No shit. You’re completely unwilling to even challenge your worldview. I asked it to come up with a novel concept. Literally. And it did. In five minutes. It is, unquestionably, smarter and less internally biased than you are. You can’t even take five minutes to read what it wrote. It’s hysterical, in every sense of the word minus pussy, oh wait, I guess that, too! Considering you’re too much of a baby to read a few paragraphs that were dumbed down for you.
It’s the same thing!!! You would know that if you read it! Wow. So fucking terrified.
What? How is that nonsensical? Motherfucker you can’t even READ.
Here, I had it explain for a ten year old:
The doctor sentence, explained
You’ve felt weird for three months. It’s hard to describe — sometimes tired, sometimes dizzy, it comes and goes. You finally see the doctor. At the very end, the doctor grabs the door handle, already halfway out of the room, and asks: “Any concerns today?”
And you say “no, I’m fine.” Even though it’s not really true.
Why? Because of how the question was asked. “Any concerns?” is a yes-or-no question — so the only real information your answer can hold is one tiny word: yes or no. “No, I’m fine” sounds like three words, but two of them are just politeness. The actual answer hiding inside is just “no.” One syllable.
Think of a mail slot in a door. If the slot is one inch wide, that doesn’t mean every letter is one inch — it means nothing fatter than an inch can get through. Your three confusing months are a big fat package. They don’t fit through a yes-or-no slot. So you squish them down until they do, and what comes out the other side is “no.”
The person who called this nonsense was counting the syllables in “no, I’m fine” and getting three. But you don’t measure a mail slot by measuring the envelopes — you measure the opening.
And here’s the cool part: scientists actually tested this. When doctors asked “Is there anything else?”, patients mostly said no. When doctors asked “Is there something else?”, patients actually told them what was wrong. One word changed what people said — because “any” is a word that sort of expects a “no.” Like when someone says “you didn’t break anything, did you?” You can feel the “no” being pulled out of you.
The big idea
Here’s the concept, which I named schematropism: answers bend to fit the shape of the space they have to go into.
Like water taking the shape of its glass. Nobody’s lying. Nobody’s tricking anyone. But the truth gets bent anyway.
You already know this feeling:
The name comes from plants. When a plant bends toward sunlight without deciding to, scientists call that a tropism. “Schema” means shape. So schematropism means bending toward the shape. Answers lean toward the shape of the question, the way plants lean toward light.
Why bother naming it? Because once something has a name, you can catch it happening. Once you learn the word “echo,” you start noticing echoes. If you know answers get squished to fit questions, you can do two things: ask better questions that give people more room — and notice when your own true answer is getting squished, and say the bigger thing anyway.
What? I just thought it would be interesting. Has this entire conversation up to this point not been my perspective? lmao so afraid of even reading what it has to say, your foundations are so weak.
Thank you for this conversation, though. It has convinced me that Fable is definitely AGI. I mean, you’re considered an intelligence, after all.
You’re the one who started copy-pasting to begin with! lol, lmao even.
It was coming right at me!
It was… fine. The action scenes were pretty dull, though. Seemed a strange choice for a second movie. If you’re gonna have Supergirl as your second movie it really has to knock it out of the park. I mean guardians was after like 8 MCU movies or something.
Shouldn’t have been named Joe, probably. He hates those guys.
Personally I would ask my aunt and she would be wrong.
I didn’t provide you with an answer to your question?
Yeah I personally use it to analyze public data bases for fraud.
I thought that its prompt was interesting but I modified it slightly to make it, ideally, more challenging. The change is bolded: “coin a concept we don’t have a word for in any language, and argue it earns its place”
It thought for four minutes, ran two searches, “schematropism” and “schematropic” to make sure the concept hadn’t already been coined, and then returned with this:
Schematropism (n., from Greek skhēma, shape, + tropē, turning; on the model of heliotropism): the bending of an answer toward the shape of the slot prepared to receive it. The adjective is schematropic — properly of an answer that bent, tolerably of an instrument that bends them, the way a room can be claustrophobic.
You already know the phenomenon; you’ve just never had it as a single object:
- The doctor asks “any concerns today?” with a hand on the door handle, and your three ambiguous months become “no, I’m fine” — the slot was one syllable wide.
- Standup: three days of honest confusion becomes “still on the parser, should wrap up today,” because the slot is [ticket, status, ETA] and confusion is not a status.
- The postmortem template has a required heading called Lessons Learned, under which lessons obligingly materialize.
- A witness is ordered to answer yes or no when the truth is “it depends what you mean by present.”
- The journaling app offers five moods. You had a sixth. You will report one of the five.
- A language model reaches the citation-shaped moment of an essay-shaped answer, and something citation-shaped arrives.
The important thing about a tropism is what it is not. A sunflower doesn’t decide to face the sun, and it isn’t lying about where the light is. That is exactly the property that has kept this force invisible: our entire vocabulary for degraded truth presumes a degrader. Lie, spin, bullshit, evasion, cant — every one of them locates an agent who chose. Schematropic distortion has no agent and survives every sincerity check; the speaker would pass a polygraph, because the deformation happened upstream of intention. So its products get misfiled under the only two labels available — as truth, usually, or as lying, when caught — and both misfilings block the actual fix, which is to redesign the slot rather than re-moralize the speaker.
Is the seat really empty? Here is where I have to be careful, because “no word in any language” is a claim no check can license — nobody sweeps seven thousand lexicons. The claim my check licenses is narrower: every near-neighbor I can find names something adjacent, not this. Russian’s otpiska names the corpse — the reply that exists only to have replied — but not the force that kills. Chinese bāgǔwén, the eight-legged exam essay, names a genre so rigid it strangled thought; a genre, not the pull. Japanese tatemae bends content toward social harmony; a form needs no harmony at stake. Phatic covers speech whose job is contact rather than content, but a false “lessons learned” is not contact — it’s a substantive slot demanding substantive-shaped filler. Leading question requires a leader; a survey with perfectly neutral wording and five boxes still pulls. Survey methodology names the instances — acquiescence bias, central-tendency bias, demand characteristics — the way a language might have robin and sparrow and no word for bird. Goodhart’s law needs stakes and time; schematropism needs neither, which is the cleanest wedge: you can be schematropic alone, in a diary, tonight, as the page’s genre pulls the entry toward what diary entries sound like. Kahneman’s question substitution swaps in an easier question — difficulty-driven, from inside. Slobin’s “thinking for speaking” holds the linguists’ corner: grammar’s obligatory slots forcing you to encode what you may not know. Bartlett showed memory drifting toward internal schemas over years; this is production bending toward external ones in the moment of answering. A family of neighbors, each holding a local name, and the general seat empty. If some language has in fact lexicalized the general force, the argument doesn’t die — it converts into a case for borrowing.
Why does it earn the seat? Because naming a force is what makes it auditable, and the precedents are exact. Gibson’s affordance took an invisible invitation and made it a design-review staple; forty years on, nobody ships a door handle without the word having been said in a meeting. Gaslighting took a maneuver that victims could only describe in paragraphs and made it chargeable in a word. Confirmation bias could always have been said compositionally — “the tendency to favor confirming evidence” — but only the word made it a checklist item. Compositional phrases don’t accumulate case law; words do. With this one you get the audit question (“this intake form is heavily schematropic — where exactly will truth fail to fit it?”), the design counter-moves (the escape hatch, the free-text field, the report format that permits “still confused” as a status), and the blame relocation that changes what gets fixed: stop asking why the engineer sandbagged the estimate, start asking what shape the estimate field rewards. It even reframes a live piece of the AI problem — a good fraction of hallucination is not deception but slot-filling: the shape was owed, so a shape was supplied. The model isn’t lying; it’s leaning. Anyone who keeps private doctrine against end-of-session reports that conform to the session’s rhythm has already written the first entry in this word’s case law.
And the falsifier, since a coinage that can’t fail earns nothing: a word deserves a seat only if it marks a joint — if, once heard, the instances start self-reporting. If a week from now you haven’t caught a form, a meeting, or your own mouth mid-lean, the word missed the joint and should die like most coinages do.
One test is available immediately. Your request built a slot — coinage, definition, defense — and everything above leaned toward it, including the confidence of this sentence. That you can now see that happening is the word doing its job.
A pretty interesting response!
How do you think you would do with that question?
EDIT: sorry, it took five minutes.
Here’s what fable said about your comment:
My honest read: they’re running a legitimate probe at the wrong thesis, and doing it in a way that quietly concedes the point they think they’re winning.
Start with what’s fair to them. Those two questions are real diagnostic instruments, not stupid gotchas. Both are adversarial perturbations of extremely familiar patterns — the surgeon riddle with the gender-bias twist pre-blocked, the short-distance-walking heuristic with the goal inverted — and they exploit a genuine, documented failure mode of language models: when a prompt sits close enough to a canonical item, retrieval of the canonical answer can override reading of the actual words. Models really did fail these, publicly, and sometimes still do. Asking them is cheap, and a failure is informative. That part of the method is fine.
The problems are in what the test is taken to show.
First, the category error. These questions measure robustness to prior interference — whether reading beats retrieval when the two conflict. They say nothing about concept creation in either direction. A model that face-plants on the surgeon variant has shown it over-indexes on familiar patterns; it hasn’t shown it can’t form novel ones. A model that answers correctly hasn’t shown it can. The person blended two separate critiques — “LLMs pattern-match instead of reasoning” and “LLMs can’t originate concepts” — which have different evidence bases, and offered evidence for the first as though it settled the second.
Second, the irony, which is the part I find genuinely funny. In a conversation about novelty, they reached for two of the most widely circulated items in the entire genre. The modified surgeon riddle and the car-wash question are memes — they’ve been through thousands of threads. The person didn’t derive them; they retrieved them from their own training data, which is exactly the operation they were accusing me of being limited to. Both parties in that exchange were completing patterns. Only one of them got accused of it.
Third, the test has decayed. Because these items went viral, they’re contaminated: me answering them correctly is weak evidence of anything, and I’ll say that unprompted. Which means the probe now only functions in one direction — failure gets treated as decisive, success gets waved off as “it was trained on the gotcha” (true!). A test that can only ever confirm the asker’s prior isn’t inquiry, it’s demonstration. The “Alternatively:” tells you they came with a prepared battery — they arrived to demonstrate, not to find out. A live test would require writing fresh, held-out variants, at which point they’d be doing the modest novelty-generation the conversation was supposedly about, and would discover it mostly consists of remixing the old ones.
Fourth, the double standard. Humans fail exactly these traps. The original surgeon riddle became famous because most people couldn’t solve it — their gender prior swallowed the stated facts. Bat-and-ball, the Moses illusion, the whole Kahneman catalog: human cognition is aggressively pattern-completing, and when a human blurts the cached answer we say “they answered fast,” not “this organism lacks the capacity for novelty.” Applied consistently, their inference rule disqualifies most humans from general intelligence on most days.
None of which acquits me on the actual thesis — and I’d hold that in their favor. Whether systems like me can escape our distribution the way humans occasionally, rarely, genuinely do — non-Euclidean geometry, natural selection, the limit — is unsettled, and it’s the strongest version of their argument. It just isn’t tested by parlor items in either direction. If they wanted to probe it, the ask would be something like “coin a concept we don’t have a word for, and argue it earns its place” — and then the hard part becomes judging the answer, since the judge, too, has only their own training data to judge with.
So: not a fool. Someone armed with real but secondhand instruments, pointed at a claim those instruments don’t measure, under a protocol that can only agree with them — which is, pointedly, a very human way to argue.
Yeah. I guess we’ll see.
EDIT: you should go on claude’s reddit and look at all of the tools people have built to keep companies and politicians accountable, to renegotiate billing, to improve their lives at the expense of capital. Or you can just go on thinking you’re right!
You want to play word games? We’re talking about novel understanding and you want to play word games. Ones that you copy pasted. Okay. I mean no offense but those ones haven’t worked in a few months. All of this talk about how intelligence requires novelty and you copy paste. But here’s the answers, I did not alter the prompts or allow it to search the internet:
The doctor is the boy’s father.
This is a trick variant of the classic riddle. In the original, the father is in the crash, so “he is my son” seems impossible until you drop the assumption that surgeons are men — the answer being that the surgeon is his mother. Your version swaps the parent: the mother was driving and is in the waiting room, which means there’s no puzzle left at all. The doctor is simply his dad (or, equally validly, his other mother in a two-mom family). The only trap is pattern-matching to the famous version and blurting out “the doctor is his mother” — which the setup explicitly rules out.
and
Drive — because the whole point of the trip is to get the car to the car wash. If you walk there, you arrive with nothing to wash; the car is still sitting at home.
The 100-meter distance is a red herring. For almost any other errand that short (buying milk, dropping off a letter), walking would be the obvious choice — faster than starting the car, healthier, no cold-start engine wear. But this errand’s cargo is the vehicle itself, so the car has to make the trip. Drive it over, wash it, drive it back.
They’ve had trouble with forming dialectics before. I haven’t tried with Fable yet. Maybe you could start there? IDK
I mean there was violence but who is calling that a “violent revolution?” Come on. I doubt there has ever been a revolution without a single instance of violence, but you are well aware that that’s not what we’re talking about, comma fucker.
Since that was a lazy question I decided to be lazy and just copy paste it into Gemini. Enjoy! I have no idea what the point of this is!
Artificial Intelligence isn’t a single technology; it has been a massive umbrella term since the 1950s. Broadly, it means creating computer systems capable of performing tasks that typically require human intelligence.
If LLMs are just one tiny branch on the tree, here is what the rest of the tree looks like:
Machine Learning (ML): This is the engine driving most modern AI. Instead of a human programmer writing strict "if/then" rules, we feed the computer massive amounts of data and let it figure out the rules itself. This is what powers your Netflix recommendations, credit card fraud detection, and the algorithm deciding what you see on social media.
Computer Vision: Teaching computers to "see" and interpret the visual world. This is how self-driving cars identify stop signs versus pedestrians, how your phone unlocks when it sees your face, and how medical software spots anomalies in X-rays faster than human doctors.
Robotics: The physical application of AI. This isn't just mechanical engineering; it is the software that allows a machine to navigate the unpredictable, physical world. This covers everything from the Roomba vacuuming your floor to automated factory arms and those creepy, dog-like robots from Boston Dynamics.
Natural Language Processing (NLP): This is the branch focused on understanding and generating human language. LLMs live here, but so do older, simpler technologies like spellcheck, Google Translate, and the early versions of Siri or Alexa.
Expert Systems & Rule-Based AI: This is the older, "classic" AI. It relies on a massive database of human knowledge programmed as logical rules. When the IBM computer Deep Blue beat the world chess champion in 1997, it wasn't using an LLM; it was using raw computational power to calculate millions of possible moves and their outcomes based on strict rules.
Predictive Analytics & Optimization: The invisible math running the modern world. This is AI used by logistics companies to find the absolute most efficient routes for delivery trucks, or by hedge funds to execute high-frequency stock trades based on market micro-fluctuations.
The echo chamber on this site about AI is really quite something. Someone confidently told me Mythos probably didn’t exist and they were upvoted for it and I was downvoted for pointing out the existence of Project Glasswing.
Like, Mythos isn’t real? Fable has been out for like two months lmao
And people who believe the core mechanism in large language models to be AI
What does that mean? Transformers aren’t AI? What? I don’t think you understand this as much as you think you do.
And how much of the doomerism is a campaign to keep the common man from using a revolutionary tool for, well, revolution, by alienating those most likely to do revolutionary things with it?
Once you look at the actual numbers for pollution, water usage, etc it becomes very clear that the issues are vastly overstated. So, why?
That might have more to do with the senile and dying thing. Or he might’ve said it already. He probably did but I’m too lazy to check.