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A contact just told me that my old "LLMs generate nonsense code" blog post from 2 years ago is now very outdated with GPT5 because it's so awesome and so helpful. So I asked him to give it a test for me, and asked it my favorite test question based on a use-case I had myself recently:
Without adding third-party dependencies, how can I compress a Data stream with zstd in Swift on an iPhone?
Very confident, very bold, even claims "Works on iOS 16+".
Problem with that: Just like any other LLM I've tested that provided similar responses, it is - excuse my language but I need to use it - absolute horseshit. No version of any Apple SDK ever supported or supports ZSTD (see developer.apple.com/documentat… for a real piece of knowledge). It was never there. Not even in private code. Not even as a mention of "things we might do in the future" on some developer event. It fundamentally does not exist. It's completely made up nonsense.
This concludes all the testing for GPT5 I have to do. If a tool is able to actively mislead me this easy, which potentially results in me wasting significant amounts of time in trying to make something work that is guaranteed to never work, it's a useless tool. I don't like collaborating with chronic liars who aren't able to openly point out knowledge gaps, so I'm also not interested in burning resources for a LLM that does the same.
Because it already happened: if you read my post and you feel an urge to respond with something along the lines of "it's just a hallucination", "it's just a bug", "it will be better in ChatGPT 6", or anything even close into that direction, please stop. Read this post and the next post, think about them, and if you have a factual argument to respond to me, only then reply. Focus on my factual claims, not on some inaccuracies in my analogy because of course it's not 100% accurate, that's the nature of analogies.
ChatGPT making up ZSTD compression in the Compression framework is not a bug. It's not even a weird edge-case. ChatGPT is doing exactly what it is designed to do. Let me try to explain.
If we grossly oversimplify what an LLM is, it's "just a statistical model" that generates "language" based on a chain of "what is most likely to follow the previous phrase". "language" can be anything: it can be human language, a fictional language, but it also can be code or even genetic information. Any kind of textual thing that you can feed large amounts of into a model works. "Not having an answer" is not a possibility in this system - there's always "a most likely response", even if that makes no sense.
ChatGPT inventing ZSTD compression in the Compression framework isn't due to a lack of training data. If you request an overview over all compression algorithms supported, it answers correctly with a comprehensive list that does not include ZSTD. So, if you want to anthropomorphize ChatGPT, you could say "it knows that ZSTD isn't supported", but that doesn't matter. LLMs do not possess the ability of logical thinking, deductive reasoning, or anything else. "It knows" that there are a bunch of compression algorithms available, the constants are all called COMPRESSION_[method], so there's a high likelihood of COMPRESSION_ZSTD to be the answer to a user asking for ZSTD compression in Swift. And so it generates that.
The only way ChatGPT will stop spreading that nonsense is if there is a significant mass of humans talking online about the lack of ZSTD support. For example a bunch of StackOverflow questions asking "How do I do this?" and people responding "you don't, Apple doesn't support it, you have to use third-party libraries" - or if you have a bunch of white dudes working in tech complaining on social media about Apple not supporting ZSTD in the Compression Framework.
My next post will be an attempt at comparing human thinking and LLMs generating text. As mentioned earlier, it's an analogy - and it's not going to be 100% accurate. If you want to reply, focus on the factual claims. If you only want to nit-pick my analogy, I have to assume you're not interested in productive argumentation.
Let's imagine you're colorblind. The kind of colorblindness that only allows you to see grayscale - no colors at all - but everything else is fine.
You're stressed and need fidget toy - so a friend hands you a ball, roughly filling your hand. It's hard, but somewhat squishy, and has a weird fabric-like, furry texture. You now want to know what color that ball is. But, well, you're colorblind, and your friend already disappeared and isn't reachable - probably riding a Deutsche Bahn train or something.
So you take a picture and post it to a "what color is this?" subreddit. Seems reasonable. You get 200 responses - 198 of them say "it's yellow", two of them say "it's pink". A few people helpfully say it's a "tennis ball". That's helpful, because even the Wikipedia article states that only yellow and white tennis balls are officially approved colors. Sweet.
A few days later, a random person approaches you and says "wow, cool ball - what color is it?" and you say "yellow!". Alright, end of the chat. A LLM would do exactly the same - given the "yellow" responses far outnumbered the "pink" responses, your ball is probably yellow. Ball==yellow is something both you and the LLM "learned". A few weeks after that, another friend asks you "ALice has a ball, too! Do you know which color her ball is?" - and now it gets interesting.
The LLM would immediately say "yellow". Of course it would. It makes sense. Yellow is the most likely response to that question.
But you're not an LLM - you're a human, and your brain is cool. Instead of saying "yellow", you respond "huh I don't actually know that? My ball is yellow, maybe she has a similar ball. But it could also be that she has a completely different ball that might a different color! Also, lol, I'm colorblind, so I can't really answer that anyway - you should ask Alice." And now, your brain is already doing better than any LLM. Your logical thinking engine already realized that you don't actually know something, and you're honest enough to just say that. Your job isn't to be a ball color guesser, you're just a person.
Wait, it's gets more fun! A few weeks after that, you hang out with me. You hand me your ball, and say "hey look at my cool yellow ball!". Oddly enough, my reaction is "huh? this ball isn't yellow, it's a pink tennis ball..." and now things get funky. If you were an LLM, you would either insist that no, your ball is absolutely yellow - or you'd come up with some kind of "oh, sorry for the misunderstanding - it's pink, you're correct", almost implying that my definition of color is different - and the next time someone asks you about the color of your ball, you'd still say "Yellow!!" again. Because of course, there's still only three people claiming it's pink, and still 198 people saying it's yellow.
But you're not an LLM. You're human, and your sexy human brain immediately goes into a "uhhh we have a conflict of information! how exciting! let's figure things out!" You now have to conflicting hypotheses, and you're thinking about ways to experiment on your ball to learn more. And you have an idea! You know your additive color mixing theory, so you realize that your phone camera can take pictures and you can look at the RGB values. If it's yellow, you'd expect to see lots of red and green but no blue - but if it's pink, you'd see lots of red and blue, but no green! You can test that!
So you take a photo, and... rgb(255, 0, 255). Turns out your ball is actually pink! It's still a tennis ball, but a fun one not meant for official tournaments, so it's pink! Wow! You immediately learned something new - and from now on, if someone asks you about the color of your ball, you'll say "pink!" and you'll have a heck of a story to tell alongside. Also, after some self-reflection, you realize that the subreddit your posted your image to wasn't a real "what color is this?" subreddit - it was one of those "false answers only" shitposting subreddits. Whoops.
This process of having assumptions, but being able to question them, to come up with tests for it, and to immediately change your opinion on something when you have good evidence for it is what makes humans awesome. You don't rely on the majority of people screaming "pink!" at you. You don't need to rely on manual weights that give some sources more weight than other sources - you can independently process information and deduct things. Give your brain a pat on the.. uh.. cranium.
LLMs can be a useful tool, maybe. But don't anthropomorphize them. They don't know anything, they don't think, they don't learn, they don't deduct. They generate real-looking text based on what is most likely based on the information it has been trained on. If your prompt is about something that's common and the majority of online-text is right, you'll most likely get a right answer out of the LLM. But if you're asking something that not a lot of real people had interactions on, the LLM will still generate text for you - but it might be complete nonsense. You're just getting whatever text is "statistically most likely".
If you're a coder stuck on something, identify a colleague or friend who is more knowledgeable in that specific area. They'll happily help you out and provide all sorts of fun added context that'll allow you to learn. If you're a nerd on the internet who enjoys ranting on social media, just do it yourself instead of having an LLM generate it, because that'll allow you to insert some bad jokes and a bit of your own personality to it instead of just getting a "default-feeling" text. If you're a manager in charge of something and you need to come up with new directions to push your company towards, go take a walk outside and listen to some cool music and let your ideas roam free - don't ask an LLM to generate the statistically-most-likely direction for your project, because that's by definition the opposite of creative and innovative.
> Uhh I have a conflict of information! How exciting!
Yeah people can do that. But they often don't. They especially don't do that when the thing they're wrong about is part of their identity or group identity. And that makes me sad.
@cleantext in any case, we should be striving for truth, and while humans sometimes struggle with that, we should be developing computers in a direction that helps us be more logical and intellectually honest, not ones that push us towards lying and appeasement.
I think that's not optional. That is to say, as you push the limits further and further, failure modes get amplified, you end up on a knife-edge, and if you try to bias it in any way, that bias gets echoed into a feedback loop and you get a basket case.
@cjd @cleantext I highly doubt that all possible forms of AI have the failure mode of answering incorrectly, and AI is far from the only way to use a computer.
Many kinds of software, from a spreadsheet to a SAT solver, help humans be more rigorous and make less mistakes. We don't need to pursue LLMs.
Oh right indeed, I read your post and mentally inserted LLM around the "intellectually honest" part.
Actually that's kind of a microcosm of the same thing: Intellectually honest software is like simple unix philosophy, open source, etc. Has longevity, continues to endure and evolve.
Intellectually dishonest software is like overcomplicated, meant to sell support, planned obsolescence, etc. Has very poor longevity, gets replaced (maybe replaced by different dishonest software, but replaced nonetheless).
My argument re LLMs is that we will hit a point at which NOT trying to be as honest as possible while building them will cause the above effect to take place within seconds, and the thing will just collapse.
Twenty years ago a blind friend showed me a gadget that spoke colours. Works for wires.
I'd also call red + blue without green either violet, purple or magenta, Pink is mostly de-saturated red.
Just nit-picking. The tennis ball and grey only seeing person example is nice, though grey only colour-blind is extremely rare and usually basic vision is poor.
I tried to explain pretty much that ⬆️ to an acquaintance last week. Not even two sentences in, I was met with "oh shut up and stop talking nonsense", repeatedly. I kept explaining (to the rest of those present) a simplified version of how LLM training works, and said person kept interjecting telling me I knew nothing and to shut up.
The reason? They use ChatGPT at work "daily" and it's so amazingly fast and it provides "sources". When I pointed out those sources are often wholesale false, they said "well you have to check them of course!", but declined to answer my question what the advantage of ChatGPT is if you have to do all the reading yourself anyway (probably because they don't actually do that).
People's opinions on LLMs have become one of my go to metrics to judge someone's character at this point, because someone who's unwilling to engage with factual arguments that run counter to what they want to believe is, frankly, a danger to everyone around them. Today it's ChatGPT worship, tomorrow it's climate change denial and anti-vaxxing. Because anyone who spends even an hour learning about what's under the hood of an LLM would be thoroughly disenchanted with the frauds who push that shit onto everyone.
I'm imagining right now the CEO of some weapon producing company asking a LLM what would be the best idea for a next product, and getting something like swords or spears, because for a long time that is how wars where fought and won.
Your example reminds me on how at the beginning of ChatGPTs existence, I asked if vampires get swollen feet after standing for too long, because of the lack of a circulatory system. The generated answer was that vampires are imaginary beings, and therefore human physiology can't be applied to them. That is imo a boring but accurate answer.
Some time later it generated something more exiting, that was wat I wished to read, but that felt wrong because depending on the world, vampires either don't have blood, or have some sort of stomach where it's stored.
I love that last line and I'm going to borrow that when LLMs come up.
I tried saying something similar to my coworkers that LLMs can't ever innovate they can only regurgitate. We're required to use them at work now at least some of the time, and I've been one of the only vocal skeptics.
Thanks for this beautiful analogy and your engagement. One thing that I like to add: How come, that so many people are enthusiastic about the achievement to use a machine, that can deliver millions of exact calculations in one second to provide one unreliable result in eight? It's such a waste of energy (electric and in thinking) #donttrusttheparrot
thanks. This was a really nice way to explain the “mostly plausible, sometimes accidentally correct” to my kids during breakfast.
I like your tennis ball analogy too. I think you mention in it some of what makes us different from (current) AI.
We have learned from experience and evolution that you sometimes need to be correct. It matters. It can ultimately be a matter of life and death for us. Of bruises, cuts, hunger, cold, social disapproval.
So we can value being correct. We’ve can “feel” it in some sense. We’ve got a stake in the game.
Current AI training doesn’t seem to feature that. Or give an ai a universe to reckon with correctness in.
I suspect that’s surmountable. Future training approaches might be able to embody that kind of learning process. Reckoning with reality.
I thought maybe the chain of thought and reinforcement learning used in more recent LLM training might start to do that, but it doesn’t seem to have.
Thank you. I knew what it did intellectually. I also checked it out for myself with some examples like that compression. I was still never able to explain it. I will try tennis balls now.
someone else may already have mentioned it (many may have). But if not, I'd add a section acknowledging that unless your camera is color accurate in the lighting conditions present when you shot the photo of the tennis ball, the resulting image of a truly white ball could easily come out yellow - or pink. The human eye/brain connection tends to understand changes in color temperature far better, so I'd go for asking multiple people to look at the ball and aggregate their responses.
well I'm glad you can find coders to help you, but nobody knows how to make a vulkan Wayland compositor that I can contact so I'm kinda desperate... LLMs doing research across hundreds of sites with no documentation to pick out things is useful!
even as a totally blind person, im' still trying out the point of this post. i think it'd just be easier to say the entire point of the post. "don't use redit". "don't use an lLM". please, actually get to the fucking point...
- here's the new version it's so much better - ok can it pass this test - ah you're right, there's an issue. Here is the new version that solves previous problems - ok can it pass this test - ah my bad, here's a version with your problems fixed
An epic thread! 👏 You nailed the fundamental nature of #LLM #AI and #GenAI. They are incapable of “knowing” anything or reasoning about factuality in general.
I suppose they might be able to tell you something reasonable about letter, word and phrase frequency distribution in their training data if they tabulated it, but that information is only implicit in their model.
Thanks for writing this! it really puts alot of what i feel about LLMs into words. I feel alot of people are trying gaslight me into thinking being anti-LLM is some anti-technilogy stance, but its just not great technology. Maybe it has its uses, but the layman has so many better choices.
And thats without getting into the environmental impact
Friends don't let friends use vibe code in production. Maybe I sound old-fashioned, but I really don't like this trend at all. I'm by no means a great programmer, but even I see the value in struggle and failure as part of my own practice in becoming better at my craft. There's no shortcuts.
what is my option if I want to, say package my favourite program in a snap, the information given in documentation does not work, no one answers in the forum, it's a hobby project, and I don't know programming?Before llm I had to stop. But now I succeeded by reiterating the processes in multiple LLM, debugging the wrong code of one by another, and finally create an automated workflow for the process. Yes there was a lot of electricity and water consumed. But was there a way before?
"ChatGPT making up ZSTD compression in the Compression framework is not a bug. It's not even a weird edge-case. ChatGPT is doing exactly what it is designed to do."
You didn't prompt it correctly. Even ChatGPT 4 gets it right:
"Without adding third-party dependencies, can I compress a Data stream with zstd in Swift on an iPhone?
Do not make up any answers. Use the real iOS developer documentation as your reference."
Then it explains that ZSTD isn't supported and tells you everything that is supported in great detail
It's your job to establish the rules. Your example is like telling a student to write a 500 word essay on George Washington, but not that they have to cite their sources and then getting flabbergasted when they tell you he was 6 foot 8 and weighed a ton
Why would petrostate despots like Alwaleed bin Talal, Charles Koch, and #PrinceBonesaw Mohammed bin Salman take a sudden interest in a niche tech development in 2018? axios.com/2017/12/14/koch-trie…
I enjoyed this thread. I've been experiencing these issues with LLM's for some time now, they constantly make up new switches for Unix commands, make up new syntax for things like Zabbix triggers, make up new features in Ceph and new commands for Ceph interrogation that don't exist. ChatGPT and CoPilot are confidently wrong most of the time. Bullshit generators are the most correct of descriptions. I'll use the free tools when I'm being utterly lazy but wouldn't pay for these LLM's.
Still better than that team member I did not choose and that aggressively bitches back
I have seen all the criticism in LLMs and my impression is: they are pretty great, approximating training data I fear is there. They speed up a process that might have had flaws before by bigger better faster more flaws.
Police in London arrested at least 365 protesters on Saturday who defied an anti-terror law by holding placards expressing support for a recently banned
"A new psychological study has found that people who report favorable views of Donald Trump also tend to score higher on measures of callousness, manipulation, and other malevolent traits—and lower on empathy and compassion. The findings, based on two large surveys of U.S. adults, shed light on how personality traits relate to political beliefs, including support for Trump and conservative ideology."
"Conservative political ideology is associated with social dominance orientation (SDO), right-wing authoritarianism (RWA), psychopathic propensities (PPs), and other malevolent dispositions, and reduced empathy."
"We examined the links between SDO, RWA, PPs and political ideology, and whether those who view Trump favorably reported higher PPs (or malevolent traits) and reduced empathy or benevolent dispositions."
I know there are no algorithms here, but I was *just* having this conversation with some friends in the car as we were coming back from the city and this popped up.
I'm not sure what we can do about it. This kind of mindset and way of being is starting to be baked into certain sectors of society, and they are always the loudest ones and the brashest ones as well, so the quieter, more sane, compassionate voices just get drowned out completely by their constant noise.
Iran welcomes the recent peace agreement between Armenia and Azerbaijan as a step toward regional stability, while warning over foreign meddling in the Caucasus region.
c'est une excellente question. Je l'ai entendue cette aprèm et j'aurais tendance à dire la Symphonie. Mais j'ai l'impression que ce ne serait pas très raisonnable
I thought the ability to "pin" a given model to a character/profile in AgentV3N would be a gimmick, not a real selling point
Then GPT-5 dropped and a few subreddits are flooded with people mourning the loss of something they've grown attached to. Obviously, I can relate to that.
While we're obviously in no position to capitalize on GPT-5's release, we think that the people affected by this will remember it. And while they'll be reluctant to trust again, or will have already put their trust back into OpenAI, we want to build reliability into the system from the start.
We will be strategically selecting "Forever Models", open-weights models that demonstrate consistency, are available on a large number of inference providers and, if absolutely necessary, can be run in-house on our hardware.
If you pin a character to a Forever Model, the model won't change. It will be able to call nicer, newer models as a tool call, but ultimately, the response will be written by the one you chose.
The whole point of digital anything is that it can be backed up and replicated. You should never have to say goodbye to something that's digital. That's the whole point.
ChatGPT 5 was released today.
ChatGPT-maker OpenAI has unveiled the long-awaited latest version of its artificial intelligence (AI) chatbot, GPT-5, saying it can provide PhD-level expertise.
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Indeed... It's a coalition for the National marches... stopwar.org.uk/events/national… I don't want to knock the actual marches but it is a bit of a closed shop, very in bed with the Palestinian Authority... In the space of 29 marches it's gone from being branded as hate marches to praise yesterday from Yvette Cooper for being peaceful... The truth is the only thing that makes them fearful is direct action and BDS both of which they have made illegal... gov.uk/government/news/uk-publ…
Ranjeet Brar on today’s news that more than 380 people have been arrested for holding signs in parliament square that say “we oppose genocide - we support Pa...
From the US and Australia to France and Italy, those seeking to obliterate privacy and restrict content are on the move, says technology journalist Taylor Lorenz
We speak to Matt Kennard about Britain’s role in the Israeli genocide, particularly its spy flights over Gaza.Kennard is an independent journalist and previo...
Un proyecto de real decreto quiere obligar a estas instalaciones a informar de su eficiencia energética y consumo de agua, así como a aprovechar el calor residual de sus equipos
Compartimos lanzamiento de nueva campaña contra la burbuja de los centros de datos en Aragón. Desde El Juncar es Vida hemos querido contribuir con nuestros esfuerzos y formar parte de esta iniciativa, pues defendemos que ni Aragón, ni nuestra agua, ni nuestra energía, puede ser vendida a grandes fondos de inversión y empresas tecnológicas para su enriquecimiento individual bajo la promesa de falsos empleos.
Anota la fecha: 27 de septiembre, manifestación en Zaragoza.
Queremos anunciaros la puesta en marcha de una nueva campaña titulada No es sequía, es saqueo, dedicada a la defensa del territorio Aragonés, con quienes definitivamente compartimos intereses comun…
#MidiLibre Bitchat : le cofondateur de Twitter lance son nouveau réseau social révolutionnaire qui fonctionne sans connexion Internet
> Bitchat, un réseau social fonctionnant sans Internet grâce au Bluetooth basse consommation. Les messages, chiffrés et éphémères, transitent dans un rayon de 300 mètres sans compte utilisateur. Si la plateforme mise sur la sécurité, elle suscite des inquiétudes sur la modération.
Jack Dorsey, cofondateur de Twitter, a lancé le 28 juillet 2025 l’application gratuite Bitchat, un réseau social fonctionnant sans Internet grâce au Bluetooth basse consommation.
J'ai hâte d'entendre les francophones parler dans les médias de Bitchat. Ça sonne trop bien.
Donc en gros c'est un pseudo IRC par bluetooth... Moais, à voir. Peut-être sur un campus, dans une conf, un concert, ou dans un train ça peut être rigolo.
Editor’s Note: This release was edited Aug. 9, 2025, to update the International Space Station docking port for the Crew-10 mission. The first crew to splash down in the Pacific Ocean off the coast of California as part of NASA’s Commercial Crew Program completed the agency’s 10th commercial crew rotation mission to the International Space Station […]
Some New York teens are risking their lives by “subway surfing” to gain social media clout. NBC News’ Gadi Schwartz reports on how the NYPD is using drones to prevent these incidents.
By Philip Giraldi. Our leaders and decision-makers, who have worked so hard to promote Israel at the expense of the United States, may soon have to pay a high price for their maneuvers, because the tide is undoubtedly turning.
it's not even bait, it's the truth, why play video games with a demographic like that? i never understood matched multiplayer with randos, it's just the worst kind of gaming experience you can make. play on the lan over multicast so that only people who visit your house or have access to low latency multicast backbone networks can play matches with you.
Season 4 Reloaded of Black Ops 6 & Warzone has just dropped & with it came a chunk of new content was released for players to enjoy. However, with all this new content, some content was found in the files by leakers online.
@bronze @jeff black ops 6 is literally why bf6 has so many players right now, there's serious cod fatigue but at least unlike bf6 if you install Windows it'll run on the deck youtu.be/MA_yAwum7bI?t=231
I got Black Ops 6 (Xbox Gamepass) Working properly on my Steam Deck LCD running Windows 11 and I am really enjoying it. Here are my settings along with some ...
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On the night of June 5, 1944, before the first wave stormed the beaches of Normandy, elite paratroopers from the 101st Airborne Div were already deep behind enemy lines. Their mission was critical: secure key crossroads, disrupt German defenses, and pave the way for the beach landings at dawn.
This video uncovers rare original footage and firsthand accounts from the paratroopers who landed near
History should be shared.
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The channel dedicated to bringing you your military history fix, from the perspective of a serving Military Officer.
Marmion Farm, a vital objective just outside Carentan. What they encountered there was brutal, chaotic, and decisive. Facing fierce German resistance, the battle for Marmion Farm became one of the earliest and most dangerous engagements of D-Day.
Through restored archival film, maps, & testimony, this video brings you as close as possible to the experience of the first soldiers on the ground. These men weren’t storming the beaches—they were already fighting for their lives behind enemy lines.
Pretty wild how Kubrick shot his scenes dozens if not over a hundred times always and then you got directors like Clint Eastwood who rarely did more than two takes. And as much as I like Eastwood as an actor, he was an even better director and I wouldn't put him outside of Kubrick's level.
Steven Spielberg vs Alfred Hitchcock. Epic Rap Battles of HistoryYou decide! Want to help ERB? Support us here: http://patreon.com/erbYou can listen to this ...
Socialist, Zohran Mamdani has won the primary for next potential Democratic mayor of New York, today we'll discuss how we got here and the true impact that both legal and illegal immigration has had o
Many more than Hitlery are the reason for the treason. They, too, will pay for their treason, child trafficking, murders, voter fraud, & the list goes on.
Toni Aittoniemi
in reply to Ann1944 • • •Somebody better check the status of that promised moon landing / interplanetary transport system while they’re at it.
Should’ve been a lander on the moon by now, if I’m not mistaken.. 🤔
John
in reply to Ann1944 • • •That’s not going to happen until after the next #AmericanCivilWar #USPol #Musk
Actions have consequences.
felis_catus_domesticus
in reply to Ann1944 • • •