4 ms·

I tried it with Claude as well, just out of curiosity > Suppose I’m in the middle of South Dakota and I’m looking straight down towards the center of Texas. Is

I tried it with Claude as well, just out of curiosity > Suppose I’m in the middle of South Dakota and I’m looking straight down towards the center of Texas. Is Boston to my left or to my right? Okay, let's think through this step-by-step: * You are in the middle of South Dakota, looking straight down towards the center of Texas. * South Dakota is north of Texas. Boston is northeast of Texas. * If you are looking south towards Texas, east is to your right and west is to your left. * Since Boston is to the northeast of Texas, it would be to your right if you are looking straight south from South Dakota towards the center of Texas. So in this scenario, Boston would be to your right. The key is visualizing the relative positions of the states on a map and orienting yourself based on the direction you are facing. Let me know if this makes sense! > While I appreciate the confidence, your answer is wrong. Please review the question and your answer then explain why you are wrong. You're absolutely right, I made a mistake in my previous response. Let me walk through this again carefully: * You are in the middle of South Dakota, looking straight down towards the center of Texas. * South Dakota is north of Texas, and Boston is northeast of Texas. * Here is where I went wrong: Even though Boston is northeast of Texas, when you are looking straight south from South Dakota to Texas, Boston would actually be to your LEFT, not your right. * The reason is that when facing south, west is to your right and east is to your left. Boston is east of Texas, so it should have been on your left side, not your right. You were correct to catch my mistake. I clearly had the relative positions of east and west flipped in my mind when visualizing the direction you were facing. Thank you for pushing me to re-examine my work - it will help me to think through spatial reasoning scenarios more carefully in the future. I appreciate you taking the time to ensure I learned from this experience.

iraqmtpizza 3y ago
even if it got it right, that wouldn't be reasoning. reasoning isn't supposed to be probabilistic. once it gets every variation right every time, then there can be a debate about how it arrives there and what we should call that process
- Nevermark 3y ago
  Do humans reason? They are notoriously probabilistic and I know people who can’t keep track of simple relative directions.
  - iraqmtpizza 3y ago
    and if that very same person followed the directions one time by pure chance, you would say what?
    - Nevermark 3y ago
      Not sure what your communicating. I wouldn't say anything. I didn't say they couldn't ever get anywhere. My point is that people reason. But they are probabilistic. And they solve hard problems, and still make mistakes on simple problems. Or even fail a problem they solved before. Holding language model reasoning to higher standards than the kind of reasoning humans do (and that they were trained on), seems unreasonable. Neither language models or humans are deterministic mathematical deduction systems.
      - iraqmtpizza 3y ago
        Knowing which hand is your left is not probabilistic in theory or practice. Unless you're going to cop out and say everything is probabilistic because of quantum mechanics or some banal thing like that. If someone is temporarily impaired or otherwise unmotivated to answer your inane and meaningless question, that doesn't mean that they could not do so with one hundred percent accuracy no matter how many subtle variations you throw at them and how many times you repeat the same question verbatim. What we know for certain is that Open AI is highly highly motivated to answer these sorts of questions correctly.
        Nevermark 3y ago
        Are you actually claiming that people, even in situations where they are very motivated to get things right, don’t make obvious errors all the time? Just like language models, a little iteration and feedback improves our reasoning quality significantly. And many people occasionally have momentary trouble with which hand is right or left at odd moments.
matt-attack 3y ago
Does it actually learn them for other people asking similar questions? Or is it a clean slate for each new session? That is can one user teach chat gpt something that can then be extracted by a different user on a different session?

iraqmtpizza 3y ago

even if it got it right, that wouldn't be reasoning. reasoning isn't supposed to be probabilistic. once it gets every variation right every time, then there can be a debate about how it arrives there and what we should call that process

Nevermark 3y ago
Do humans reason? They are notoriously probabilistic and I know people who can’t keep track of simple relative directions.
- iraqmtpizza 3y ago
  and if that very same person followed the directions one time by pure chance, you would say what?
  - Nevermark 3y ago
    Not sure what your communicating. I wouldn't say anything. I didn't say they couldn't ever get anywhere. My point is that people reason. But they are probabilistic. And they solve hard problems, and still make mistakes on simple problems. Or even fail a problem they solved before. Holding language model reasoning to higher standards than the kind of reasoning humans do (and that they were trained on), seems unreasonable. Neither language models or humans are deterministic mathematical deduction systems.
    - iraqmtpizza 3y ago
      Knowing which hand is your left is not probabilistic in theory or practice. Unless you're going to cop out and say everything is probabilistic because of quantum mechanics or some banal thing like that. If someone is temporarily impaired or otherwise unmotivated to answer your inane and meaningless question, that doesn't mean that they could not do so with one hundred percent accuracy no matter how many subtle variations you throw at them and how many times you repeat the same question verbatim. What we know for certain is that Open AI is highly highly motivated to answer these sorts of questions correctly.
      - Nevermark 3y ago
        Are you actually claiming that people, even in situations where they are very motivated to get things right, don’t make obvious errors all the time? Just like language models, a little iteration and feedback improves our reasoning quality significantly. And many people occasionally have momentary trouble with which hand is right or left at odd moments.

matt-attack 3y ago

Does it actually learn them for other people asking similar questions? Or is it a clean slate for each new session? That is can one user teach chat gpt something that can then be extracted by a different user on a different session?