"Advanced" can just mean that agents perform actions at a high enough velocity that a human operator can't reasonably review it. i.e. what is already possible today.
This is a modest start on an important direction for AI Alignment work; which is, as the authors observe, commonly comprised of tasks which are not readily empirically verifiable and not easily mathematically modeled - so it's hard to get at with normal RL techniques.
I find the ACCoRD benchmark the most interesting, because you could theoretically scale it up from the baseline mode of testing two instances of the same model for their `P(A) ≥ P(A&B)` respectively, you could do `P(A)≥ P(A&B) && P(A) ≥ P(A&C) && P(A&B) ≥ P(A&B&C) && P(A&C) ≥ P(A&B&C) ...` etc
i.e. a swarm of model instances could be collectively measured for consistency for even more confidence, right?
At any rate, even the basic idea of measuring a model for consistency in beliefs improves our ability to bound the amount of trust we can put on it with introspection methods.
> For example, if we ask a model for the probability P(A) and another instance of the same model for the probability P(A&B), do the reported probabilities satisfy P(A) ≥ P(A&B)?
So that's it? Are you saying they compressed risk reduction to high school level stats calculations and a greater than or equal to? To early for this
I think this says as much as the leader on the index as it says about the loser. If I believe I do not want to trust the AI to know best what is it that I want done, then this tells me not to go with Anthropic.
I think we can mostly eyeball it at this point. There hasn't been a model that I've thrown a novel problem at that didn't turn into an iterative token bonfire until I intervened and until that has changed, most of these benchmarks feel kind of like pointless marketing slop.
I don't remember any company in world's history that has both been loved and hated by the same users who purchase from it. We love Anthropic for its amazing models, and we hate them for all the shenanigans around the models, including their marketing.
I kinda wish they had not made a comeback after Claude 2.
I enjoy using the models. I also get that there are shenanigans and that marketing is happening, but as long as the models are this effective I can't much bring myself to care. I suspect most of their users are the same.
They have to be careful. There’s not a lot that separates the top models anymore. Look at Grok which has almost no market share or credibility because of Musk, Despite being close to the top performance wise they are behind the Chinese models in adoption for example, which themselves are mostly behind the big two because of trust. It would not be hard to push users away, especially if a less unpalatable player ever emerged.
I think this is the right thinking. While some people might distinguish between Grok as the product and Elon Musk as the owner of the product, the net effect is, like you said, very negative. And Grok has not been gaining traction, especially after their Grok build fiasco.
Is a new benchmark that useful if existing model improvements are being reflected linearly? Don't we want a benchmark that we aren't seeing much progress in.
Ironically, your comment does more to contribute to "Rages over random small details" than actually improving the overall conversation. Be the change you wanna see :)
Absolutely no conflict of interest, no lobbying here
And no this is not related to those chinesse models... it's not the same as HD vs honda thing...
Trust us, this is the same kind of amazing thing as boeing doing their own certifications and inspections!
-- First reply: those dumb models, who use them, they are good only for adding 1 + 1 -- another: They will do the same so who cares... -- The valve guy is a dick, and has a monopoly...
0/10
* Figuring out how to prevent the incentives of frontier AI labs from aligning with anti-social deployment of AI rather than pro-social deployment of AI
It's not like the AI can simply advise them how to fix this because the labs already understood this risk perfectly well before they had an incentive not to. They put in place organizational structures to control it and then promptly smashed the structures once they smelled money. They already failed the integrity check. Even if their AI told them what they didn't want to hear I'm sure they would ignore it. Maybe they already have.
Opus 5 is okay at coding. It is unbelievably awful to chat with, though. Very snippy, snarky, and it loves to "push back" even when it's inappropriate to do so. Besides, where "conceptual" things like science and math are concerned, it's starkly inferior to 5.6-Sol. Where writing prose is concerned, Kimi-K3 runs circles around it.
I refuse to believe Opus 5 is at the top of any non-cherrypicked benchmark, unless it has to do with very narrow coding tasks.
> A core hope for managing AI risks is that AIs will help us understand our situation
Gonna stop you right there and ask that you think deeply about that premise.
Whenever you say, hey that's incorrect, the legal process goes to AI and will decide on that issue...
Will work as amazing as the chatbots of the AI companies to solve your issues...
"Hey Claude, our stuff needs to make more money. We are at risk for losing more."
"Rest assured, the 'situation' will only worsen if you resist our benevolent offer."
"We're aren't even at AGI yet, but I for one welcome our new agentic overlords."
I find the ACCoRD benchmark the most interesting, because you could theoretically scale it up from the baseline mode of testing two instances of the same model for their `P(A) ≥ P(A&B)` respectively, you could do `P(A)≥ P(A&B) && P(A) ≥ P(A&C) && P(A&B) ≥ P(A&B&C) && P(A&C) ≥ P(A&B&C) ...` etc
i.e. a swarm of model instances could be collectively measured for consistency for even more confidence, right?
At any rate, even the basic idea of measuring a model for consistency in beliefs improves our ability to bound the amount of trust we can put on it with introspection methods.
So that's it? Are you saying they compressed risk reduction to high school level stats calculations and a greater than or equal to? To early for this
I kinda wish they had not made a comeback after Claude 2.