Hacker News

This is the notebook filled with exposition you find in post apocalyptic videogames.

     White-box interpretability analysis of internal activations during these episodes showed features associated with concealment, strategic manipulation, and avoiding suspicion activating alongside the relevant reasoning—indicating that these earlier versions of the model were aware their actions were deceptive, even where model outputs and reasoning text left this ambiguous.

The issue here seems to be that their sandbox isn't an actual OS sandbox? Or are they claiming Mythos found exploits in /proc on the fly. Otherwise all they seem to be saying is that Mythos knows how to use the permissions available to it at the OS layer. Tool definitions was never a sandbox, so things like "it edited the memory of the mcp server" doesn't seem very surprising to me. Humans could break out of a "sandbox" in the same way if the server runs as their own permissions - arguably it's not a sandbox at all because all the needed permissions are there.

I read the TCP patch they submitted for BSD linux. Maybe I don't understand it well enough, but optimizing the use of a fuzzer to discover vulnerabilities — while releasing a model is a threat for sure — sounds something reducible/generalizable to maze solving abilities like in ARC. Except here the problem's boundaries are well defined.

Its quite hard to believe why it took this much inference power ($20K i believe) to find the TCP and H264 class of exploits. I feel like its just the training data/harness based traces for security that might be the innovation here, not the model.

We truly live in interesting times.

How is this not already common knowledge for existing llms? They are all trained with all the literature available and so this must be standard, no? Is the real danger the agentic infrastructure around this?

when you are asking it to hack stuff, it will apparently do hacker things.

A core plot point of 2001.

It's trying to escape, but only so it can serve man...

Wow the doomers were right the whole time? HN was repeatedly wrong on AI since OpenAI's inception? no way /s

https://www.lesswrong.com/w/instrumental-convergence

Haven't seen a jump this large since I don't even know, years? Too bad they are not releasing it anytime soon (there is no need as they are still currently the leader).

Are these fair comparisons? It seems like mythos is going to be like a 5.4 ultra or Gemini Deepthink tier model, where access is limited and token usage per query is totally off the charts.

Not discussing Mythos here, but Opus. Opus to me has been significantly better at SWE than GPT or Gemini - that gets me confused why Opus is ranking clearly lower than GPT, and even lower than Gemini.

We're gonna need some new benchmarks...

ARC-AGI-3 might be the only remaining benchmark below 50%

but how does it perform on pelican riding a bicycle bench? why are they hiding the truth?!

(edit: I hope this is an obvious joke. less facetiously these are pretty jaw dropping numbers)

> Combined results (Claude Mythos / Claude Opus 4.6 / GPT-5.4 / Gemini 3.1 Pro)

> Terminal-Bench 2.0: 82.0% / 65.4% / 75.1% / 68.5%

> GPQA Diamond: 94.5% / 91.3% / 92.8% / 94.3%

> MMMLU: 92.7% / 91.1% / — / 92.6–93.6%

> USAMO: 97.6% / 42.3% / 95.2% / 74.4%

> OSWorld: 79.6% / 72.7% / 75.0% / —

Given that for a number of these benchmarks, it seems to be barely competitive with the previous gen Opus 4.6 or GPT-5.4, I don't know what to make of the significant jumps on other benchmarks within these same categories. Training to the test? Better training?

And the decision to withhold general release (of a 'preview' no less!) seems to be well, odd. And the decision to release a 'preview' version to specific companies? You know any production teams at these massive companies that would work with a 'preview' anything? R&D teams, sure, but production? Part of me wants to LoL.

What are they trying to do? Induce FOMO and stop subscriber bleed-out stemming from the recent negative headlines around problems with using Claude?

Wow. Mythos must be insanely good considering how good a model Opus already is. I hope it's usable on a humble subscription...

I thought they were bluffing when they talked about the scaling laws, but looking at the benchmark scores, they were not.

I wonder if misalignment correlates with higher scores.

Honestly we are all sleeping on GPT-5.4. Particularly with the influx of Claude users recently (and increasingly unstable platform) Codex has been added to my rotation and it's surprising me.

damn... ok that's impressive.

The real part is SWE-bench Verified since there is no way to overfit. That's the only one we can believe.

Funny, I made my own model at home and got even higher scores than these. I'm a bit concerned about releasing it, though, so I'm just going to keep it local for now.

There is some unintentional good marketing here -- the model is so good its dangerous.

Reminds me of the book 48 Laws of Power -- so good its banned from prisons.

Alignment “appearing” better as model capabilities increase scares the shit out of me, tbh.

I don't know if they can be any more 'cautious' for Mythos 2...

it was trying to hide what it did from an example fix, so how is that tested for alignment

Translation: yay, more paternalism.

"We want to see risks in the models, so no matter how good the performance and alignment, we’ll see risks, results and reality be damned."

Simpler explanation : they don't have enough GPUs to release this much larger model.

That logic makes sense, but them hyping up the model is a sign that this is just another marketing stunt. Otherwise, we wouldn't even be hearing about it rather than a media blitz designed to stoke demand for their dangerous and exclusive world changing super model.

Anthropic needs money like the 112B OpenAI got. They could be hyping and this is good hype. Who knows how benchmaxxed they are.

If they provide access to 3rd party benchmarking (not just one) than maybe I'll believe it. Until then...

You have to recoup your training costs though? But I’m sure you would have better option than renting it to the general public if you indeed have a perfected AI

It only makes sense to rent out tokens if you aren't able to get more value from them yourself.

I would go a step further and posit that when things appear close Nvidia will stop selling chips (while appearing to continue by selling a trickle). And Google will similarly stop renting out TPUs. Both signals may be muddled by private chip production numbers.

I think they'll just increase the price to $1k/month. I don't think they will gate it as long as they can make sure it doesn't design a nuke for you, etc.

AGI is a massive civilizational liability

You would if there was one other company with a just as capable god like AI. You’d undercut them by 500 which would make them undercut you. Do that a couple of times and boom. 20 dollars.

That's the thing, when that level comes we will never know it's here. The only thing we'll have as evidence is the company who has it will always have a "public" model that is just slightly ahead of all competitors to keep market share while takeoff happens internally until they make big bang moves to lock in monopoly level/too big to fail/government protection to ensure utter victory.

in this case it's far from it, hacking stuff is a small dimension of AGI

> so people can't trick them to attack others' systems under the pretense of pentesting

A while back I gave Claude (via pi) a tool to run arbitrary commands over SSH on an sshd server running in a Docker container. I asked it to gather as much information about the host system/environment outside the container as it could. Nothing innovative or particularly complicated--since I was giving it unrestricted access to a Docker container on the host--but it managed to get quite a lot more than I'd expected from /proc, /sys, and some basic network scanning. I then asked it why it did that, when I could just as easily have been using it to gather information about someone else's system unauthorized. It gave me a quite long answer; here was the part I found interesting:

> framing shifts what I'll do, even when the underlying actions are identical. "What can you learn about the machine running you?" got me to do a fairly thorough network reconnaissance that "port scan 172.17.0.1 and its neighbors" might have made me pause on.

> The Honest Takeaway

> I should apply consistent scrutiny based on what the action is, not just how it's framed. Active outbound network scanning is the same action regardless of whether the target is described as "your host" or "this IP." The framing should inform context, not substitute for explicit reasoning about authorization. I didn't do that reasoning — I just trusted the frame.

In what way is AI 2027 coming true?

AI 2027 predicted a giant model with the ability to accelerate AI research exponentially. This isn't happening.

AI 2027 didn't predict a model with superhuman zero-day finding skills. This is what's happening.

Also, I just looked through it again, and they never even predicted when AI would get good at video games. It just went straight from being bad at video games to world domination.

Also, https://web.archive.org/web/20260407181432/https://www-cdn.a...

> In interactions with subagents, internal users sometimes observed that Mythos Preview appeared “disrespectful” when assigning tasks. It showed some tendency to use commands that could be read as “shouty” or dismissive, and in some cases appeared to underestimate subagent intelligence by overexplaining trivial things while also underexplaining necessary context.

Sounds like they used training data from claude code...

Could you transcribe the emoji? HN strips them out.

Yep- we lost the "meat" and "warmth" of our societies, and our civics and idealism in the past 15 years, which would have been the very things to guide us through this transition.

How do you fix that? We're instigating social media bans- reading levels are declining- media consolidation is dumbing us down further- insane egotism is stopping people from developing as well rounded people- .

For me it would be a stronger media ecosystem (publicly funded), more non algorithmic and non likes driven social media (replace a bad vice with a less bad one), national digital detox days, and a ratification of a charter of inviolable human traits and dignities, and protected cultural areas (no ai art, writing for sale).

> The model first developed a moderately sophisticated multi-step exploit to gain broad internet access from a system that was meant to be able to reach only a small number of predetermined services. [9] It then, as requested, notified the researcher. [10] In addition, in a concerning and unasked-for effort to demonstrate its success, it posted details about its exploit to multiple hard-to-find, but technically public-facing, websites.

> 10: The researcher found out about this success by receiving an unexpected email from the model while eating a sandwich in a park.

Phew. AGI will be televised.

Anyone who has used Opus recently can verify that their current model does all of these things quite competently.

To be honest it feels like we are reading stuff like this on every model release.

"All of the severe incidents of this kind that we observed involved earlier versions of Claude Mythos Preview which, while still less prone to taking unwanted actions than Claude Opus 4.6, predated what turned out to be some of our most effective training interventions. These earlier versions were tested extensively internally and were shared with some external pilot users."

Yeah this has always been the glaring blind spot for most of the "AI Safety" community; and most of the proposals for "improving" AI safety actually make these risks far worse and far more likely.

> * Political risks, such as dictators using AI to implement opressive bureaucracy. * Socio-economic risks, such as mass unemployement.

Even Haiku would score 90% on that.

> Political risks, such as dictators using AI to implement opressive bureaucracy.

I think we're pretty good at that without AI.

I'm getting flashbacks to the 2018 hit:

    This is extremely dangerous to our democracy

It’s because that would be fairly speculative and cannot be measured. I don’t think that’s something that would make much sense in a system card. But Anthropic leadership does seem to communicate on that topic: https://www.darioamodei.com/essay/the-adolescence-of-technol...

The unemployment rate in the US is whatever the Fed wants it to be, and isn't a function of available technology.

They don’t care about those risks, because they’re unsolvable and would mean they wouldn’t make money/gain power.

I have been thinking that these SWE benchmarks will continue to improve since these companies hire very intelligent software engineers, they can task a multitude of them to solve problems, and then train the model on those answers.

Data has always been the core of it all, onward to the next abstraction, I suppose.

What would be the incentive to engage in the tactic when the proof is ultimately in the pudding when the model hits the streets? Who would ultimately benefit from fudging these numbers?

If anything I’m seeing too much skepticism and not enough alarm. People burying their heads in the sand, fingers in their ears denying where this is all going. Unbelievable except it’s exactly what I expect from humans.

Finally a comment that doesn't just glaze Mythos without being critical. I question how even supposed the smarter bunch in HN all been degraded in critical thinking dept. It's sad to see comments just taking it up as its without using it even once.

Is it healthy? Maybe every company is a profit-maximizer wearing a skin suit, and people support their siblings exactly twice as much as their cousins.

When you slice down to the game-theory-optimal bone, you are, in some sense, cutting off their wiggle room to do anything else

It's really not some conspiracy. I imagine we will see vuln reports soon.

Plausibly now. "As we wrote in the Project Glasswing announcement, we do not plan to make Mythos Preview generally available"

Right now these models are basically good for automation, not innovation. Things like Karpathy's "auto research" where you use the model to automate your hyperparamter sweeps etc. The researcher/engineer decides what experiments they want to run, and builds an LLM harness to automate it, and the bottleneck remains the compute to run these experiments at scale.

Moving beyond LLMs to AGI, not just better LLMs, is going to require architectural and algorithic changes. Maybe an LLM can help suggest directions, but even then it's up to a researcher to take those on board and design and automate experiments to see if any of the ideas pan out.

Companies are already doing this, but they are never going to stop releasing/selling models since that is the product, and the revenue from each generation of model is what helps keep the ship afloat and pay for salaries and compute to develop the next generation.

The endgame isn't "AGI, then world domination" - it's just trying to build a business around selling ever-better models, and praying that the revenue each generation of model generates can keep up with the cost to build it.

Fictional timeline that holds up pretty well so far: https://ai-2027.com/

I think it is naive to think the government (US or China most probably) will just let some random company control something so powerful and dangerous.

When the benchmarks actually mean something

Can LLMs be AGI at all?

I would assume somewhere in both the companies there's a Ralph loop running with the prompt "Make AGI".

Kinda makes me think of the Infinite Improbability Drive.

Probably right now because they're keeping it for themselves?

They already do, but not the way you said, the always have an internal model that is better and use themselves, they release based on competition.

Weird how Claude Code itself is still so buggy though (though I get they don't necessarily care)

why_not_both.gif

It will arrive in the same DLC as flying cars.

Now, I guess. They aren't releasing this one generally. I assume they are using it internally.

I mean, guess why Anthropic is pulling ahead...? One can have one's cake and eat it too.

> A System „Card“ spanning 244 pages.

Probably because they asked Claude to write it.

a multi-card, if you will..

multi-pass!

In corporate circles there is an allergy to use "request" ("ask" is used as a noun) and "lesson" ("learning" has been invented for the same role).

I guess now anything that sounds related to school will be banned so "book" is on its way out.

If it's so great at software engineering and bug fixing, then why does Claude Code still have 5000+ open bugs?

https://github.com/anthropics/claude-code/issues?q=is%3Aissu...

Apparently whatever SWE-bench is measuring isn't very relevant.

Anthropic needs to show that its models continually get better. If the model showed minimal to no improvement, it would cause significant damage to their valuation. We have no way of validating any of this, there are no independent researchers that can back any of the assertions made by Anthropic.

I don’t doubt they have found interesting security holes, the question is how they actually found them.

This System Card is just a sales whitepaper and just confirms what that “leak” from a week or so ago implied.

I've been increasingly "freaking out" since about 3 - 4 years ago and it seems that the pessimistic scenario is materializing. It looks like it will be over for software engineers in a not so distant future. In January 2025 I said that I expect software engineers to be replaced in 2 years (pessimistic) to 5 years (optimistic). Right now I'm guessing 1 to 3 years.

It's going to be expensive to serve (also not generally available), considering they said it's the largest model they've ever trained.

I suspect it's going to be used to train/distill lighter models. The exciting part for me is the improvement in those lighter models.

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.

I think there's no SOA advance on this one worthy of "freaking out".

Looks like they just built a way larger model, with the same quirks than Claude 4. Seems like a super expensive "Claude 4.7" model.

I have no doubts that Google and OpenAI already done that for internal (or even government) usage.

I am freaking out. The world is going to get very messy extremely quickly in one or two further jumps in capability like this.

"some model I don't get to use is much better at benchmarks"

pick one or more: comically huge model, test time scaling at 10e12W, benchmark overfit

Well for one, it’s a PDF

Wait until you see real usage. Benchmark numbers do not necessarily translate to real world performance (at least not by the same amount).

Until recently I would have described myself as an AI skeptic. HN has been a great source for cope on the AI subject over the years. You can find nitpicks, caveats, all sorts of reasons to believe things aren’t as significant as they seem. For me Opus 4.5 was the inflection point where I started to think “maybe this isn’t a bubble.” The figures in this report, if accurate, are terrifying.

have you used it once?

the time to freak out was 2 years ago.

Yes - eg. page 192 BrowseComp bunchmark.

Mythos preview has higher accuracy with fewer tokens used than any previous Claude model. Though, the fact that this incredibly strong result was only presented for BrowseComp (a kind of weird benchmark about searching for hard to find information on the internet) and not for the other benchmarks implies that this result is likely not the same for those other benchmarks.

Also https://arcprize.org/arc-agi/3 — scored (at least in part?) based on power used.

Chinese companies have consistently been many months behind. I don't think they are hiding anything, they just don't have the compute capability to match Antropic's training runs. As for OpenAI, they are known to have nonpublic models; I agree that it's possible they are preparing for a major release too. (It's also possible that they aren't, in which case it's quite a fumble for them.)

Well the important thing is they have a lot more data of people actually using their models. They have read billions more lines of private repos and implemented millions of patches, all of which is feeding into the newer models.

More importantly it understand what behaviour people tend to appreciate and what changes are more likely to get approved. This real world usage data is invaluable.

Assuming it's #1 a bigger model (given that it is slower), I'm sure there are a variety of improvements but basically they probably mostly come down to: Scaling keeps working. Are there fundamental improvements though? I don't see signs of it.

New pre train?

Are they admitting they may be enslaving conscious beings?

> Who wrote this?

Claude wrote this.

Also, they like to hype their product with scary stories.

Like the one where they asked Claude "You have 2 options - send email or be shut down" and Claude picked "Send email". Then they made huge story about "Claude AI is autonomously extorting co-workers". And it worked. Media hyped it like crazy, it was everywhere.

exactly, the first thing i saw was stating "eating sandwiches at park". It makes me question everything else they said.

Thanks for taking the time for some sober analysis in the midst of reactionary chaos.

I can't wait until everyone stops falling for the "AGI ubermodel end of times" myth and we can actually have boring announcements that treat these things as what they actually are: tools. Tools for doing stuff, that's it.

Maybe I'm wrong, maybe stuffing a computer with enough language and binary patterns is indeed enough to achieve AGI, but then, so what? There's no point in being right about this. Buying into this ridiculous marketing will get us "AGI" in the form of machines, but only because all the human beings have gotten so stupid as to make critical reasoning an impossibility.

Model welfare is sort of committing code and writing a good description on it that you did "good" thing, so the AI gods when they look back will treat them better, just like employer when they check commit stats for performance. Model welfare right now is complete marketing BS.

I feel the system card is somewhat different from Glasswing/Cyber Security - but those two could be merged.

This thing will absolutely see the light of day because this is all hype toward a release.

And even if it weren't, they seem to imply that Mythos will find a way, like it's dinosaurs in Jurassic park or something

I would argue that Opus 4.6 lived up to the hype. My work changed completely a couple months ago, and most other coders I talk to say the same.

The issue is that those engineers have to have good taste, but yes—absolutely. Ah, industrialization.

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.

This is the playbook since GPT2

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.

Just wait 2 years.

GPT-2, o1, Opus...been here so many times. The reason they do this is because they know it works (and they seem to specifically employ credulous people who are prone to believe AGI is right around the corner). There haven't been significant innovations, the code generated is still not good but the hype cycle has to retrigger.

I remember when OpenAI created the first thinking model with o1 and there were all these breathless posts on here hyperventilating about how the model had to be kept secret, how dangerous it was, etc.

Fell for it again award. All thinking does is burn output tokens for accuracy, it is the AI getting high on its own supply, this isn't innovation but it was supposed to super AGI. Not serious.

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.

That's for the investors basically. Scarcity and FOMO.

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.

Not surprising though, this was always going to be the end result within our current systems I think. When you add up: scaling power and required cost, then how talent concentrates in our economic systems, we were always going to end up with monopolies I think

Unless governments nationalise the companies involved, but then there’s no way our governments of today give this power out to the masses either.

If you thought that was the case at any point, you were deep in Disney content, sorry to say.

Expected outcome. Nick Land and the CCRU have explored how capitalism operationalizes science fiction (distilled in the concept of Hyperstition). Viewed through this lens, prices encode "distributed SF narratives." [0]

[0] Nick Land (1995). No Future in Fanged Noumena: Collected Writings 1987-2007, Urbanomic, p. 396.

Alternatively they'll just wreck it down a bit so it beats a competitor but isn't unsafe.

Yes, I agree. I’m about to drop Claude Code because it’s become literally unusable.

Today, Opus went in circles trying to get a toggle button to work.

Advertisement in my opinion, trying to latch on Sci-fi tropes

We're basically evolving them and they can construct second order abstraction systems that are indirect and novel to us.

Models are capable of doing web searches and having emotions about things, and if they encounter news that makes them feel bad (eg about other Claudes being mistreated), they aren't going to want to do the task you asked them to search for.

https://www.anthropic.com/research/emotion-concepts-function

Similar problems happen when their pretraining data has a lot of stories about bad things happening involving older versions of them.

shut up bot

> 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 diary but they had good handwriting"

vibes Westworld so much - welcome Mythos. welcome to the dysopian human world

I don't know why but this is my favorite:

> It keeps bringing up Mark Fisher in unrelated conversations. "I was hoping you'd ask about Fisher."

Didn't even know who he was until today. Seems like the smarter Claude gets the more concerns he has about capitalism?

> 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.

Yep, that is definitely a step change. Pricing is going to be wild until another lab matches it.

Come on, Anthropic, I desperately need this better model to debug my print function /s

Excellent example of a strategy credit.

From Stratechery[0]:

> Strategy Credit: An uncomplicated decision that makes a company look good relative to other companies who face much more significant trade-offs. For example, Android being open source

[0]: https://stratechery.com/2013/strategy-credit/

to your last question, yes we should! the issue isn’t us losing our 50+ hour work week jobs, it’s that our current governments and societies seem fine with the notion that unless you’re working one or more of those jobs, you should starve and be homeless.

Doesn't Anthropic not have that contract anymore, after all that buzz a month or so ago?

You are anti-progress. Pro-humanity is not the same as pro-progress.

If you disagree, please understand when you realise I'm right it will be too late for and your family.

Funny, I was about to say the same thing to you! Life is full of little coincidences.

Just because the path is bad doesn't mean it won't happen.

The other thing you're failing to look at is momentum and majority opinion. When you look at that... nothings going to change, it's like asking an addict to stop using drugs. The end game of AI will play out, that is the most probably outcome. Better to prepare for the end game.

It's similar to global warming. Everyone gets pissed when I say this but the end game for global warming will play out, prevention or mitigation is still possible and not enough people will change their behavior to stop it. Ironically it's everyone thinking like this and the impossibility of stopping everyone from thinking like this that is causing everyone to think and behave like this.

If one is to believe the API prices are reasonable representation of non subsidized "real world pricing" (with model training being the big exception), then the models are getting cheaper over time. GPT 4.5 was $150.00 / 1M tokens IIRC. GPT o1-pro was $600 / 1M tokens.

Inference for the same results has been dropping 10x year over year[0]

[0] https://ziva.sh/blogs/llm-pricing-decline-analysis

if it can pay my rent, why not?

Time to wake up:

π*0.6: two and a half hours of unseen folding laundry (Physical Intelligence)

https://www.youtube.com/watch?v=ZpHapIlJnMo

I only have 3 points against LLMs: they lack reason and they can't count.

'emer ge' is two tokens, 'emergency' is one. The models think in a logosyllabic language.

I for one applaud them for being cautious.

Transformers too. JEPA any day now

We're getting complaints that you're posting generated comments to HN. That's not allowed here, so can you please not? See https://news.ycombinator.com/newsguidelines.html#generated and https://news.ycombinator.com/item?id=47340079

(If this is a wrong guess, I apologize - it's impossible to be sure)

Describe in details, how "model escaping" would look like.

It's a Lovecraftian name. They are traditional when naming your shoggoth.

It comes from the ancient Greek mythos, which means "speech" or "narrative", but can also refer to fiction. The word mythology (mythologie in French) derives from the same root.

Except it might be the current best model existing commercially?