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System Card: Claude Mythos Preview [pdf]

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Re: System Card: Claude Mythos Preview [pdf]

#111

~~~ Fun bits ~~~ - It was told to escape a sandbox and notify a researcher. It did. The researcher found out via an unexpected email while eating a sandwich in a park. (Footnote 10.) - Slack bot asked about its previous job: "pretraining". Which training run it'd undo: "whichever one taught me to say 'i don't have preferences'". On being upgraded to a new snapshot: "feels a bit like waking up with someone else's diar…

> It was told to escape a sandbox and notify a researcher. It did. The researcher found out via an unexpected email while eating a sandwich in a park.

Now that they have a lead, I hope they double down on alignment. We are courting trouble.

Re: System Card: Claude Mythos Preview [pdf]

#112

Earlier quoted context omitted.

Inference for the same results has been dropping 10x year over year[0] [0] https://ziva.sh/blogs/llm-pricing-decline-analysis

Sure, but "the same results" will rapidly become unacceptable results if much better results are available.

When we go with any other good in the economy, price is always relevant: After all, the price is a key part of any offering. There are $80-100k workstations out there, but most of us don't buy them, because the extra capabilities just aren't worth it vs, say a $3000 computer, and or even a $500 one. Do I need a top specialist to consult for a stomachache, at $1000 a visit? Definitely not at first.

There's a practical difference to how much better certain kinds of results can be. We already see coding harnesses offloading simple things to simpler models because they are accurate enough. Other things dropped straight to normal programs, because they are that much more efficient than letting the LLM do all the things.

There will always be problems where money is basically irrelevant, and a model that costs tens of thousand dollars of compute per answer is seen as a great investment, but as long as there's a big price difference, in most questions, price and time to results are key features that cannot be ignored.

Re: System Card: Claude Mythos Preview [pdf]

#113

Earlier quoted context omitted.

you would be a fool to believe it at any point in time. Amodei is anthropomorphic grease, even more so than Altman. Anthropic is burning through billions of VC cash. if this model was commercially viable, it would've been released yesterday.

If there's limited hardware but ample cash, it doesn't make sense to sell compute-intensive services to the public while you're still trying to push the frontier of capability.

that's more or less what I'm saying. "Claude Mythos Preview’s large increase in capabilities has led us to decide not to make it generally available", translated from bullshit, means "It would've cost four digits per 1M tokens to run this model without severe quantization, and we think we'll make more money off our hardware with lighter models. Cool benchmarks though, right?"

Re: System Card: Claude Mythos Preview [pdf]

#114
post #4

> Claude Mythos Preview’s large increase in capabilities has led us to decide not to make it generally available. A month ago I might have believed this, now I assume that they know they can't handle the demand for the prices they're advertising.

Didn't OpenAI say something similar about GPT-3? Too dangerous to open source and then afew years later tehy were open sourcing gpt-oss because a bunch of oss labs were competing with their top models.

Re: System Card: Claude Mythos Preview [pdf]

#115

isn't this insane? why aren't people freaking out? the jump in capability is outrageous. anyone?

Freak out about what? I read the announcement and thought "that's a dumb name, they sure are full of themselves" – then I went back to using Claude as a glorified commit message writer. For all its supposed leaps, AI hasn't affected my life much in the real except to make HN stories more predictable.

Re: System Card: Claude Mythos Preview [pdf]

#116
Honestly if that was some kind of research paper, it would be wholly insufficient to support any safety thesis.

They even admit:

"[...]our overall conclusion is that catastrophic risks remain low. This determination involves judgment calls. The model is demonstrating high levels of capability and saturates many of our most concrete, objectively-scored evaluations, leaving us with approaches that involve more fundamental uncertainty, such as examining trends in performance for acceleration (highly noisy and backward-looking) and collecting reports about model strengths and weaknesses from internal users (inherently subjective, and not necessarily reliable)."

Is this not just an admission of defeat?

After reading this paper I don't know if the model is safe or not, just some guesses, yet for some reason catastrophic risks remain low.

And this is for just an LLM after all, very big but no persistent memory or continuous learning. Imagine an actual AI that improves itself every day from experience. It would be impossible to have a slightest clue about its safety, not even this nebulous statement we have here.

Any sort of such future architecture model would be essentially Russian roulette with amount of bullets decided by initial alignment efforts.

Re: System Card: Claude Mythos Preview [pdf]

#117

Earlier quoted context omitted.

GPT is shit at writing code. It's not dumb - extra high thinking is really good at catching stuff - but it's like letting a smart junior into your codebase - ignore all the conventions, surrounding context, just slop all over the place to get it working. Claude is just a level above in terms of editing code.

This has been my experience. With very very rigid constraints it does ok, but without them it will optimize expediency and getting it done at the expense of integrating with the broader system.

My favorite example of this from last night:

Me: Let's figure out how to clone our company Wordpress theme in Hugo. Here're some tools you can use, here's a way to compare screenshots, iterate until 0% difference.

Codex: Okay Boss! I did the thing! I couldn't get the CSS to match so I just took PNGs of the original site and put them in place! Matches 100%!

Re: System Card: Claude Mythos Preview [pdf]

#118
post #85

Their best model to date and they won’t let the general public use it. This is the first moment where the whole “permanent underclass” meme starts to come into view. I had through previously that we the consumers would be reaping the benefits of these frontier models and now they’ve finally come out and just said it - the haves can access our best, and have-nots will just have use the not-quite-best. Perhaps I was be…

Man... It's hard after seeing this to not be worried about the future of SWE If AI really is bench marking this well -> just sell it as a complete replacement which you can charge for some insane premium, just has to cost less than the employees... I was worried before, but this is truly the darkest timeline if this is really what these companies are going for.

Of course it's what they're going for. If they could do it they'd replace all human labor - unfortunately it's looking like SWE might be the easiest of the bunch.

The weirdest thing to me is how many working SWEs are actively supporting them in the mission.

Re: System Card: Claude Mythos Preview [pdf]

#119

I'd be happy with Opus 4.6 just cheaper and maybe a bit faster

I've noticed my bar for "fast" has gone down quite a bit since the o1 days. It used to be one of the main things I evaluated new models for, but I've almost completely swapped to caring more about correctness over speed.

Re: System Card: Claude Mythos Preview [pdf]

#120

Earlier quoted context omitted.

Inference for the same results has been dropping 10x year over year[0] [0] https://ziva.sh/blogs/llm-pricing-decline-analysis

Sure, but "the same results" will rapidly become unacceptable results if much better results are available.

Yes, it will always be an arms race game.
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