No, seriously, people need to be punished for submitting LLM-generated garbage without specifying that it's LLM-generated garbage. 400+ points, oh my god, people, what's wrong with you...
We buried the post for seeming obviously-LLM-generated. But please email us about these (hn@ycombinator.com) rather than posting public accusations.
There are two reasons why emailing us is better:
First, the negative consequences of a false allegation outweigh the benefits of a valid accusation.
Second and more important: we'll likely see an email sooner than we'll see a comment, so we can nip it in the bud quickly, rather leaving it sitting on the front page for hours.
Hey Tom! Earnest question here - I am seeing on the order of one AI post a day on HN, sometimes more than that. It's good to know we can email in about these things, but I think most users don't understand that - certainly I didn't for the last few month as this has been going on. It would be nice if there was an affordance on the site to flag these, similar to the existing flag function.
Just flagging them is fine. Emailing us with the link is even better. Part of me wonders if we should have a new, specific-purpose flag for generated content, but it’s not the HN way to add new features for actions that can already be satisfied by existing UI features.
I would suggest a new feature here. I have been hesitating on flagging them because I feel 'flag' is for things which are obvious rule violations. I feel a bit bad flagging a submission off the front page when I only have a vague feeling that it was AI-written. (And sometimes AI generated content isn't that bad, i.e. if an author just used AI to translate their writing into English.)
This thread is a great discussion and I have kept coming back to it over the last couple days to read more of it when I have a chance. I’m kind of disappointed that it artificially ended. I think at some useful comment threshold level you just have to let it go.
You buried a popular post because of the public accusation or just your "hunch"?
Why not let your audience decide what it wants to read?
I say this as a long time HN reader, who feels like the community has become grumpier over the years. Which I feel like is a shame. But maybe that's just me.
It's my job to read HN posts and comments all day, every day, and these days that means spending a lot of time evaluating whether a post seems LLM-generated. In this case the post seems LLM-generated or heavily LLM-edited.
We have been asking the community not to publicly call out posts for being LLM-generated, for the reasons I explained in the latest edit of the comment you replied to. But if we're going to ask the community that, we also need to ask submitters to not post obviously-LLM-influenced articles. We've been asking that ever since LLMs became commonplace.
> I say this as a long time HN reader, who feels like the community has become grumpier over the years. Which I feel like is a shame. But maybe that's just me.
We've recently added this line to the guidelines: Don't be curmudgeonly. Thoughtful criticism is fine, but please don't be rigidly or generically negative.
HN has become grumpier, and we don't like that. But a lot of it is in reaction to the HN audience being disappointed at a lot of what modern tech companies are serving up, both in terms of products and content, and it doesn't work for us to tell them they're wrong to feel that way. We can try, but we can't force anyone to feel differently. It's just as much up to product creators and content creators to keep working to raise the standards of what they offer the audience.
Thanks Tom, I appreciate the openness. You are seemingly overriding the wishes of the community, but it your community and you have the right to do so. I still think it's a shame, but that's my problem.
> You are seemingly overriding the wishes of the community
That's false. The overwhelming sentiment of the community is that HN should be free of LLM-generated content or content that has obvious AI fingerprints. Sometimes people don't immediately realize that an article or comment has a heavy LLM influence, but once they realize it does, they expect us to act (this is especially true if they didn't realize it initially, as they feel deceived). This is clear from the comments and emails we get about this topic.
If you can publish a new version of the post that is human-authored, we'd happily re-up it.
>> You are seemingly overriding the wishes of the community
> That's false. The overwhelming sentiment of the community is that HN should be free of LLM-generated content or content that has obvious AI fingerprints.
Yeah it is indeed, and for good reason: why would I spend time reading something the author didn't spend time thinking through and writing?
It's not that people don't like Postgres articles (otherwise, the upvotes would be much lower), but once you read a bit of the article, the LLM stench it gives off is characteristic. You know: Standard. LLM. Style. It's tiresome. Irksome. Off-putting.
What I'm wondering is, if LLMs are trained on "our" (in the wider sense of the word) writing style, and spew it back at us, what data set was it that overused this superficial emphatic style to such a degree, that it's now overwhelmingly the bog-standard generative output style?
I’d be grumpy over wasting my time on an HN post that’s LLM generated which doesn’t state that it is. If I wanted this, I could be prompting N number of chat models available to me instead of meandering over here.
I just pasted the first paragraph in an "AI detector" app and it indeed came back as 100% AI. But I heard those things are unreliable. How did you determine this was LLM-generated? The same way?
Apart from the style of the prose, which is my subjective evaluation: This blog post is "a view from nowhere." Tiger Data is a company that sells postgres in some way (don't know, but it doesn't matter for the following): they could speak as themselves, and compare themselves to companies that sell other open source databases. Or they could showcase benchmarks _they ran_.
Them saying: "What you get: pgvectorscale uses the DiskANN algorithm (from Microsoft Research), achieving 28x lower p95 latency and 16x higher throughput than Pinecone at 99% recall" is marketing unless they give how you'd replicate those numbers.
Point being: this could have been written by an LLM, because it doesn't represent any work-done by Tiger Data.
For what it's worth, TigerData is the company that develops TimescaleDB, a very popular and performant time series database provided as a Postgres extension. I'm surprised that the fact that TigerData is behind it is not mentioned anywhere in the blog post. (Though, TimescaleDB is mentioned 14 times on the page).
In terms of that example: they should link to how they got those numbers, and it should state the benchmark used, the machines used, what they controlled for etc.
Just using LLMs enough I've developed a sense for the flavor of writing. Surely it could be hidden with enough work, but most of the time it's pretty blatant.
It’s got that LLM flow to it. Also liberal use of formatting. It’s like it cannot possibly emphasize enough. Tries to make every word hit as hard as possible. Theres no filler, nothing slightly tangential or off topic to add color. Just many vapid points rapid fire, as if they’re the hardest hitting truth of the decade lol
ChatGPT has a pretty obvious writing style at the moment. It's not a question of some nebulous "AI detector" gotcha, it's more just basic human pattern matching. The abundant bullet points, copious bold text, pithy one line summarizing assertions ("In the AI era, simplicity isn’t just elegant. It’s essential."). There are so many more in just how it structures its writing (eg "Let’s address this head-on."). Hard to enumerate everything, frankly.
I know everybody just wants to talk about Postgres but it’s still sad to see any sort of engagement with slop. Even though the actual article is essentially irrelevant lol
