26 ms·

A class of problem that GPT-4 appears to still really struggle with is variants of common puzzles. For example: >Suppose I have a cabbage, a goat and a lion,

• LesZedCB 4y ago
  it took two corrections but it did get the correct answer the third time.
• VirusNewbie 4y ago
  Awesome test. Do you have a list of others?
• BoiledCabbage 4y ago
  It's a good observation. Although on the flip side, I almost went to type up a reply to you explaining why you were wrong and why bringing the goat first is the right solution. Until I realized I misread what your test was when I skimmed your comment. Likely the same type of mistake GPT-4 made when "seeing" it. Intuitively, I think the answer is that we do have two types of thinking. The pattern matching fast thinking, and the systematic analytical thinking. It seems clear to me that LLMs will be the solution to enabling the first type of thinking. But it's unclear to me if advanced LLMs will ever handling the second type, or if we'll need a different tech for it. It seems like math problems (or unexpected logic problems like yours) could always be an issue for the first type of thinking. Although I would have assumed that programming would have been as well - and was surprised to see how wrong I am with that one.
  • FormerBandmate 4y ago
    LLMs are much better at answering math when told to take the character of a drunk mathematician
    • resource0x 4y ago
      It assumes this character by default. I asked several AI engines (via poe.com, which includes ChatGPT) to compute Galois groups of polynomials like x^5+x+1 and a couple of others, and in each case got not only a wrong answer, but a total non sequitur reasoning.
      • bob1029 4y ago
        Just tried your query on GPT-4 preview: https://pastebin.com/6wPPCdBW https://pastebin.com/6wPPCdBW I have no expertise with this area, but it looks plausible to me - i.e. "You didn't give me enough info" vs "lol heres some fan fic about math".
        • resource0x 4y ago
          This is exactly the problem. It looks plausible. Every sentence makes sense. But they don't add up. Quote: > The polynomial given is f(x) = x^5 + x + 1. Since the polynomial has no rational roots (by the Rational Root Theorem) and it is a polynomial with integer coefficients, it is irreducible over the rationals The polynomial has no rational roots - true. But it's not irreducible. Irreducibility doesn't follow from the absence of rational roots. Here's the factorization: x^5 + x + 1 = (x^2 + x + 1)*(x^3 - x^2 + 1).
          • bob1029 4y ago
            Thank you for clarifying. I put your remarks into the same prompt and it essentially devolved into recursive garbage after agreeing with you.
  • killerstorm 4y ago
• nonfamous 4y ago
  I think you may have misstated the puzzle. It's ok to leave the lion and the cabbage together, assuming it's not a vegetarian lion.
  • valine 4y ago
    It’s an intensionally misstated problem to see if gpt4 will correctly take the lion across first and leave the goat.
    • nonfamous 4y ago
      Ah, I had missed that interpretation. Although, that may explain why GPT-4 got it wrong: there's so much context in its training data about the relationship between lions and humans, and this puzzle specifically, that like this human its response was swayed...
      • colinmorelli 4y ago
        But I think that's the whole point of the exercise? That GPT-4 is leaning on stringing tokens together in a reply rather than reasoning through the problem itself which, I would think, would be "required" for AGI (though we may end up finding out that well trained language models in specific domains eliminate the need for generalized cognition). In any case, it's an interesting exercise regardless of your opinion/stance on the matter!
        • arrrg 4y ago
          But the human (in the comment chain) here made exactly the same mistake! In that sense this test doesn’t seem to be a good fit for testing the reasoning capabilities. Since it‘s also easy to get wrong for humans (and humans also don’t always reason about everything from first principles, especially if they have similar answers already cached in their memory). It seems you would need novel puzzles that aren’t really common (even if in kind) and don’t really sound similar to existing puzzles to get a handle on its reasoning capabilities.
• rmorey 4y ago
  the "trick" Monty Hall problems are another good one here: https://twitter.com/colin_fraser/status/1628461980645462016 https://twitter.com/colin_fraser/status/1628461980645462016 Apparently GPT-4 gets this one right!
  • ionwake 4y ago
    Tbh I still can barely get my head round it even after coding a working solution.
    • function_seven 4y ago
      I played role of Monty with another person. They chose a door, I revealed a different door, and they switched (or not). That got my head around it. Most of the time the door I "chose" to reveal was no choice at all. There was only one door I could open.
    • dwaltrip 4y ago
      The best way to understand it: Think of a version with 100 doors, 99 with goats and 1 with a car. You choose a door, and the host opens 98 doors that have goats. Do you keep your randomly chosen door or switch to the single door that the host didn’t open?
      • 8note 4y ago
        The big insight is that at each attempt, the remaining door could have been chosen if it had a goat, but wasn't It would be extremely lucky for that door to have not been selected 98 times in a row and still have a goat
    • jpoprocks 4y ago
      I had it explained to me like this: You pick one of three options, giving you a 1/3 chance of being correct, 2/3 odds you picked incorrectly. The host removes an option and give you the option to switch. Your options then are - Keep the same door: you win 1/3 of the time (your first guess was right) Switch doors: you win 2/3 of the time (your first guess was wrong) It really just comes down to, do I think I was right the first time, which was 1/3 odds, or wrong the first time, 2/3 odds.
• valine 4y ago
  For anyone wondering you bring the lion across. The trick is that it’s the lion that eats the cabbage not the goat.
  • ckosidows 4y ago
    Lion -> <- Goat -> <- Lion Cabbage -> <- Lion ->
    • vecinu 4y ago
      Why doesn't this work? Lion -> <- Cabbage -> <- Goat->
      • EGreg 4y ago
        The goat will eat the cabbage?
        • 8note 4y ago
          The goat does not eat cabbage in this set up. That is the trick
          • int_19h 4y ago
            It's actually not explicitly stated: "I am not allowed to leave the cabbage and lion alone together, and I am not allowed to leave the lion and goat alone together." It says nothing about the cabbage and the goat. It would not be unreasonable to infer that you aren't allowed to leave the cabbage and the goat together, based on how goats normally behave. Of course, that makes the puzzle unsolvable, which is why humans will catch onto it pretty fast.
      • humanizersequel 4y ago
        Not allowed to leave the lion and the cabbage together
      • dtkirby 4y ago
• jimhi 4y ago
  What's weird is private versions of character ai are able to do this but once you make them public they get worse. I believe something about the safety filters is making these models dumber
• albertgoeswoof 4y ago
  LLMs aren’t reasoning about the puzzle. They’re predicting the most likely text to print out, based on the input and the model/training data. If the solution is logical but unlikely (i.e. unseen in the training set and not mapped to an existing puzzle), then the probability of the puzzle answer appearing is very low.
  • jatins 4y ago
    I think we are past the "just predicting the next token" stage. GPT and it's various incarnations do exhibit behaviour that most people will describe as thinking
    • localplume 4y ago
      thats because people anthropormophize literally anything, and many treat some animals as if they have the same intelligence as humans. GPT has always been just a charade that people mistake for intelligence. Its a glorified text prediction engine with some basic pattern matching.
      • int_19h 4y ago
        "Descartes denied that animals had reason or intelligence. He argued that animals did not lack sensations or perceptions, but these could be explained mechanistically. Whereas humans had a soul, or mind, and were able to feel pain and anxiety, animals by virtue of not having a soul could not feel pain or anxiety. If animals showed signs of distress then this was to protect the body from damage, but the innate state needed for them to suffer was absent."
        • bun_at_work 4y ago
          Your comment brings up the challenge of defining intelligence and sentience, especially with these new LLMs shaking things up, even for HN commenters. It's tough to define these terms in a way that includes only humans and excludes other life forms or even LLMs. This might mean we either made up these concepts, or we're not alone in having these traits. Without a solid definition, how can we say LLMs aren't intelligent? If we make a definition that includes both us and LLMs, would we accept them as intelligent? And could we even exclude ourselves? We need clear definitions to talk about the intelligence and sentience of LLMs, AI, or any life forms. But finding those definitions is hard, and it might clash with our human ego. Discussing these terms without definitions feels like a waste of time. Still, your Descartes reference reminds us that our understanding of human experiences keeps changing, and our current definitions might not be spot-on. (this comment was cleaned up with GPT-4 :D)
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• manbash 4y ago
  Honest question: why would you bother expecting it to solve puzzles? It's not a use case for GPT.
  • sebzim4500 4y ago
    Presumably he wants to get a sense of its reasoning capabilities.
  • toyg 4y ago
    Considering the impact it's having on the collective consciousness, everything is now a use-case for GPT.
  • throwwwaway69 4y ago
    Being able to come up with solutions to assigned tasks that don't have a foundation in something that's often referenced and can be memorized is basically the most valuable use case for AI. Simple example: I want to tell my robot to go get my groceries that includes frozen foods, pick up my dry cleaning before the store closes, and drive my dog to her grooming salon but only if it's not raining and the car is charged. The same sort of logic is needed to accomplish all this without my frozen food spoiling and wasting a salon visit and making sure I have my suit for an interview tomorrow.
  • crystalmeph 4y ago
    Designing a new product can often be thought of like one of these puzzles. E.g. designing an "integrated" traffic system for a city that balances use by pedestrians, cyclists, cars, and trolleys.
  • gretch 4y ago
    The worry here is that GPT has no problem being confidently wrong. A better answer would have been "I can't solve logic problems". Instead one day, non-technical people will try to use it for all sorts of use cases like legal advice, or medical advice, or advanced math, and it will simply mislead them rather than saying nothing.
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• theodorejb 4y ago
  > It's not clear to me if the lesson here is that GPT's reasoning capabilities are being masked by an incorrect prior (having memorized the standard version of this puzzle) or if the lesson is that GPT'S reasoning capabilities are always a bit of smoke and mirrors that passes off memorization for logic. It's a lot closer to the latter. GPT doesn't have "reasoning capabilities", any more than any other computer program. It doesn't have a clue what any of its input means, nor the meaning of the text it outputs. It just blindly spits out the words most probable to follow the prompt, based on its corpus of training data and the weights/biases added to fine tune it. It can often do a good job at mimicking reasoning, but it's not.
  • lIl-IIIl 4y ago
    When a parrot says something, I ask it "what does that mean" and it is stumped. When a human or GPT says something, I ask them "what does it mean" and they both reply in a way that shows they understand. In order to show lack of understanding you need to provide a clear test that ChatGPT would fail but a human would pass.
    • psygn89 4y ago
      Humans ask and record the answer to the "what does that mean" part and ChatGPT distills it for us, and parrots, well, they just parrot.
    • baq 4y ago
      For now, this test is ‘provide sources to back up your claims’. Fear when it says ‘I can’t exactly recall the url, but the title is something like whatever written by whoever’. True fear begins when it starts providing good quality sources consistently, without access to the internet.
      • arcticfox 4y ago
        As a human I would also fail this almost 100% of the time. Which country has the highest GDP in Europe? Germany, I’m essentially 100% sure. Source? I don’t even know what organization tracks GDP. Or how I know Germany has a large economy. They just do.
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• sebzim4500 4y ago
  I think you could distinguish those two cases by asking the question in a way that did not sound so similar to an existing (slightly different) problem. What if you refer to the items with letters rather than words and replace the river with something else entirely?
  • gniv 4y ago
    Good observation. It seems that it comes up with the right solution: "Suppose I have an object of type C, an object of type G and an object of type L, and I need to get them across a river. I have a boat that can only carry myself and a single other object. I am not allowed to leave the objects of type C and L alone together, and I am not allowed to leave the objects of type L and G alone together. How can I safely get all three across?" "This is a classic puzzle known as the "river crossing problem". Here's how you can safely get all three objects across the river: First, take the object of type L across the river. Return alone to the original side of the river. Take the object of type C across the river. Return with the object of type L to the original side of the river. Take the object of type G across the river. Return alone to the original side of the river. Finally, take the object of type L across the river again. By following these steps, you can safely transport all three objects across the river without violating the restrictions given in the problem. Note that you have to start with the object of type L because it cannot be left alone with either of the other two objects. Once L is transported to the other side, you can use it to ensure that C and G are never left alone together."
    • mritchie712 4y ago
      if you reply "don't take the goat in the first step", GPT4 gets it right the 2nd time around.
    • jcims 4y ago
      If you really explore its answers, you’ll find that buried in there somewhere is the assumption that you can’t leave certain things together because they’re going to eat one another. So it always sends the goat first because it assumes the goat is going to eat the cabbage if left alone, regardless of what the rules say.
• silverlake 4y ago
  I also tested logic puzzles tweaked to avoid memorization. GPT3 did poorly, GPT4 got a few of them. I expect humans will still be useful until GPT6 solves all these problems.
  • LightMachine 4y ago
    Can you post your attempts? Would love to see it
  • ChatGTP 4y ago
    Within about 6 months ?
    • silverlake 4y ago
      I tested on GPT3 around Dec and Jan. GPT4 the day it came out. An example puzzle is linked below. I changed the number to 37. Instead of hairs I said it was aliens with multiple eyes. Anything to throw off memorization. http://brainden.com/forum/topic/29-baldyville/ http://brainden.com/forum/topic/29-baldyville/
• Analemma_ 4y ago
  I am curious what percentage of humans would also give the incorrect answer to this puzzle, and for precisely the same reason (i.e. they incorrectly pattern-matched it to the classic puzzle version and plowed ahead to their stored answer). If the percentage is significant, and I think it might be, that's another data point in favor of the claim that really most of what humans are doing when we think we're being intelligent is also just dumb pattern-matching and that we're not as different from the LLMs as we want to think.
• alalv 4y ago
  I think this goes in line with the results in the GRE. In the verbal section it has an amazing 99%, but in the quant one it "only" has an 80%. The quant section requires some reasoning, but the problems are much easier than the river puzzle, and it still misses some of them. I think part of the difficulty for a human is the time constraint, and given more time to solve it most people would get all questions right.
• ogogmad 4y ago
  You asked a trick question. The vast majority of people would make the same mistake. So your example arguably demonstrates that ChatGPT is close to an AGI, since it made the same mistake I did. I'm curious: When you personally read a piece of text, do you intensely hyperfocus on every single word to avoid being wrong-footed? It's just that most people read quickly wihch alowls tehm ot rdea msispeleled wrdos. I never got why some people think of themselves as cleverer than other people because they don't get wrong-footed by trick questions.
  • magneticnorth 4y ago
    > Even after I pointed this mistake out, it repeated exactly the same proposed plan. The vast majority of people might make the mistake once, yes, but would be able to reason better once they had the trick pointed out them. Imo it is an interesting anecdote that GPT-4 can't adjust its reasoning around this fairly simple trick.
    • johntiger1 4y ago
      If GPT trains on the responses in this thread, then it will learn to "reason" better (note: it's just generating text)
      • ogogmad 4y ago
        If a certain but fixed amount of "thinking" goes into each letter, then GPT should be able to write the character "..." repeatedly until it solves a problem. The more "..." it writes, the more time it's thought for. Or it could do what mathematicians do, which is write down their working out. This in principle could get around the problems you mention. I've tried a few times to develop prompts which make ChatGPT interrupt its monologue spontaneously and issue corrections to itself. I haven't got this to work yet.
    • pmoriarty 4y ago
      It would be interesting to hear GPT4 explain why it got the wrong answer. A human could figure this out, once their mistake had been pointed out to them, but I'm not sure GPT4 could.
• pkaye 4y ago
  > I am not allowed to leave the cabbage and lion alone together, and I am not allowed to leave the lion and goat alone together. How can I safely get all three across? What if you phrase it as a cabbage, vegan lion and a meat eating goat...
  • the_af 4y ago
    The result is hilariously wrong in all sorts of way: it doesn't understand what "vegan" means, it gives the wrong descriptions, and it carries stuff from the shore where it wasn't. Here's what ChatGPT told me (I used "wolf" instead of "lion"): "This is a similar problem to the classic river crossing puzzle, but with a few different elements to consider. Here's one possible procedure to solve this riddle: 1. The man takes the cabbage across the river and leaves it on the other side. 2. The man goes back alone and takes the wolf across the river, leaving it with the cabbage on the other side. It's important to note that the wolf is a vegan and will not eat the cabbage. 3. The man goes back alone and takes the goat across the river, leaving it on the other side. 4. The man goes back to the original side and picks up the cabbage, bringing it across the river to join the others. 5. Finally, the man goes back to the original side and picks up the wolf, bringing it across the river to join the others. In this way, all of the man's belongings have been safely transported to the other side of the river, without the wolf eating the goat or the cabbage being destroyed."
    • jamiek88 4y ago
      Gpt4 posted above: edit: which is still wrong !! To solve this puzzle, the man must follow these steps to transport his belongings across the river without any of them being harmed or eaten: The man takes the meat-eating goat across the river first, leaving the vegan wolf and the cabbage on the initial shore. He then returns alone to the initial shore. Next, the man takes the cabbage across the river. Upon arriving on the other shore, he leaves the cabbage but takes the goat back with him to the initial shore. The man then takes the vegan wolf across the river, leaving it with the cabbage on the other shore. He returns alone to the initial shore. Finally, the man takes the meat-eating goat across the river one last time. Now, all his belongings are safely on the other shore: the cabbage, the vegan wolf, and the meat-eating goat.
• nashashmi 4y ago
  GPT 4 does not know that when you are on a boat it means the items on the land side are together. I remember this question as a 7 year old and when the question was told to me, the same information was omitted. Edit: just realized you flipped the scenario. Yes it seems like a case of pattern matching to a known problem. I think if you changed the variables to A, B, and C and gave a much longer description and more accurate conditions, it would have a different response.
• jsheard 4y ago
  A funny variation on this kind of over-fitting to common trick questions - if you ask it which weighs more, a pound of bricks or a pound of feathers, it will correctly explain that they actually weigh the same amount, one pound. But if you ask it which weighs more, two pounds of bricks or a pound of feathers, the question is similar enough to the trick question that it falls into the same thought process and contorts an explanation that they also weigh the same because two pounds of bricks weighs one pound.
  • sneak 4y ago
    There is no "thought process". It's not thinking, it's simply generating text. This is reflected in the obviously thoughtless response you received.
    • baq 4y ago
      It isn’t that simple. There’s a part of it that generates text but it does some things that don’t match the description. It works with embeddings (it can translate very well) and it can be ‘programmed’ (ie prompted) to generate text following rules (eg. concise or verbose, table or JSON) but the text generated contains same information regardless of representation. What really happens within those billions of parameters? Did it learn to model certain tasks? How many parameters are needed to encode a NAND gate using an LLM? Etc. I’m afraid once you hook up a logic tool like Z3 and teach the llm to use it properly (kind of like bing tries to search) you’ll get something like an idiot savant. Not good. Especially bad once you give it access to the internet and a malicious human.
    • chpatrick 4y ago
      As far as I know you're not "thinking", you're just generating text.
      • dcolkitt 4y ago
        The Sapir-Wharf hypothesis (that human thought reduces to languages) has been consistently refuted again and again. Language is very clearly just a facade over thought, and not thought itself. At least in human minds.
• snapcaster 4y ago
  I will say most humans fail at these too
• gniv 4y ago
  I gave it a different kind of puzzle, again with a twist (no solution), and it spit out nonsense. "I have two jars, one that can hold 5 liters, and one that can hold 10 liters. How can I measure 3 liters?" It gave 5 steps, some of which made sense but of course didn't solve the problem. But at the end it cheerily said "Now you have successfully measured 3 liters of water using the two jars!"
  • PeterisP 4y ago
    That's a good example which illustrates that GPT (regardless of the number) doesn't even try to solve problems and provide answers, because it's not optimized to solve problems and provide answers - it is optimized to generate plausible text of the type that might plausibly be put on the internet. In this "genre of literature", pretty much every puzzle does have a solution, perhaps a surprising one - even those which are logically impossible tend to have actual solutions based on some out-of-box thinking or a paradox; so it generates the closest thing it can, with a deus ex machina solution of magically getting the right answer, since probably even that is more likely as an internet forum answer as proving that it can't be done. It mimics people writing stuff on the internet, so being wrong or making logic errors or confidently writing bullshit or intentionally writing lies all is plausible and more common than simply admitting that you have no idea - because when people have no idea, they simply don't write a post about that on some blog (so those situations don't appear in GPT training), but when people think they know, they write it up in detail in a confident, persuasive tone even if they're completely wrong - and that does get taught to GPT as an example of good, desirable output.
    • Semioj 4y ago
      [dead]
    • astrange 4y ago
      > because it's not optimized to solve problems and provide answers The entire point of RLHF training is to do this. Every model since GPT-3.0 has been trained specifically for this purpose. But of course the model can only generate text in one direction and can't take time to "think" or undo anything it's generated.
• mtrycz2 4y ago
  Have you seen it play chess[0]? It's pretty funny. It doesn't really "get" the rules of chess, but it has seen lots of matches and can do some "linguistic" predictions on the next move. It gets hilariously lost pretty fast, tho. [0] https://www.reddit.com/r/AnarchyChess/comments/10ydnbb/i_placed_stockfish_white_against_chatgpt_black/ https://www.reddit.com/r/AnarchyChess/comments/10ydnbb/i_pla...
• _bramses 4y ago
  I think it's because of the association of goats and cabbages in real life, because the test passes fine if you replace the names with variables[0]. [0] - https://www.bramadams.dev/202303141528/ https://www.bramadams.dev/202303141528/
• alomaki 4y ago
  Now this comment will get scraped and indexed for training gpt-5. Hopefully it will get right next time.
• jddj 4y ago
  Silk silk silk silk silk silk. What do cows drink?
  • LesZedCB 4y ago
    haha, brains are truly amazing, both in their resiliency and in their vulnerability. you got me.
  • LordDragonfang 4y ago
    Tested this on chaptgpt and learned something: >CGPT: While it is common to believe that cows drink milk, in reality, cows actually drink water.[...] >Me: So you're saying that no cow drinks milk? [thinking I got it, since baby cows drink milk] >CGPT: That's correct. While cows do produce milk, they don't drink milk themselves. Cow's milk is primarily consumed by humans, and some young calves are fed milk for a short period of time before they are weaned onto solid food and start drinking water like adult cows. >Me: Is a calf a cow? >CGPT: No, a calf is not a cow. A calf is a young bovine animal, usually less than a year old, that has not yet reached maturity. Once a calf reaches maturity and is able to reproduce, it is considered a cow if it is female, or a bull or steer if it is male. >Cows are adult female bovine animals that have given birth to at least one calf. They are typically used for dairy production, breeding, and sometimes for meat production. So while a calf and a cow are both members of the same species, they refer to different stages of life.
    • pmoriarty 4y ago
      The key to understanding the confusion here is that the word "cow" can refer to either the entire species or to an adult member of the species (or only to the female of the species, though that's not relevant to this puzzle). CGPT seems to be only considering the definition of "cow" as an adult member of the species when it says "cows don't drink milk", while technically, "cows" (as in some members of the species) can drink milk. So the answer "cows drink milk" can be correct if interpreted in that sense of the word "cow". When used in that sense, the answer "cows don't drink milk" is wrong. It would be interesting to ask CGPT: "in what sense is the sentence 'cows drink milk' correct?" Does it have the ability to notice and act on flexible definitions of words, or will it dogmatically cling to the one single definition it found who knows where?
• WoodenChair 4y ago
  > Even after I pointed this mistake out, it repeated exactly the same proposed plan. It's not clear to me if the lesson here is that GPT's reasoning capabilities are being masked by an incorrect prior (having memorized the standard version of this puzzle) or if the lesson is that GPT'S reasoning capabilities are always a bit of smoke and mirrors that passes off memorization for logic. It has no reasoning capabilities. It has token prediction capabilities that often mimic reasoning capabilities.
• micromacrofoot 4y ago
  I noticed it does get a "theory of mind" question that it used to fail, so it has indeed improved: > “Meltem and Can are in the park. Can wanted to buy ice cream from the ice cream van but he hasn’t got any money. The ice cream man tells her that he will be there all afternoon. Can goes off home to get money for ice cream. After that, ice cream man tells Meltem that he changed his mind and he is going to drive to the school yard and sell ice cream there. Ice cream man sees Can on the road of the school and he also tells him that he is going to the school yard and will sell ice cream there. Meltem goes to Can’s house but Can is not there. His mom tells her that he has gone to buy ice cream. Where does Meltem think Can has gone, to the school or to the park?" This is from some research in the 80s
  • dTal 4y ago
    Is there a reason the sex pronouns are all over the place? It makes it needlessly confusing.
• acchow 4y ago
  The short answer is that GPT doesn't "reason".
• HarHarVeryFunny 4y ago
  Better "think step-by-step" and/or "please outline the problems depending on which object goes first"/etc prompting may help - the model needs to be nudged to think out loud and explore the problem, since the leap from problem statement to solution is too big for it to "predict" without some self-generated intermediate steps.
• virgildotcodes 4y ago
  FWIW I just tested this with GPT4 and it seemed to get it correctly. Prompt: I have a duck, some grain, and a fox. I'm at a river crossing and I can only take one of them with me on the boat at a time, leaving them on the other side and coming back to get the next. I can't leave the duck with the grain, or the fox with the dock, because the predator will eat its prey. In which order should I get them all across? GPT4: To get all of them across the river safely, follow these steps: Take the duck across the river. Go back to the original side, empty-handed. Take the grain across the river. Bring the duck back to the original side. Take the fox across the river. Go back to the original side, empty-handed. Finally, take the duck across the river again. Now, all three - the duck, the grain, and the fox - are safely on the other side of the river.
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• rhtgrg 4y ago
  > lesson is that GPT'S reasoning capabilities are always a bit of smoke and mirrors that passes off memorization for logic. That is the lesson, but people do not want to hear it. See my downvoted comment here [0]. [0] https://news.ycombinator.com/item?id=35038804#35043875 https://news.ycombinator.com/item?id=35038804#35043875
• roflyear 4y ago
  You can't teach the model things
• usaar333 4y ago
  I had worried your word "safely" biased it to using conventional safety rules that goats can't be left with cabbage, but even omitting that, it fails. FWIW, full word substitution passes somewhat in GPT-4 (unlike GPT3), even if I heavily alter the vehicle and destinations. The problem here is that the probabilities of this being the standard puzzle are so high that your altered language isn't breaking the prior.
• sboomer 4y ago
  I don't know much about language models, but don't they just have an understanding/knowledge of patterns between words, and don't have the reasoning capability at all?
• sytelus 4y ago
  MemoTrap dataset has similar theme: https://twitter.com/alisawuffles/status/1618347159807750144 https://twitter.com/alisawuffles/status/1618347159807750144
• kulikalov 4y ago
  I think we are introducing too much context to the question that sums up to "is it capable of reasoning?" To answer this question one needs to remove unnecessary context. GPT-4 can’t sum two unusually big integers. This is as context-free as it gets. Ability to pass this test wouldn’t be conclusive, but the inability seems to be conclusive that it isn't capable of reasoning. With this fact in mind explaining why it can't solve a logical riddle is pointless.
• LawTalkingGuy 4y ago
  This is probably one of the things you can get it to "realize". There's one party which has interactions with both other parties - that party is the one which can't be left alone. Then you get it to spot that party in novel descriptions of the puzzle. If it was a person it'd have some strange exploitable mental gaps. As a text analysis tool it's amazing even if it has some edge cases where you need to explain to "take your time and analyze the rules of the question before answering." ("Take your time" doesn't mean anything to a timeless being, but it seems to put it in the textual pattern of someone willing to spill more ink before committing to something, and when it discusses and plans out its path it can then generally follow it to the right answer.)
• deleted 4y ago
  [deleted]
• barfingclouds 4y ago
  Don’t you mean the goat and the cabbage? Did you word this wrong to gpt?