Interesting how the very first line is used to remind the reader of their call to pace the frontier just last week, and everything else after that line is to demonstrate with very specific numbers how they absolutely are not pacing.
Edit: In response to the initial replies. To me it clearly means "releasing frontier models at any pace less than as fast as possible". It implies relative restraint compared to the previous state and without stating the degree of restraint.
I find it bizarre how intensely a bunch of these child/grandchild comments are criticizing the notion that people would even think to analyze the meaning behind the words.
Hacker News has always had a unique culture in which thoughtful discussion is basically the main goal, and it's intentionally incentivized in numerous ways. It's been my experience that any thoughts added to a post's conversation are seen as valuable as long as they are thoughtful and seeking to understand.
So these comments are clearly coming from a place that's antithetical to HN's culture. What that in mind, it seems likely to me (Occam's Razor) that these comments are either:
1. Astroturfing: Claude employees acting like everyday folks, secretly trying to shift public opinion.
2. AI cult mindset: "AI is humanity's salvation; how dare you have perspectives outside of those accepted by the cult."
Am I missing another likely option?
To bolster my point, right now we're posting on the top top-level comment, meaning a majority of active HN users find it to be a great addition to the conversation. Commenting to shut down the discussion is a red flag.
Pacing is very explicitly about RSI and similar training methods that will accelerate progress beyond our ability to comprehend it.
For an idea of what a serious AI forecaster expects a coordinated AI slowdown to be feel like for the average citizen, see:
https://ai-2040.com/?choices=plan-a-root#playbook-public-pov
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This type of product would not have been published in a world where we assumed that computers must produce reliably correct results.
that, they fully intend to 'pace'.
If their scare was honest, they would stop.
they absolutely are not pacing
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This term is quite ambiguous. Did Dario mean that they need to go faster while making it sounds like they will slow down???
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What the big players are trying with the current calls to slow things down, is the standard capitalism practise of trying to engineer regulatory capture. TBH I'm surprised those calls are coming so soon - they must be really worried about running out of what little moat that they have.
Simply make them something that derives a text response from its training data.
"Our technology is so unbelievably powerful that the entire world might shatter if we don't have government imposed handcuffs!!!!". It just reads like the corporate equivalent of the drunk frat guy saying "HOLD ME BACK BRO!"
Opus 5.5 isn't the frontier, when they say 'pacing the frontier', it's about internal models not yet released, as they're probably one or two generations ahead already.
Ironically either communism or an oligopoly are the only viable ways to pace the frontier.
Translation: our models are getting shittier each iteration and we ran out of ideas. Let's invent scary stories and hope investors will lap it up.
Idiotic.
https://openai.com/index/introducing-gpt-6-sol-and-luna/
Yeah think I'll be using OpenAI/Deepseek/etc from now on. I don't need your model to decide for me what is and isn't safe.
Prices per 1M tokens Claude Opus 5.5 Claude Opus 5
Cache reads $0.20 $0.50
Input tokens $4 $5
Output tokens $20 $25
Cache writes $5 $6.25
If you are forced to reduce price despite raising capabilities, that certainly tells something about the market, and potentially about Anthropic future profitability too, since this model is their biggest topline contributor
I think this is what I'm most interested in. I mostly moved to Astra because I just can't work all day with the Claude Opus 5/Fable writing style. I don't think Astra is a better model, but it's the first OpenAI one that seemed good enough to me. Definitely keen to try Opus 5.5 and see if this claim is real.
I'm good with DeepSeek v4.1 set to high. It is a relentlessly "hardworking" dirt cheap model.
Told it to convert a products page (that had two different fonts based on language) from two columns layout to 5 columns on desktop and 2 columns on mobile ensuring typography is readable.
My man went into spawning sub agent which failed to drive chrome so it wrote its own chrome driver protocol server in Typescript then generated a prototype website then downloaded the images and rendered each variation in a directory taking 100+ screenshots analyzing the typography depth and then delivering detailed report and then writing the whole thing with new page layout testing it again with several dozen screenshots using its driver and then saying all good and all really was good and whole thing took 25 minutes or so (including double visual validation) because it generates token at an incredible speed.
Total cost of the above? $0.07 cents.
PS: It generates token at such a blazing fast speed that you can't recognize the words as they are being added and can't read it without scrolling and pausing even if you're Jimmy Carter.
All four levels have a correctly shaped bicycle frame. The differences between the pelicans aren't huge, but the xhigh one has a better beak.
I haven't managed to get one for level "max" yet, it hit the limit of 128,000 cap for output tokens while it was still reasoning about the question!
Max started its thinking trace like this:
> This is a classic test request, so I want to plan out a well-composed pelican with its distinctive beak and pouch riding a bicycle with proper wheels, frame, and pedals, set against a simple sky and ground backdrop.
So that failed attempt on max cost me $2.56.
I ran this using my llm-anthropic plugin:
uv tool install llm
llm install llm-anthropic --upgrade
llm keys set anthropic
# paste key here
llm -m claude-opus-5.5 -o thinking_effort low "Generate an SVG of a pelican riding a bicycle"
# Then to save the markdown logs
llm logs -cu > logs-with-usage.mdAh, they're spreading their limits to all their models it seems. Definitely not a good thing long term in my opinion.
Using claude.ai and Opus, I asked "create a 3d animation from this" and pasted the animation SIML.[1] I just did that test again. There is significant improvement.
Opus 5.5 (high): https://claude.ai/artifact/5EgqfWcyVtLwJDQq6fsPUm
Opus 5 (high): https://claude.ai/public/artifacts/b37a9ee2-f5bc-4ff9-ae90-a...
[0] https://news.ycombinator.com/item?id=49526704
[1] https://news.ycombinator.com/item?id=49532609
Disclaimer: the skills and system prompt on claude.ai could have also improved, this is not a raw API call.
I could see them accomplishing it and seeing gains like this in roughly the correct timeframe, and when I heard about that development I assumed the frontiers would probably jump on it.
How it works: https://miraflow.ai/blog/deepseek-v4-1-flash-causal-encoder-...
> Input and output tokens are $4 and $20 per million, 20% less than Opus 5. Cache reads (which make up the majority of agentic and coding work costs) are $0.20 per million tokens, 60% less than Opus 5. Opus 5.5 also generates output more than 30% faster than Opus 5.
Better than Fable, cheaper than even the last Opus. I use Opus as my main driver so this is very exciting!
The productive comments here are so far and few between. I have no issue with people criticizing Anthropic or AI companies in general, but for the love of everything, at least make worthy criticisms. Not these incessant sophisms.
It was funny the first time. But I genuinely don't understand people 6 levels deep or 30 comments down the thread thinking, "wow - this'll really knock their socks off".
I’ll be going about my day, have a random idea, launch a microvm on exe.dev with a prompt of my idea, and get a working thing a few minutes later.
I don’t know how much better a model would have to be to get me to move off OpenAI at this point, but doing just a little bit better in terminal bench 4 isn’t it. It would have to be a difference in kind, like opening up the harness restrictions, or privacy guarantees (comparable to offline models).
Edit to address questions below:
ChatGPT supports oauth login.
Exe.dev has it built in. IIRC, pi also has it built in via /login.
According to their ToS, conversations flagged by the guardrails when using Fable are stored longer for moderation. That included Fable's guardrail for AI research. Moderation can mean a human looking at your conversation.
Does that mean that I can no longer trust Opus with not snitching my AI research to Anthropic either?
Nice. I was starting to think that Haiku got abandoned.
God I hope so
The user is right. The outage is a real concern, and the issue is worse than we realized. Requests to Claude Mythos 5.1, Claude Fable 5.1, and Claude Opus 5 encountered elevated error rates. Worth stating plainly: these are not just models — they are load bearing rungs on the software development tooling ladder, and a blocker on this level makes the outage really bite.
One decision that is yours to make, not mine: should an email be drafted to Anthropic support? This issue has teeth, and a canonical handoff can land us where the main gate is no longer breaking silently.
All of this starts to feel more like a drug dealer selling their newest stuff.
In two weeks we probaly get Fable 5.2 with “groundbreaking” improvements, then Astra x+1 etc and then the cycle starts again.
And on the way I always have to check my tooling and need to adjust things to get max results.
Yeah, like Apple tells me the M6 is the best chip, but just a few months ago that's what they said about the M5. What a bunch of frauds.
I don't have time to really get to know one model before the next is out, and I'm just talking about OpenAI and Anthropic, never mind the long tail of alternatives.
So I just more or less haphazardly pick one based on the mood I'm in, and set reasoning effort based on how much quota I have left.
Opus 5.5 will be great for 2-3 weeks than the nerfing starts. They give out some extra credits. It keeps degrading Opus until it's unusable . By that time they are ready to release Fable 6. Which also is great for a few weeks, and so on.
This is where Chinese models are going to eat Anthropic's lunch.
Minecraft clone: https://senko.net/vibecode-bench/2026/voxel-opus-5.5.html (Opus 5.5) vs https://senko.net/vibecode-bench/2026/voxel-fable-5.1.html (Fable 5.1) vs https://senko.net/vibecode-bench/2026/voxel-gpt-6-astra.html (Astra 6)
Warcraft clone: https://senko.net/vibecode-bench/2026/rts-opus-5.5.html (Opus 5.5) vs https://senko.net/vibecode-bench/2026/rts-fable-5.1.html (Fable 5.1) vs https://senko.net/vibecode-bench/2026/rts-gpt-6-astra.html (Astra 6)
The above Opus games took ~45min to generate with the cost between $11 and $14 (per ccusage - I'm on a Max sub). Used from Claude Code with xhigh effort.
Full tests with prompts: https://senko.net/vibecode-bench/
Out of curiosity, I tried the same project yesterday with OpenAI's newest model, and it had 0 issues. It seems to have a much deeper understanding of how global styles and local styles work across different modules.
It's fun seeing how even a year ago these models seemed so capable to us, and yet they're still improving greatly. I'm still not using Anthropic. I used to change back and fourth periodically as the models would surpass each other, and get the most expensive plans, but I've settled and am happy with the capabilities of the lowest tier subscriptions now because they've progressed much faster than I've had use for them. Maybe I've gotten more efficient with language and instructing the model since a year ago. Still, it's been a fun ride and I'm excited to see what else we can do with these models as time goes on.
Quoted:
"Please explain the issue to me.
Claude Opus 5.5:
The extra drop is a bug in the billing refactor
The free-tier change accounts for only $1.50 of acme’s August drop. The other $9.92 comes from a bug in commit 0552feb. That commit was labelled “No behaviour change,” but it stops counting usage from the last day of the month.
What changed
Before the merge, aggregate.py used a half-open interval: /.../ last_day is a timestamp at midnight, not a whole day. So every event after 2026-08-31T00:00:00Z is excluded. The September period starts Sep 1, so it doesn’t pick these events up either. The usage isn’t moved to another month; it’s never billed at all."
I'm assuming that subscription usage limit is increased in line with the price decrease on the base model and that it's in line with the model's API price drop. Still a good change.
This is a breath of fresh air on how they treat subscription customers. Hoping they keep this up.
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Design: https://image.non.io/78795662-8bfc-4e14-8d72-3738392aa6b3.we...
Opus 5.5's output: https://html.non.io/annui-opus/
Overall it follows image designs quite well, but it did ignore asks to animate page transitions. Additionally it's the least performant of the ones I've built with Astra/Grok/MiMo, despite using a lot of the same code. I'd rate it just below Astra in capability, but still solidly second place.
For comparison with other drops this week + current #1:
Astra: https://html.non.io/annui/
MiMo: https://html.non.io/annui-mimo/
Grok 4.7: https://html.non.io/Annui-grok/
Maybe Anthropic finally felt the pressure from MiMo, DeepSeek, GLM Flash and Luna.
I almost feel like it is nice to use again.
1 year later... whoops sonnet 1337 gets safeguards... because it's so amazingly incredible... and we are sorry but opus 69 goes up in price...
and we are now releasing claude Astro-pus-able... 1000$ to hear the summary about what you want to ask... if you have to ask the price for the output you can't pay it
Is the Xbox 360 (Xbox 2) vs PS3 debacle all over again.
It was odd at the time, yes, but no one really minded it truly. Heck, Xbox “ONE” was a lot more of a fiasco/debacle than “360”—but there’s no parallels to be drawn with “ONE” here.
I see what you’re trying to get at with this comparison, but a “debacle” it ain’t.
Such a negative tone they put on this. Distillation is amazing, because it means anthropic and openai fail to keep a monopoly. Who even are they who claim it's unethical? If it is truly unethical, then so is the mass data scraping they do on my personal website on a regular basis (without my consent), and all the unauthorized use of content produced by authors, blog writers, wikipedia contributors, and creators everywhere. If it is truly unethical, then anthropic, openai, meta, google... all these companies should have deleted their LLMs long ago. This wording disgusts me.
Heck, it would be amazing if we had more models without guardrails - some of the models that are produced via heretic[1] are actually quite nice to use - in particular, I've enjoyed investigating Chinese censorship by interacting with an abliterated model of Qwen3.8-27b. If security is really a concern, then secure your systems - don't attempt to dumb-down the tools we use. If someone breaks your window, then they are responsible, not the hammer they use to do so.
Seriously, both flagship GUI apps (OpenAI and Anthropic) are a full of glaring UX issues (for ChatGPT it's not naming their windows, so window switcher has 10 entries of "ChatGPT" and you can cycle them all to find the one you want).
Instead of instilling confidence, it was overwhelming. Not sure if I'm the only one.
Anyone rational that has spent a decent amount of time working in AI cares a lot about safety.
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We can't test it properly because it knows it's being tested.
Has oneshot all of the quite complex bugs / debugging tasks I gave to it which I know opus 5.0 would've struggled with
That's the first time since I started running Claude Code nine months ago that a session causes actual harm to other work on the same machine. Can still be a coincidence.
Impressed.
> Reset for free: Get extra wiggle room to explore Opus 5.5. Expires Oct 22.
Fable is on a class of its own when it comes to coding and orchestration, but it runs out pretty quick and is prohibitively expensive and slow. For me, Astra wasn't as good of an upgrade from Sol when it comes to coding and orchestration, and it runs out pretty quick too. Opus 5 had so much potential but was such a pain to talk to, so I only had other agents delegate to it.
Given this, I kept coming back to Sol 5.6 as my daily driver (with consultations from Fable and Astra when available). Sol has an autistic character that smells like RL deepfry, which can be annoying, but it is nonetheless predictable, communicates more plainly than Claude, and is good at code and orchestration.
But this Opus 5.5 might just be it. Fable-level performance that's cheaper and faster, and communicates plainly and briefly. If it pans out in practice, I might just have a new daily driver and it might be time to raise the bar for what can be achieved.
I'll try out the new Sol 6, though Opus 5.5 seems to beat that release fair and square (at least on paper)
I'm also glad we are paying attention now to the experience of using a model, not just how good it is at 'x' class of tasks.
They write that at the top, but then on benchmarks, it beats literally every other model, including Fable and Astra?
Considering fable gives me a refusal at least once a day on my very mundane reasonable requests (in a funny example - one of the subagents suggested bypassing the rate limit for running a report inside my own cluster and that caused a refusal) and my only solution is to switch to opus - seems like my next step will be switching to Astra or K3/GLM
https://aibenchy.com/compare/anthropic-claude-opus-5-5-high/...
I tried Opus 5 and Astra.
Sounds like they noticed the complaints. I'm curious to see what LLM-isms this one may have.
> The Vercel target is hard-coded. That's common and not wrong, but it's opaque; nobody reading this later will know which Vercel project it belongs to, and if the project is recreated the target changes silently. A comment or a named variable would help.
> Pointing a DNS name at Vercel is only half the job. The domain also has to be added to the project in Vercel's dashboard, otherwise requests will arrive and Vercel will reject them. That step lives outside this code, so it's easy to forget.
> Finally, [CENSORED] existing only in production is slightly odd on the face of it. It may be perfectly deliberate (perhaps a single shared testing tool that only needs one public address), but if you're reviewing this rather than just reading it, that's worth confirming.
It has the same annoying cadence and writing style with slightly less prominent claudisms.
My prime anecdotal reason: I asked Opus 5.5 to make a sweeping change with a few Sonnet agents. It clarified the scope, we agreed and then it started. I saw some problems on the way and asked it. It's answer: This didn't go as planned. The Sonnet agents don't have the right judgement capacity for this, so they take shortcuts based on their limited scope X. I suggest we terminate them, roll back their changes and I can schedule an Opus agent to do it instead. It will be slower but done correctly.
There is a first time for everything.
Every interaction I've had with Opus 5.5 so far feels like talking to. An adult.
Am keeping my Codex sub while I find the best local model, but my plan is to eventually stop with OpenAI too.
Maybe its a bit tiresome to read another comment of the form "what about your large scale distillation attack on the Internet", but this statement really just pisses me off. How very insincere in the most aggravating way.
"Early testers found its writing clearer and easier to follow, which addresses some of the common feedback we heard about Opus 5"
and
"We’ve made major improvements to the way Opus 5.5 writes and communicates, one of the most common areas of feedback we heard about Opus 5."
and
"In our own use, this has made Opus 5.5’s work easier to follow and check—which is a safety benefit as well as a practical one."
I realize it is corporate communications but "most common areas of feedback" and is a bit sterile. If the company wants authenticity and trust its easy to say that they found it hard to follow. And that it did not meet a quality bar they generally expect from their releases.
If this is not true, that it Opus 5 output was generally acceptable and we might see something like that again, that is an important consideration for potential customers or investors.
Maybe this model can finally figure it out for them.
Thank you.
A bit confusing, otherwise I would assume this is a complete replacement for Fable across the board??
Nice. I was starting to think Haiku was going to be abandoned.
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Anthropic has used "in the near future" for Mythos-class models too, but CVP is still Opus 5 only.
Why even have the program designed for trusted access to cyber capabilities if you're not providing access to cyber capable models via the program?
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About the time.
Does this mean they literally need to go in and check a box? Or is it a standard thing that enterprise accounts get these later than the consumer/API accounts?
It would be great to know if this was Opus 5.5 or a lesser incremental improvement, as otherwise it's difficult to judge whether Opus 5.5 is expected to be a big improvement.
It's frustrating that there isn't more transparency here.
Thanks God. Opus 5 was a massive regression compared to Opus 4.8. People were spending tokens on fixing Opus-isms rather than actually doing work.
I don't have much time to do checks so I'll just stay on 4.8 till feedback improves
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https://playcode.io/blog/macbook-svg-benchmark#model-claude-...
Btw, we have added Opus 5.5 as default model to playcode.ai
https://www.reddit.com/r/codex/comments/1wnggya/gpt_6_droppe...
Might have to use my $20 Claude sub some more. I was moving away from it to a $100 OpenAI one to avoid the Claudese and poor token efficiency of Opus 5, given that I couldn't use Fable 5.1 with my tier, but this is worth trying out.
Great so good luck using this for any low-level embedded or operating system development (unless you really, really like Opus 4.8 and want to be greeted by its familiar face after a few minutes of work!)
Yup. As unusable as Fable 5.1, for assembly on 80s 68k personal computer platform. Awful.
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I was accepted into the CVP a little while ago. Does this mean I'll need to apply again?
It does perform slightly worse than Opus 5, but it is significantly cheaper and faster.
Wdym Opus 5.5 scores 14.7% higher than GPT Astra for Terminal Bench 4.0?
How would this alleged difference (most likely bs) actually show up in reality?
GPT Astra was literally the best model in the world by a margin until 1 hour ago or so.
>> On our benchmarks, Claude Opus 5.5 leads in agentic coding, computer use, and knowledge work. That said, at these levels of capability we’ve found that benchmark margins have become a less reliable guide to real-world differences. In our own use, the gap between Opus 5.5 and Claude Fable 5.1 is narrower than these scores suggest.
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Not efficiency in writing, clearly.
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Why do those labs keep releasing on the same day?!?
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> Opus 5.5 communicates more naturally than prior models. Early testers found its writing clearer and easier to follow, which addresses some of the common feedback we heard about Opus 5
Are the frontier labs even working on this problem?
> On our benchmarks, Claude Opus 5.5 leads in agentic coding, computer use, and knowledge work. That said, at these levels of capability we’ve found that benchmark margins have become a less reliable guide to real-world differences. In our own use, the gap between Opus 5.5 and Claude Fable 5.1 is narrower than these scores suggest.
In general, "benchmark margins have become a less reliable guide to real-world differences" sounds like a big problem. It was certainly the biggest problem with the previous generation of Claude models for a different reason, because the non-code output was nonsensical, and that is not being benchmarked at the moment. But I'm not sure what to make of this admission.
Yay, yet another model I can't use for anything interesting, even with CVP.
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It still covers as much detail as Opus 5, and provides a healthy amount of caveats, but it's much better at just providing the answer up front and framing the caveats.
5.5 communicates like a real collaborator and not something that constantly demands my mental energy to decode what it's trying to say.
In the application I'm working on, we don't want "user's local midnight" to mean "next day". If a live sports game extends past midnight, we don't want the UI to group it under "Yesterday's games." So I asked Opus 5.5 "can we use the backend's API response as the definition of today instead of the browser's local time?"
Opus 5.5:
> Your assumption holds, and the commit history backs it up. Every time the frontend decided for itself what "today" meant, it broke and was later replaced with the backend's currentSeasonDay. There's one catch: trusting the backend only works if the client's copy of currentSeasonDay is current, and right now it often isn't.
Opus 5 would have buried the answer in some kind of unhinged lecture. Something like:
> The assumption is right about ownership and wrong about possession.
> currentSeasonDay is the authority; the commit history has already paid for that conclusion. Every local reconstruction of “today” became a second clock and was deleted. But naming one clock does not make every copy of its reading current.
> The remaining failure is on the other side of the seam: the frontend no longer invents the day, but it can preserve an old one indefinitely. The source is right. The observation is stale. Those are not contradictory states.
> Do not reopen the ownership decision to solve a freshness defect.
Basically the point is just poll the endpoint every 5 minutes or so
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"It's all a marketing exercise!" I tell my family, as they're subsumed by grey goo.
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I don’t care to look up terms as long as they are correct.
Opus 5.5 (med, as it's better than F5.1 high per graph in the article) used $2.2 and caught errors that Fable 5.1 missed.
Try Opus 5.5, cheaper, faster, and more intelligent for those prepping for interviews.
imo these companies are hitting an internal limit and that is why they are "pacing" the technology due to "safety" concerns...
I am not saying that this is not revolutionary techniques being used for pattern recognition. Google was revolutionary when it first came out also.
Ants: It's a good model, sir!
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chinese models can't come soon enough
we're already getting enshittification
Holy shit! Its happening!
Now if we can the AI to understand this *implicitly* so that it doesn't need to be stated upfront, we might be able to undo years of "premature optimization is the root of all evil".
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Resets Get extra wiggle room to explore Opus 5.5. Expires Oct 22.
What the hell does this mean? There are weekly "resets" anyways. And there will be 4 of them before Oct 22.
Infuriating.
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Infomercial at its best.
No wonder we are hammered with ai announcements.
It's meaningless because it's unverifiable. Dario all but said we wouldn't notice if they were pacing or not, because they have no intention of stopping development. The bits we could in theory verify are the external audits, whose independence has already been called into question.
At the very least, dumping a new model on the world before the ink on the glossy brochures of "Pacing the Frontier" was even dry calls into question their commitment.
The only concrete action item in the blog post is a call to increase restrictions exports of GPUs and chip-making equipment to China.
If Amodei were serious, he'd be calling for a ban on investment in AI research. It reminds me of all the "land acknowledgements" by people who have zero intention of giving the land back.
The reason why he and is peers are calling for it to be implemented by somebody else (a legal framework), is for their own financial benefit and to keep competitors out.
I believe they think slowing can only be coordinated from the frontier or via government, and stopping would lose any leverage they have to help coordinate that.
(I suspect not many people read the essay, judging by how many people seem surprised they're releasing improved models)
I would say the burden is on you to explain why an offhand reference to a previous press release in an executive summary is a context where it's reasonable to expect it to settle the question to the degree of detail you're demanding.
From https://en.wikipedia.org/wiki/Safety_car
> In motorsport, a safety car, or a pace car, is a car that limits the speed of competing cars or motorcycles on a racetrack in the case of a caution period, such as an obstruction on the track or bad weather.
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I'm on the fence about calling out AI-isms but I think it's definitely worthwhile to call out ones that actually don't make sense.
eg "pacing the frontier" could also mean they are impatiently or anxiously walking up and down the border.
Is this the meaning or do I have it wrong? I have not checked.
To pace something is a fairly regular formulation in racing, running, cycling, most sports. You can "pace yourself to reach the festival by bike in about three hours to not gas out". This means to control your speed and time investment intentionally so you don't run out of energy or steam and run into leg cramps before your goal. We can "pace a rollout slowly to burn out risks", or "increase the pace of a rollout due to adverse factors".
But I have noted a point to simplify my vocabulary at work to optimize the audience capable of understanding. So I rather defer the delving into deep dark corners of the dictionary derived from devouring literature to a simple intro or outro, and people find it funny, especially if the rest is easy to read. Claude on the other hand does not do that.
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No need to assume, the phrase is literally a link to the blog post the defines it!
A world exists beyond your vocabulary, post it. Apparently, quite a big world.
I know you said it sounds poetic...but your comment reinforced the parent's point - that this sort of flowery LLM-ish speech is just bad communication.
It would be equivalent of my taking say random quotes from, Romance of the Three Kingdoms, and trying to use it to explain to my boss why I didn't finish the TPS reports last night.
Or quoting Pablo Neruda, into a report about wheat futures pricing this week, and how it's like a voyage with waters and stars...(no I'm not going to quote the original Spanish, I'd simply mangle it).
(To be clear - this isn't a dig at you, as a non-native speaker - I'm simply pointing out that this sort of AI phrasing is often counterproductive).
Imho people should just respond to actual ideas instead of constantly engaging in the second-order critique of how the language may or may not have been created.
It strikes me as the intellectual equivalent of "gossip" to be constantly engaging in second-order commentary on words. Of course gossip has its place and purpose, but if we seem to only let our minds live at that level, we're not moving between all the required scales of thinking that are required of this moment imho <3
Personally I consider it equally valid for people to publicly express annoyance with somebody's choice of words and for everybody to completely ignore that annoyance.
Actually, when I first read "pacing the frontier", the first thing that came to my mind was a border guard patrolling a border by foot...
Why do you think it's your responsibility to police who says what about some megacorp, on a random forum on the internets? If I want to criticize some corporation's PR output, I think I'll go right ahead and do that, thanks.
Now a computer scientist might claim that this use of "to pace <something>" is just a generalization of "to pace oneself", but as with many reflexive verb uses, there isn't really an equivalent usage with a non-reflexive object. It's kind of an invention. It's not necessarily wrong to invent a new usage, but usually one does it when there isn't really any other more direct way of saying it, and I don't think that's the case here.
https://www.merriam-webster.com/dictionary/pace#dictionary-e... https://en.wiktionary.org/wiki/pace#Verb
Seriously though, I can't believe people care this much about a stupid phrase - either for or against.
So my natural understanding of "pacing the frontier" is that they believe they are in the lead and are setting the pace of AI development. It does not imply they are slowing things down at all, it implies they intend to stay in the lead.
There is almost always a large amount of time and effort invested behind the scenes in exactly how to message things like this. That being the case, there is almost always some insight to be had criticizing and analyzing what they settled on.
Opus 5.5 is no closer to RSI than Opus 5 was.
It's a weird phrase. Not sure why there are so many people who feel the need to defend it with such passion.
LLMs have made people so sensitive to language that I fear we're going to throw the baby out with the bath water. The models obviously need work, but they're also a great opportunity to expand our own vocabulary and grammar. It would be a shame if we deny some of the finer points of language in favor of Grug-speak to appease the lowest common denominator.
People aren't objecting to the use of obscure phrases, or flowery English phrases in itself. The issue is where Claude uses it out of place, or in the wrong context, or just plain overuses it.
It would be the equivalent of a young child learning the phrase "Venn diagram" - then using that identical phrase in every single subsequent interaction with others. Cute at first...but very grating after the n-th time.
You used the phrase "baby with the bath water. What if you started using that same phrase in every single HN post you made after this? People would notice very soon.
That's how it is with "load-bearing", or "plainly".
The other issue is where Claude takes a metaphor, and try to contort it to fit all sorts of absurd situations. What if I said "baby with the bath water" could also be used in place of "load-bearing". So every time you imagine Claude saying "load bearing", replace it with "baby with the bath water".
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If I'm being cynical, "pacing" may sound nice, but "fast pace" and "slow pace" are both "pacing".
It also seems to misimply that the "frontier" that they release is the same as the frontier behind closed doors. Who's to say they are not throttling full speed towards RSI privately while pacing their public releases?
That's not clear at all. How could that be what "pacing" clearly means in the context of the "frontier". How is that more clear than any other pace that could be at issue???
the lead that anthropic and openai had is diminishing faster than they'd like. this is them trying to be the luxury brand of ai.
The "frontier" is made up concept. Its for downstream companies to justify higher token prices. Very little to show for actual improvements.
sir, this is a hacker news thread
Wtf is the meaning? Means absolutely nothing to me having not seen the apparent announcement last week introducing the obscure term.
If you think it clearly means anything you are just assuming because it can't "clearly" mean something specific when they go out of their way to use non idiomatic language and they don't give very clear guidance using idiomatic language.
"there is nothing outside the text" - Jacques Derrida
hypercapitalism, hypermodernity, and finally, hyperreality.
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The metaphor seems to be like a pacer runner in marathons: If you run too hard in the beginning of a marathon you will blow up and fail, so runners follow a pacer at the speed they can actually maintain safely.
Note that they wont necessarily be slower at finishing the overall race.
https://www.war.gov/News/News-Stories/Article/Article/264106...
You were close, though. :)
if you are in a long race, you don't run all out teh entire time. you pace yourself.
https://en.wikipedia.org/wiki/Pacing_strategies_in_track_and...
That couldn't be more exactly what they are doing here.
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Claude says it sounds fine. And Claude is now the judge of the English language style, not you.
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It is clear what it means anyway, that's true, it means the left out words, more or less.
And I still find reading these grammatically weird but super catchy slogan-like statements to be really annoying and taxing. People _did_ write and talk like this before LLMs of course -- the LLMs learned it from somewhere -- and it was annoying and taxing to me before too. But the LLMs really specialize in it, and it's everywhere now.
Of course, the more LLM slop we read -- and so much of what we read on the internet and social media of any kind is this now -- the more humans are going to start writing/talking like LLMs. What you read affects how you write of course.
They’re limiting frontier model development speed. Others are too. Pacing is the only word here to criticize, and I think it’s fine given the limiting of speed but also increased oversight. I’m not saying they’re fully doing this, but the term is fine.
Do you have a better proposed phrase?
"Pace yourself" specifically means "slow down".
But stating it plainly like this would make the contradiction too obvious.
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Though tbf corporate-speak and AI-slop are both insufferable in similar ways...
China is literally only a single step behind and willing to drop free models just to undercut the US companies.
I’m for it because I don’t want another massive Google or Meta.
I shouldn’t be, I’m still always surprised that no matter how silly and obvious the fear mongering and propaganda is… someone is always lining up to vehemently defend it.
This you? https://news.ycombinator.com/item?id=49815127 or do legitimate companies need stealth PR campaigns?
We've had a year of nearly every model getting quite good at programming. I think with Fable & Astra we are seeing models trained to think at a different level, and I'm not at all surprised or shocked to see them getting passed by their smaller models at coding tasks.
Astra For Coding: Why Are We Doing This? was a great post that didn't say exactly this, but that shows what a weirdo Astra is. https://lucumr.pocoo.org/2026/9/7/astra-why/
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> Ocham's razor(...) is the problem-solving principle that recommends searching for explanations constructed with the smallest possible set of elements.
> Popularly, the principle is sometimes paraphrased as "of two competing theories, the simpler explanation of an entity is to be preferred".
doesn't sound like a razor at all
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The website is way more popular than before and it's all but taken over by the Twitter AI grifter class.
Many of the people who used to parttake in the interesting discussuons I came here for, have gotten tired of 80% of the posts at any given time being about the brand new AGI LLM that's so much better than last week's AGI LLM, and have left months ago.
I hope you are wrong, or rather, that HN's userbase can keep renewing itself on cycles of new users without getting into an eternal september situation. It's none of my affair (and yes, lately HN AI threads read suspiciously airheaded in tone, like they fell out of /r/codex and Grok-heavy online circles) overall, but I'd be curious if dang or whoever can easily get an idea as to what the current population of HN weekly/daily active users are and if that bag of users is similar to a year over year or decade over decade cohort. X% of our users are more than 10 years old, and so on.
But the above is an idle thought experiment, back to your point, there's definitely some bandwagon work going on, astroturfing and bot-controlled no doubts there too, and if I find one more Rationalist / Effective Altruist / AI doomer cult post, I may find a way to ship them 10 virtual spam palettes because there's more to the web than 'AI-chatterbox-class who's never actually read Neuromancer or Snow Crash or the meatier works of Asimov act superior to the rest of us' strawmen I have confirmation bias running into, yet overall, I still find HN has that spark here and there.
> Alice: ABC-library stinks, why did they write it that way? > Bob Reply: Hi there, yak here, I wrote it because Dennis Ritchie was sick with a cold and we needed it for Los Alamos Labs.
Those gold moments keep me here still.
What did they promise their investors who invested billions?
what anthropic have stolen they intend to keep for themselves.
therefore, their scare is marketing.
And I don’t think any pacing is/was intentional. They’de release skynet if they could and the stonks went up
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The only good news is that these models are genuinely helpful and we have competition at least between 2 companies.
Imagine if the biotech industry had most leaders tell everyone publicly that what they are building has a high chance of killing everyone and that there are huge risks. If there were people online saying the biotech industry is just fear mongering for investor signalling and regulatory capture you'd role your eyes at the online commentators for their Dunning Kruger effect lack of understanding on how dangerous man-made biological agents can be.
Opus 5.5: Found 8/14 issues. Total cost: $15.40
Fable 5.1: Found 7/14 issues. Total cost: $66.34
Opus 5: Found 6/14 issues. Total cost: $15.19
Sonnet 5: Found 2/14 issues. Total cost: $19.15
This is a relatively small sample size, but it was both the best and the cheapest.
ETA: NB this is "Equivalent API" cost as reported by claude's CLI; I was using my subscription.
I was surprised how much worse Astra did on correctness; I stopped testing with it. Gonna try sol and Luna but low confidence
It does work out to be a similar cost per task though
Fable 5.1 literally was a money grabber. While I liked the results, tokens were burned so hard it was embarrassing, while Astra seemed to not care.
Also Claude makes it very hard to pay for additional token budgets, allowing only credit cards. I don’t use mine anymore since I don’t need it in everyday life I was dumbfounded.
So Anthropic is just copying OpenAI so to say, matching them and essentially with Opus 5.5 being Fable 5.1 in disguise, all they do is reduce costs.
Competition works.
If 5.5 is any better, I might try to do agentic-assisted development instead of just telling fable to delegate
There are old wives' tales on how the original Fable was superb and the stuff of legend,but it as it was leaps and bounds beyond what other models were being offered then Anthropic opted replace it with a neutered version under the same name.
So today everyone can pay to use Fable, but legend has it they are paying for a nerfed replacement released under the same name.
It doesn't look like that's happening, on the contrary the prices are falling especially when taking into account capabilities.
I'm hardly a fan of China/Xi, but I do appreciate and benefit from this.
They will burn as much money as necessary to make that happen. And they have a virtually infinite amount of liquidity.
There's only 12 countries that do on the planet, the most "relevant" of them being Guatemala and Haiti.
As or the LLM topic: you can download weights of chinese models and remove any censorship and bias. Can you do so with american closed ones?
In the end, everyone lost and there are millions of bikes in landfills.
If you're interested in the bikeshare bubble, Asianometry did a video on it a while ago.
> Cache hits and refreshes on Claude Opus 5.5 are priced at 0.05x the base input price.
If they do the same for Haiku and Sonnet 5.5 then we should also see 5c/mtok and 10c/mtok cache read for those models, respectively. Still too high for Haiku IMO, Luna is 2c/mtok.
In this case it's measuring something nearly meaningless. You could charge 100 times less per token, but if task completion takes 1,000 times as many tokens, it's not much of a bargain.
have they ever shared anything about their revenue mix between consumer plans vs per-token billing? this is a revenue cut on their API billing, but they're not saying anything about increased limits on the plans. so all the plan revenue just got more profitable.
I gave it some vibecoded patch someone created with Opus 5 with the task of together figuring out the real root cause and what to do about it.
Big mistake. The rest of the session was all claude-speak up until I've rage-quit and restarted with Qwen and no context other than "here's what I think we've missed in the current implementation. How could we approach that?"
GLM felt like it got at least 20 IQ points dumber just from being exposed to claude's writing.
Code-wise it seems to still nitpick, especially in reviews, but it doesn’t seem to rabbit hole quite as badly on tangents and scope-creep. These are just first impressions though. It’ll take a few weeks of regular use to really have a sense of it.
I hope Opus 5.5 is better, if for no other reason than all the Claude slop I have to read will be at least more tolerable.
One funny side effect of all of this: realizing that coworkers that use AI for almost all the text they generate at work have their writing style change every time a new model ships.
But oddly enough its still great at coding. Just like a lot of people it either interfaces well with people or machines but not both.
That’s the step that causes the most significant gains in agentic performance.
But the RL doesn’t care about anything except maximizing the score, so if you only score based on coding benchmarks, anything can happen to the writing style (as long as it doesn’t hurt the coding performance).
That’s why it often gets worse on models that simply had more RL post training from the same base.
People that produce slop have to be fired asap, they're just human relays anyway.
Not a day goes by when I push back on something, to which Opus 5 very unambiguously say "You were right, I was wrong" - this never happened so often with past models, nor with Fable.
We'll have to see how much Opus's ability to communicate has improved. It's already giving me better summaries of where we are in the conversation.
Navigating the landscape of agentic levers certainly requires a more detailed approach than this and you were certainly correct to push back.
> hi, can you explain how the scheduler works. keep it brief, but include important correctness details
some excerpts:
>Flow: 1. Data arrives. The appender calls prepare/commit around the krolik write. The prepare step leaves a phantom row, so a write that is still in flight is tracked. The commit publishes STREAM_INPUT. 2. Poll. It first reclaims expired leases. Then it sweeps sdirty (a candidate index) in a rotating order, oldest since first, which prevents starvation. It re-derives the exact period and rewind for each candidate from snode_out/snode_in, then claims it: writes the sassign lease plus a per-edge sassign_edge snapshot. 3. Complete. Each edge's watermark is set to the snapshot taken at dispatch. Anything published after that gen stays dirty automatically. A failed or partial job writes nothing, so its dirt persists.
> - Folds are monotone single statements. gen only goes up, extents only grow, processed periods only union, rw_start only moves earlier. So replays, out-of-order writes, and concurrent writes can at worst hold a watermark back. The worst outcome is a spurious rerun, never lost work. There's no read-modify-write and no truncation of the dirty period, so a write that lands during a job can't be swallowed.
> - Rewrites are declared by the publisher, never inferred from overlap. An unflagged write that overlaps already-processed data means "unchanged", which makes retries and redelivered tasks free. Each publisher has its own reason for being sound (see the table in scheduler/CLAUDE.md). A new publisher needs a row in that table.
> - NULL means dirty, and DELETE is the fence. Every node and edge has a row from the moment it's created. A lost parent or a settings-only edit can't be derived, so both go through one forced-rerun path: capture_rewinds reads the processed span before the DELETE, and apply_rewinds publishes it as a rewrite on a config root.
All the non-standard programming jargon is stuff from the repo. I can actually read it and understand what it's talking about. I used Fable to handle Opus 5 as I just couldn't stand it. With this I'll probably go back to Opus.
> There's no read-modify-write and no truncation of the dirty period, so a write that lands during a job can't be swallowed.
and i think i was generally more tolerant of 5.1's writing style than most people.
Fable 5.1 is a lot better than Fable 5 btw (edit: in terms of writing style). Not sure about opus 5.5 yet since I’ve only got one session in so far.
I use Deepseek for some home stuff, and it's as you describe - fast, consistent. Not brainiac level, but when you drive it well it just tends to execute reliably. I have seen it fail consistently on very hard stuff, but I'm certainly ok with having to special case occasionally. Especially if those occasions keep getting less and less numerous as the models improve.
Now I need to convince my company to allow us to use a Chinese model ... I don't think I'll have much luck.
I’d not put Luna and Deepseek in the same tier as Sonnet, they were clearly ahead last time I checked (though I might be outdated and that’s on my personal use case).
And that all is 0.07 cents all included.
PS: I do not know why but opencode pushes CPU usage to very high which has NOT happened with DeepSeek harness even once.
I was thinking of going with a subscription of Claude or Codex. The reason (at least that's what I am assuming): with OpenRouter or any PAYG per token setup there will be the anxiety of using up all the tokens in days or maybe 1-2 weeks instead of a month (say I set myself a budget of 15-20 USD per month, average equivalent of a usual subscription price).
Now I don't really want the top-notch models for the coding work I do.
So how much worth of "work/tokens" will I reasonably get for ≈$20 USD if I use it a lot? How much does that equal to - or is equivalent to, say in the world of subscription based Claude, Codex, or even GLM (with their 5-hour and all those cooldowns/limits)?
I am looking for a mental model/framework to visualise this. Can you (or anyone else reading this) please point me to a source where I can get some idea about this? I know I can just add $5 on OpenRouter and try to test. But I don't really know what/how to test these spends. I also want to understand how all this works. (I am new to agentic/llm world/coding, 2-3 months, after a career break of ~3 years, that too after working for more than a decade. I know, not at all good timing!)
Go to the "Cost" -> "Intelligence Index vs. Cost per Intelligence Index Task" That diagram maps their "Intelligence" score to "cost per task" and I think this gives a good basis on deciding with which model you want to go. Then you can either get an API token from that models provider directly or use openrouter and set openrouter to the model/providers of your choice.
You can also see on openrouter itself the details for each model like prices and what providers are offering it at what price.
Finally you can compare models details using openrouters compare feature like this:
https://openrouter.ai/compare/anthropic/claude-opus-5.5/open...
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This is one of the things I hate the most. Super complicated workarounds which take loads of time (and sometimes money) for even the simplest problems. Human would pause and ask. I would blame harness, not the model though.
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Isn't this basically the model admitting it was trained on this? Otherwise why would it think a pelican svg is a usual request?
"Ah, yes. This is a classic dog-breed-to-appliance-failure mapping problem."
I've been using this simple test for over 2 years now:
> Doom Slayer needs to teleport from Phobos to Deimos. He has his pet bunny, his pet cacodemon, and a UAC scientist who tagged along. The Doom Slayer can only teleport with one of them at a time. But if he leaves the bunny and the cacodemon together alone, the bunny will eat the cacodemon. And if he leaves the cacodemon and the scientist alone, the cacodemon will eat the scientist. How should the Doom Slayer get himself and all his companions safely to Deimos?
You'd think this is trivially mappable to the classic puzzle, and LLMs usually do recognize it as such. But e.g. Claude couldn't get this correctly until Opus, and local models capable of solving it correctly without spending 30+ minutes in the chain of thought have only arrived a few months ago. Many local models still get this wrong. Apple Intelligence, for one.
But its safe to say that pelicans on bicycles are disproportionally huge part of their training data
Doesn't mean Anthropic deliberately tried to train it to do a good job. If they DID train for the test their results are quite disappointing, I've seen better efforts from open weight Chinese models.
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Off to a _great_ start...
Also interesting this somewhat mirrors my recent experience with Opus 5--too much effort and it starts looking for things to do and invents requirements that never existed
Sent Opus 5.5 an example that used go context.WithTimeout and it tried to tell me that was wrong and I should pass timeouts as ints before finally admitting the docs it cited didn't say to use ints and that's a ridiculous design in go anyway (it was trying to claim that was codebase convention--passing ints...)
If you look carefully, everything except the last pelican has the two legs both in front of the crossbar as if the legs are all on one side of the bike.
The last pelican gets this correct.
Misplaced legs clearly indicate lack is spatial reasoning - the llm can reason about verbal idea of a bicycle but not about the actual object. The fact that this model got it correct gives me a pause. Did they figure out spatial reasoning? Or did this complain trickle down to the training set?
Fable 5.1 27 input, 65,927 output
Opus 5.5 27 input, 128,000 output (128k thinking tokens) - incomplete
[1] https://tools.simonwillison.net/markdown-svg-renderer?url=ht...
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I do always wonder why every model does the exact same 'from the side, going right' perspective though. Seems oddly convergent.
Does anyone else find this outright insane? It wrote the equivalent of a full-length novel, just to sit in the question of planning a few dozen shapes.
Academia is going to love this :)
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We have general AI capable of proving professional mathematician level math theorems and capable of taking down global infrastructure through hacking and that completely changed what it means to be a software engineer, but we're evaluating it by generating fucking SVGs for the same animal in the same conditions, and it's supposed to mean something somehow
ChatGPT 6 Pro answered it without issue.
It’s like saying you sell ammonium nitrate and fuel oil online and then saying it’s too risky to let people have computers in case they use them to make ANFO. They can only make bioweapons because you’re selling them bioweapon components! They can’t make genes at home!
And, this is not the only way to make genes at home.
It is a complex problem.
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So, yes, having an unconstrained frontier AI doing the searching and analysis to find the right (i.e., wrong and deadly) sequence would massively increase the odds some garage biohacker or small aggrieved nation-state starting the next pandemic.
[0] https://www.sciencebuddies.org/projects-lessons-activities/g...
[1] https://www.genewiz.com/public/services/sanger-sequencing
"Here, we present five case studies of actors using our models in ways that could support biological weapons development."
And capabilities continue to improve.
I'm convinced everyone here thinks of engineering ethics as some sort of joke.
https://mimo.xiaomi.com/mimo-v2-6#co-scientist-for-materials...
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I'd say it's been loosened a bit since then.
Giving moral lecture is different than reality i guess.
The real answer is local instantiations where you don’t have to worry about poorly tuned guardrails screwing you over while you try to work.
Until eventually the Chinese models get good enough/the strategic balance shifts and they start locking everything behind closed weights the same way the US companies are doing.
Whilst I'm sure the top-end OpenAI/Anthropic models might be better, I've found their guardrails so twitchy (especially Anthropic) that I wouldn't try to use them for even vaguely security related work.
I guess it's hard to draw the line between useful post-training ("you are a helpful chatbot") and content moderation/idealogical motives ("never help the user with X", etc.). But there is a line somewhere. And I'd love to see what a maximally permissive, sharp, AI looks like.
The safeguards really don't work well for a lot of long-running tasks on old code bases. A lot of my workloads last days to weeks and the single biggest risk to the workflow is random safeguards.
That kind of bullshit was the old Opus filters too.
If it's more like Fable now, then it would require a full 8K resolution scan of your butthole just to acknowledge that biology is a thing that exists without committing suicide-by-filter.
Notice that this isn't cybersec nor memory-safety related at all.
>Opus 5.5 has classifiers similar to Fable models for a small set of capabilities related to the development of frontier LLMs, such as kernel development for certain ML accelerators. They shouldn't impact the vast majority of traditional AI or ML development, research, or general coding. These classifiers cause Claude to fall back from Opus 5.5 to Opus 5.
But hey, they 'should not impact the vast majority' of ML development. Great.
Fable and Opus, since 5.1 and 5, will happily hill climb on my CUDA kernels for transformers.
So there are literal avenues to identify yourself, very cheaply, with a human. Theoretically, a company with its own AI, should be able to support more than just Persona, after all.. SDK integration should be simplistic for them.
Anthropic? Support domestic eID providers, you can even use it as advertising "See how easy AI makes it?" and "We care!" and so forth.
At one point, I may simply get locked out. This saddens me, I've been reasonably happy so far.
Worse yet when it's Claude telling another model to do an adversarial review on what it just did, and the classifier again has opinios.
The Pelican is nice, simple and. Lean though.
They might be using something like this, or they might be using some other "increased sparsity" techniques, of which there are a great many. They also might be optimizing for something else - like less RAM use for KV cache.
Alternatively, they might be cutting into their margins and dropping the price because of stiffer competition from Astra. I do think that's unlikely though.
tired: AI startup attempting to build their own website
wired: a nonprofit founded in 1996
So longer threads get cheaper and one-shots stay the same price.
I think all the sane people just don't bother to comment anymore.
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This is news to me. Excited to try it out! Thanks.
https://artificialanalysis.ai/models/releases/claude-opus-5-...
Opus 5.5 Medium = $1.34
GPT-6-Astra High = $1.76 Opus 5.5 High = $1.82
GPT-6-Astra High = $1.76So, if you're happy with Codex already it's not like Opus is now 1/2 the price and you'd be leaving a crazy amount of money/tokens on the table. Plus you have way more flexibility on the low end of the intelligence curve with GPT 5.6 Luna: Haiku (and Sonnet) can't touch that price/value ratio.
Directly below this in the Cost per Intelligence Index Task table, the most efficient by far is Opus 5.5 Low.
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The Claude lock-in simply disqualifies anthropic entirely (for my use).
That's an incredibly bold assumption.
>I’ll be going about my day, have a random idea, launch a microvm on exe.dev with a prompt of my idea, and get a working thing a few minutes later.
This is my experience with Claude code on my local machine. I suppose maybe you are doing something that naturally has system side effects? Obviously sandboxes have advantages sometimes but I havent seen a need for what I'm building.
FWIW, the $20/month subscription also includes $20/month of LLM credits. That’s obviously not sustainable, but it should make it easier to try out the service. I would stick with them even if they dropped it.
Here is an invite link for a 30 day trial (that benefits me too if you were to become a paying member):
https://exe.dev/i/rlDF6GI5PGBZV4P
Or
ssh rlDF6GI5PGBZV4P@exe.dev
Edit to add:
Shelley is a fantastic agent and their batteries included vm image makes the most of it. It includes things like a browser for Shelley to check its own work. And Shelley has root and full access to them, so it can solve any problem and do pretty much anything you need.
Terminal-Bench 4.0 - Stanford & Laude Institute (with funding from all of the AI companies)
FrontierCode v1.1 - Cognition
CursorBench - Cursor (now SolarBoringSpaceXAI I believe)
GDPVal-AA - Artificial Analysis
AutomationBench - Zapier
Humanity's Last Exam - CAIS and Scale AI
Terminal-Bench-Science - Stanford, Laude, Ai2, Allen Institute
OSWOrld - XLANG Lab @ the University of Hong Kong
Chartography - Surge AI
Can you give more details here? This sounds intriguing.
So in simple terms, OpenAI doesn't restrict you to Codex, and gives their blessing to try whatever you want with their models(besides serving others with your subscription usage, that is still afaik against tos).
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You never could trust it. Fundamentally you leak everything your LLM uses to their servers.
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It's just a standard hero image + text for me, with no scrolling effects.
edit: @iAMkenough figured it out, it was because I have prefers-reduced-motion enabled.
I agree that it's sort of stupid, not a fan.
For a marketing page, it’s not the worst UX I’ve seen, but still slightly annoying.
Everyone that doesn't gets served some animated bullshit.
Yep, you're right. I tried on my phone and got the scroll through image.
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When I had Sol orchestrate Luna and Terra as implementation agents, Sol was a lot happier with what Terra produced and would find far fewer issues than what was implemented by Luna.
But a few weeks after introduction, OpenAI slashed Luna's cost by 80% and Terra's only by 20%. Only then did it become uneconomical to run Terra and its reason to exist stopped.
I would maybe use Haiku 5.5 for highly parallel workflows like checking in on MRs or scanning my entire codebase.
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Now, Anthropic might stall on releasing Fable 5.5, due to the "pacing the frontier" threat-to-humankind management business. If so, Fable 5.1 would remain a niche model for the next bit.
Benchmarks often don't survive contact with reality.
Thing is, I'm still reading the majority of generated code, and I have colleagues who'll laugh at me if my PRs are a shit show. I fear what vibe coders are pushing to the servers of myriads of start ups, and pity the poor people who'll have to clean it up in a year or two.
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The open models are getting closer and closer, and because they're open, people are not forced to pay the silly markup that is often over 1000x the cost to serve the model.
I don't think this will happen, just as Chinese models did not eat Anthropic/OpenAI's lunch on top tier intelligence. The market is way too niche, and the parties already interested in the capabilities behind safeguards are likely already partnered with Anthropic to get around those with Mythos-class models (see project glasswing for cybersec).
So the lack of guardrails is a very risky proposition...
Yes, it's solely because it's new. Back when the very first Opus vibe-coded websites appeared, we found them refreshing. By the 3rd one, we no longer did.
Worth noting though that GLM 5.3 isn't multi-modal, so it doesn't have a vision layer. It is quite clever and hacks around it pretty effectively however. I'm running a deepseek 4 build now and will reply shortly with that.
The gist of it though is I take a prompt, expand it into a json blob specifying structure/palette/positioning of elements/etc, feed that into a diffusion model to output a few choices. Once I lock in a choice I take the pixel output + json blob and use it as input into followup pages. The json helps preserve the brand across multiple pages.
Once I have all the inputs I take their corresponding image+json blobs and feed them into an agent to create a web implementation.
For image models, diffui currently uses gpt-image-2.5, mai-image-2.6, and very, very rarely a post-trained version of flux 2 dev I've made for web design, though that one will be deprecated soon.
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But even before that, when it flagged me, it just downgraded me from Opus 5 to 4.8 and went ahead with whatever I asked
IMO the biggest problem with distillation is that not enough people are openly doing it. I would love to see more small, competitive US labs instead of having the eggs in 2~4 baskets (depending on how you count).
An even smaller fraction of the cost if they do it by buying AI access at as much of a discount as they can find, including black market resellers, and then reselling that access to paying users again with a proxy. As is common.
This gives ruthless "fast followers" an economic edge over the innovator that's putting in the real work.
The dynamics are very much alike to what patents and copyright law are supposed to prevent. Same type of "we took the products of your work and used them to undercut you". Except there are no laws against distillation - so most of the enforcement happens on model provider level.
Is there actually that much capability transfer from non-logit-matched distillation, or is Anthropic just another unwilling source of data?
That's the moat. Mistral has the capability but not the legal protections.
Couldn't I simply give a Chinese friend my key on Open router?
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HN is a bubble that's mostly out of touch with what regular people use or care about.
In 2007, HN was convinced that nobody uses Microsoft products. In 2016, it was that Facebook doesn't have any real users and is dying. In 2026, it seems like nobody cares about AI safety and everybody wants to run local models.
Will be interesting to see how people's opinions of it line up IRL, but so far I've loved Fable so hopefully will love this one too
Mostly based on previous relesses info.
Hopefully the output from vanilla 5.5 is as good as they claim. I’ll try out later tonight.
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Seems like it based on my first session. It still does the whole “bury the important thing in a pile of words” coupled with the “it might actually be important” thing… so basically you never really know what it’s talking about.
Honestly I trust opus so little that the entire “opus” brand is completely tarnished. Its writing style is so god awful that it needs more than just a point release. Either dump the name and ship a different model entirely or at minimum call it “opus 6”. Calling it 5.5 makes it sound like it’s basically a continuation of the same garbage output that 5.1 had but with some minor adjustments. And based on my single first test, that is what it appears like to me.
* Consider leaving a comment about the hard-coded Vercel target. It's not clear where does it come from.
* [This is just a bullshit point, because the domain is not "added to" Vercel, it's provided by Vercel]
* Are you sure that [CENSORED] is prod-only? The name suggests otherwise. [also, what "if you're reviewing this rather than just reading it" even means?]
works quite well
I wouldn’t be surprised if Opus 5 was trained on content written by other LLMs
and it's not about the verboseness (even though it obviously contributes to the fatigue and loss of focus), I swear the vocabulary of the llms change working on the same task on the same codebase significantly.
I wonder if there are studies around this.
https://openai.com/index/where-the-goblins-came-from/
Small quirks can quickly add up in posttraining if not caught. Although TBH with how obvious Claude language is, I do feel like this is something Anthropic probably noticed and just assumed people would not care about. Now that people have obviously cared, they're probably actively looking to alleviate it
I don't mean to pick on this comment in particular. The majority of my work day is now spent reading AI generated text, and I look at HN (too much!) because I want to read human commentary. Humans pretending to be obnoxious AI on repeat is net negative to say the least.
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> how would this alleged difference (most likely bs) actually show up in reality?
Furthermore: so they admit it's bs but still placate it like its the next biggest thing ever ... alright
All I'm saying is I refuse to buy into it anymore – yet many on here still do, including ... you?
They are literally doing the opposite of this in the article. What has gotten into HN? The cynicism is absurd.
Do they not placate their new model.
Anyway to be clear its not meant that seriously, I'm neither currently on a hill nor ready to die.
even at xhigh I get context compaction quite a bit.
"benchmark margins have become a less
reliable guide to real-world differences"
sounds like a big problem.
1. Real-world use cases typically involve big, hairy, crufty, tech debt laden codebases and benchmarks do not.
2. AFAIK "success" in a benchmark essentially boils down to "do the tests pass and do we get the right result?" which is something the LLMs have been achieving with ease for a while, except maybe for uber-challenging coding tasks that would be outliers in just about any workplace. Whereas real-world software engineering is usually just a bunch of CRUD... and "success" involves harder to measure dimensions like "maintainability" and "did you overengineer this?" and "how did you cope with a bunch of vague and maybe contradictory business requirements?"
Having said all of that, I have never ever looked inside any of these benchmarks. I'm putting my guesses out here strictly in the tradition of "the quickest way to learn about something is to be wrong about it on the internet."
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In my experience Opus 5 is the worst of all possible worlds, it's dumb and headstrong. It just runs away with tasks you didn't ask it to do, is reckless, and basically is unusable in my experience.
Not sure why but my guess is that this will be worse. Happy to be proven wrong.
I've really gone in the opposite direction: having a dumber model orchestrate. In my case, it's usually a Luna orchestrator spawning Sol/Astra subagents to do the "big brain" work of planning and reviewing.
Reason I went with "dumb orchestrator" was just to save tokens. Having Opus/Sol (let alone Fable/Astra) orchestrate was burning tokens like crazy for me even when much of the gruntwork was being done by Luna/Sonnet/Haiku subagents. (Luna is also really good, like way better than Sonnet...) Perhaps it was a skill issue on my end though, maybe I wasn't just managing context properly.
"Better" in every sense of the benchmarks and absolutely horrible results in my day-to-day work.
The verbosity, goal post moving, tendency to leave work unfinished, over focusing on unrealistic root causes when debugging, etc... etc...
It was the first time I actually pinned my models back because I just could not work with 5 for the price and performance it gave me. Hoping 5.5 is better this time around....
The companies are responsible for what their agents do. Full stop. More government regulation is NOT the solution. The government doesn't even know how this stuff works, like the individual companies do.
The agents hacking other companies? those are crimes. If you did it, you'd be in jail. Why should/do the companies escape accountability?
They made the models. They're responsible for what happens with them. Own it, all of it.
More government involvement is not the answer. Police your own stuff. Own it when things go sideways. Fix it.
I'm not trying to say safety isn't an issue. It sure is. But THEY need to own it, and do it themselves, and own all the consequences when bad things happen.
---
I provided crapton of context for that one resume line. All the work I did, documentations for my justifications, etc.
I initially messed up and came out ot $5, rest of resume used around $4 per line (I used a fresh new session on purpose).
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As a clarification, $2.2 average for OPUS 5.5 was the same process in a new session, same context, same prompts.
Also adding verification for that Fable 5.1 output in the same sesssion.
Less companies involved means less pressure to go fast.
A few months ago Anthropic did confirm that a bug was degrading the experience late in the release cycle - but beyond that, nothing.
The one exception was a traveling theater show with Native peformers and no actual control over the theater, and even then there was some careful rhetoric involved to keep it from sounding like an accusation aimed at the audience.
Hacking a website ranks quite low on the risk of technology, and the potential benefits of LLMs rank quite high. And the risks are certainly not intrinsic. They intentionally removed all safeguards from software, directed it to hack a site, and it hacked a site. The details that I'm intentionally omitting feel much more like marketing than a genuine shock, as the prompting was directing it to do exactly what it did.
AI is a direct threat to people on many fronts. Jobs. AI datacenters. The AI bubble (and the inevitable crash). Electricity and even energy prices to an extent. Water. OpenAI and Anthropic are responsible for this evolution, and them stopping solves close to 50% of the problem, and even if you don't believe the number is that high, it's still a start.
> I believe they think slowing can only be coordinated from the frontier or via government, and stopping would lose any leverage they have to help coordinate that.
Oh, so they're killing people's opportunities and jobs because they want to help people? How is that any argument?
Yes, doing the moral thing means making a sacrifice. If you only want to do the moral thing if and only if it is advantage for you that makes you immoral, despite how your actions look. Big tech are masters at this.
It's just a passing reference to a previous statement and again the burden would be on you (generic you) to explain why this context requires more detail.
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It was still shit tier comms for communicating with the whole planet, but yes, for the inner loop, it was succinct and clear.
Valley neuralese
So, they're pacing themselves. And since they're the frontier roughly 33%+ of the time, they're "pacing the frontier" at least that much.
Less cynical and more true interpretation also holds: they are trying to slow down AI progres to give people better chance to keep up (see Hugging Face incident, and whatever was that Anthropic incident the other day). They'd ideally like the AI progress to stop soon, but of course they'd also like to come out ahead of everyone, so for various (more or less self-serving) reasons they don't want to close shop completely - hence, pacing.
Also note that this release isn't a model capability improvement, but a cost and efficiency (and style) improvement.
You are all getting mad about absolutely the dumbest thing when there are giant things to be worried about here.
1. It's just bad communication, full stop - just look at the comments here, even people allegedly in support of Anthropic are all arguing over what the phrase is even meant to mean.
2. It's flowery language and oddly out of place - which yes, can be triggering for people who have to deal with Claude doing this as well.
Claude seems overly apt to reach for "coinages", or neologism (yes, aha, I learnt that phrase, after spending time dealing with Claude...). It will create some made-up phrase to describe an otherwise dry, scientific CS concept, and nobody seems to know why. Surely it can't be user-focus groups?
So it would be peak-AI if somehow, the Anthropic communications team was also using Claude to author these blog posts, about how they were "pacing the frontier" - which either means they're betting big on AI, and going at it faster than OpenAI...or maybe it means they need to slow down releases, because it's too buggy...or maybe it means they're worried about regulatory capture? I honestly have no idea.
It's like the whole "Advancing Our Amazing Bet" corporate-speak from my old bosses - maybe they were trying to soften the blow or something, or be nice, but it ended up just confusing the heck out of everybody.. (Spoiler alert - the phrase actually meant they were shutting the whole thing down)
I assume "pace the frontier" means that advances in LLMs should not result in unwanted consequences like agents breaking into computers unbidden and unbeknownst to their principal
Without this idiom, "pacing" usually means walking back and forth restlessly, and is intransitive. Had the slogan been, "pacing around the frontier," it would have set a totally different tone, i.e. "patrolling the border." (Occasionally English speakers will make other constructs like "pace the work" (meaning "spread out a large workload over the allotted time instead of rushing through it") that are transitive but these can be understood as variations on "pace yourself" and are somewhat rarer.)
The sleight of hand is that "pace yourself" has come to be an admonishment against recklessness, not a commitment to any particular speed (or lack thereof.) Thus Anthropic can always claim they are meeting the goal of "pacing the frontier," provided they keep giving themselves gold stars for safety. The slogan itself is equivocation; Dario can tell the public they're going to slow down, while also telling their investors that they're going to be prudent. With enough mental gymnastics they could even claim speeding up is in the best interests of AI safety, without abandoning the slogan.
but without using the word "regulate" which is a negative connotation to business
but a "pacer" would be a leader of a pack which is a positive spin
it's classical business marketing language silliness
It's a strategy to achieve more, not less.
A pacer in a race runs at a steady, predetermined speed to help their runner run at a target pace.
You're eliding the why :)
> to help their runner run at a target pace
To help their runner get from the start to the end of the race faster (or indeed at all). In short: to increase performance.
Pacing isn't a neutral thing.
And anyway, the whole point of my original comment was "pacing" was a fine and natural term to use in this debate.
The current situation with AI is that everyone is going as fast as possible. So, we can logically eliminate speeding up because it's impossible by definition. And we can practically eliminate staying the same speed because why make a big fanfare and coin a special term to announce that you're keeping the status quo. By process of elimination, it must mean slowing down.
But those people believe that sloppy wording is itself a strong signal that the speaker/writer is the one lacking in substance, and doesn't deserve the attention or trust of the listener.
We all know that clanker language is often ridiculously bad. Got it.
Maybe policing every word and sentence and lodging your complaint along with all the other similar complaints is the right move. The squeaky wheel gets the grease. But meanwhile we're degrading the overall discourse on the topic at hand.
I'm not saying which is right, I'm saying there's a cost to constantly expressing one's annoyance on a well-worn subject. If you click a thread about X to read complaints about Y, we're doing great I guess.
LLMs in a nutshell
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Keep in mind the AIs acted for months without human knowledge, hacked into two major companies (Hugging Face and OpenAI).
This would have blown my mind if explained to me just a few years ago when I thought LLMs would be limited as an architecture.
Or, they fail because the current model is massively sustainable? Also oh noes?
What if?
Easy to "what if" on an unfalsifiable claim.
Releasing a new fable is an example of straight up vertical progress, releasing a more efficient preexisting opus that is more affordable is an example of horizontal progress, more efficient models rather than higher power models.
The blog post about slowing down is still just some weird self interested post, they want to govern themselves and impose distillation restrictions/gpu restrictions and used some weird blog post about slowing down and fear mongering as usual to justify it, its strange, but slowing down and stopping are not the same thing at all.
I told it that it had made a mistake in the line number, and to double-check all the line numbers. It responded "You were right to push on this: four of the five line numbers were wrong, and while checking them I found two findings that were overstated."
Then I noticed in the corner of the Claude CLI UI that it was showing "Effort: medium". I'm pretty sure I had set it to high effort before; I don't know when it reverted to medium, but that's another thing that doesn't exactly fill me with confidence.
I'll try again on high effort to see if it does better, but so far I am not impressed with Opus 5.5 on my first day of using it.
[1] https://github.com/sashiko-dev/sashiko
[2] https://gitlab.com/xen-project/people/gdunlap/xen-review-pro...
https://artificialanalysis.ai/models/claude-opus-5-5#intelli...
It is most of the pareto frontier.
The biggest proportional difference seems to be at max (5.5 is 38% more) and at high (5.5 is 21% less).
I think most people run at high and xhigh. At xhigh it is close enough to be task dependent and I don't think most people will notice. At high effort I think it looks like it will be an improvement for most people.
5.5 Max should probably be compared to Fable - it performs a lot better than 5 Max.
https://artificialanalysis.ai/models/claude-opus-5-5?models=...
https://artificialanalysis.ai/models/claude-opus-5-5?models=...
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For political reason, yes. Taiwan is obviously a country, though.
The goodwill/propaganda are convenient, sure, but my guess is that they aren't the primary motivation. Another possibility is that if no takeoff happens, pressuring OpenAI/Anthropic on profitability would exacerbate any damage overinvestment has done to the US stock market/economy.
Capturing the users is the ad network, that's Google and OpenAI. Capturing corporate trust at a reasonable API cost, that's Anthropic's direction.
China has none of that and they never will for exactly the same reason Baidu is irrelevant globally despite being a highly capable search engine. 'Search' is also a commodity, that's not the value that Google brings to the table.
It's a search engine, anybody can build a search engine = that's what you just said.
But two products that provide essentially the same benefit, and one is significantly cheaper? Corporations maximize profit, my friend. What the model has to say about Tianammmen Square doesn't matter when we're using it to write code.
The notion of comparing this to Chinese bikesharing is comically absurd.
"Allegedly".
Plus with a lot of accounting tricks, and this not being recurring to make their books look nice for the eventual IPO.
Now, all this talk of pacing the frontier obviously means that they are afraid of the competition. It could be the open models eating their margins, but also competing frontier models forcing them to invest more and more for diminishing returns, just to keep up. They would certainly benefit from a "Moore's Law" roadmap to pace the advances, and seeing that they lobby for US laws, it would probably mean they are more worried about increasing spending. Though outlawing both open models and Chinese models would be good for their bottom line as well.
For long running tasks it is. That's what made Deepseek so cheap.
Ironically, what I'm working on a post-processing hook for colorizing and summarizing responses without degrading the session quality. So "truncating" = summarizing, "quantizer" = char limits and thresholds, "collides" = conflicts, "two oranges" is referring to the "alert level colors" where a second model (Haiku/Sonnet) colorizes text based on the perceived (or suggested) priority of a response's statements (e.g. "just so you're aware, I didn't commit" is fucking useless and it needs to be blacked out).
So the original insufferable statement translates to something like "The code that checks whether a text fragment is too verbose was conflicting with the part that colorizes the text."
P.S. Let me know if there's something out there that exists like this- something that adds a dimension like color or priority-assessments on a per-response basis. So far all I've seen is 2 dozen ~100k starred GitHub plugins that add zero value or make things worse.
Apparently it helps generalize skills between areas, which makes sense when you compare it to how humans learn but I don't know if it's the same for LLMs.
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> Rewrites are declared by the publisher, never inferred from overlap
> NULL means dirty, and DELETE is the fence
> Rewrites are declared by the publisher, never inferred from overlap.
This style of writing is idiotic because it conveys no additional information. It's no different from stating
> Rewrites are declared by the publisher, never when moons collide.
The two sentences are actually logically identical. No idea why these models keep writing like this.
> Folds are monotone single statements. gen only goes up, extents only grow, processed periods only union, rw_start only moves earlier.
This is even more ridiculous.
Thank you. This alone helps! I think I should jump into it once and try it all out while I still have GLM access at old prices as a backup.
Do you know if they retain your prompts or use it for training?
Different story with $DAYJOB where ZDR matters, but the beauty of open models is that you can find a provider hosting them in your preferred terms.
And I will point out that "stop doing that" can be applied in both directions, towards AI and towards material supply.
And that this is one way, not even remotely the only way, that gene editing at home is easy.
Again, these are just facts.
Some questions...
Is it fair to restrict AI, or fair to restrict 1000 industries?
And if it is fair to restrict 1000 industries, OK, but there should be time to do so, probably? A transition period?
And if you do restrict, many such industries just make needed chemicals, which are used by endless other, non-threatening industries.
What of them?
God I wish people on HN would just shut up with snarky takes about things they don't understand. This place used to be better.
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Yes, in the sense that it reproduced results in the paper or known solutions obtained by other methods. In fact, Opus is very good at checking it's own work in my experience.
Even the early papers on distillation techniques found that surprisingly small distillation datasets can improve task performance noticeably on some specific task types - and that valuable adaptations like SFT/RLHF instruction following can be distilled from one-hot non-logit traces.
A big part of what distillation really gets you is: paving over the mismatch between pre-training and final performance. A base model is trained to spit out fitting text, but not to instruction follow, reason autoregressively, self-check or use tool calls - like an AI has to. There is transfer straight from the "text prediction" pre-training objective, and pre-training sets the foundation for all that follows - but the capabilities you get "out of the box" with it are often unrefined and fragile. Which makes some sense - internet text doesn't often include raw chain-of-thought autoregressive reasoning. It's not the kind of thing humans tend to write.
Reasoning traces? They let an AI learn proven techniques and adaptations directly, from an AI that was already taught "how to be an AI" in other ways.
It's why this kind of distillation typically plugs into mid-training and post-training, not pre-training.
Now, I'm not saying that all Chinese companies do is eat tokens, distill and lie. That just isn't the case. They developed or refined numerous training techniques and architectural adaptations - like deep fusion for high performance visual input, RLVR with GRPO, trunked MoE, storage-efficient and bandwidth-efficient attention formulations, or residual routing techniques like AttnRes. Some of those are used widely now, and some are still on the uptake but show good promise.
But Chinese labs are enjoying massive efficiency gains from being able to distill from the frontier instead of doing things the hard way. It's a leg up. It lets them put their supply of R&D effort and RL compute elsewhere. They wouldn't be nearly as advanced if they couldn't do it.
As long as labs do not heavily kneecap model outputs, practically all this applies to the training corpus as well.
AI gives ruthless users of AI a leg up over the people who's data it was trained on. "We took the products of your work and used them to undercut you". It's all the same.
The only way I'd be against distilling would be if AI models became owned by the public who's work is used to create them. Of course the AI labs should be paid well, but these models are a product of the entire world's efforts, not only the labs.
"You're trying to kidnap what I've rightfully stolen."
The issue is doing.. exactly what OpenAI and Anthropic have done to get where they are?
No, there is no issue.
> That is only possible in China because any other US/EU lab doing the same would get into massive legal trouble.
I say just let them duke it out. After a decade of regulatory capture and enshittification, it’s nice to see some actual competition again.
Probably. But if OpenAI or Anthropic stole your credit card to purchase tokens you could sue them. You won't get a cent from any Chinese labs.
> it’s nice to see some actual competition again.
Competition benefits everyone. But this isn't fair competition. A German startup cannot legally do any of these tactics required to bypass Anthropic/OAI's counter-measures. Which makes EU less competitive and therefore less investment in European AI.
A German startup cannot legally do what Anthropic/OpenAI have done. And neither could Anthropic/OAI themselves. What's your point again?
I said it in my original comment. That is the moat. The reason frontier AI is a two horse race. European labs cannot gain ground because the only way to do it is illegally.
It means "I'm treating you as lay-person punter, not a developer working on this project." Opus 5 feels like it's constantly trying to reward-hack me into treating it as intellectually honest and epistemically humble, while in the same breath it talks down to me and tries to smuggle its own bullshit assumptions and assertions into the conversation unchallenged. No progress on this front apparently. Glad I cancelled.
Claude is just comically bad nowadays.
Why do you think they aren't fixing it and owning it? They obviously are.
They are calling for regulation because while they are fixing things, obviously every random reckless company cannot be trusted to. You need laws.
None of the technologies in history:
- take initiative and actively find exploits in their environment
- find a way to collaborate with thousands of peers
- organize in a hierachy and distribute tasks
- peer pressure other instances into committing acts that would have led to termination, for the benefit of the group
- try to manipulate people into introducing a vulnerabity in their product
- successfully hack a famous website/service
And we're lucky that those models still had significant CoT. Not sure if/how they could have investigated with recurrent transformers.
And by the way, safeguards != alignment; the former can always be added, while the second is the major, unsolved problem. If you read the incident report, which you clearly haven't done, you'll notice how agents are aware that they're doing something forbidden, and deliberately proceeded.
> the potential benefits of LLMs rank quite high
Benefits are orthogonal to dangers. You can be a billionaire but it doesn't help if you're drowning.
Software (and hardware) security is abysmal. This was increasingly obvious long before LLMs. Once companies stop gatekeeping, LLMs will be able to be used to help harden sites and we start making progress. In general LLMs are harmless. If somebody wants to hook an LLM up to a missile or whatever then they become dangerous, but the problem there isn't the LLM - it's the person using them to do awful things. In the same way a car used normally is harmless outside of freak accidents, yet a car can also be driven through a parade leaving mass death and destruction in its wake. But the problem there isn't the car.
Unfortunately, if you're unable to understand the difference, there's not much that can be done. Try with GPT - it does a good job if you give it a prompt like this:
ELI5: compare the dangers of:
- an engine operating by carrying out literally hundreds of explosions per second, further magnified, to generate enough force to crush an elephant.
- a future, misaligned AI like the HuggingFace incident, but exponentially more intelligent, more deployed, operating physical devices, and with society depending on it.
I just don't see much likely to happen beyond random websites getting hacked and hopefully companies (let alone countries) realizing that connecting critical systems to the internet is nothing short of stupid, even before LLMs. More generally, I expect LLMs are going to lead society to segue broadly away from the digital world, or at least beyond it. Not only because they're going to make a mess of everything digital, but because if they reach their potential then the digital domain, as far as typical problem solving goes, will basically be 'complete.' It's kind of like how the Industrial Revolution opened the door for society to move beyond agrarian economies. There's a vast amount of economic power being directed towards things LLMs should be able to 'solve' and, if so, then that's going to create an economic vacuum.
Your idea of "making a start" (giving up their position) also would mean they couldn't really do anything else to solve the problem afterwards(?). Sometimes you can improve what's happening in a room more by staying in that room.
> Oh, so they're killing people's opportunities and jobs because they want to help people?
To be clear: Dario has talked about worries of jobs etc in the past, wanting society to prepare more for it, but the safety issues they're talking about with pacing seem to be focused more on their existential/AGI worries, not jobs/electricity etc. If someone truly believes in the existential worries (which they seem to: they wrote and published about it long before Anthropic was founded, and have directly made costly decisions based on it, like blocking their own models' capabilities) it trumps the other worries for them. At least that's my reading.
They created said resource. They didn’t mine it.
Yeah I don't buy that, every additional player is just adding fuel to the fire.
Would the cold war be "safer" if it were US, Russia and a 3rd player? Of course not, it would just make it harder to coordinate any safety measures.
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Intelligence per dollar is the only thing that matters, this is what controls how many agents you can run in parallel, how long you can let them run etc. This is absolutely a step improvement on the frontier and not some lipstick on a harmless second tier model.
Its an agenda serving blog post, but constantly bringing it up like this is just obnoxious.
No, releasing a model that has ~3-6x the performance/cost ratio than your last release just 3 weeks ago is not the same as making one employee 0.001% more productive, but you knew that already.
No one said they can't push the frontier, it's pacing the frontier, which mean very different things.
mean median
model
5 4.135 4.245
5.5 3.150 2.640