[solid_fuel]

It feels generated to me too. It’s this:

    When you enable the Gemini API (Generative Language API) on a Google Cloud project, existing API keys in that project (including the ones sitting in public JavaScript on your website) can silently gain access to sensitive Gemini endpoints. No warning. No confirmation dialog. No email notification.

Specifically, the last bit - “No warning. No confirmation dialog. No email notification.” Immediately smells like LLM generated text to me. Punchy repetition in a set of 3.

If you scroll through tiktok or instagram you can see the same exact pattern in a lot of LLM generated descriptions.

[MrJohz]

I think there's a lot more than just that, but I think part of the problem is that you just get an uncanny valley feeling. All of the phrases and rhetorical tricks that these tools use are perfectly valid, but together they feel somehow thin?

That said, some specific things that feel very AI-y are the mostly short, equally-sized paragraphs with occasional punchy one-sentence paragraphs interspersed between them; the use of bold when listing things (and the number of two-element lists); there are a couple of "it's not X, it's Y"-style statements; one paragraph ends with an "they say it's X, but it's actually Y" construct; and even the phrasing of some of the headings.

None of these are necessarily individually tells of AI writing (and I suspect if you look through my own comments and blog posts on various sites, you'd find me using many of the same constructs, because they're all either effective rhetorically, or make the text clearer and easier to understand). But there's something about the concentration of them here that feels like AI - the uncanny valley feeling.

I would put money on this post at least having gone through AI review, if not having been generated by AI from human-written notes. I understand why people do that, but I also think it's a shame that some of the individual colour of people's writing is disappearing from these sorts of blog posts.

[tyre]

Using threes is common in English writing and speaking. It has an optimal balance of expressiveness (three marking a pattern or breadth; creating momentum) without being overwhelming.

It’s not uncommon, as basic writing advice, to use sets of three for emphasis. That isn’t a signifier of LLM generation, in my opinion.

[Gigachad]

It's also seemingly the only way ChatGPT knows how to write, while being very uncommon for blogposts beforehand. Of course it's not 100% proof, but it's the most likely explanation.

[coliveira]

This excerpt is demonstrating the use of a literary technique to write non-literary prose. It's an almost sure sign that an LLM is generating the text.

[larusso]

I’m not a native speaker so my level of AI recognition is already low. I find it very interesting what patters people bring up to declare it’s AI. The 3 punchline one for instance is a pattern I use while speaking. Can’t say I would write like this though.

[solid_fuel]

It's not so much the grouping of 3 or way it's supposed to be punchy specifically that's the problem, that is just one example of what gives the article the "LLM Generated" feeling since whatever cheap model people are using for this kind of spam has some common ticks.

I use groupings of 3 and try to make things punchy myself sometimes, especially when I'm writing something intended to sway others. I think the problem with this article is the way it feels like the perfect average of corporate writing. It's sort of like the "written by committee" feel that incredibly generic pop music often has.

When I write things, I often go back and edit and reword parts. Like the brushstrokes in an oil painting, the flow of thought varies between paragraphs and even sentences. LLMs only generate things from left to right (or vice versa in RTL languages, I presume). I think that gives LLM generated text a "smooth" texture that really stands out to anyone who reads a lot.

[deaux]

I'm not a native speaker and my level of AI recognition is higher than 99.999% of native speakers - and I'd be happy to be tested on it for proof.

The biggest factor is simply how long you've been using LLMs to generate text, how often, how much. It's like how an experienced UI designer can instantly tell that something is off by a single pixel off upon first seeing a UI, whereas if you gave me $200 to find it within 10 minutes I might well fail.

[Gigachad]

Aside from particulars like the set of 3, LLMs add a lot of emotive language which doesn't mean anything or is a repetition of already established points. Since they can't add any actual substance beyond what was in the prompt, the only thing they do is pad the prompt with filler language.

[bryanrasmussen]

OK I've seen many people make this point on this site over just the last few months, but where do you think LLMs pick up these patterns? How did this rule of threes https://en.wikipedia.org/wiki/Rule_of_three_(writing) get into the LLM so they are so damn recognizable as LLMs and not as humans?

HN Note: Yes the rule of threes is broader than just this particular pattern here, but in my opinion this common writing and communication pattern is a specific example of the rule of threes.

Punchy repetition in a set of 3. Yes. LLMs are able to capably mimic the common patterns that how to write books have suggested for the last 100 years as ways to make your writing more "impactful" and attention-grabbing. So are humans. They learned it from watching us.

I am a little bit worked up on this as I have felt insulted a couple times at having something I've written been accused of being by an LLM, in that case it was because I had written something from the viewpoint of a depressed and tired character and someone thought it had to be an LLM because they seemed detached from humanity! Success!

I too would like to be able to reliably detect when something has been written by an LLM so I can discount it out of hand, but frankly many of the attempts I see people make to detect these things seem poorly reasoned and actively detrimental.

People have learned in classes and from reading how to improve their writing. LLMs have learned from ingesting our output. If something matches a common writing 101 tip it is just as likely to be reasonably competent as it is to be non-human. The solution to escape being labelled an LLM is not to become less competent as a writer.

I have been overly verbose here, as I am somewhat worked up and angry and it is too late in the morning to go back to sleep but really too early to be awake. I know verbosity is also a symptom of being an LLM, but not giving a damn is a symptom of humanity.

[kgeist]

>but where do you think LLMs pick up these patterns?

>LLMs are able to capably mimic the common patterns that how to write books have suggested for the last 100 years as ways to make your writing more "impactful" and attention-grabbing. So are humans. They learned it from watching us.

Don't forget that LLMs (at least the "instruct" versions) undergo substantial post-training to align them with the authors' objectives, so they are not a 100% pure reflection of the distribution seen on the internet. For example, it's common for LLMs to respond with "You're absolutely right!" to every second message, which isn't what humans usually do. It's a result of some kind of RLHF: human labelers liked to hear that they're right, so they preferred answers containing such phrases, and those responses became amplified. People recognize LLM-generated writing because LLMs' pattern distribution is different from the actual pattern distribution found in articles written by humans.