| ▲ | BurritoKing 6 hours ago |
| As someone who is aggressively pro AI, I've also noticed how awful everything is to read lately. It's always so hard to put my finger on the exact thing, but it's a mixture of everything sounding identical and everything being a rambling unconcise mess. I find I routinely start reading interesting posts and just .. stop part way, abandoning it. A site I read stories on has been flooded with AI generated content, all of it terrible, and it just makes me retreat to things created before 2023 as a way of filtering it all out. |
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| ▲ | HarHarVeryFunny 5 hours ago | parent | next [-] |
| A model trained to minimize statistical prediction errors is going to sound ... predictable (aka boring). A (good) human author tries to keep their writing interesting, while an LLM strives for predictable instead. It's not just predicting content but also the form/shape of the response, highly shaped by RLHF preferences, which seems to encourage longer form responses which need padding with filler to generate the "preferred" amount of verbiage. It seems most of these models have been trained to interpret questions as wanting a long-form authoritative/comprehensive-sounding response (even when midwit filler is all it has to offer), rather than initiating a short-turn conversation which would better allow you to steer the conversation. Apparently Muse is much better in this regard, but so far I've resisted signing up for any Meta/FaceBook service, and not inclined to break this winning streak! |
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| ▲ | hxtk an hour ago | parent | next [-] | | I vaguely remember a study that I was able to find when fact-checking this comment before publishing it [1], which found that music needs periods of high predictability to nurture listener expectations for the sake of later subverting those expectations, and the most enjoyable parts of music are those moments where expectations are subverted. This sounds like a similar effect. 1: PDF warning https://www.cell.com/current-biology/pdfExtended/S0960-9822(... | |
| ▲ | jacmilts 4 hours ago | parent | prev [-] | | Gemini models are so, so much better in this regard. Their outputs are actually readable. |
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| ▲ | NichoPaolucci 5 hours ago | parent | prev | next [-] |
| Don't these sort of conflict with being "aggressively pro AI"? > how awful everything is to read lately
> flooded with AI generated content, all of it terrible
> everything sounding identical and everything being a rambling unconcise mess. I can see the benefits of AI and enjoy using the technology - but, like many have said, it's wreaking havoc on the "content" that's out there nowadays. Gotta take some bad with the good, I suppose. |
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| ▲ | iLemming 4 hours ago | parent | next [-] | | > Gotta take some bad with the good, I suppose. Well, it's quite simple if you think about it. Intelligence is all about awareness of the imminence of death and the finite amount of time given to any of us. So, we humans intrinsically evolved to make the most of it. The majority of the tools we create have the ultimate purpose - to save time. Even money is nothing but a way to cut some time. It's not really about time but experiences - we want to have as many and as rich as we can get, and we innately try to cut time somewhere else, so we can use what we saved for better experiences. Therefore, inventing cars was an easily predictable event. There's not a single hypothetical timeline or dimension where humans don't end up with cars - to transport things and to travel faster. Similarly, it was always simply inevitable - we would have invented something like LLMs, sooner or later. Cars required significant sacrifices - they are absolutely deadly machines, they kill thousands of people every single day, kill wildlife, endager our own existence, and we're kind of okay with that. I can absolutely assure you, if someone tomorrow invents a gravitational jump travel that allows moving things between continents in minutes, even with a success rate as low as 10%, we would still be using it. So, yes. We can't un-invent cars and AI, the only way to move forward is to adjust to this new reality and extract the best possible experiences, preferably by not robbing other people of their - i.e., enjoy life while it lasts, it still remains finite. | |
| ▲ | derefr 3 hours ago | parent | prev | next [-] | | You can be pro-"thinking AI is going to get really good and solve many problems" (i.e. be the sort of person who would "go long" on AI), while also being anti-"applying AI right now to domains outside of the few it's been specifically optimized for [e.g. coding]" (because in these other domains, AI is yet to approach, let alone surpass, "authentic quality" equivalent to that of a skilled junior professional.) | |
| ▲ | soulofmischief 4 hours ago | parent | prev | next [-] | | I can like the concept of the engine, and the leverage it provides, but I hate traffic and get anxious about having an accident on the freeway. And the people behind the industrial revolution have destroyed the climate. I love computers and the internet, and the internet has ruined a lot of people and things around me. It's possible to be interested in a new technology and enjoy its leverage while still being extremely apprehensive about how it intersects with game theory and politics. The race to the bottom of the barrel keeps coming for the jugular of every cool new thing. | | |
| ▲ | throwaway_7274 4 hours ago | parent | next [-] | | I’ve been starting to think that a lot of the variance in how people see the world can be explained by whether their attention is drawn to first-order localized effects, or nth-order distributed effects. This is not the same thing as optimism vs. pessimism, but it sure is correlated! | | |
| ▲ | ctippett 3 hours ago | parent | next [-] | | This sounds intriguing. Can you expand on what your thinking is or link to somewhere I could read more? | |
| ▲ | soulofmischief 2 hours ago | parent | prev [-] | | It's a multi-mandate to focus on what's best for your yourself and society such as your mind, your body, your chosen family, your friends, your neighborhood/community, your city, state, country, the global population, and more abstract things such as the human condition, when evaluating things such as privilege or fairness or duty. You often have to make compromises somewhere in the hierarchy, especially in late-stage capitalism where even access to basic needs comes at a moral cost, and as such those compromises sometimes come with a moral duty. I am writing this via a computer built from limited natural resources, some of which have been obtained through what I see as slave labor. I don't eat meat and still have to acknowledge the harm that clearing and maintaining farmland does to wildlife, even if the result could theoretically be a net gain. When you start viewing situations through the lens of game theory, you realise some compromises are inevitable for the rational individual. But you must acknowledge the individual is not the only concern. As such, I use AI as part of my work, but I opposed the local buildout of a large data center in my community and tried in vain to make the person responsible for the deal understand the issues it could introduce. This isn't NIMBYism, we need a halt on all buildouts until fundamental environmental and accountability concerns are addressed. And many other aspects of my existence and quality of life, poor and underprivileged as I was growing up, have depended upon US imperialism. I have also produced a ton of waste just existing and owning pets. It's abhorrent. I continue to ask myself how I can fulfill the moral duty which I have accrued and reduce my dependence on exploitative economic systems, but I also recognize that AI is the new social leverage and we only have so much time to use it to our advantage before it becomes institutionalized and wielded against the people. I also might only find future income stability by evolving with my industry. Life is complicated. |
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| ▲ | smcleod 4 hours ago | parent | prev [-] | | This resonates with me and I suspect a lot of others here. As always life is more nuanced that many would have argue. |
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| ▲ | ballsac 4 hours ago | parent | prev [-] | | [dead] |
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| ▲ | jonshariat 4 hours ago | parent | prev | next [-] |
| Agree but also want to point out that this started with the SEO boom of the last decade where sites started rambling so they would keep you on the site longer and get more SEO "points", they were articles meant for a robot to catch humans. AI has made it even worse and lots of content on the web, for both these reasons, is not worth you time (now wonder users don't read most of the text on our apps!) |
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| ▲ | altairprime 3 hours ago | parent | next [-] | | In a prior evolution of this, if you look into the Get Rich Quick marketing copy of the early 2000s (before SEO had taken over content formatting), you can see a parallel of sorts in those marketers doing human sales optimization Impact with bold and underline. It derives from research into the human response to ads from decades of print ads and centuries of printed matter prior, and I think there is a direct lineage from ‘how can we bias humans through restructuring text’ to ‘how can we bias machines through restructured text’. This isn’t to disagree, but to call out how rapidly humanity (merely twenty years!) has switched from marketing to people, to marketing to algorithms, in search of a favorable bias. | |
| ▲ | psychoslave 4 hours ago | parent | prev [-] | | Ah yes I remember meeting this end of spontaneous expression to bend toward whatever might please some algorithm. Soulless Enshitificatoon Oblivion now exercises a huge weight on societies to such an extent, it's ridiculous. |
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| ▲ | basch 6 hours ago | parent | prev | next [-] |
| I suspect it’s partially an average / regression to mean. If you built a model only based on long form journalism and The New Yorker voice, including both the template structure of the article and the grammar and syntax, the model would replicate the patterns it is built upon. You could do the same for high vocabulary rap. When you stuff all of English or all of human thought into it with somewhat equal weight, including very technical writing the sum is a lack of style and elegance and personality. The second problem is that writing often doesn’t happen linearly. You write bookends and fill in, edit and revise. You sort of know where you’re going and can then make decisions how to get there. Language models may benefit from being redesigned to perform passes. Select a template of some sort, fill in the mad lib, then run a detail pass, then run a persuasion / emotion pass, then run a style pass. Current model writing very much sounds like I would expect autocomplete to. |
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| ▲ | notfromhere 5 hours ago | parent | next [-] | | It’s heavily RL’d and it’s gotten worse because they’re using LLM judges, that’s why it’s gotten worse. The last good writing model was GPT 4.5. I suspect they’re leaning heavily on some kind of auto verifier, and that’s why the writing sucks, because good writing is so subjective. And they’re probably nerfing what it can get from training as they’ve lost lawsuits for scraping copyrighted work, so they’ll purposefully avoid anything that references a specific writers style, etc. | |
| ▲ | BrokenCogs 5 hours ago | parent | prev | next [-] | | Isn't this easy for frontier 'labs' to fix? If the user requests lots of writing and prose, then use an auxiliary model which has been trained on 'award-winning' writing instead of all the crap on the internet? | | |
| ▲ | FeteCommuniste 5 hours ago | parent [-] | | Award-winning writing has all kinds of different styles. The average of them will probably get you some boring median soup once again, though maybe a bit less bland than the LLMs trained on oceans of LinkedIn and Reddit slop. |
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| ▲ | capnrefsmmat 4 hours ago | parent | prev [-] | | The "regression to the mean" or "it's just the training data" hypothesis doesn't work. Pretrained models do not have these weird writing styles and sound much more human. It's only after instruction tuning -- SFT, DPO, etc. -- that LLMs develop weird writing styles. That is, the original training on massive text corpora seems to produce an average of human writing, but that average looks pretty average. It doesn't feel like LLM slop. But the instruction tuning on specific tasks (answer this prompt, summarize this text, do this math problem), which turns text predictors into chatbots, seems to create strange style features as a side effect. And because that tuning step depends on company-specific training data (rather than just a crawl of the entire Internet), each company's LLM has a different style. It's not that difficult to measure this. Linguists have had measures of style variation for a long time, though NLP and AI researchers seem to have forgotten. We've generated parallel human and AI corpora to measure it, and can show specifically which writing features change: https://arxiv.org/abs/2410.16107 Currently we're working on tweaking the instruction tuning process to see if we can pin down which steps and what types of tasks tend to produce the weird style features. |
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| ▲ | fxwin 3 hours ago | parent | prev | next [-] |
| > it's a mixture of everything sounding identical and everything being a rambling unconcise mess. For me it's mostly the latter, which is a natural consequence of LLM writing. When the (time) cost-per-word goes down, there is less incentive to keep signal-to-noise ratio high, so it ends up verbose and bloated. I also believe that this is (at least partially) upstream from everything sounding identical: take two articles on two different subjects - when SNR is high, there isn't really much room for them to become similar (The ingredient list for a risotto will never read the same as the ingredient list for pizza), but when 80% of them is fluff, they can blend together more easily (To take the recipe comparison, this would be the background/story part above the recipe), especially when written by the same LLM |
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| ▲ | Animats 3 hours ago | parent | prev | next [-] |
| > sounding identical In AI-generated entertainment, the names "Marcus", "Chloe", "Sterling", "Meridian", and "Apex" keep appearing. Those aren't common names, but LLMs seem to prefer them. |
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| ▲ | psadauskas 5 hours ago | parent | prev | next [-] |
| The part I find grating is the attempts to punch everything up. ("It's not X. It's Y"). Like, its a react badge component, it doesn't need punching up. You didn't find the smoking gun in a murder mystery, just a misplaced CSS rule. |
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| ▲ | triMichael 4 hours ago | parent [-] | | I've noticed this as well, I've been comparing it to 4Chan Greentext memes. Everything is a short punchy sentence, and every sentence has the same "weight" to it. There's no flow or rhythm, it's like reading off bullet points. |
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| ▲ | kinduff 6 hours ago | parent | prev | next [-] |
| How is someone "aggressively pro AI"? This is the first time I read such concept. |
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| ▲ | unified101 6 hours ago | parent | next [-] | | Is typically called ai booster. The opposite is ai doomer. | | |
| ▲ | SrslyJosh 4 hours ago | parent [-] | | Importantly, both boosters and doomers are believers (or perhaps cultists). A doomer isn't skeptical; they're nearly as credulous as boosters, or maybe more so in some ways. | | |
| ▲ | bigfishrunning 4 hours ago | parent [-] | | Not necessarily -- I am extremely anti-AI; I think the danger is not that it's good, it's that it's convincing. Turns out most people don't care about the quality of art or prose or code that they interact with, and it's very depressing. | | |
| ▲ | topaz0 an hour ago | parent | next [-] | | That's not exactly what I've heard called a doomer. Doomers are the ones who think we're building the wrong AI god. (But I agree with you fwiw) | |
| ▲ | ragequittah 4 hours ago | parent | prev [-] | | My take is that most art, prose, and code was really bad before AI too. Now there's just more of it good and bad. It's like hating that YouTube exists because cable TV was so good. Now anyone with a camera can make and upload whatever nonsense they want but in the end lots of very good content was made on top of the huge pile of rubbish. |
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| ▲ | drusepth 6 hours ago | parent | prev | next [-] | | https://en.wikipedia.org/wiki/Effective_accelerationism | |
| ▲ | paulddraper 6 hours ago | parent | prev [-] | | Leans into AI adoption. |
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| ▲ | xendo 3 hours ago | parent | prev | next [-] |
| This applies to code btw, it's so much nicer to read a human made pull requests. It's also much faster as people tend to be lazy and produce denser code. |
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| ▲ | alabut 4 hours ago | parent | prev | next [-] |
| I’ve got the same bright red line for 2023. E.g. I treat a handful of youtube channels with long electronic jams almost like oldies at this point - keep listening to the same stuff from at least two years ago because it’s the authentically good stuff. |
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| ▲ | ashkankiani 5 hours ago | parent | prev | next [-] |
| Do you have some personal financial or other incentive to be “aggressively pro AI”? |
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| ▲ | rvz 5 hours ago | parent [-] | | They will never admit it, but they give clues. It makes no sense on being "aggressively pro AI" without any payment. It is like being an unpaid shill. | | |
| ▲ | crummy 5 hours ago | parent [-] | | There are plenty of people that genuinely believe it’s going to cure cancer, solve all our problems, and end work. |
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| ▲ | jansport123 4 hours ago | parent | prev | next [-] |
| to AI verbosity and weird use of diction is natural, to humans it makes it hard to parse. The number of time i start reading long winded AI written design docs, and i just can't get into the flow after reading a few sentences and have to keep re reading certain sentences. |
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| ▲ | pton_xd 4 hours ago | parent | prev | next [-] |
| LLMs have made the internet unreadable. It used to be just Google search results were SEO-gamed empty prose, but now it's every blog post, news article, product announcement ... everything. I've stopped reading basically everything online except user comments on a few websites. It's the last place remaining to actually connect with other human minds, but even that seems like it won't last forever. |
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| ▲ | giancarlostoro 3 hours ago | parent | prev | next [-] |
| Personally, for blog posts, documentation (unless I flat out vibe code the entire thing) etc are all written by me by hand. If the model can save me hours of "oops that was really dumb of me" why can't I take time to read and document things by hand? I think everyone's embracing AI in the wrong ways. Maintain your knowledge of things, and keep the documents nice. There's still room for letting your agent manage agent specific docs, but for the humans, just write it yourself, ask the model for feedback and tweak it by hand. Let the machine talk to the machines. |
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| ▲ | pj_mukh 6 hours ago | parent | prev | next [-] |
| Gentle reminder that most AI token spend is used for TPS report type writing not Cutting edge fiction writing. Creative writing, or general human-to-human communication was never really the target. It's not surprising the first majority use of this was code. Endless headlines like, "aArON SORkIn SAYs hE WiLL Never UsE ai to WRite" doesn't change that base fact. No one asked him to, other than clickbait journalists. If you find this hard to believe, just think about relative market sizes. |
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| ▲ | SrslyJosh 5 hours ago | parent | prev [-] |
| > I've also noticed how awful everything is to read lately. Yeah, thanks dude. We appreciate your efforts to enshittify everything. Edit: Sure, downvote, but the parent comment is really not very different from "arsonist puzzled and upset that so many buildings have burned down". |
