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I think you're kind of proving the OPs point. The argument is that GPT3 has no understanding of the world, just superficial understanding of words and their re

by typon 6y ago

I think you're kind of proving the OPs point. The argument is that GPT3 has no understanding of the world, just superficial understanding of words and their relationships. If it did have a real understanding, prompt construction wouldn't matter as much, but it clearly does because all GPT3 cares about the structure of sentences, not their meanings.

SpicyLemonZest 6y ago
Prompt construction matters because GPT-3's goal is predicting what you're likely to write next, not responding to questions with informative and correct answers. If your prompt makes it sound like you're telling a silly story that doesn't make any sense, the correct continuation is to keep rolling with the nonsense.
ma2rten 6y ago
GPT-3 doesn't care about anything except predicting the next token. It learned something about structure and meaning in the process.
- pwinnski 6y ago
  About structure, clearly. About meaning, not so clear. It seems more supportable to say that GPT-3 knows nothing about meaning, but that its knowledge of structure often gives an illusion of meaning.
  - armitron 6y ago
    How is that different from how we use language besides our knowledge of structure being more layered and the abstractions more tight? What is meaning if not illusion?
  - chillacy 6y ago
    This is the thesis of Bender 2020 https://www.aclweb.org/anthology/2020.acl-main.463.pdf https://www.aclweb.org/anthology/2020.acl-main.463.pdf when evaluating GPT-2. They distinguish between meaning and form. We don't _really_ know what the physical manifestations of meaning and form are in the brain... they're just concepts we invented. If anything, GPT-3 is suggesting that either: 1. Tasks which were previously thought to require meaning actually turn out only to require form. 2. Meaning and form are more related than previously thought. Both are interesting findings imo, but 2 would be huge, especially if it suggests how the brain might work. Could meaning be an emergent phenomenon of form?
    - canjobear 6y ago
      It seems like Bender & Koller's argument can just as easily prove that humans don't have representations of meaning either. Our brains get input from multiple "languages"---conventional natural languages as well as the neural codes that represent our sensory inputs. All we have access to is the form of these inputs, and so we can never learn the underlying "meaning".
      - visarga 6y ago
        Meaning comes from the game, not from the brain. It's the relation between agent and environment that creates meaning.
        chillacy 6y ago
        The paper makes reference to the Symbol Grounding Problem, but I have not found the SGP's distinction between form and meaning to be completely convincing without some evidence of a physical, observable process. At the end when you look long enough it seems to call into question the very nature of consciousness.
      - chillacy 6y ago
        Hmm I think I see what you're saying. Reality is experienced through electrical signals, arguably we're just learning those inputs. But then I (as always I can only speak for myself, everyone else could be a p-zombie for all I know!) also have a qualitative experience of trees, and words, and an experience of meaning and understanding. If you look too deeply it quickly gets philosophical. https://en.wikipedia.org/wiki/Hard_problem_of_consciousness https://en.wikipedia.org/wiki/Hard_problem_of_consciousness
        vladTheInhaler 6y ago
        > Reality is experienced through electrical signals, arguably we're just learning those inputs. That's exactly what we're doing. And we're never given the "answer sheet" to figure out whether we understood the platonic, capital T Truth, or whether we just learned a spurious correlation. We just keep getting more of those inputs. Which is why it seems to me that an unsupervised sequence prediction model like GPT-3 is the only sort that could ever give rise to something akin to human consciousness. The big differentiator seems to be that with a pure text sequence model, inputs go in, but the outputs don't have any control over future inputs. It isn't structured to have anything like agency, just passive observation and prediction. But a useful "understanding" in a human sense is related to what can be done with that understanding to enact change in the environment. I don't know how you would teach it that without giving it a Reddit account and setting it loose. > But then I (as always I can only speak for myself, everyone else could be a p-zombie for all I know!) also have a qualitative experience of trees, and words, and an experience of meaning and understanding. If you look too deeply it quickly gets philosophical. I'm not so sure I have those things. I'm glad you do. That's one reason I'm never going to do ketamine.
  - ma2rten 6y ago
    I'm not sure what your definition of meaning is. Take this example from the GPT3 paper: To do a "farduddle" means to jump up and down really fast. An example of a sentence that uses the word farduddle is: One day when I was playing tag with my little sister, she got really excited and she started doing these crazy farduddles. According to my understanding of the concept it must know something about meaning and is able to reason about it if it was able to generate this.
    - notahacker 6y ago
      Depends what you're talking about by meaning. It correctly interprets the first part of the prompt as 'farduddle ~= jump' and the second part as an instruction to generate a sentence containing farduddle, possibly utilising a corpus of existing sentences containing jump in the context of 'really fast'. But that's also a series of instructions you could imagine as a DSL a relatively simple program could parse and generate a satisfactory response to. Which I believe the OP is classing as 'structure' since it's just performing translations based on familiar syntax. Understanding the concept of 'jumping' is a step further, before we get into the more philosophical stuff about qualia and whether things that can't jump can ever truly understand the experience of jumping...
      - ma2rten 6y ago
        Right, in this context I define meaning as the relationship between symbols. Form would be how to structure a sentence (but that sentence wouldn't have to make sense). If the parent comment was making some kind of Chinese Room argument than I think that's not very helpful for the discussion. "GPT-3 learned nothing about meaning because no computer program can do that by definition". But I don't think they were trying to make that kind of argument as you seem to be suggesting because they said they were unsure if it learned anything about meaning.
    - YeGoblynQueenne 6y ago
      - ...And Morris? - Um, it actually already is a word. Tnetennba. - Good heavens, really? Could you, uh, use it in a sentence for us? - "Good morning. That's a nice Tnetennba" [1]. ______________ [1] Moss from IT Crowd on Countdown: https://youtu.be/g9ixvD0_CmM?t=52 https://youtu.be/g9ixvD0_CmM?t=52 Edit: to clarify, if you don't know what a word means, just seeing it used in a sentence won't necessarily tell you much about its meaning, so that a language model was able to generate a phrase with the word in it doesn't necessarily tells us it understands the word's meaning.
  - visarga 6y ago
    The old debate about syntax and semantics. I would say syntax, when embodied in the world gains meaning. Meaning comes from the context of the agent and its goals.
hackinthebochs 6y ago
>If it did have a real understanding, prompt construction wouldn't matter as much This is only true if we assume GPT was never trained on satire or intentionally absurd text. But there's no reason to think this. Because it continues a bad prompt in an absurd or comical way does not demonstrate it doesn't "understand" common facts. If you treat GPT as a conversation bot and expect it to call you out when you give it an absurd prompt, then it is your expectations that are wrong.
- ClumsyPilot 6y ago
  > if continues a bad prompt in an absurd or comical way does not demonstrate it doesn't "understand" common facts. Well then you can justify it outputting anything at all.
  - dodobirdlord 6y ago
    This is why it’s fair to call some prompt designs bad. With a bad prompt you can’t really judge anything from the response. But better prompt design can uncover interesting behaviors. GPT-3 will generally not reject a prompt as nonsense or unreasonable, and will instead do a straight-faced continuation, probably because it has been trained on plenty of jokes, satires, dream sequences, etc. But if you specifically give it space in the prompt to reject nonsense, it’s actually quite good at rejecting nonsense. https://arr.am/2020/07/25/gpt-3-uncertainty-prompts https://arr.am/2020/07/25/gpt-3-uncertainty-prompts
    - ClumsyPilot 6y ago
      I have read your link, but think this is an unfair argument. We are not talking about nonsense, we are talking about unexpected input, which will happen in any real-world situation. It might be text about something a kid, or depressed person has done. The text about stirring with a cigar is firmly withing the realm of plausibility. And what happens is that GPT seemingly goes off the rails.
  - im3w1l 6y ago
    It's an autocompleter. If you want an answer to question, you have to make the answer the obvious (to a human) completion. If you want it to continue in a serious tone, you have to make sure the prompt is serious.
bigyikes 6y ago
Lacking “understanding” doesn’t make GPT-3 less impressive and also doesn’t make comparisons to human abilities unwarranted. I read the prompt, and I expected that this was the beginning of some kind of fiction. In my mind, it sounded like I was reading the beginning of a somebody’s dream. What does it even mean to understand something? Because naively, it looks very much like GPT-3 and I have a shared understanding of the first prompt. Do I actually think the model understands like a human does? No. But I would bet that, in isolation, the part of my brain which processes and generates language might not understand much either... Or maybe I’m a bot and neither I nor GPT-3 understand anything at all. Beep boop
- smsm42 6y ago
  > Lacking “understanding” doesn’t make GPT-3 less impressive Yes it does. A model that latches on superficial frequentist links between words is much less impressive than one that would understand what those words actually mean, and the latter is how most humans use words. The former is just chinese-rooming, the latter is understanding. Of course, a model that is chinese-rooming something like a coherent text is impressive, but it is less impressive than one that would demonstrate actual grasp of the fact that words mean something.
- junon 6y ago
  It's not about impressiveness - surely, it's impressive. However, the article is more or less critiquing the discourse surrounding the model - namely, that there is a strange misconception floating around that it's somehow a general purpose AI that can understand and think about the world similar to a human. Which, of course, it cannot. If the claims about GPT-3 were accurate, there'd be a lot less of a flare-up about it. Don't claim your software does what it can't.
  - monkpit 6y ago
    I fail to see where openai is making any false claims
    - mcguire 6y ago
visarga 6y ago
GPT-3 is a statistical model of text sequences, it has just textual understanding of the world. But the funny thing is that it can do lots of tasks without explicit training, and that is something amazing, it shows a path forward. In order to have real understanding it needs to be an embodied agent that interacts with the world like us, and has goals and needs like us.
- smsm42 6y ago
  It is impressive, but I'm not sure why doing stuff without training is such a good thing. Giving a choice, I'd rather have a model that works better with extensive domain-driven training than one that works worse without it. After all, when choosing an expert, you usually go for one that has the best experience in the field, not the one that can speak most eloquently on the widest variety of subjects (unless we're talking about politicians, there everybody does the opposite for some reason).
- YeGoblynQueenne 6y ago
  The tasks that GPT-3 can do are all language modelling tasks: given a sequence of tokens, what is the most likely sequence of tokens following from it? It's not surprising that this covers tasks like translation and question answering, which are language generation tasks. Other language models have been used in the same manner before, e.g. BERT. I don't remember metrics off the top of my head but I'm not sure GPT-3 is really top notch in many NLP tasks, if any. In any case a language model is a language model. It has no other ability than calculating the probabilities of sequences of tokens. Leaving aside the question of how something like that can have "real understanding" just by being embodied in the world, how do you even "embody" a language model? I'm genuinely curious to hear how far you have thought about that and how clearly. I mean in practical terms- you have a trained language model. You have a robotic body (not your own). How do you put them together to produce an embodied agent? What are the intermediarey steps that lead to a robot that can use its language model to... (what does an embodied language model do)?
evrydayhustling 6y ago
Just because something doesn’t display understanding by responding to your expectation doesn’t mean it doesn’t possess understanding . If you ran into my office with these prompts, the response to each would be “what the hell are you doing in my office?” All behavior is contextualized, and GPT-3’s native context is predicting continuous text, not answering questions. It’s a distracting anthropomorphism to even attempt ascribing “understanding” to a model like GPT-3. An assessment of its useful capabilities should be through an honest effort to get it to do something - and should of course include consideration of the effort/intelligence required to do so. Marcus knows enough to know this set up is inappropriate, so the article reads as disingenuous.
- dllthomas 6y ago
  Right. If I went to a human speaker, who presumably possesses "actual understanding", and I said "I have some prompts for you. Please try to continue where they left off" and then provide them a question, it wouldn't be strange that they don't answer it. Do we ever answer a question right after we've asked it? Sure. Do we always? I wonder if you can force "an attempt" at answering a question (to flagrantly anthropomorphize) by following the question with something like "The answer is ..."
  - evrydayhustling 6y ago
    Yeah, the suffix you suggest is an example of what you’ll see folks calling “prompt design”. It’s becoming an important theme in NLP literature, partly as a forensics tool to find out what kinds of knowledge models encode, and partly as a path to getting a single expensive training regime to assist a variety of tasks.
  - killerstorm 6y ago
    Yes, if you want answers, you need to frame it as a Q&A session: https://lacker.io/ai/2020/07/06/giving-gpt-3-a-turing-test.html https://lacker.io/ai/2020/07/06/giving-gpt-3-a-turing-test.h...
IanAWP 6y ago
This seems unreasonable. Gpt3 is stateless and any given prompt could require a news article, a fiction, a farce, real world logic. Prompt construction absolutely should matter in this situation. Consider that the article you read provided an immense amount of context to you about exactly what kind of tests were being run and how the answers were being evaluated (they want logic not creativity). If they had provided only the prompts and responses with no mention of gpt3 or the purpose of the article or anything else, would you have been able to judge the result? Why should gpt3 be able to do better when it had access to a single prompt at a time.
Rioghasarig 6y ago
Does GPT-3 need to understand the world to be useful? If you use it the right way, it still may be possible to accomplish some impressive things.
cel1ne 6y ago
> The argument is that GPT3 has no understanding of the world, just superficial understanding of words and their relationships. We don't really know what "understanding of the world" means in humans. We just "see it when it's there". We might be radically different from GPT-3, or we might not. Our way of learning is different in any way. Something that came to my mind: Various GPT-3 answers resemble answers given by children: Mostly correct, but having misunderstood some crucial point. In real human learning and conversation these points are easily corrected by feedback by explanation: "You see, the point is no one wears bathing suites to work". Which would then be incorporated as new wisdom. Maybe this feedback-mechanism is what GPT-3 is missing. Maybe we should talk to it.

by typon 6y ago

SpicyLemonZest 6y ago

Prompt construction matters because GPT-3's goal is predicting what you're likely to write next, not responding to questions with informative and correct answers. If your prompt makes it sound like you're telling a silly story that doesn't make any sense, the correct continuation is to keep rolling with the nonsense.

ma2rten 6y ago

GPT-3 doesn't care about anything except predicting the next token. It learned something about structure and meaning in the process.

pwinnski 6y ago
About structure, clearly. About meaning, not so clear. It seems more supportable to say that GPT-3 knows nothing about meaning, but that its knowledge of structure often gives an illusion of meaning.
- armitron 6y ago
  How is that different from how we use language besides our knowledge of structure being more layered and the abstractions more tight? What is meaning if not illusion?
- chillacy 6y ago
  This is the thesis of Bender 2020 https://www.aclweb.org/anthology/2020.acl-main.463.pdf https://www.aclweb.org/anthology/2020.acl-main.463.pdf when evaluating GPT-2. They distinguish between meaning and form. We don't _really_ know what the physical manifestations of meaning and form are in the brain... they're just concepts we invented. If anything, GPT-3 is suggesting that either: 1. Tasks which were previously thought to require meaning actually turn out only to require form. 2. Meaning and form are more related than previously thought. Both are interesting findings imo, but 2 would be huge, especially if it suggests how the brain might work. Could meaning be an emergent phenomenon of form?
  - canjobear 6y ago
    It seems like Bender & Koller's argument can just as easily prove that humans don't have representations of meaning either. Our brains get input from multiple "languages"---conventional natural languages as well as the neural codes that represent our sensory inputs. All we have access to is the form of these inputs, and so we can never learn the underlying "meaning".
    - visarga 6y ago
      Meaning comes from the game, not from the brain. It's the relation between agent and environment that creates meaning.
      - chillacy 6y ago
        The paper makes reference to the Symbol Grounding Problem, but I have not found the SGP's distinction between form and meaning to be completely convincing without some evidence of a physical, observable process. At the end when you look long enough it seems to call into question the very nature of consciousness.
    - chillacy 6y ago
      Hmm I think I see what you're saying. Reality is experienced through electrical signals, arguably we're just learning those inputs. But then I (as always I can only speak for myself, everyone else could be a p-zombie for all I know!) also have a qualitative experience of trees, and words, and an experience of meaning and understanding. If you look too deeply it quickly gets philosophical. https://en.wikipedia.org/wiki/Hard_problem_of_consciousness https://en.wikipedia.org/wiki/Hard_problem_of_consciousness
      - vladTheInhaler 6y ago
        > Reality is experienced through electrical signals, arguably we're just learning those inputs. That's exactly what we're doing. And we're never given the "answer sheet" to figure out whether we understood the platonic, capital T Truth, or whether we just learned a spurious correlation. We just keep getting more of those inputs. Which is why it seems to me that an unsupervised sequence prediction model like GPT-3 is the only sort that could ever give rise to something akin to human consciousness. The big differentiator seems to be that with a pure text sequence model, inputs go in, but the outputs don't have any control over future inputs. It isn't structured to have anything like agency, just passive observation and prediction. But a useful "understanding" in a human sense is related to what can be done with that understanding to enact change in the environment. I don't know how you would teach it that without giving it a Reddit account and setting it loose. > But then I (as always I can only speak for myself, everyone else could be a p-zombie for all I know!) also have a qualitative experience of trees, and words, and an experience of meaning and understanding. If you look too deeply it quickly gets philosophical. I'm not so sure I have those things. I'm glad you do. That's one reason I'm never going to do ketamine.
- ma2rten 6y ago
  I'm not sure what your definition of meaning is. Take this example from the GPT3 paper: To do a "farduddle" means to jump up and down really fast. An example of a sentence that uses the word farduddle is: One day when I was playing tag with my little sister, she got really excited and she started doing these crazy farduddles. According to my understanding of the concept it must know something about meaning and is able to reason about it if it was able to generate this.
  - notahacker 6y ago
    Depends what you're talking about by meaning. It correctly interprets the first part of the prompt as 'farduddle ~= jump' and the second part as an instruction to generate a sentence containing farduddle, possibly utilising a corpus of existing sentences containing jump in the context of 'really fast'. But that's also a series of instructions you could imagine as a DSL a relatively simple program could parse and generate a satisfactory response to. Which I believe the OP is classing as 'structure' since it's just performing translations based on familiar syntax. Understanding the concept of 'jumping' is a step further, before we get into the more philosophical stuff about qualia and whether things that can't jump can ever truly understand the experience of jumping...
    - ma2rten 6y ago
      Right, in this context I define meaning as the relationship between symbols. Form would be how to structure a sentence (but that sentence wouldn't have to make sense). If the parent comment was making some kind of Chinese Room argument than I think that's not very helpful for the discussion. "GPT-3 learned nothing about meaning because no computer program can do that by definition". But I don't think they were trying to make that kind of argument as you seem to be suggesting because they said they were unsure if it learned anything about meaning.
  - YeGoblynQueenne 6y ago
    - ...And Morris? - Um, it actually already is a word. Tnetennba. - Good heavens, really? Could you, uh, use it in a sentence for us? - "Good morning. That's a nice Tnetennba" [1]. ______________ [1] Moss from IT Crowd on Countdown: https://youtu.be/g9ixvD0_CmM?t=52 https://youtu.be/g9ixvD0_CmM?t=52 Edit: to clarify, if you don't know what a word means, just seeing it used in a sentence won't necessarily tell you much about its meaning, so that a language model was able to generate a phrase with the word in it doesn't necessarily tells us it understands the word's meaning.
- visarga 6y ago
  The old debate about syntax and semantics. I would say syntax, when embodied in the world gains meaning. Meaning comes from the context of the agent and its goals.

hackinthebochs 6y ago

>If it did have a real understanding, prompt construction wouldn't matter as much This is only true if we assume GPT was never trained on satire or intentionally absurd text. But there's no reason to think this. Because it continues a bad prompt in an absurd or comical way does not demonstrate it doesn't "understand" common facts. If you treat GPT as a conversation bot and expect it to call you out when you give it an absurd prompt, then it is your expectations that are wrong.

ClumsyPilot 6y ago
> if continues a bad prompt in an absurd or comical way does not demonstrate it doesn't "understand" common facts. Well then you can justify it outputting anything at all.
- dodobirdlord 6y ago
  This is why it’s fair to call some prompt designs bad. With a bad prompt you can’t really judge anything from the response. But better prompt design can uncover interesting behaviors. GPT-3 will generally not reject a prompt as nonsense or unreasonable, and will instead do a straight-faced continuation, probably because it has been trained on plenty of jokes, satires, dream sequences, etc. But if you specifically give it space in the prompt to reject nonsense, it’s actually quite good at rejecting nonsense. https://arr.am/2020/07/25/gpt-3-uncertainty-prompts https://arr.am/2020/07/25/gpt-3-uncertainty-prompts
  - ClumsyPilot 6y ago
    I have read your link, but think this is an unfair argument. We are not talking about nonsense, we are talking about unexpected input, which will happen in any real-world situation. It might be text about something a kid, or depressed person has done. The text about stirring with a cigar is firmly withing the realm of plausibility. And what happens is that GPT seemingly goes off the rails.
- im3w1l 6y ago
  It's an autocompleter. If you want an answer to question, you have to make the answer the obvious (to a human) completion. If you want it to continue in a serious tone, you have to make sure the prompt is serious.

bigyikes 6y ago

Lacking “understanding” doesn’t make GPT-3 less impressive and also doesn’t make comparisons to human abilities unwarranted. I read the prompt, and I expected that this was the beginning of some kind of fiction. In my mind, it sounded like I was reading the beginning of a somebody’s dream. What does it even mean to understand something? Because naively, it looks very much like GPT-3 and I have a shared understanding of the first prompt. Do I actually think the model understands like a human does? No. But I would bet that, in isolation, the part of my brain which processes and generates language might not understand much either... Or maybe I’m a bot and neither I nor GPT-3 understand anything at all. Beep boop

smsm42 6y ago
> Lacking “understanding” doesn’t make GPT-3 less impressive Yes it does. A model that latches on superficial frequentist links between words is much less impressive than one that would understand what those words actually mean, and the latter is how most humans use words. The former is just chinese-rooming, the latter is understanding. Of course, a model that is chinese-rooming something like a coherent text is impressive, but it is less impressive than one that would demonstrate actual grasp of the fact that words mean something.
junon 6y ago
It's not about impressiveness - surely, it's impressive. However, the article is more or less critiquing the discourse surrounding the model - namely, that there is a strange misconception floating around that it's somehow a general purpose AI that can understand and think about the world similar to a human. Which, of course, it cannot. If the claims about GPT-3 were accurate, there'd be a lot less of a flare-up about it. Don't claim your software does what it can't.
- monkpit 6y ago
  I fail to see where openai is making any false claims
  - mcguire 6y ago

visarga 6y ago

GPT-3 is a statistical model of text sequences, it has just textual understanding of the world. But the funny thing is that it can do lots of tasks without explicit training, and that is something amazing, it shows a path forward. In order to have real understanding it needs to be an embodied agent that interacts with the world like us, and has goals and needs like us.

smsm42 6y ago
It is impressive, but I'm not sure why doing stuff without training is such a good thing. Giving a choice, I'd rather have a model that works better with extensive domain-driven training than one that works worse without it. After all, when choosing an expert, you usually go for one that has the best experience in the field, not the one that can speak most eloquently on the widest variety of subjects (unless we're talking about politicians, there everybody does the opposite for some reason).
YeGoblynQueenne 6y ago
The tasks that GPT-3 can do are all language modelling tasks: given a sequence of tokens, what is the most likely sequence of tokens following from it? It's not surprising that this covers tasks like translation and question answering, which are language generation tasks. Other language models have been used in the same manner before, e.g. BERT. I don't remember metrics off the top of my head but I'm not sure GPT-3 is really top notch in many NLP tasks, if any. In any case a language model is a language model. It has no other ability than calculating the probabilities of sequences of tokens. Leaving aside the question of how something like that can have "real understanding" just by being embodied in the world, how do you even "embody" a language model? I'm genuinely curious to hear how far you have thought about that and how clearly. I mean in practical terms- you have a trained language model. You have a robotic body (not your own). How do you put them together to produce an embodied agent? What are the intermediarey steps that lead to a robot that can use its language model to... (what does an embodied language model do)?

evrydayhustling 6y ago

Just because something doesn’t display understanding by responding to your expectation doesn’t mean it doesn’t possess understanding . If you ran into my office with these prompts, the response to each would be “what the hell are you doing in my office?” All behavior is contextualized, and GPT-3’s native context is predicting continuous text, not answering questions. It’s a distracting anthropomorphism to even attempt ascribing “understanding” to a model like GPT-3. An assessment of its useful capabilities should be through an honest effort to get it to do something - and should of course include consideration of the effort/intelligence required to do so. Marcus knows enough to know this set up is inappropriate, so the article reads as disingenuous.

dllthomas 6y ago
Right. If I went to a human speaker, who presumably possesses "actual understanding", and I said "I have some prompts for you. Please try to continue where they left off" and then provide them a question, it wouldn't be strange that they don't answer it. Do we ever answer a question right after we've asked it? Sure. Do we always? I wonder if you can force "an attempt" at answering a question (to flagrantly anthropomorphize) by following the question with something like "The answer is ..."
- evrydayhustling 6y ago
  Yeah, the suffix you suggest is an example of what you’ll see folks calling “prompt design”. It’s becoming an important theme in NLP literature, partly as a forensics tool to find out what kinds of knowledge models encode, and partly as a path to getting a single expensive training regime to assist a variety of tasks.
- killerstorm 6y ago
  Yes, if you want answers, you need to frame it as a Q&A session: https://lacker.io/ai/2020/07/06/giving-gpt-3-a-turing-test.html https://lacker.io/ai/2020/07/06/giving-gpt-3-a-turing-test.h...

IanAWP 6y ago

This seems unreasonable. Gpt3 is stateless and any given prompt could require a news article, a fiction, a farce, real world logic. Prompt construction absolutely should matter in this situation. Consider that the article you read provided an immense amount of context to you about exactly what kind of tests were being run and how the answers were being evaluated (they want logic not creativity). If they had provided only the prompts and responses with no mention of gpt3 or the purpose of the article or anything else, would you have been able to judge the result? Why should gpt3 be able to do better when it had access to a single prompt at a time.

Rioghasarig 6y ago

Does GPT-3 need to understand the world to be useful? If you use it the right way, it still may be possible to accomplish some impressive things.

cel1ne 6y ago

> The argument is that GPT3 has no understanding of the world, just superficial understanding of words and their relationships. We don't really know what "understanding of the world" means in humans. We just "see it when it's there". We might be radically different from GPT-3, or we might not. Our way of learning is different in any way. Something that came to my mind: Various GPT-3 answers resemble answers given by children: Mostly correct, but having misunderstood some crucial point. In real human learning and conversation these points are easily corrected by feedback by explanation: "You see, the point is no one wears bathing suites to work". Which would then be incorporated as new wisdom. Maybe this feedback-mechanism is what GPT-3 is missing. Maybe we should talk to it.