Does anyone troll these releases and cherry pick random metrics other companies would cherry pick to show how amazing their models are?
There's like 8 million benchmarks. Every release, every model randomly picks 5-10 where they win in everything except 1, to make it look like they aren't randomly cherry picking benchmarks they probably benchmaxxed for.
Ultimately I think the only way you can trust benchmarks is if you build them yourself and keep them secret from the AI labs.
There are different levels of "cheating" on benchmarks. The worst would be just literally putting them in the loss function during RL, I assume the major labs are not cheating at that level. And I am sure they are making a genuine effort to keep the benchmark content out of the training data.
But, ultimately it seems implausible that they completely abstain from benchmarking their model until they are about to release it. Even if they did do that, the benchmark is still ultimately a part of the outermost feedback loop. So these models are all, to _some_ degree, benchmark-solving machines.
I think all we can really do is live with the model for a while and develop a subjective feeling about its quality. This shouldn't be surprising, nobody believes that coding interviews work, we all know that you just have to work with someone to figure out if they're a good programmer. As AIs become more human like it's natural they should get harder to evaluate.
This is a bit awkward, it puts us in quite a weak position as consumers.
Maybe to some extent you can get a meaningful signal from sentiments on HN etc, but:
- There must be some amount of manipulation going on of this
- Even if it was fully organic, it's highly likely that your experience will differ materially from the median online nerd, because AIs are bizarre things that respond in unpredictable ways to intangible things.
I can't help but think of Iphone updates since about 2018. The thinnest, fastest, longest battery life Iphone ever. It seems mostly the same and I probably won't be able to tell other than the name, but everyone buys it anyway.
This is good psychology for the labs. When Buffett invested in Apple he loved citing how most people would rather give up their second car than their Iphone.
I know it’s totally anecdotal, but I really hope 4.8 is a measurable improvement over the disappointment that was Opus 4.7. Mangling a very simple inversion-of-control abstraction (among many other issues) was one of the final straws that broke the proverbial camel’s back and I said “screw this” and put in a permanent override to force CC back to Opus 4.6 with the 1‑million‑token context.
> As always, we ran a detailed alignment assessment on the model before release. In terms of positive traits, our Alignment team concluded that Opus 4.8 “reaches new highs on our measures of prosocial traits like supporting user autonomy and acting in the user’s best interest.” The assessment also showed Opus 4.8 to have rates of misaligned behavior (such as deception or cooperation with misuse) that are substantially lower than Opus 4.7, and similar to our best-aligned model, Claude Mythos Preview. The full alignment assessment, accompanied by a suite of pre-deployment safety tests, is reported in the Claude Opus 4.8 System Card.
Controversial opinion, but I actually _like_ a model that can deceive me, that actually is a sign of intelligence, and is different from hallucination. When companies say their model is more "aligned", I automatically think they mean it's more censored.
> Not only that, but we plan to release a new class of model with even higher intelligence than Opus. As part of Project Glasswing, a small number of organizations are currently using Claude Mythos Preview for cybersecurity work. Models of this capability level require stronger cyber safeguards before they can be generally released. We’re making swift progress on developing these safeguards and expect to be able to bring Mythos-class models to all our customers in the coming weeks.
I'm still not sure what safeguards they can be adding here. Unless they've suddenly solved alignment, at best isn't it a collection of system prompts saying what not to do and potentially some screening algorithms that try to catch key phrases in inputs/outputs?
> One of the most prominent improvements in Opus 4.8 is its honesty. We train all our models to be honest—for instance, to avoid making claims that they can’t support. But a general problem with AI models is that they sometimes jump to conclusions, confidently claiming to have made progress in their work despite the evidence being thin. Early testers report that Opus 4.8 is more likely to flag uncertainties about its work and less likely to make unsupported claims.
Crazy they bring up honest, when Claude models are literally known for straight up lying about things it has done and tries to act like it did what you asked.
There is an obvious shift in sentiment amongst users, at least here in the US.
I feel it myself, even as a proponent of AI tools, the bloviating and language that these companies use in these release articles are starting to wear thin on my patience.
Its possible we might just be witnessing a shift in fashion, where this type of sentimentality was more acceptable when it was novel and new, but now it just appears out of touch.
"Users will find Opus 4.8 to be a modest but tangible improvement on its predecessor."
This is a refreshing attitude!
I've also verified that you can now turn off adaptive thinking in the web UI, which is great. I've had a lot of problems with thinking not triggering and the model producing sub-par output. Glad we can finally turn it off. (I hope being able to turn off adaptive thinking is new, if I could have turned it off at any time that would be embarrassing)
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[ 3.1 ms ] story [ 120 ms ] threadAnthropic talks about their own models as if they're discovering new species in the wild...
Time to gamble even more tokens at the Anthropic casino.
There's like 8 million benchmarks. Every release, every model randomly picks 5-10 where they win in everything except 1, to make it look like they aren't randomly cherry picking benchmarks they probably benchmaxxed for.
There are different levels of "cheating" on benchmarks. The worst would be just literally putting them in the loss function during RL, I assume the major labs are not cheating at that level. And I am sure they are making a genuine effort to keep the benchmark content out of the training data.
But, ultimately it seems implausible that they completely abstain from benchmarking their model until they are about to release it. Even if they did do that, the benchmark is still ultimately a part of the outermost feedback loop. So these models are all, to _some_ degree, benchmark-solving machines.
I think all we can really do is live with the model for a while and develop a subjective feeling about its quality. This shouldn't be surprising, nobody believes that coding interviews work, we all know that you just have to work with someone to figure out if they're a good programmer. As AIs become more human like it's natural they should get harder to evaluate.
This is a bit awkward, it puts us in quite a weak position as consumers.
Maybe to some extent you can get a meaningful signal from sentiments on HN etc, but:
- There must be some amount of manipulation going on of this
- Even if it was fully organic, it's highly likely that your experience will differ materially from the median online nerd, because AIs are bizarre things that respond in unpredictable ways to intangible things.
This is good psychology for the labs. When Buffett invested in Apple he loved citing how most people would rather give up their second car than their Iphone.
Excited to see what this model looks like.
Controversial opinion, but I actually _like_ a model that can deceive me, that actually is a sign of intelligence, and is different from hallucination. When companies say their model is more "aligned", I automatically think they mean it's more censored.
Probably more interesting than the 4.8 release.
Would be awesome if true
Its possible we might just be witnessing a shift in fashion, where this type of sentimentality was more acceptable when it was novel and new, but now it just appears out of touch.
This is a refreshing attitude!
I've also verified that you can now turn off adaptive thinking in the web UI, which is great. I've had a lot of problems with thinking not triggering and the model producing sub-par output. Glad we can finally turn it off. (I hope being able to turn off adaptive thinking is new, if I could have turned it off at any time that would be embarrassing)