3 ms·

>but nothing so bizzare it needs to be "explained". It's not bizarre and I've already explained it: ChatGPT has no understanding of the rules that it communica

>but nothing so bizzare it needs to be "explained". It's not bizarre and I've already explained it: ChatGPT has no understanding of the rules that it communicates so perfectly. We've openly observed it in its errors. You just responded with another denial of that obvious fact, but you're now acknowledging that "GPT-4 can't play chess. It's that simple". So you've essentially agreed with what I've said, except to say you don't agree, but that you prefer no explanation to the obvious one. I'm not quite sure what to do with that. >A plane isn't "simulating flight". It flies. Respectfully, that is another irrelevant analogy. >You want to believe in an imaginary distinguisher that's so important but can't be tested for and it's silly. This entire discussion is about the distinguisher, so I wouldn't classify it as imaginary. You just keep repeating that it doesn't mean anything. But, I do agree that a model can be trained to a sufficient degree that its ability to demonstrate understanding is immaterial in effect from actual understanding. I also agree that this discussion has veered into silly territory. I clearly am not getting the point across, so I will respectfully thank you for the engagement. But, even ChatGPT will tell you that it doesn't "understand" in the traditional sense. That it essentially finds patterns, etc. So perhaps it will convince you where I could not. :) Thanks again for the discussion.

famouswaffles 3y ago
>ChatGPT has no understanding of the rules that it communicates so perfectly. Right >So you've essentially agreed with what I've said, except to say you don't agree, but that you prefer no explanation to the obvious one. I never disagreed that 4 can't play chess. It's right in my first comment. I literally say LLMs can play chess and you just tested a model that couldn't. >This entire discussion is about the distinguisher, so I wouldn't classify it as imaginary. You just keep repeating that it doesn't mean anything. >But, I do agree that a model can be trained to a sufficient degree that its ability to demonstrate understanding is immaterial in effect from actual understanding. You're still making the same mistake here. If a scientist happens upon a piece of yellow metal and runs every gold test there is on the metal and it passes then that is gold. What you are doing here is essentially saying that it is "fake gold that is immaterial in effect from real gold". It's just kind of a meaningless statement. The only thing any human does is "demonstrate understanding". I can't peek into your brain and say you understand. You can't prove to me right now that you "actually understand".If I think you understand it's because I say you demonstrated it. There is no "actual understanding" separate from demonstrating it. >But, even ChatGPT will tell you that it doesn't "understand" in the traditional sense. That it essentially finds patterns, etc. So perhaps it will convince you where I could not. :) Either GPT doesn't understand what it's saying and this holds no importance or it does. You have to pick one. I could just as soon go to Claude to have this discussion and get different answers. Open AI obviously train it on how they want it to respond to this sort of questions.
- unclebucknasty 3y ago
  >What you are doing here is essentially saying that it is "fake gold that is immaterial in effect from real gold I've agreed that there can be the effect of an immaterial difference in a given context or application. For instance, if I'd stopped at asking ChatGPT about the rules, then it wouldn't have mattered that it couldn't employ them properly. But, that's context-dependent (e.g. when I asked it to play, it did matter and the difference was no longer immaterial). In your gold analogy, it's either gold or it's not. If our tests couldn't distinguish it, then it doesn't change the fact of what it is. It just represents a shortcoming in our ability to discern. If it had the same conductive properties as gold such that it could be used in applications that required those properties, then there's no material difference in that application. But, if we later find that it wears out twice as fast, then we realize it's not gold and the difference becomes material. But, here's the key piece you're missing: even if we never find a demonstrable difference in the metal, it doesn't change what it is. That is, even if the difference is immaterial for any application or test we can devise, the facts don't change. You can argue that if the difference never becomes material then it doesn't matter. Maybe. But, that's not a practical way to approach AI, as it leaves open the possibility that it fails in unexpected ways. So, in the case of LLMs, I think it matters. Massively. In how we approach it, use it, train it, understand its limitations, our expectations, etc. But, I'm not making that argument. >Either GPT doesn't understand what it's saying and this holds no importance or it does. You have to pick one No. We've already agreed that GPT can get facts right. You're kind of going backwards on me. At the bottom of it, we agree that GPT-4 can cite the rules, but can't play chess (i.e. use its facts). I believe that reveals how these models work WRT to reasoning and understanding. You disagree (or think it's immaterial). So, we draw different conclusions from the same information. Not unprecedented in human history!

famouswaffles 3y ago

>ChatGPT has no understanding of the rules that it communicates so perfectly. Right >So you've essentially agreed with what I've said, except to say you don't agree, but that you prefer no explanation to the obvious one. I never disagreed that 4 can't play chess. It's right in my first comment. I literally say LLMs can play chess and you just tested a model that couldn't. >This entire discussion is about the distinguisher, so I wouldn't classify it as imaginary. You just keep repeating that it doesn't mean anything. >But, I do agree that a model can be trained to a sufficient degree that its ability to demonstrate understanding is immaterial in effect from actual understanding. You're still making the same mistake here. If a scientist happens upon a piece of yellow metal and runs every gold test there is on the metal and it passes then that is gold. What you are doing here is essentially saying that it is "fake gold that is immaterial in effect from real gold". It's just kind of a meaningless statement. The only thing any human does is "demonstrate understanding". I can't peek into your brain and say you understand. You can't prove to me right now that you "actually understand".If I think you understand it's because I say you demonstrated it. There is no "actual understanding" separate from demonstrating it. >But, even ChatGPT will tell you that it doesn't "understand" in the traditional sense. That it essentially finds patterns, etc. So perhaps it will convince you where I could not. :) Either GPT doesn't understand what it's saying and this holds no importance or it does. You have to pick one. I could just as soon go to Claude to have this discussion and get different answers. Open AI obviously train it on how they want it to respond to this sort of questions.

unclebucknasty 3y ago
>What you are doing here is essentially saying that it is "fake gold that is immaterial in effect from real gold I've agreed that there can be the effect of an immaterial difference in a given context or application. For instance, if I'd stopped at asking ChatGPT about the rules, then it wouldn't have mattered that it couldn't employ them properly. But, that's context-dependent (e.g. when I asked it to play, it did matter and the difference was no longer immaterial). In your gold analogy, it's either gold or it's not. If our tests couldn't distinguish it, then it doesn't change the fact of what it is. It just represents a shortcoming in our ability to discern. If it had the same conductive properties as gold such that it could be used in applications that required those properties, then there's no material difference in that application. But, if we later find that it wears out twice as fast, then we realize it's not gold and the difference becomes material. But, here's the key piece you're missing: even if we never find a demonstrable difference in the metal, it doesn't change what it is. That is, even if the difference is immaterial for any application or test we can devise, the facts don't change. You can argue that if the difference never becomes material then it doesn't matter. Maybe. But, that's not a practical way to approach AI, as it leaves open the possibility that it fails in unexpected ways. So, in the case of LLMs, I think it matters. Massively. In how we approach it, use it, train it, understand its limitations, our expectations, etc. But, I'm not making that argument. >Either GPT doesn't understand what it's saying and this holds no importance or it does. You have to pick one No. We've already agreed that GPT can get facts right. You're kind of going backwards on me. At the bottom of it, we agree that GPT-4 can cite the rules, but can't play chess (i.e. use its facts). I believe that reveals how these models work WRT to reasoning and understanding. You disagree (or think it's immaterial). So, we draw different conclusions from the same information. Not unprecedented in human history!