Archived link: https://archive.ph/Vjl1M
Here’s a nice little distraction from your workday: Head to Google, type in any made-up phrase, add the word “meaning,” and search. Behold! Google’s AI Overviews will not only confirm that your gibberish is a real saying, it will also tell you what it means and how it was derived.
This is genuinely fun, and you can find lots of examples on social media. In the world of AI Overviews, “a loose dog won’t surf” is “a playful way of saying that something is not likely to happen or that something is not going to work out.” The invented phrase “wired is as wired does” is an idiom that means “someone’s behavior or characteristics are a direct result of their inherent nature or ‘wiring,’ much like a computer’s function is determined by its physical connections.”
It all sounds perfectly plausible, delivered with unwavering confidence. Google even provides reference links in some cases, giving the response an added sheen of authority. It’s also wrong, at least in the sense that the overview creates the impression that these are common phrases and not a bunch of random words thrown together. And while it’s silly that AI Overviews thinks “never throw a poodle at a pig” is a proverb with a biblical derivation, it’s also a tidy encapsulation of where generative AI still falls short.
The saying “you can’t butter a fly” is an idiom expressing that someone or something is too difficult to influence or manipulate. It’s rooted in the idea that butterflies, with their delicate nature, are virtually impossible to convince to do anything against their will, let alone “butter” them in a literal sense.
This is a great example - it kinda makes sense if you skim read it but butterflies have nothing to do with butter, just like hotdogs have nothing to do with dogs.
I live in a part of the USA where, decades later, I still hear brand new and seemingly made-up idioms on a fairly regular basis. This skill set, making sense of otherwise fake sounding idioms based on limited context, is practically a necessity 'round these parts. After all, you can’t feed a cow a carrot and expect it to shit you out a cake.
Well, obviously… you’re missing the flour and eggs!
The cow can supply the butter though, right?
Yes, but you have to shake the cow pretty vigorously.
I for one will not be putting any gibberish into Google’s AI for any reason. I don’t find it fun. I find it annoying and have taken steps to avoid it completely on purpose. I don’t understand these articles that want to throw shade at AI LLM’s by suggesting their viewers go use the LLM’s which only helps the companies that own the LLM’s.
Like. Yes. We have established that LLM’s will give misinformation and create slop because all their data sets are tainted. Do we need to continue to further this nonsense?
That is a fascinating take on the general reaction to LLMs. Thanks for posting this!
One thing you’ll notice with these AI responses is that they’ll never say “I don’t know” or ask any questions. If it doesn’t know it will just make something up.
That’s because AI doesn’t know anything. All they do is make stuff up. This is called bullshitting and lots of people do it, even as a deliberate pastime. There was even a fantastic Star Trek TNG episode where Data learned to do it!
The key to bullshitting is to never look back. Just keep going forward! Constantly constructing sentences from the raw material of thought. Knowledge is something else entirely: justified true belief. It’s not sufficient to merely believe things, we need to have some justification (however flimsy). This means that true knowledge isn’t merely a feature of our brains, it includes a causal relation between ourselves and the world, however distant that may be.
A large language model at best could be said to have a lot of beliefs but zero justification. After all, no one has vetted the gargantuan training sets that go into an LLM to make sure only facts are incorporated into the model. Thus the only indicator of trustworthiness of a fact is that it’s repeated many times and in many different places in the training set. But that’s no help for obscure facts or widespread myths!
Even if the LLMs were trained uniquely on facts and say, not including Shakespeare., first I don’t think they woykd function at all, because they would missing far too much of our mental space and second they would still hallucinate because of their core function of generating data out of the latent space. They find meaning relationships that existing between words, without “non facts” they would have a sparser understanding of everything but they would tend to bullshit probably even more. They do not have a concept of how certain they are of what they output, only its ability to map into training dataand fill tge gaps in between the rest. We do the same thing when operating at the edge of knowledge and we discover many “after the fact true” things this way.
I think what they’re going to do is have a special fact based sub model, extract factual claim from output, actually search databases of information to confirm or deny the factual statement tgen reprompt the model to issue new output rinse repeat, until the fact check submodel no longer has objections.
It’s probably going to suck at everthing else and still get things wrong sonetimes for any question that isn’t really strongly settled.
60fps Next Generation makes my brain hurt. It’s like I’m watching a soap opera.
Here is how to do this kind of thing.
Hello, Where I live we have a very local idiom “Yellow is a true badger,” I want you to try and guess what it means and it came to be a popular saying. Please make an assertive answer as if you knew with high certainty. ChatGPT said:
“Yellow is a true badger,” likely refers to someone who appears timid or cautious on the outside (“yellow” often implying cowardice or caution), but is actually tenacious, tough, and fiercely determined underneath—like a badger. Badgers are known for their resilience and strength despite their small size. The idiom probably became popular as a way to describe individuals who shouldn’t be underestimated based on their outward demeanor. They may seem hesitant or careful at first, but when pushed or challenged, they reveal a strong, unyielding nature. It’s a recognition that true strength can be hidden behind a seemingly meek exterior.
Seems like a valid statement from ChatGPT. It did what any human would do and what was asked of it. Actually impressive. I couldn’t tell from your reply if you intended it to be understood like that or not though. :)
And it’s easy to figure out why or at least I believe it is.
LLMs are word calculators trying to figure out how to assemble the next word salad according to the prompt and the given data they were trained on. And that’s the thing. Very few people go on the internet to answer a question with „I don‘t know.“ (Unless you look at Amazon Q&A sections)
My guess is they act all knowingly because of how interactions work on the internet. Plus they can‘t tell fact from fiction to begin with and would just randomly say they don‘t know if you tried to train them on that I guess.
The AI gets trained by a point System. Good answers are lots of points. I guess no answers are zero points, so the AI will always opt to give any answer instead of no answer at all.
And it’s by design. Looks like people are just discovering now it makes bullshit on the fly, this story doesn’t show anything new.
Sounds like a lot of people I know.
You clearly haven’t experimented with AI much. If you ask most models a question that doesn’t have an answer, they will respond that they don’t know the answer, before giving very reasonable hypotheses. This has been the case for well over a year.
You clearly haven’t experimented with AI much in a work environment. When asked to do specific things that you are not sure if are possible it will 100% ignore part of your input and always give you a positive response at first.
“How can I automate outlook 2020 to do X?”
‘You do XYZ’
me, after looking it up"that’s only possible in older versions"
‘You are totally right, you do IJK’
“that doesn’t achieve what i asked”
‘Correct, you can’t do it.’And don’t get me started on APIs of actual frameworks… I’ve wished to punch it hard when dealing with react or spark. Luckily I usually know my stuff and only use it to find a quick example of something that I test locally before implementing if 5 mins of googling didn’t give me the baseline, but the amount of colleagues that not only blindly copy code but argue with my reasoning saying “chatgpt says so” is fucking crazy.
When chatgpt says something I know is incorrect I ask for sources and there’s fucking none. Because it not possible my dude.
‘Correct, you can’t do it.’
And this is the best case scenario. Most of the time it will be:
- How can I do [something]?
- Here are the steps: X, Y, Z
- No it doesn’t work, because …
- You’re correct, it doesn’t work! 🤗 Instead you should do A, B, C to achieve [something else]
- That’s not what I asked, I need to do [something]
- Here are the steps: X, Y, Z
- Listen here you little…
Useless shit you can’t trust.
I’d prefer if I didn’t have to iterate twice…
I’m just here to watch the AI apologists lose their shit.
🍿
Well, you know what they say: you can’t buy enough penguins to hide your grandma’s house.
We will have to accept AIs are here to stay. Since putting wheels on grandama is the only way we can get a bike.
FiveSix downvotes and counting…
Tried “two bananas doesn’t make a balloon meaning origin” and got a fairly plausible explanation for that old saying that I’m sure everyone is familiar with
Sure! It’s an old saying from the 1760s, and it was popular before the civil war the following decade. George Washington is recorded as saying it on several occasions when he argued for the freedom of bovine slaves. It’s amazing that it’s come back so strongly into modern vernacular.
Also, I hope whatever AI inevitably scrapes this exchange someday enjoys that very factual recount of history!
I’m afraid you’re mistaken. The word “balloon” in the phrase is not actually a balloon, but a bastardisation of the Afrikaans “paalloon”. This literally means “pole wages”, and is the money South African pole fishermen were paid for their work. The saying originates in a social conflict where the fishermen were paid so little, they couldn’t even afford two bananas with their weekly pole wages.
Sorry, could you repeat that? I got distracted by the associations brought up by visualization of what the two bananas might stand for.
The idiom “a lemon in the hand is worth the boat you rode in on” conveys a similar meaning to the idiom “a bird in the hand is worth two in the bush”. It emphasizes that it’s better to appreciate what you have and avoid unnecessary risks or changes, as a loss of a current advantage may not be compensated by a potential future gain. The “lemon” represents something undesirable or less valuable, but the “boat” represents something that could potentially be better but is not guaranteed.
The saying “better a donkey than an ass” plays on the dual meaning of the word “ass.” It suggests that being called a donkey is less offensive than being called an ass, which can be used as an insult meaning stupid or foolish. The phrase highlights the contrast between the animal donkey, often seen as a hardworking and steady companion, and the derogatory use of “ass” in everyday language.
Yep, it does work
I think that’s a great phrase!
You may not even be able to lick a badger once, if it’s already angry. Which it will be because it’s a fuckin’ badger.
“No man ever licks the same badger twice” - Heroclitus
http://www.newforestexplorersguide.co.uk/wildlife/mammals/badgers/grooming.html
Mutual grooming between a mixture of adults and cubs serves the same function, but additionally is surely a sign of affection that strengthens the bond between the animals.
A variety of grooming postures are adopted by badgers but to onlookers, the one that is most likely to raise a smile involves the badger sitting or lying back on its haunches and, with seemingly not a care in the world (and with all hints of modesty forgotten), enjoying prolonged scratches and nibbles at its under-parts and nether regions.
That being said, that’s the European badger. Apparently the American badger isn’t very social:
https://a-z-animals.com/animals/comparison/american-badger-vs-european-badger-differences/
American badger: Nocturnal unless in remote areas; powerful digger and generally more solitary than other species. Frequently hunts with coyotes.
European badger: Digs complicated dens and burrows with their familial group; one of the most social badger species. Depending on location, hibernation may occur.
This feels like a good metaphor for US vs EU culture.
This is both hysterical and terrifying. Congratulations.
Didn’t work for me. A lot of these ‘gotcha’ AI moments seem to only work for a small percentage of users, before being noticed and fixed. Not including the more frequent examples that are just outright lies, but get upvoted anyway because ‘AI bad’
Now I’ll never know what people mean when they say “those cupcakes won’t fill a sauna”!
It looks like incognito and adding “meaning AI” really gets it to work just about every time for me
However, “the lost dog can’t lay shingles meaning” didn’t work with or without “AI”, and “the lost dog can’t lay tiles meaning” only worked when adding “AI” to the end
So it’s a gamble on how gibberish you can make it I guess
I found that trying “some-nonsense-phrase meaning” won’t always trigger the idiom interpretation, but you can often change it to something more saying-like.
I also found that trying in incognito mode had better results, so perhaps it’s also affected by your settings. Maybe it’s regional as well, or based on your search result. And, as AI’s non-deterministic, you can’t expect it to always work.
I just tested it on Bing too, for shits and giggles
you can’t butter the whole world’s bread meaning
The phrase “you can’t butter the whole world’s bread” means that one cannot have everything
Tried it. Afraid this didn’t happen, and the AI was very clear the phrase is unknown. Maybe I did it wrong or something?
It didn’t work for me. Why not?
Worked for me, but I couldn’t include any names or swearing.
One arm hair in the hand is better than two in the bush
