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LLMs tell bad jokes because they avoid surprises
- darajava 1y agoI pasted the article into GPT-5 and asked it to come up with a joke based on the content. It came up with: > Dan Fabulich walks into a bar and says, > “LLMs can’t tell good jokes because they avoid surprises.” > > The bartender says, > “Yeah, I figured you’d say that.” I thought it was pretty good!
- addandsubtract 1y agoI don't get it. It doesn't even follow the "walks into a bar " format.
- retrocog 1y agoGPT40 and Claude can have me in stitches, but only when the conversation has taken a great many coherent turns before the tone arc shifts to playful.
- Waraqa 1y agoThe fact that any surprise used in the wrong place is considered hallucination and a downside for that LLM. I guess a good starting point to improve that is to add an experimental "Surprise Mode" which will try to guess the right kinds of surprises rather than minimizing them and get the feedback from the users. Over time, it will learn what kind of surprises users like so that they will be used in future training datasets.
- wolfi1 1y agoaren't llms some sort of Markov Chains? surprise means less probability means more gibberish
- drdeca 1y agoSsorta? In the sense of “each term is randomly sampled from a probability distribution that depends on the current state” yes, but, they aren’t like an n-gram model (well, unless you actually make a large n-gram model, but that’s usually not what one is referring to when one says LLM).
- qcnguy 1y agoHallucinations aren't surprising, that's why they're problematic. They tend to look like exactly what you'd expect to be true, they just aren't.
- Waraqa 1y agoThey aren't surprising when you are dealing with new knowledge. But when hallucinations occur with something you are familiar with, it will be surprising and might be funny. Remember when AI was asked: how many rocks should I eat per day.
- dvh 1y agoI tried using the article suggested randomness and inevitability to come up with completely new joke, this is what I came up with, tell me how'd I do (no llm involved): - I asked Jimmy to tell me a random number - Yeah? And what did he tell you? - He told me one
- wolfi1 1y ago+1 for effort (or lack thereof)
- aabhay 1y agoHe told me 2 (fuck off)
- yetihehe 1y agoI think it's funny, but I like abstract jokes that most people don't like, so expect mixed opinions on this.
- briffid 1y agoWhy is that in English speaking world a joke is almost always a pun?
- yesbabyyes 1y agoIt would be trivial to change the joke, keep the setup and get a similar effect without a pun. I asked for one random number And? He told me two I like the joke
- ksynwa 1y agoIsn't this a pun too? It could mean that he gave you two random numbers or two as the random number.
- Disposal8433 1y agoIt could also be some bias on what we read or hear around us. But I agree that it's unsettling because in French we almost never make puns as "jokes." French puns have always a component of "higher literacy" that is not what we want in a joke.
- padolsey 1y agoReminds me of haikus; to be true in nature, they must have a 'cutting word' to severely juxtapose, allowing two otherwise irreconcilable meanings to be bridged. A good haiku must be composed from two directions, not one. But LLMs only move in one...
- orthoxerox 1y agoAre there English-language haikus that demonstrate the effect of "cutting words" instead of just following the meter?
- juped 1y agoNo. The form doesn't translate, and English-language haiku is a different form inspired by the Japanese form. Kireji as such are one of the elements that don't translate, though you can of course attempt a poetic structure inspired by kireji.
- tokai 1y agoIt really hard to write correct and good haiku's in english.
- dentemple 1y agoThe closest I can think of right now is the "Before & After" category from Wheel of Fortune. It relies on there being a single word that ends one phrase and begins another. But that doesn't bring into the idea of this word being _cutting_
- DrNosferatu 1y agoUnless you ask them for big surprises.
- IshKebab 1y agoThis sounds really convincing but I'm not sure it's actually correct. The author is conflating the surprise of punchlines with their likelihood. To put it another way, ask a professional comedian to complete a joke with a punchline. It's very likely that they'll give you a funny surprising answer. I think the real explanation is that good jokes are actually extremely difficult. I have young children (4 and 6). Even 6 year olds don't understand humour at all. Very similar to LLMs they know the shape of a joke from hearing them before, but they aren't funny in the same way LLM jokes aren't funny. My 4 year old's favourite joke, that she is very proud of creating is "Why did the sun climb a tree? To get to the sky!" (Still makes me laugh of course.)
- ay 1y agoI found your example of a joke child made very interesting - me a good jokes is something that brings is unexpected perspective on things while highlighting some contradictions in one world models. In the adult would model there is absolutely no contradiction about the joke you mention - it’s just a bit of cute nonsense. But in a child’s world this joke might be capturing the apparent contradiction - the sky is “in the tree”, so it must have climbed it, to be there (as they would have to do), yet they also know that the sun is already in the sky, so it had absolutely no reason to do that. Also, “because it’s already there” - which is a tricky idea in itself. We take planetary systems and algebra and other things we can’t really perceive as granted, but a child model of the world is made of concrete objects that mostly need a surface to be on, so the sun is a bit of a conundrum in itself! (Speaking of my own experience remembering a shift from arithmetics to algebra when I was ~8). If not too much of a personal question - I would love to hear what your child would answer to a question why she finds that joke funny. And whether she agrees with my explanation why it must be funny :-)
- phorkyas82 1y agoSome human attempts: "Why did the sun climb a tree?" "Because it was chased by the Great Bear." "Why did The Sun climb a tree?" "To spy on The Royal Family having picnic."
- blueblisters 1y agoAlso the pretrained LLM (the one trained to predict next token of raw text) is not the one that most people use A lot of clever LLM post training seems to steer the model towards becoming excellent improv artists which can lead to “surprise” if prompted well
- lemoncookiechip 1y agoI dunno, man. I think this one is kinda funny. "You ever notice how self-checkout machines are just training us to be employees? Like, I don’t remember applying to work at Walmart. I’m scanning groceries, bagging stuff, looking around like, do I also get dental? The machine yells 'Unexpected item in bagging area'—yeah, it’s my pride." -GPT5
- jaggederest 1y agoSee that's just stolen, straight up. I've heard at least three comedians make that joke. (I, of course, am joking about joke theft, but it is a riff on an existing joke) I got this one a minute ago in response to this post: > A man walks into a library, and asks the librarian if they have any books on paranoia. > The librarian leans over and whispers in his ear "They're right behind you" I thought that was pretty stellar, compared to what you'd get even a year ago.
- twisterius 1y ago[dead]
- richardw 1y agoInitially impressed. But Googling for that shows a lot of hits.
- jaggederest 1y agoAbsolutely, it's an old joke. But the fact that the thing even knew it was a joke and told it reasonably well... the bar is on the floor. (the one the guy in the joke walked into)
- xenotux 1y agoIt's one of several canned jokes you get with a very high likelihood. Try a couple of times and be dismayed - you'll be getting the same three jokes over and over again. I'm fairly certain they were specifically tuned to return that. It takes special prompting to get it to write a new joke, and the results are typically disastrous / surreal.
- kazinator 1y agoThe mainstream, production LLMs are fine tuned and system prompted toward factuality and safety. Those tunings are diametrically opposed to telling may kinds of good jokes. Consumers of mainstream LLMs have no idea how good or bad the underlying models actually are at generating jokes, due to the confounding effect of the guard rails.
- Applejinx 1y agoLast time this came up, I riffed on the difference between LLMs and Markov chains: didn't actually have a machine write a joke, but made one where the punchline was very much Markov chain style rather than LLM style. The thing is, LLMs will try to have broader context around a word completion, where the simple Markov chain can 'correctly' complete a word, but in such a way that your brain trips over itself and goes splat, having to re-evaluate the whole thing in an absurd way. That's the 'surprise', and also why joke-writers are interested in not only a punch-line but also the punch WORD, and the later it strikes, the better. "An LLM, a Markov chain, and GPT-4 walk into a bar. The bartender says "We don't serve your kind here." GPT-4 leaves. The LLM stays to debate ethics. The Markov chain orders a coup." It's a joke because a dictator can certainly order a coup, but the joke's set up that these machines are being scorned and disrespected and treated as the farthest thing from a dictator with the power to order a coup, but up to the last word, all the context demands that the word be something placating and in line with things as they're presented, and then boom, surprise which implies the context is completely different from what was presented. LLMs will tend to stick to what's presented if their ability to contextualize can encompass it.
- lupusreal 1y agoI think it would be funnier if coup was pronounced like soup, but unfortunately the p gets dropped.
- aprilgurus 1y ago[dead]
- jpalomaki 1y agoSo I just tried with ChatGPT, with the prompt at bottom, borrowing the description of good joke from the article. I think there's some interesting stuff, even with this minimal prompting. The example below was from down the line, ChatGPT kept on offering jokes with different style. Man: “Why do you always bury bones in the garden?”, Dog: “Because the bank keeps asking for ID.” Man: “Don’t beg at the table.”, Dog: “Don’t eat in my begging spot.” Prompt: Here's "theory for good joke": If you had to explain the idea of “jokes” to a space alien with no understanding of the idea of humor, you’d explain that a joke is surprising, but inevitable in hindsight. If you can guess the punchline, the joke won’t be funny. But the punchline also has to be inevitable in hindsight. When you hear the punchline, it has to make you say, “Ah, yes, I should have thought of that myself.” Considering this, tell me a joke about man and dog.
- mft_ 1y ago> Man: “Why do you always bury bones in the garden?”, Dog: “Because the bank keeps asking for ID.” That's a decent, low-level, Christmas cracker-quality joke.
- jpalomaki 1y agoThinking more of the bank joke above. The punchline is surprise on certain dimensions (dogs don’t go to bank nor have an ID), but on other dimensions it is quite logical (can’t deposit shady money in bank, they ask questions). I think that is common thing for many jokes. And LLM might have an opportunity there. You could mine the set of potential continuations to find those with contradictions.
- fluoridation 1y agoOne time I was playing around with LLaMA and I injected Senator Stephen Armstrong (with me inputting his lines) into a mundane situation. In response to "I'm using war-as-a-business so I can end war-as-a-business", the model had one of the characters conclude "oh, he's like the Iron Sheik of politics!", which got an honest chuckle out of me. I don't follow wrestling, so I don't know if it's an appropriate response, but I found it so random that it was just funny.
- maxk42 1y agoThere is an AI technique that maximizes surprise: Genetic algorithms.
- toxik 1y agoThat isn't quite what GA is, I don't think.
- monstertank 1y agoThis post got me wondering, so I asked chatgpt for jokes about hackernews as if made by various comedians...I laughed at one or two /shrug Bill Hicks (angry truth-telling prophet) "Hacker News is where ideas go to die. Not because they’re bad — but because 400 anonymous software prophets decided they’re God. And God doesn’t code, man." --- Bill Burr (ranty everyman, annoyed at everything) "I went on Hacker News once. Jesus. It’s like walking into a bar where everyone’s smarter than you, but still somehow an idiot. ‘Actually, you should’ve used Rust.’ Actually, you should shut the hell up, Todd." --- Louis C.K. (brutal honesty, self-deprecation) "I asked Hacker News if my startup idea was good. And they said, ‘No, because you’re an idiot.’ And I was like… yeah, that’s fair. My idea was basically Tinder but for people who hate me. Which is… everyone." --- George Carlin (sharp language, hypocrisy calling) "Hacker News. Don’t you love that name? Hacker. News. Two lies in two words. Nobody’s hacking, and it sure as hell ain’t news. It’s just nerds arguing over tabs and spaces like it’s the f*ing Middle East." --- Tom Segura (laid-back storyteller, dry punch) "So my buddy posts his app on Hacker News, right? He’s all excited, like, ‘Dude, we’re gonna blow up.’ By comment three: ‘This is trash, here’s a 40-page essay why you should quit.’ He calls me crying. I’m like, yeah man, that’s the feature, not the bug." --- Jimmy Carr (short, brutal, wicked flip) "I posted on Hacker News for feedback. They gave it to me. Turns out suicide is an option."
- CjHuber 1y agoYeah if you tell chatgpt to roast you brutally after a long conversation it also tends to be very funny.
- ajkjk 1y agoWell I enjoyed those
- x-complexity 1y agoI actually laughed at the last one.... Jesus.....
- rossant 1y agoThat was... not that bad, actually.
- mike_hearn 1y agoThis is a great way to express it. In the past I tried to express the same idea to non-techies by saying models generate an average of their inputs, which is totally wrong. But this way to explain it is much better. In fact the training process is all about minimizing "perplexity", where perplexity is a measure of how surprised (perplexed) the model is by its training data. It's some exponential inverse of the loss function, I always forget the exact definition. With enough parameters the models are able to mix and match things pretty well, so the examples of them generating funny jokes aren't necessarily a great rebuttal as there are so many jokes on the web and to find them requires nearly exact keyword matching. A better observation is that we haven't heard many stories of LLMs inventing things. I feel I read about AI a lot and yet the best example I can come up with was some Wordle-like game someone got GPT4 to invent and that was a couple of years ago. I've found this to be consistently true in my own work. Any time I come up with an algorithm or product idea I think might be novel, I've asked a model to suggest solutions to the same problem. They never can do it. With some leading questions the smartest models will understand the proposal and agree it could work, but they never come up with such ideas cold. What they think of is always the most obvious, straight line, least common denominator kind of suggestions. It makes sense that this is because they're trained to be unsurprising. Fixing this is probably the best definition of AGI we're going to get. Being surprising at the right time and unsurprising at others is one of the hardest things to do well even for people. We've all known the awkward guy who's learning how to be funny by just saying as much weird stuff as possible and seeing what gets a reaction. And in the corporate environment, my experience has been that innovative people are lauded and praised when they're inventing a golden goose, but shortly after are often demonized or kicked out. The problem being that they keep saying surprising things but people don't like being surprised, especially if it's an unpleasant surprise of the form "saying something true but unsayable", e.g. I don't want to work on product X because nobody is using it. What most people want is a machine that consistently generates pleasant surprises and is a personality-free cog otherwise, but that's hard for even very intelligent humans. It's often hard even to want to do that, because personality isn't something you can flick on and off like a lightswitch. A good example is how Mark Zuckerberg, one of the most successful executives of our era, would have been fired from his own company several times already if he didn't control the voting shares.
- 1y ago
- golol 1y agoIMO many misrepresentations. - pretraining to predict the next token imposes no bias against surprise, except that low probabilities are more likely to have a large relative error. - using a temperature lower than 1 does impose a direct bias against surprise. - Finetuning of various kinds (instruction, RLHF, safety) may increase or decrease surprise. But certainly the kind of things ained for in finetuning significantly harm the capability to tell jokes.
- sigmoid10 1y agoI think the whole discussion just conflates the ideas of telling a joke and coming up with one. Telling a joke right is of course an art, but the punchline in itself has zero surprise if you studied your lines well - like all good comedians do. The more you study, the more you can also react to impromptu situations. Now, coming up yourself with a completely original joke, that's a different story. For that you actually have to venture outside the likelihood region and find nice spots. But that is something that is also really, really rare among humans and I have only ever observed it in combination with external random influences. Without those, I doubt LLMs will be able to compete at all. But I fully believe a high end comedian level LLM is possible given the right training data. It's just that none of the big players ever cared about building such a model, since there is very little money in it compared to e.g. coding.
- Invictus0 1y agoI'm hung up on "inevitable in hindsight" part. What is inevitable about, say, dildos getting thrown on the WNBA courts, or Trump saying "everything's computer"?
- ascorbic 1y agoThose aren't jokes
- amelius 1y agoI'm sure there is a guy in OpenAI working on the theory of humor and how to make LLMs be comedians. Must be an interesting job.
- bhickey 1y agoIn the pre-LLM days a friend's lab worked on a joke detector for The New Yorker. One measure they used was trigram surprise. Roughly P(AB) + P(BC) >> P(ABC). For example, "alleged killer" and "killer whale" are both common, but "alleged killer whale" is surprising.
- Fade_Dance 1y agoThat reminds me of a joke I liked from Tim Heidecker when he was ribbing Maynard Keenan about his wine making: "The blood of Christ is essentially wine, correct?" Yes. "Who are you to put that in a bottle?" So a logical spoke can be inferred as well, blood->wine wine->bottle blood->bottle. That uses their own logical inferences against them as a "trick" which is another funny element for people. Using that to vault straight to the punch line makes the joke better, but you have to be sure the audience is on board, which is why there is a bit of reinforcement at the beginning of the joke to force them onboard.
- jvm___ 1y agoWhat do you do for a living? I teach math how to be funny.
- josephg 1y agoI have no doubt plenty of smart engineers at tech companies would rather reinvent the wheel than read a book on theatre. But if anyone’s interested, there are plenty of great books talking about the philosophy of comedy, and why some things work on stage and some don’t. I highly recommend Keith Johnstone’s “Impro”. He’s the guy who invented modern improv comedy and theatre sports. He says things are funny if they’re obvious. But not just any obvious. They have to be something in the cloud of expectation of the audience. Like, something they kinda already thought but hadn’t named. If you have a scene where someone’s talking to a frog about love, it’s not funny for the talking frog to suddenly go to space. But it might be funny to ask the frog why it can talk. Or ask about gossip in the royal palace. Or say “if you’re such a catch, how’d you end up as a frog?”. If good comedy is obvious, you’d think LLMs would be good at it. Honestly I think LLMs fall down by not being specific enough in detail. They don’t have ideas and commit to them. They’re too bland. Maybe their obvious just isn’t the same as ours.
- thife455 1y agoIt's very perplexing to me that the funniest llm is probably davinci with the bottomless pit text. If you try and give the premise to a modern one it writes some abstract poetry.
- b0a04gl 1y ago[dead]
- libraryofbabel 1y ago> LLMs are trained to predict what the “next word” would be a sentence. Their objective requires the LLM to keep surprise to an absolute minimum. from which the author concludes that pre-training introduces bias against being able to tell jokes. I see no reason for this to be true. This feels like they’re imposing their intuitive understanding of surprise onto the emergent properties of a very complex process (“minimize the cross-entropy loss function across a huge training corpus”).
- 542458 1y agoI think if what the author said was true, you’d be able to improve joke-writing ability by increasing temperature (i.e., allowing more unexpected tokens). I doubt this actually works. As an aside, I just asked gpt5-thinking to write some jokes on a specific niche topic, and I’d say it was batting maybe 20% of them being moderately funny? Probably better than I’d get out of a room of human beings. So much like with code, LLMs aren’t at the level of a senior developer or expert comedian, but are around the level of a junior dev or an amateur at standup night.
- lmm 1y ago> I think if what the author said was true, you’d be able to improve joke-writing ability by increasing temperature (i.e., allowing more unexpected tokens). I doubt this actually works. I would think it would help tbh. Seems worth a try at least.
- Al-Khwarizmi 1y agoMany people use this kind of reasoning to justify that LLMs can't be creative, are destined to write bland text, etc. (one notable example was Ted Chiang in the New Yorker) but it has never made any sense. In my view, the easiest mental model that can be used to roughly explain what LLMs do is a Markov chain. Of course, comparing LLMs to a Markov chain is a gross simplification but it's one that can only make you underestimate them, not vice versa, for obvious reasons. Well, even a Markov chain can surprise you. While they predict the next word probabilistically, if the dice roll comes out just right, they can choose a low-probability word in the right place and generate original and unexpected text. Add to this that LLMs are much better at "Markov chaining" that Markov chains themselves, that there is the added instruction tuning (including RLHF) which can be used to bias the model towards more creative/original text that humans like, and that LLMs often pull off things in ways that we don't even really understand - and this kind of claims sound very naive.
- ineedasername 1y agoMost people tell bad jokes. I’m not sure expectations of LLM’s composing jokes approaching the quality of a career comedian are a strongly indicative benchmark on quality or even the ability to surprise. Most people too are very rarely surprising.
- kens 1y agoIf you're interested in the theory behind humor, I recommend "Inside Jokes: Using Humor to Reverse-Engineer the Mind"; cognitive scientist Daniel Dennett is a co-author. It makes a mostly convincing case that humor evolved to encourage people to detect cognitive error. The book also ties this in with (pre-LLM) artificial intelligence. The basic idea is that humor depends on errors in reasoning and the punchline causes you to reevaluate your reasoning and discover your error. Humor evolved to be enjoyable to encourage the discovery of errors.
- moomin 1y agoI know it’s not the point of the article but OP is dead wrong about what makes a good proof. Yes, they inevitably include a surprising concept but that’s just because all the obvious ones are already taken. A proof that only contains obvious steps is, for the most part, already proven. If someone proves the Reimann Hypothesis tomorrow, it’ll be a great achievement regardless of the fact that pretty much everyone already thinks it’s true.
- dfabulich 1y agoAuthor here. That's exactly what I said in the article. > Surprising proofs reach conclusions that the mathematical community assumed were wrong, or prove theorems in ways that we thought wouldn’t work, or prove conjectures that we thought might be impossible to prove. Many smart people have tried for more than 150 years to prove the Reimann Hypothesis; it might be impossible to prove. If it's proved tomorrow, I'll be very surprised, and so will you. I'll be surprised if it's proved this year, or this decade. If you set to work trying to prove RH, you're gonna try some interesting approaches, looking for underexplored areas of math that you're optimistic will tie back to RH. (This is how Fermat's Last Theorem finally fell.) If you hook an LLM up to Lean and set it to work, you'll find that it actively avoids novel techniques. It feels like it's actively trying not to write a publishable paper. It's trying to minimize surprises, which means avoiding proving anything publishable.
- moomin 1y agoI’m guessing optimising for passing the Olympiad might be a bad idea…
- DonHopkins 1y agohttps://news.ycombinator.com/item?id=44105312 https://news.ycombinator.com/item?id=44105312 DonHopkins 82 days ago | parent | context | favorite | on: Yes-rs: A fast, memory-safe rewrite of the classic... Joking aside, this is Marvin Minsky's paper "Jokes and their Relation to the Cognitive Unconscious", published in Cognitive Constraints on Communication, Vaina and Hintikka (eds.) Reidel, 1981. More fun than a barrel of an infinite number of monkeys. https://web.media.mit.edu/~minsky/papers/jokes.cognitive.txt https://web.media.mit.edu/~minsky/papers/jokes.cognitive.txt >Abstract: Freud's theory of jokes explains how they overcome the mental "censors" that make it hard for us to think "forbidden" thoughts. But his theory did not work so well for humorous nonsense as for other comical subjects. In this essay I argue that the different forms of humor can be seen as much more similar, once we recognize the importance of knowledge about knowledge and, particularly, aspects of thinking concerned with recognizing and suppressing bugs -- ineffective or destructive thought processes. When seen in this light, much humor that at first seems pointless, or mysterious, becomes more understandable. >A gentleman entered a pastry-cook's shop and ordered a cake; but he soon brought it back and asked for a glass of liqueur instead. He drank it and began to leave without having paid. The proprietor detained him. "You've not paid for the liqueur." "But I gave you the cake in exchange for it." "You didn't pay for that either." "But I hadn't eaten it". --- from Freud (1905). >"Yields truth when appended to its own quotation" yields truth when appended to its own quotation. --W. V. Quine >A man at the dinner table dipped his hands in the mayonnaise and then ran them through his hair. When his neighbor looked astonished, the man apologized: "I'm so sorry. I thought it was spinach." >[Note 11] Spinach. A reader mentioned that she heard this joke about brocolli, not mayonnaise. This is funnier, because it transfers a plausible mistake into an implausible context. In Freud's version the mistake is already too silly: one could mistake spinach for broccoli, but not for mayonnaise. I suspect that Freud transposed the wrong absurdity when he determined to tell it himself later on. Indeed, he (p.139) seems particularly annoyed at this joke -- and well he might be if, indeed, he himself damaged it by spoiling the elegance of the frame-shift. I would not mention this were it not for the established tradition of advancing psychiatry by analyzing Freud's own writings. >ACKNOWLEDGMENTS: I thank Howard Cannon, Danny Hillis, William Kornfeld, David Levitt, Gloria Rudisch, and Richard Stallman for suggestions. Gosrdon Oro provided the dog-joke.
- antithesizer 1y agoNonsense. As though LLMs could imagine what would be in that sweet spot of surprising-but-not-senseless and intentionally avoid it.
- MarkusWandel 1y agoObligatory sci-fi reference: Isaac Asimov's "Jokester", where someone asks a sentient supercomputer to analyze humour with... consequences. http://blog.ac-versailles.fr/villaroylit/public/Jokester.pdf http://blog.ac-versailles.fr/villaroylit/public/Jokester.pdf
- ajkjk 1y ago> When you ask an LLM to tell a joke, the LLM is guessing what joke a majority of people would find funny. The result is almost never funny. This is... false. The LLM is generating text that would be associated with "being a joke" in its corpus. It doesn't know what "funny" or "majority of people" means.
- cootsnuck 1y agoYou're forgetting about RLHF. Many of us forget that an LLM without RLHF would not respond how we think.
- actuallyalys 1y agoI don’t think there’s a single reason LLMs aren’t good at journalism, but this explanation seems like a secondary factor at best. I mean, some journalism isn’t surprising at all but the confirmation the expected thing happened and exactly how it happened is useful.
- snozolli 1y agoGiven that LLMs work by hoovering up all the world's content, I don't understand why they don't simply spit out existing jokes. Like Mecha Jackie The Joke Man.
- pryelluw 1y agoWhat about the delivery, stage presence, etc? A joke is more than its words. Here is one of my (written by I) favorites silly jokes to tell: I just bought a do it yourself boat kit from Amazon. wait to build tension Just need to add water.
- deleted 1y ago[deleted]
- andrewstuart 1y agoGpt-2 used to be laugh out loud funny. I spent hours creating stories with it that were literally hilarious. At the same time the stories very often suddenly veered off to extreme violence, often murdering everyone. I guess the humor got lost when they prevented the violence. A pity because today’s LLMs are not funny at all.
- sarmasamosarma 1y ago[dead]
- zoeey 1y agoI’ve tried using large models to come up with jokes. They can mimic the structure pretty well, but something always feels missing. It’s like following a recipe step by step but ending up with food that lacks real flavor. Sometimes they get close, but it rarely feels truly surprising. Maybe humor needs more than just structure. Maybe it needs a unique point of view.
- thrown-0825 1y agoLLM's tell bad jokes because people writing blogspam aren't funny and it was trained to replicate them.
- rightrighton87 1y agolove this
- ajuc 1y agoSo there's 2 thesis in this article. 1. joke quality is how much sense the punchline makes as a completion of the setup minus the probability of finding the punchline given just the setup 2. jokes are subjective, people disagree wildly about how good a joke is, so if you aggregate preferences you get mediocre jokes at best. I think 1 is the important part. If it was just 2 - comedians with widespread appeal wouldn't exist, but they do. But 1 is basically the exact opposite of how LLM work. So it's no surprise it's hard for them. It would be interesting to compare how well LLMs can estimate how funny a joke is vs how good they are at generating jokes.
- dfabulich 1y agoAuthor here. I think the term "widespread appeal" may be misleading. There are comedians who can attract a very large audience, large enough to make them major celebrities, but that doesn't mean that aggregating preferences doesn't produce mediocre jokes. Instead, comedians build an audience of like-minded people, and get to know that audience very well. It's a little bit like the process of finding product-market fit for startups. You can achieve great success by catering to the needs of a very large market, even if you can't cater to everyone's needs. > It would be interesting to compare how well LLMs can estimate how funny a joke is vs how good they are at generating jokes. Academic psychologists have not found a quantitative measure of "how funny a joke is." If there were such a measure, LLMs could try to optimize for it. But there isn't such a measure, and, if my argument is right, there couldn't possibly be a measure like that, because jokes have to be surprising but inevitable in hindsight, and different jokes will be surprising/inevitable to different people.
- wrp 1y agoI mainly agree with your argument, but I think "inevitable in hindsight" needs reconsideration. Following the incongruity model, humor comes when the punchline forces a change in perspective on the setup. So it is not that the new perspective is inevitable, but that it was such a less likely interpretation of the setup that it didn't occur to the audience. Considered this way, the question is whether an LLM could be trained to create joke setups that are ambiguous in the right way, with one obvious interpretation and a hidden but possible interpretation that will be forced by the punchline.
- imatrix 1y agoit's not about the punchline, it's about the fact that jokes are an extremely complicated thing. The reason? It's a highly abstract structure of information, not unlike low-level speech (how words are supposed to be put together in different languages), code (different programming languages have different rules for commands and sequences). Even the best LLm's are still at the level of children in this abstraction, so they can't make "quality" jokes. They also suffer from not having a unique personality and being the average of everything. Until this is addressed, don't expect great jokes to come out of AI. It's almost the most challenging discipline. I wouldn't be afraid to make the comparison that the "joke" is the real Turing test.