One thing I'm not so glad to see is one paragraph that starts with this sentence:
"The distinction is important. Archaeological maps..."
That "The distinction is important" smells like AI writing... but maybe we all just have to accept that now?
As someone who loves to read (well, on and off) I wonder what the median vocabulary is and how I and other readers compare. I guess language has always been functional for most people.
LLMs average human writing thats out there, its not making up new expressions or language constructs so just move on if you (anybody) can and put that little obsessive pedantic part of you behind you.
I couldn't care less, why be a prick and not just enjoy & discuss the content, not this ultra focus on the form. If content is crap then thats another story altogether. I wish there would be some plugin/feature to just block those rather empty subthreads.
Subconsciously we all pick up patterns that we regularly encounter.
English is not my native language.
If all you know about archeology is from daytime television and clickbait articles, all you know about history is what you vaguely remember from school, you never met anybody working in those fields and actually don't even have a passing interest to engage with the subject, then yes, you might be inclined to believe that's how it works.
EDIT: of course this comment accumulates nothing but drive-by down votes from arrogant computer touchers, presumably before heading off to other comment sections to discuss law, macroeconomics, quantum physics and whatever else they are experts at, having watched YouTube videos. You see, only CS requires years of study and is divided into dozens of intricate sub fields, everything else is simple, straight forward and can be "disrupted".
I learned a great lesson for a gamedev youtuber this summer: Use AI to give you a summary what you have to implement, what functions you'll need, what edge case you missed and then write it yourself. Putting this into practice helps me to refine the ticket I'm working on. With the last ticket I had to persuade the AI (Atlassian's Rovo in my case) that a new data model wasn't necessary and we can do it more elegantly with less code.
Many of us still have to figure out how AI fits into our workflow, letting it do all the work isn't it but asking AI to point you towards the goal and let it review/refine your work sounds a lot more acceptable to me.
Wrong wrong wrong.
Bad writing makes the reader stop thinking about what you wanted to convey. As unintuitive as it is for most people in this forum, AI writing smell is as bad as bad grammar. Doesn't matter how you get rid of it. Maybe even more AI can clean those up, but those unintuitive phrases that pop up in AI writing are going to be a hindrance for many people who would love for the focus to be on what they're presenting, not the sloppy way they've written it up
I am not affiliated with pangram.
teehee
A lot of pigments react to oxygen, and the sandy winds must not be kind to this kind stuff so I'm curious.
I know they've had to close Lascaux to the public for example.
What's annoying is that you can't opt out of certain cookies.
https://en.wikipedia.org/wiki/African_humid_period
I guess we'll find out when the next cycle blows the sand away?
It sounds to me like you want to censor perfectly fine phrasing just because AI rolled the dice to use it. Let's not forget that AI learned to "speak" from people in the first place.
Not to mention that as people shift their phrasing to avoid being accused of using AI, the AI will keep evolving, training on the new phrasing and then adopting it, too.
I understand the language evolves, but evolving language just to sound different from AI feels like wasting effort better spent elsewhere. On actual substance of the message for example.
We're not talking about bad grammar, but sentences that are correct and sensible, and if you wrote them before AI, nobody would bat an eye. But because they are used by AI, these days they make people dismiss the whole piece.
It's not really different from dismissing people because they happened to use the same phrasing as Stephen King. You can't even tell if it's because they read Stephen King that much, Stephen King wrote it for them, and they are now trying to pass it as their own, or just coincidentally arrived at the same literary construction.
Whenever I see those threads, they usually don't discuss the merits of the writing. They claim that AI must have been used, so it's not even worth reading.
But I still find that I have to consciously fight the urge to sound like an LLM. It's terrible.
- Distinction
- Is
- Important
Not really, and also they do not vary their writing like humans would. Human writers do not repeat the same pattern over and over as much as LLMs do. They'd get bored of their own writing.
People as a whole are always going to be sick of whichever affectation current popular LLMs have, since they'd be reading a fair bit of that. As a writer you should steer clear of things that would elicit groans in a contemporary audience and "LLM prose" is just the latest addition.
So, as the person you're replying to said, you'll have to get used to this being a new angle from which writing is critiqued. You'll live happier if you don't let your cortisol spike over it. If it is any comfort, writers will eventually adjust and you'll encounter less of it.
“I’m not sure…” / “I don’t…” hedges before disagreement Negation followed by correction/reframing is a recurring structure: essentially “It’s not X, it’s Y”.
And dozens of other examples. I wonder if LLMs really are more liable for it or if it simply seems that way purely because when you use a model it's almost as if you're speaking to the same "person". I think that human language is naturally formed by common agreed meanings of words first, and then phrases.
> “I’m not sure…” / “I don’t…” hedges before disagreement Negation followed by correction/reframing is a recurring structure: essentially “It’s not X, it’s Y”.
I did a manual human dig through GP's profile and I don't see any evidence supporting this. The literal strings "I'm not sure" and "I don't" do appear a lot (also in replies, which I'm hoping your LLM was intelligent enough to exclude?), and they are used to hedge before making a statement, but not a single one of them even approaches the "It's not X, it's Y" thing your LLM has claimed they do.
Your LLM did not find dozens of examples, it told you it did and you didn't even bother to check.
I could ask an LLM to generate something arguing against whatever yours put out, but I won't. I come here to talk to other people, not their electronic sycophants.
> As a writer you should steer clear of things that would elicit groans in a contemporary audience and "LLM prose" is just the latest addition.
Nope, thats you and your own self-pressures to adhere and conform to imaginary critical crowd, don't push it nor expect it form others. Its not a really happy way to live like that, is it. Maybe a warm fuzzy feeling when being in similar crowd, just pointing out that crowd may be more vocal but its actually pretty small.
Its really just some form of OCD/anxiety, unhealthy competitiveness, with a pinch of pettiness (as you write you completely reject any form of more moderate or tolerant approach or understanding how wrong in your assumptions you may be). You do you, just don't expect much respect for the n-th same comment on x-th article.
If you wish to continue the psychoanalyst LARP, feel free. Rather than be offended, myself and mine are bound to be further entertained.
But with reasoning enabled I find that even with a large context that induces mistakes most of the time a decent model realises and corrects itself before output.
And it's always been known that prompting what it should do is far better than what it shouldn't, since just introducing "DON'T do X" into the prompt means that the tokens for X are present and can be paid attention to in the wrong way.
But even then I've used plenty of "Do X, not Y" recently, especially for tools "Use this for x, don't use this for Y" and models perform like 90% of the time.
I would be interesting to experiment to see performance curves given a restriction on reasoning tokens allowed to n% of context tokens and see if there's some magic number of "reasoning should be at least n tokens for a context of length p" even ignoring the complexity of instructions in the prompt itself.