7 ms·

Its vast limitations in anything reasoning-based are indeed evident.

p1esk 3y ago
GPT-4 is better at reasoning than 90% of humans. At least. I won't be surprised if GPT-5 is better than 100% of humans. I'm saying this in complete seriousness.
- chimpanzee 3y ago
  Do you put yourself in the 10% or the 90%? I’m asking in complete seriousness.
  - deleted 3y ago
    [deleted]
  - p1esk 3y ago
    Oh it's definitely better than me at reasoning. I'm the one asking it to explain things to me, not the other way around.
    - krainboltgreene 3y ago
      If you think it's better than you at reasoning then you cannot at all be confident in the truth of it's dialog.
      - p1esk 3y ago
        I am not. I treat it as I'd treat any smart human being.
        AdieuToLogic 3y ago
        LLM's are not a "smart human being." They are predictive statistical models capable of producing results based on training data. LLM's do not think. LLM's are algorithms.
        int_19h 3y ago
        Your brain is also basically an algorithm that produces results based on training data. It's just a much more complicated and flexible one.
        runlaszlorun 3y ago
        But it’s also based on neurons with far more complex behavior than artificial neurons and also has other separate dynamic systems involving neurochemicals, various effects across the nervous system and the rest of the body (the gut becoming seemingly more and more relevant), various EEG patterns, and most likely quantum effects. I personally wouldn’t rule out that it can’t be emulated in a different substrate, but I think calling it “an algorithm” is to def stretch and misapply the usefulness of the term.
        int_19h 3y ago
        If it performs a computation, it is by definition running some algorithm regardless of how it's implemented in hardware / wetware. How is it a stretch? The only way our brains could be not algorithmic is if something like soul is a real thing that actually drives our intelligence.
        YeGoblynQueenne 3y ago
        Why? Rain is not algorithmic, clouds are not algorithmic, waves in the sea are not algorithmic, yet they are entirely physical processes that have nothing to do with souls.
        int_19h 3y ago
        None of these are computational processes, unlike intelligence. Unless you're trying to argue that intelligence isn't, either?
        YeGoblynQueenne 3y ago
    - chimpanzee 3y ago
      Ah ok. Here you use the word “explain” which implies more of a descriptive, reducing action rather than extrapolative and constructive. As in, it can explain what it has “read” (and it has obviously “read” far more than any human), but it can’t necessarily extrapolate beyond that or use that to find new truths. To me reasoning is more about the extrapolative, truth-finding process, ie “wisdom” from knowledge rather than just knowledge. But maybe my definition of “reasoning” isn’t quite right. Edit: I probably should define reasoning as solely “deductive reasoning”, in which case, perhaps it is better than humans. But that seems like a premature claim. On the other hand, non-deductive reasoning, I have yet to see from it. I personally can’t imagine how it could do so reliably (from a human perspective) without real-world experiences and perceptions. I’m the sort that believes a true AGI would require a highly-perceptual, space-occupying organ. In other words it would have to be and “feel” embodied, in time and space, in order to perform other forms of reasoning.
      - p1esk 3y ago
        Why don't you suggest an example we can run and see what it's capable of (compared to what I, or other humans, are capable of)?
        chimpanzee 3y ago
        (In case it was missed, I’ve added a relevant addendum to my previous comment.) Not sure an example is needed because I agree it “explains” better than pretty much everyone. (From my mostly lay perspective) It essentially uses the prompt as an argument in a probabilistic analysis of its incredibly vast store of prior inputs to transform them into an output that at least superficially satisfies the prompter’s goals. This is cool and useful, to say the least. But this is only one kind of reasoning. A machine without embodied perceptual experiences simply cannot reason to the full-extent of a human. (It’s also worth remembering that the prompter (very likely) has far less knowledge of the domain of interest and far less skill with the language of communication, so the prompter is generally quite easily impressed regardless of the truth of the output. Nothing wrong with that necessarily, especially if it is usually accurate. But again, worth remembering.)
- chimprich 3y ago
  Google search is better than reasoning than most humans - in that if you search for an explanation of something then Google's first result is often correct, or one of the following ones. GPT-4 will often come up with a solution to a problem, but only if it has learnt something similar (it's better than Google in some respects: it can extract and combine abstractions). However, both need handholding by a human (supplying the initiative and directing around mistakes). If GPT-4 can't intuit an answer then it just goes in circles. It can't reason its way through a novel problem. If you start questioning it then it's clear that it doesn't understand what it's doing. It might be a stepping stone towards AGI, but I'm a bit bemused by anyone claiming that it has anything like the reasoning skills of a human. That is far from the impression I get, even though I find it a useful tool.
  - p1esk 3y ago
    OK, you have a point. But, if you replace "GPT-4" with "an average human" in your response - it still makes sense.
    - YeGoblynQueenne 3y ago
      When you ask a question of "an average human", they will reply with a sentence answering your question, or maybe asking for clarifications, etc. When you ask a question of GPT-4, it generates one token. One. Token. One token, that is not an answer to your question, that is not asking for clarifications, that is not trying to reason about your question, or how to answer it, because it's just one token. One. Token. For example, say you ask: "What is the sieve of Eratosthenes? Speak in chicken". Then GPT-4 will answer with something like: Chicken You don't see that because you don't interact with the GPT-4 model directly. You interact with ChatGPT, a "wrapper" around GPT-4, that takes your prompt, passes it to the model, then takes the token returned by the model and decides what to do with it. In the example above, ChatGPT will take the " Chicken" token generated by GPT-4 and append it to your question: What is the sieve of Eratosthenes? Speak in chicken. Chicken Then it will send this new string back to the model, which will generate a new token: chicken And then it will go like this: Iteration 2: What is the sieve of Eratosthenes? Speak in chicken. Chicken chicken ... Iteration k: What is the sieve of Eratosthenes? Speak in chicken. Chicken chicken chicken chicken chicken chicken chicken chicken chicken chicken ... At no point is GPT-4 trying to reason about your question, or try to answer your question, or do anything else than generate one. token. at a time. There's no thinking, no reasoning, no calculation, no logic, no deduction, no intelligence, no anything. It's only token, token, token. Chicken, chicken, chicken. And do you know when the chickens stop? When GPT-4 generates a special and magickal token, called a stop-token (or a "stop sequence" in OpenAI docs). That's a token, not found in the training corpus, added to the end of every string during tokenisation. That's how ChatGPT knows to stop sending back your prompt + generated tokens, to the model. It can't look back to what GPT-4 has generated so far, because it doesn't understand any of that. Because it doesn't understand anything, and therefore cannot reason about your question, or realise it has answered it. It cannot do anything except a) ask GPT-4 to generate another token or b) stop asking for more tokens. "What is the sieve of Eratosthenes? Speak in chicken". Chicken, chicken, chicken, chicken, .... chicken, stop_token! No more chickens. And that's how GPT-4 explains what the Seive of Eratosthenes is, but in chicken. So what you see as a user is like watching a movie where a plate of spaghetti is flying through the air, lands on a table cloth, the tablecloth lands on a table, the table lands on the floor, four chairs land around it and suddendly there's people in the chairs eating the spaghetti. It's not that someone has figured out how to reverse time: it's a recording, played backwards. It looks like things are going backwards, but they're not. It looks like ChatGPT is answering your questions, but it's not. It looks like ChatGPT is interacting with you, but it's not. It's a magick trick.
- AdieuToLogic 3y ago
  > GPT-4 is better at reasoning than 90% of humans. At least. This makes as much sense as me asserting a binary search can tell one why they are looking for what they want. That is to say, it cannot.
- croes 3y ago
  >GPT-4 is better at reasoning than 90% of humans. Even for obviously nonsens that 90% of humans would recognice as such.
- afarviral 3y ago
  I intuit the same given the jumps we've seen from gpt 3.5 fo 4. The next jump will feature considerably more general intelegence than any one human being, though I think it will have certain weaknesses.

GPT-4 is better at reasoning than 90% of humans. At least. I won't be surprised if GPT-5 is better than 100% of humans. I'm saying this in complete seriousness.

chimpanzee 3y ago
Do you put yourself in the 10% or the 90%? I’m asking in complete seriousness.
- deleted 3y ago
  [deleted]
- p1esk 3y ago
  Oh it's definitely better than me at reasoning. I'm the one asking it to explain things to me, not the other way around.
  - krainboltgreene 3y ago
    If you think it's better than you at reasoning then you cannot at all be confident in the truth of it's dialog.
    - p1esk 3y ago
      I am not. I treat it as I'd treat any smart human being.
      - AdieuToLogic 3y ago
        LLM's are not a "smart human being." They are predictive statistical models capable of producing results based on training data. LLM's do not think. LLM's are algorithms.
        int_19h 3y ago
        Your brain is also basically an algorithm that produces results based on training data. It's just a much more complicated and flexible one.
        runlaszlorun 3y ago
        But it’s also based on neurons with far more complex behavior than artificial neurons and also has other separate dynamic systems involving neurochemicals, various effects across the nervous system and the rest of the body (the gut becoming seemingly more and more relevant), various EEG patterns, and most likely quantum effects. I personally wouldn’t rule out that it can’t be emulated in a different substrate, but I think calling it “an algorithm” is to def stretch and misapply the usefulness of the term.
        int_19h 3y ago
        If it performs a computation, it is by definition running some algorithm regardless of how it's implemented in hardware / wetware. How is it a stretch? The only way our brains could be not algorithmic is if something like soul is a real thing that actually drives our intelligence.
        YeGoblynQueenne 3y ago
        Why? Rain is not algorithmic, clouds are not algorithmic, waves in the sea are not algorithmic, yet they are entirely physical processes that have nothing to do with souls.
        int_19h 3y ago
        None of these are computational processes, unlike intelligence. Unless you're trying to argue that intelligence isn't, either?
        YeGoblynQueenne 3y ago
  - chimpanzee 3y ago
    Ah ok. Here you use the word “explain” which implies more of a descriptive, reducing action rather than extrapolative and constructive. As in, it can explain what it has “read” (and it has obviously “read” far more than any human), but it can’t necessarily extrapolate beyond that or use that to find new truths. To me reasoning is more about the extrapolative, truth-finding process, ie “wisdom” from knowledge rather than just knowledge. But maybe my definition of “reasoning” isn’t quite right. Edit: I probably should define reasoning as solely “deductive reasoning”, in which case, perhaps it is better than humans. But that seems like a premature claim. On the other hand, non-deductive reasoning, I have yet to see from it. I personally can’t imagine how it could do so reliably (from a human perspective) without real-world experiences and perceptions. I’m the sort that believes a true AGI would require a highly-perceptual, space-occupying organ. In other words it would have to be and “feel” embodied, in time and space, in order to perform other forms of reasoning.
    - p1esk 3y ago
      Why don't you suggest an example we can run and see what it's capable of (compared to what I, or other humans, are capable of)?
      - chimpanzee 3y ago
        (In case it was missed, I’ve added a relevant addendum to my previous comment.) Not sure an example is needed because I agree it “explains” better than pretty much everyone. (From my mostly lay perspective) It essentially uses the prompt as an argument in a probabilistic analysis of its incredibly vast store of prior inputs to transform them into an output that at least superficially satisfies the prompter’s goals. This is cool and useful, to say the least. But this is only one kind of reasoning. A machine without embodied perceptual experiences simply cannot reason to the full-extent of a human. (It’s also worth remembering that the prompter (very likely) has far less knowledge of the domain of interest and far less skill with the language of communication, so the prompter is generally quite easily impressed regardless of the truth of the output. Nothing wrong with that necessarily, especially if it is usually accurate. But again, worth remembering.)
chimprich 3y ago
Google search is better than reasoning than most humans - in that if you search for an explanation of something then Google's first result is often correct, or one of the following ones. GPT-4 will often come up with a solution to a problem, but only if it has learnt something similar (it's better than Google in some respects: it can extract and combine abstractions). However, both need handholding by a human (supplying the initiative and directing around mistakes). If GPT-4 can't intuit an answer then it just goes in circles. It can't reason its way through a novel problem. If you start questioning it then it's clear that it doesn't understand what it's doing. It might be a stepping stone towards AGI, but I'm a bit bemused by anyone claiming that it has anything like the reasoning skills of a human. That is far from the impression I get, even though I find it a useful tool.
- p1esk 3y ago
  OK, you have a point. But, if you replace "GPT-4" with "an average human" in your response - it still makes sense.
  - YeGoblynQueenne 3y ago
    When you ask a question of "an average human", they will reply with a sentence answering your question, or maybe asking for clarifications, etc. When you ask a question of GPT-4, it generates one token. One. Token. One token, that is not an answer to your question, that is not asking for clarifications, that is not trying to reason about your question, or how to answer it, because it's just one token. One. Token. For example, say you ask: "What is the sieve of Eratosthenes? Speak in chicken". Then GPT-4 will answer with something like: Chicken You don't see that because you don't interact with the GPT-4 model directly. You interact with ChatGPT, a "wrapper" around GPT-4, that takes your prompt, passes it to the model, then takes the token returned by the model and decides what to do with it. In the example above, ChatGPT will take the " Chicken" token generated by GPT-4 and append it to your question: What is the sieve of Eratosthenes? Speak in chicken. Chicken Then it will send this new string back to the model, which will generate a new token: chicken And then it will go like this: Iteration 2: What is the sieve of Eratosthenes? Speak in chicken. Chicken chicken ... Iteration k: What is the sieve of Eratosthenes? Speak in chicken. Chicken chicken chicken chicken chicken chicken chicken chicken chicken chicken ... At no point is GPT-4 trying to reason about your question, or try to answer your question, or do anything else than generate one. token. at a time. There's no thinking, no reasoning, no calculation, no logic, no deduction, no intelligence, no anything. It's only token, token, token. Chicken, chicken, chicken. And do you know when the chickens stop? When GPT-4 generates a special and magickal token, called a stop-token (or a "stop sequence" in OpenAI docs). That's a token, not found in the training corpus, added to the end of every string during tokenisation. That's how ChatGPT knows to stop sending back your prompt + generated tokens, to the model. It can't look back to what GPT-4 has generated so far, because it doesn't understand any of that. Because it doesn't understand anything, and therefore cannot reason about your question, or realise it has answered it. It cannot do anything except a) ask GPT-4 to generate another token or b) stop asking for more tokens. "What is the sieve of Eratosthenes? Speak in chicken". Chicken, chicken, chicken, chicken, .... chicken, stop_token! No more chickens. And that's how GPT-4 explains what the Seive of Eratosthenes is, but in chicken. So what you see as a user is like watching a movie where a plate of spaghetti is flying through the air, lands on a table cloth, the tablecloth lands on a table, the table lands on the floor, four chairs land around it and suddendly there's people in the chairs eating the spaghetti. It's not that someone has figured out how to reverse time: it's a recording, played backwards. It looks like things are going backwards, but they're not. It looks like ChatGPT is answering your questions, but it's not. It looks like ChatGPT is interacting with you, but it's not. It's a magick trick.
AdieuToLogic 3y ago
> GPT-4 is better at reasoning than 90% of humans. At least. This makes as much sense as me asserting a binary search can tell one why they are looking for what they want. That is to say, it cannot.
croes 3y ago
>GPT-4 is better at reasoning than 90% of humans. Even for obviously nonsens that 90% of humans would recognice as such.
afarviral 3y ago
I intuit the same given the jumps we've seen from gpt 3.5 fo 4. The next jump will feature considerably more general intelegence than any one human being, though I think it will have certain weaknesses.