This article is 100% AI written. The data was interesting, the commentary overly verbose and hard to gain useful insights from.
This article is 100% AI written. The data was interesting, the commentary overly verbose and hard to gain useful insights from.
I'm apparently not good at spotting it. I was put off by the overly dramatic presentation. It gets tiring that the author apparently finds this more exciting than I do, and writes like it's enthralling. I just assumed it was an excess of enthusiasm or the first experience with this kind of thing. If it's AI, I'm way behind the game noticing it.
There are lots of indicators in this text, and this breathless presentation is very much how modern LLMs present things.
Claude also loves to describe things as being "real", particularly saying "X is real".
In this case,
> The reallocations were real, but they were never the bottleneck.
There was never any indication or setup in the text that they weren't real, but it's how it justifies wasted effort, it insists that some phenomenon it corrected but failed to solve the problem "was real".
Another giveaway are nonsensical analogies:
> The predictor is like a barista who starts making your usual order the moment you walk in. If you are a regular, this is fantastic: the coffee is ready when you reach the counter. If you order something random every day, the barista keeps pouring drinks into the sink.
If you order "something random every day", then you don't have a usual order for them to be making, it's an analogy that doesn't work.
And of course, the smoking gun is:
> The smoking gun
It probably won't be a good indicator forever as it has been noticed so much, but it's a particular favourite of the current generation of anthropic models.
"The smoking gun" is right there in the text ;) (but also things like "Same million floats. Same threshold. Same function."). Don't know if other models have that same specific style, but it looks very 'claude-y'.
I wouldn't be surprised though if (especially) non-native speakers unconsciously start adopting the Claude writing style when they stare all day long at Claude generated text at work.
Not sure if it was added later, but there's an even more obvious sign: the top of the blog post literally says that an LLM was used to write it.
I would assume non-native speakers talk to Claude in their own language. Now I'm curious if Claude's weird quirks of speech are unique in each language or if they carry over!
I'm German but still do all my computing in English (partly out of habbit, but also because Germanized technical text is usually painful to work with because it's full of anglizisms (is that actually an English word?)).
One nice thing about English is you can just make up words with plausible etymological roots in Latin/French or Old English and often people will know what you mean. In this case though it would probably be spelled "Anglicism".
German language: hold my beer ;)
Hey, this beer glass is cold, lemme get my Handschuh.
This isn't a necessarily true assumption. I my social circles of non native English speakers, most of us use English to talk with models.
I switch languages randomly.
What do Claude's tics look like in your other language? Do they carry over or does each language get its own weird rhetorical flourishes?
> Don't know if other models have that same specific style
An awful lot of the open-weight models also talk in the Claude-y style. Not sure if an artefact of distilling anthropic models, or just a preponderance of slop in the training set...
> I was put off by the overly dramatic presentation. It gets tiring that the author apparently finds this more exciting than I do, and writes like it's enthralling.
That's one of the main tells that AI wrote this. All the stylistic tics that people usually point out combine to make the writing seem more important than it is.
Yep, “instinct“ and “smoking gun” are LLM favourites.
I find it really annoying when the LLM says “good instinct” as if I’m an animal barely able to think.
It was fun to read and insightful for me, not too artificial, and not too verbose.
I'm glad my internal AI detector doesn't win over my curiosity to learn.
The main problem with the article is that the idea to influence backend code generation decisions via specific highlevel code constructs is mostly just mystical bullshit (some compilers do detect specific patterns - usually for bit twiddling hacks, but not on a basic level like control flow optimization).
Using a highlevel language construct like "y += (x > 0) as usize;" doesn't "switch on" branchless code just because the source code looks branchless, compilers are not that dumb anymore.
E.g. I bet that writing
...generates the exact same code after optimization, otherwise I would consider that an LLVM bug.The only reliable way is to mostly bypass the optimizer via simd intrinsics, or drop down to assembler, everything else is just cargo culting.
(fwiw I can't shake the feeling now that the article is recycled, I'm pretty sure I saw those exact same code examples in another "branchless" blog post, but maybe for a different language - because the next question was ineviatably "then why is the code using "if" slower? answer: because it also behaves differently). Or maybe I'm just having a strong dejavu ;)
PS:
> fwiw I can't shake the feeling now that the article is recycled
Ok, I remembered wrong. The article I remembered was this: https://tiki.li/blog/blqsort
HN link: https://news.ycombinator.com/item?id=48375445
It's peddling the exact same myth though.
And, on some architectures, y+=(x>0) is branchful!
I just scrolled through & read the code snippets. Interesting enough solution at end
Click on their blog index page, see posts going back to early 2010s and use the same writing style. He must have been time travelling and using AI all this time!
I had a look at their blog page out of curiosity, not that you can prove much from the purported dates and text on a blog, which could be edited at any time.
The blog posts from 2010s are in a completely different style and written by a human: https://www.greyblake.com/blog/vim-preview-plugin/ https://www.greyblake.com/blog/how-to-install-firefox-icewea... https://www.greyblake.com/blog/unexpected-ruby-behaviour/ ...
This new blog post is clearly AI edited (probably 'improved' with AI), the old ones are not.
The first link you cited[0] shows up on the Wayback Machine[1] for the first time on 2022-05-16 - more than 11 years after it was purportedly written.
[0] https://www.greyblake.com/blog/vim-preview-plugin/
[1] https://web.archive.org/web/20220516225844/https://www.greyb...
> the same writing style
It's "fake corporate enthusiasm" style. LLMs were just trained in it.
I think he's asked it to write in his specific style, or possibly he has edited parts of it to his style, or maybe used AI to generate the initial draft.
Something like that anyway. There are some very clear AI tells (smoking guns if you like), but most of it does not read like the prose AI produces by default.
Author if you are here I am curious about your writing process, and why you didn't remove the obvious AI tells.
idk why this is getting downvoted, I also got this sense, plugged it into Pangram and indeed, 80% AI-written score.
I guess that's fine, but after awhile I get a spidey-sense reading something that feels like a Claude session.
Sad to see you getting voted down. But I guess both the pro-AI crowd and anti-AI crowd hate Pangram.
I always got voted down when I posted the evaluation of the parent articles I got from my Ouija board. I just want to help people understand whether they should just reject bad articles, without having to bother reading them.
I'm moving on to evaluating articles with a modified lie detector test and tarot cards, I'm sure that'll help my credibility and give my public rejections more authority.
Do you have evidence Pangram is unreliable? There are independent evaluations [1, 2] showing it works, and it's getting used more and more scientific papers. Have you used it or evaluated it yourself? What do you think these other evaluators are doing or getting wrong?
1: https://bfi.uchicago.edu/insights/artificial-writing-and-aut... 2: https://arxiv.org/pdf/2501.15654
I don't doubt that those detectors are generally correct. Pangram seems to be particularly accurate. I see independent evaluations ranging from 97% accurate to over 99%. Frankly, I somewhat doubt those numbers, but I do agree that LLM usage can be fairly accurately detected.
But procedurally, there are huge issues involved with automated tools used to harm other people. You are one of the 0.5% percent of people whose article was flagged as LLM-generated when it wasn't, one of the false positives. What do you do? Argue? The accusers will claim that you're 99.5% likely to be lying.
It's the same issue we have with automated customer service, automated insurance claims, and so forth. It is usually correct, and terrifically unjust when it fails... at which point there is no recourse. In a perverse sense, its accuracy can be a drawback, because if the false positive rate low enough, nobody is going to believe you when you're falsely accused. And people will be falsely accused.
I think it's ironic that it seems like it capitalizes on the same flaw that most LLM-posting does... "Chat GPT is usually right, I'm going with it." You shouldn't post an LLM article without independently validating its claims, so that there is a responsible person in the loop. The same is true for rejections and accusations, but more so, because they're more damaging.
because it's not much better than an RNG?
What data supports that conclusion about Pangram?
Sad little world we live in tbh.
A good part of the article feels like it was written by Claude indeed:
- "The reallocations were real, but they were never the bottleneck."
- "Note that the villain is not the branch itself. It is the branch that [..]"
- "Same million floats. Same threshold. Same function."
- "Notice the price we paid though."
[flagged]
Agree.
Interesting topic but why destroy your own credibility and reputation by shoveling llm-assisted slop to us here at hn?
The post should be flagged, and in general, i wish hn would adopt a no-tolerance policy to enhanced posting like this.
So what if the original text, if it existed in a human written form at all, had weird textual quirks and prose issues the author wished to hide. That texture's what makes humans interesting to engage with in the first place.
I think I need to build “Hacker News Except All Arguments About Whether Or Not Something Is AI-Written Are Filtered Out”