4 ms·
My strategy these days is to scan and look for the tells and click out when I see them. Mine was the same "honestly ranked, with no silver bullets on offer". I
by renlo 2mo ago
My strategy these days is to scan and look for the tells and click out when I see them. Mine was the same "honestly ranked, with no silver bullets on offer". I suspect in less than a year we won't be able to tell the difference.
- cephei 2mo agoIn a year or more, the audience will likely be an agent instead of a person. It'll be interesting to see how that shifts language and article formats.
- paulpauper 2mo agoIt already is. AI bots overflowing visitor logs now with endless IPs
- thatjoeoverthr 2mo agoIt has been for years. The actual audience for a great deal of text you see is Google’s ranking system. Look up any recipe and ask yourself who reads the ten paragraph story time about grandma’s cookies. It literally isn’t intended to be read.
- StilesCrisis 2mo agoI believe this also partly sprung up because recipes in isolation don't qualify for copyright. The flavor text gives you grounds to sue if a clone of your recipe site pops up somewhere else.
- paulpauper 2mo agolol reminds me of a Claude math paper: "honestly sharp , no hype: cos(pi+pi)+2+2=cos(2pi)+4=1+4=5"
- rogerrogerr 2mo agoI’ve thought this for a while, but why hasn’t it happened yet? At this point, OpenAI and Anthropic and friends could definitely remove the AI “smell” from writing output, or give users a first class way to specify a writing style. So why haven’t they? My theory is they see this as a sort of fingerprint, useful to not train on later. Or something. Maybe they just don’t care. Certainly feels either intentional or a result of ambivalence. It’s certainly true today that I probably wouldn’t know an AI written article if the author went out of their way to use one of the many prompts available to tone down the AI-isms.
- paulpauper 2mo agoBecause it's doing what is does best: making predictions, which works great when you're not being judged on aesthetics, such as coding or math, but the human thought process is messy or erratic. It just falls apart when you do the next token process to it. If the goal is to "convey information in readable chunks," AI does great at this.
- thatjoeoverthr 2mo agoIt’s natural to the fact it’s the same model. Everyone has tics, and when a given model is asked to write millions of texts, they become visible. But! Some portion of the audience and user base can’t see it, so there is no benefit to fixing it. Case in point, yet another hustler felt very clever posting slop, and the likely actual audience (Google’s ranking system) probably does like it.
- xboxnolifes 2mo agoIf the underlying prompt of the model stays the same, it seems to me that LLMs will always have common tells unless overridden with a thorough prompt from the end user. It's like if you had 1 person write half of the content on the internet. You'd probably get pretty good at noticing their writing style. Maybe my understanding of LLMs is wrong, but it seems obvious to me that when you have a large corpus of LLM output you will eventually notice common tells when everyone is using the same models, weights, and base prompt.
- winterbourne 2mo agohttps://en.wikipedia.org/wiki/Wikipedia:Signs_of_AI_writing https://en.wikipedia.org/wiki/Wikipedia:Signs_of_AI_writing This wiki page is updated frequently and only needs to be fed into an AI to remove its telltale writing.
- volkercraig 2mo agoYou're overthinking it. LLM's are massive scale regressors. Rhetorical techniques, cliches and memes (in the original Dawkins definition) spike the dataset and skew the data such that certain phrasings or rhetorical techniques will appear in the output in a similar ratio to what exists in the training set; however, the reality is that humans are able to change writing techniques depending on the nature of the conversation and the medium. LLM's don't have that, all of the scholastic papers, buzzfeed articles, and reddit posts factor into the output regardless of what it's writing. Meanwhile your average human can switch tone, style, and register depending on the situation and what they're writing. I asked claude to take the above and rewrite it in it's own words and it came up with: "LLMs are essentially large-scale statistical regressors — they're built on huge volumes of text, so the rhetorical patterns, clichés, and memes (in the Dawkins sense of self-replicating cultural units) that saturate the training data show up in outputs at roughly the frequency they occur in that data. The key limitation: a human writer naturally shifts register, tone, and style based on context — what they're writing, who it's for, the medium. An LLM doesn't really do that in the same way. Every academic paper, Buzzfeed listicle, and Reddit thread it was trained on bleeds into its output regardless of the actual writing task at hand, whereas a person adapts fluidly to the situation." Even with the context, it still included an emdash, the rhetorical technique of threes, and "the key limitation". It's an inherent weakness of LLM's. There is no fixing it.
- robwwilliams 2mo agoI have started beating the hell out of Claude with stylometric analyses of writers I admire; usually technical writers like Terry Winograd, Leslie Lamport, Rodney Brooks. Then the “no or minimal rhetorical flourishes” rule; no British em-dashes, and minimize the negative phrase thesis-antithesis fun”. It helps. I think you are right that in a year or two LLMs will be able to do a good impression of many technical styles. But not Nabokov, Kundera, or Kafka for subtlety. If one manages to channel Edsger W. Dijkstra I will be impressed and rank it high on my leaderboard.
- frollogaston 2mo agoThis article was too verbose for me to want to read it, but I'm still not sure about it being LLM-gen'd. All I got is Claude says "honest" a lot.