> The compute is still real. The VRAM is still real. And the memory bandwidth is where it gets genuinely surprising.
Because humans write exactly like this /s
> The compute is still real. The VRAM is still real. And the memory bandwidth is where it gets genuinely surprising.
Because humans write exactly like this /s
Where do you think llms learned to write that way?
You can also look at past posts by the same author (before LLM usage proliferated) if you’re curious.
The project is still very cool, but it’s a little less enjoyable to read when everything sounds the same. It would be just as annoying for people to manually write in a corporate/marketing style, because humanity is what makes the small web interesting.
https://blog.tymscar.com/posts/privategithubcicd/
I’m glad I’ve started this blog before the AI wave so I can prove people I’m just weird at writing.
It grinds my gears how so many people just talk about my writing style instead of the content.
> I’m glad I’ve started this blog before the AI wave so I can prove people I’m just weird at writing.
Your previous blog posts didn't trigger any LLM detector (go on - check for yourself).
Neither does this one. I replied in another thread. It comes out as 0% and the one from 2021 comes out as 8%. LLM detectors are all BS
GPTzero says 100% AI generated for specific paragraphs that I chose (such as `Multi-token prediction`). If you remove all the code listings, tables, etc and just paste the prose into these tools, it drops to 87% AI generated.
None of the 3x older blogs of yours that I tried went above 5% AI generated.
Maybe you're spending so much of time with the LLM that you are talking like it; in which case, take an old blog and a recent blog, give the prose from them both to you favourite LLM and ask them if the same author wrote both. I just did that on ChatGPT and on Gemini, and both found that it is extremely unlikely that the same author wrote both.
Look, if all the SOTA LLMs agree that your recent blogs sounds generated, you can't blame the reader, can you?
GPTzero is a joke.
It thinks this is AI: “I bought a datacenter GPU that doesn’t even have a normal PCIe connector, stuck it in my gaming PC with an adapter, and now I have 32GB of VRAM across two GPUs running a 27 billion parameter model at 32 tokens per second.”
There’s nothing AI about that. Not all SOTA LLMs agree, hell, none of them do. The same exact example I sent here gives me 0% in some, 10% in others, 100% in GPTzero.
> Not all SOTA LLMs agree, hell, none of them do.
The ones I checked all agree: your recent writing is not the same author as your writing from 3 years ago...
You can check this yourself if you don't believe; make of that, what you will.
This, setting aside the llm issue, it is dealing with hardware in ways that -- one would think - would be celebrated on HN of all places. But we focus on presentation.
Because their custom training data contains an emphasis on such verbiage. It doesn't come from the God-knows-how-many TB of web content the model is pre-trained on. There, such phrasing is only a drop in the sea. But the "yes, you're right" phrases, the em dash, etc., come from the later stage, for which content is created according to some (probably overprecise) guidelines.
Right. The overuse of "genuinely" most of all. Seems like they put Claude through a few good rounds of training to always answer questions about its consciousness, thoughts, etc., with something about how it's "genuinely unsure," and as a result, the model learned to use "genuinely" as an intensifier in all sorts of inappropriate contexts.
Oi, I personally use adverbs everywhere. Genuinely, kids these days.
Marketing content.
> Where do you think llms learned to write that way?
Not from individual human content, that's for sure - maybe MLM marketing copy? Sleazy 4AM ads?
I mean, every time this response comes up, I keep asking the person to point at something written prior to 2022 that gets 80%+ on the LLM detectors, and yet no one can find anything.
Maybe you, postalrat, can find something written in this style that was published prior to 2022.
I have written the blog post. I know empirically that I have used 0% AI while writing it. I also know LLM detectors are total BS and they don't really work. I have tried a couple on this exact blog post, and QuillBot, for example, gave me 0% AI detected on it.
I have then used a blog post of mine from 2021. QuillBot gave me 8%...
The King James version of the Bible came out at almost 100% AI generated a while ago. It was the HN front page.
Stop thinking that if someone writes in a way that is fun or looks like what you would think an AI writes, then it is AI generated. Loads of the time it is, but sometimes it's not, and it really hurts those like me.
> I have tried a couple on this exact blog post, and QuillBot, for example, gave me 0% AI detected on it.
Don't use Quillbot; not sure why, but their model is reluctant to classify anything as AI generated. I ran into this when proof-reading a students Phd - ChatGPT, Gemini, CLaude (and others) all agreed it was AI generated, but Quillbot said it wasn't.
It's a function of the LLM "thought process"! It's not really modeled after human speech. It is in short segments but not long form, same reason you see the same rather odd nuances in LLM generated code.
If they way you thought was to run a bunch of if statements, generate content, then feed that content back to get a "score" of what seems the most plausible, run the if statements again, and adjust / merge responses, then you would write similarly. The recognizable cadence of LLM generated content is pretty clearly the result of a lot of if statements being fused together.
You know what the sad bit is? Humans do write exactly like that. That's not even particularly egregious StalkedIn marketroid speak.
There's interesting stuff in this writeup but it sure seems like most of it was written by an LLM.
X is Y. Z is Y. And Alpha is genuinely Beta.
Classic LLM writing style.