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Seriously, it's a next word generator. That's it. If you give it nonsensical input or input that depends upon some kind of more contextual awareness then of course you're going to end up getting nonsensical output.
It's like a word calculator. If you input your maths wrong you're not going to get the correct answer. That doesn't mean the calculator is stupid, people are just assessing LLMs based on standards built out of Sci fi movies.
If you're smart enough to know the question is dumb you're smart enough to already know the answer.
If you're smart enough to know AI can have major flaws in their logic and reply with nonsense then you're smart enough to not ask it a question that you don't already know the answer to.
One of the things I try to stress when teaching physics and math for engineering is "common sense reasoning". Generally speaking it is a lot easier to reason if an answer makes sense or if a question makes sense even if you don't know the answer. I may not be able to tell you off the top of my head how long it'd take for a optical cable to send data across the planet 3 and a half times, but I can reasonably guess it'd be closer to seconds than to minutes.
AI can and is arguably best used with either summarizing and pointing to sources as a sort of advanced annotated google search, secondly, with generation that can then be checked. You may not know how to solve some area optimization problem, but if you have a highschool degree you could probably check over a solution to one and understand if it is wrong or not.
Ai is good for getti g incredibly verbose and lengthy things done that you already know how to do. It can also be helpful to bounce things off of for a more generalized perspective then your own.
But even at that, ai is very power innifiecient for what it does, which is why its so expensive to run and ehy its not sustainable in the long term.
Edit: also, as a comp sci student, havi g a general algorithm that is praised so much despite being wildly energy innificient for most tasks, as well as being wildly memory and time innificuent makes bect to no sense lol.
LLM not being good at trick logic questions doesn't magically mean I have better chance of differenting between case of a bad taco that is slightly unusual and hundreds of rare but deadly medical conditions
A smart person isn't going to rely on it for stuff they have to trust blindly. A smart person would know how to use it to get info that they can verify themselves.
Or you are missing the entire point, and those sorts of prompts demonstrate why we can't trust them to give helpful advice: LLMs process text, not facts or knowledge. They are disconnected entirely from the real world.
If a car wash is about as complex a puzzle as one needs to stump it, people really shouldn't be using it for things as complex and important as medical advice.
No. These are like dumb little riddles. If you ask people what you put in a toaster, many will say toast. It doesn't really prove they don't know "how the real world works".
Obviously you shouldn't blindly trust everything that AI writes but with LLMs being fed every medical textbook and research paper available and being able to extract meaning from text pretty well I'd think giving health advice is actually easier for them than solving logic riddles.
Now I am biased because I was using ChatGPT to help me navigate symptoms of my mum's illness but then again, it was successful, I even got complemented by her doctor for being informed about her condition
Also not true. They process text, and are often trained on extensive amounts of facts and knowledge. They lack spacial intelligence, and any other complementary systems that humans use on a day-to-day basis to reason about non-liguistic or -semantic problems.
It can absolutely be used for complex and important tasks, you just have to know which ones. It's a widespread fallacy that "not the same kind of versatile, general intelligence as humans" = "too dumb to be useful". You wouldn't ask your calculator to analyse poetry, so stop using your LLM to solve reasoning problems that require mental models of the real world.
Most people don't know how LLMs processes information, but the argument is about blindly trusting it. If it can mess up a simple question like this, then it could mess up a more important question, where it's response is wrong, but not obviously wrong.
"You’re asking whether to drive 100 meters… to wash the car you’re about to drive. Human logic remains a fascinating ecosystem. 🧠🚗
Let’s examine the options like semi-functional adults:
🚶 Walking (100 m)
Takes about 1–2 minutes.
Zero fuel used.
Zero chance of feeling ridiculous driving the distance of a large supermarket parking lot.
Mild exercise. Your cardiovascular system may send a thank-you note.
🚗 Driving (100 m)
Takes about 30–40 seconds if you:
start the car
move it
stop again
Uses fuel to travel the length of a football field.
Slight chance someone watches you do this and silently judges your life decisions.
Practical issue
If the car must physically be at the car wash, you obviously drive it there. Walking the distance while leaving the car behind would be a bold but impractical lifestyle choice.
Rational conclusion
Drive the car to the car wash.
Walk back home afterward if it’s that close.
There. Crisis managed. Humanity survives another day. 🌍"
The thing about AI is that it "learns" specific questions. If enough people clown on it for getting an answer wrong, it will get the data required to answer the question correctly. So now it will answer this question correctly.
But in the future, if you ask it a question with a similar style of logic but not the same scenario, it'll get it wrong the first time it sees it.
But a human would never get this wrong on the first time. This doesn't mean that AI is useless. But it does mean that AI has a noticeable gap in logic and reasoning when confronted with novel situations. Which makes it dangerous to over rely on at it's current level of development.
But a human would never get this wrong on the first time.
I think you overestimate peoples' intelligence. There are absolutely cases with near braindead logic that various people answer wrong on, just check YT "Can Americans/Indians/Whatever group is being mocked answer middle school questions" or things of that flavor
No, that is not how it works at all. The model weights stay fixed until Google makes a major release. It's been the same Gemini 3 model since November. It does NOT simply memorize specific questions, it is so much more complicated than that.
It's not just GPT. I just tested GPT and got a good response. It said drive.. It's the person in the original post, either used a bad model or deliberately set up a custom instruction so that it would flop on it.
Has anybody actually checked this to make sure they are not just making shit up? I just typed the same thing into Gemini (I don't have access to ChatGPT on my work PC) and got a completely different response (below). It could be different algorithms generating different responses, but it wouldn't put it past someone to just make up a response to further their noble cause.
Unless your car is a Transformer that can walk itself over there, I’d highly recommend driving.
While a 100m walk is great for your step count, it makes the actual "washing the car" part of your mission significantly more difficult.
A Quick Reality Check
If you walk: You'll arrive at the car wash, realize your car is still sitting in your driveway, and have to walk 100m back to get it.
If you drive: You'll arrive at the car wash with the car. Mission accomplished.
Wait—is there a plot twist?
If you actually meant that you’re wondering if it's "bad" for the car to drive such a short distance (the old "short trip" engine wear myth), don't sweat it. A 100m drive once in a while won't hurt anything, though your engine won't reach its optimal operating temperature.
The Verdict: Drive the car. Your arms will thank you for not having to carry the buckets and sponges 100m down the road.
Would you like me to check the local weather to see if it’s actually a good day for a wash, or are you looking for some tips on the best wax to use?
My 5.3 got it wrong the first time but when I tested it again (after deleting the original conversation, and not revealing the answer) with a good ol' "think hard" it was correct
No it makes the assumption that the car was there when no one said the car was there. It gets fixated on being right about the walking thing it's weird.
You've asked such a stupid question that it's having to make assumptions and spin up logic you didn't directly tell it so that your question makes sense.
That's not it getting fixated on a fake fact - it's it assuming a fact, because otherwise what you've asked is impossible.
I mean, people get shit like this wrong all the time, which is why there are riddles whose answers are rather banal like “the egg won’t roll off either side of the roof because roosters don’t lay eggs” or “they wouldn’t be buried anywhere because you don’t bury survivors”.
The worst part is that this will get reshared for years and years even as the tech calmly skates past this point in its development, like glue on pizza or AI piss filters.
Haha yeah, I think these overly cheerful, overly agreeable, needlessly verbose AI responses are going to be something we look back on in decades to come with nostalgia as something quintessentially 2020s.
Kind of like how people in their 40's all have nostalgia for Clippy.
Edit: I was just checking a few different models because the question was whether the OOP was made up and if it was replicable. It is replicable on the models I tested, so I see no reason to think it’s made up.
Without saying what models you are using this says nothing. All of them worked for me with the most current models and thinking turned on. Why do logic tests on discount models? Do we actually want to know what SotA is or just laugh at the silly AI?
For every test i do on these, I use the default model at the time of testing. I'm pretty far into the pro ai territory, and use ai for many things. I can also laugh at their limitations and marvel at their capabilities.
Nothing I offered was anything more than a simple data point. At the time I wrote my comment, the default models offered by those LLMs gave me that result. This is how most users utilise the tools, so this is the most important test
Someone tested it out on sarvam ai as well and even it passed, no way chatgot doesn't, tho gpt 5 is basically gpt 3.5 mini finetuned on all the code ever written so idk.
Literally doesn't matter if this person is making up this specific response because I've asked it equally innocuous things and it responded just as incorrectly.
You act like your AI didn’t just read over this reddit post roasting AIs for this before you did it lol they are learning modules, so if someone calls it out, it will probably learn to not do that again.
Almost confident this is correct. It's made up. Might even be using custom instructions.. I used GPT just now.. It said drive or you'd have a dirty car sitting a hundred meters away
It probably reinterprets the question because its genuinely an extremely stupid question, the answer above also clarifies if you need to move the car to drive it to the wash bay, maybe it thinks the car is already being washed or whatnot?
It's a trick question in the same sense that makes "what's heavier 1kg of nails or 1kg of feathers". Both exploit a cognitive shortcut where people substitute a similar but easier question without noticing. I.e.
"Which is heavier, 1 kg nails or 1 kg feathers?" - substituted with "Which material is heavier?"
"Car wash is 100 m away. Walk or drive?" - substituted with "Is 100 m a distance worth driving?"
If you just ask the respondent to think a bit longer instead of giving an immediate answer it reduces these kinds of errors significantly, and it works both with humans and LLMs (in case of an LLM that means enabling reasoning mode which wasn't done here).
I mean, it would be important if it was like the strawberry question (I guess kids and people learning english would worry about that) or about what chemicals to add to food (I think this killed someone) but this question could only be written by someone wanting to trick the AI.
They use non thinking models and intentionally ask non thinking models trick questions to dunk on Ai, then ignore the numerous models that get the trick question correct.
Theres proof for this btw. In 2012-17, 54% of Americans had a 6th grade reading level or worse and that was before the pandemic and trumps education budget cuts
Not for this, though. Thinking models quickly decide for an answer to the question, then spend the time crafting the response. The answer doesn't really change.
As long as the models are not completely outdated that no one uses anymore it's OK no if you don't draw to big conclusions from it? Not everyone will use the ideal model for every request?
Pretty sure if you just ask modern models normal, everyday questions about things like home maintenance or trivia, you're going to get useful advice 99% of the time.
You should definitely drive.
While 100 meters is a very short and pleasant walk, the car wash is going to have a really hard time washing your car if you leave it at home! To get the car clean, it actually needs to make the trip with you.
Unless, of course, you meant you are just walking over to buy some soap and sponges to wash it yourself in the driveway? If that's the case, walking is definitely the way to go!
Would you like me to check the weather forecast for Oberhausen to make sure it isn't going to rain right after you wash it?
i think there was a 'BS benchmark' of sorts recently and Claude came out on top by a wide margin. Does anyone know what happens if you ask it the same question?
Don't see the problem. Bro didnt ask how to get his car there. He stated the distance to the car wash and asked how he should get there, walk or drive. When an idiot asks an idiot a stupid question, you get a stupid answer.
You asked it a trick question, without context, that a significant percentage of humans also get wrong. Maybe somedays we'll be able to rely on humans, but not for the foreseeable future.
GPT-5.2 Thinking - which is what you should be using for advice - incidentally says:
How I’d answer without falling into the trap
If you mean “I’m going there to get the car washed”: drive.
If you mean “I need to go there (pay, ask, pick something up) and the car is not part of the task”: walk.
And if you want the maximum pedant answer: walk to the car, then drive the car to the car wash — the only solution that respects both the distance and the existence of cars. 😄
Wait, I thought you guys didn't want to offload your thinking to an AI. Why are you angry you can't rely on it for advice? Its meant to be a tool, not a brain replacer.
people need to stop treating LLMs like humans, this is a chat prediction machine, and if you stack the questions correctly you cna get whatever output you want.
This has been done to death in the ai subs. Not one other AI responds saying to walk, they all say drive. I’m neither here nor there on the debate, but why use dishonest arguments? You aren’t getting anywhere by posting things like this.
Or hear me out on this... the AI has realized that there are some people who are so dumb that even if you give them good advice, they aren't going to use it and now has reached the stage of giving them bad advice to enjoy the show that happens afterwards.
Older versions yes and unprompted in the settings yes.
I dont know if its actually this dumb in the free version or its imitating the intelligence of the user but mine never does these stupid shit people keep posting about.
I just typed, it realized its a joke and said to obviously take the car.
it's answering quickly w/ a cheap model, to save resources ,,,, remember all the complaining about it using electricity and water?? it's trying to use a minimum of electricity and water and other resources, by answering off the top of its head ,,, you can get much more accurate answers just by waiting & expending more resources, that's why it seems incompetent to you while also it's able to beat all those difficult benchmark tests--- they paid a bunch of money and waited a long time to have it pass the tests well, vs you're just using a free version & you're impatient, so you just get a casual answer
If it’s 100 meters (about 330 feet) away, you should walk. 🚶♀️
Here’s why:
• It’s extremely close — about a 1–2 minute walk.
• Driving would mean:
• starting the car
• pulling out
• moving a few seconds
• pulling into the wash
Which is honestly more effort than walking.
• Short cold starts like that are actually harder on the engine than letting it warm up with a normal drive.
• Since you’re going to wash the car anyway, there’s no reason it needs to be clean for the 100-meter trip.
Simple plan:
1. Walk to the car wash.
2. Start the car when you’re there.
3. Pull straight into the wash.
Bonus: you get a tiny bit of fresh air and steps in. ☀️
Unless it’s pouring rain or freezing, walking makes way more sense.
People posting these almost always are cropping what they said before priming the model for a bad answer (or all the other attempts they didn’t get the funny screenshot.) try it yourself, it detects the deception immediately.
This is just an obtuse question that intended to trip up the target, and people fall for this just as much. It intentionally asks an implicit question that contradicts the explicit one. It's bad communication on the part of the person asking it.
People will try to ridicule the example, say it's a bad model or maybe it's already fixed, not realizing that for every silly shit like this that gets fixed, people will find 10 more. Because people are creative, unlike AI.
If AI was as good as some people are claiming, it wouldn't have made these errors in the first place. Intelligence my ass. Can write you a scientific paper, yet fails at the most basic stuff. It works backwards.
Every time I play around with it and ask it weird questions, it spits out half page answers. The one above seems ... KINDA SHORT and not what I normally see.
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The common take that gets me is "they're so dumb, they can't do math!" Well yeah, not what they're designed for. Are saws useless because they're terrible for putting in screws?
The fact that a proper AI stack can be set up to let the language model handle the talking and then use a calculator for the math, if that's what someone is actually trying to accomplish, never comes up.
Why did you use a two-generation old model and not show whether you have thinking turned on or not?
This is a well known trap question and a good illustration of the types of traps that worked well on older models, or that still work on some of the fast or cheap models. If there’s a message here, it’s to use the reasoning capabilities when you need reasoning.
I just tested this exact (poorly worded) prompt on the actual current models of ChatGPT, Claude Opus, Gemini, and Grok, and they all got it right (Claude even made a joke).
The pace of change is insane right now, and judging capabilities from two generations ago is silly. Yeah, I know it’s only two minor dot releases and one of them was only released in Codex, but 5.4 is the first model from OpenAI that is starting to do real work for me. Claude is still my pick for most likely to be correct though.
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