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[Edit: The reply below is a better response from someone who knows more of the specifics than I do, link: https://news.ycombinator.com/item?id=24285024 https://

[Edit: The reply below is a better response from someone who knows more of the specifics than I do, link: https://news.ycombinator.com/item?id=24285024 https://news.ycombinator.com/item?id=24285024] While it could be memorization, their testing seem to imply something else is going on. Particularly because they excluded the exact examples they tested from the training data (to try and test if it was memorization). Since gpt-3 could solve some arithmetic even without those exact example test cases in the training data, it seems more likely to me that it's not simply memorization. It might be that it has some incomplete idea of the underlying rules, and therefore makes mistakes. A child that is learning addition will have a harder time with larger numbers and make more mistakes too. It'll be interesting to see if continuing to scale up the model improves things or not. > "In fact, it is absolutely the case that if a system needs to see "enormous" amounts of examples before it can "deduce the underlying rules" (of arithmetic) then GPT-3 can't do that, because there simply aren't enough examples of such operations (between one- and two-digit numbers)." I don't know if this is true. It depends on 'enormous' and it depends on how many examples are required to deduce how math works from trying to predict what's next. I don't think anyone actually knows the answer to this yet?

YeGoblynQueenne 6y ago
>> A child that is learning addition will have a harder time with larger numbers and make more mistakes too. GPT-3 is not a child. GPT-3 is a language model and language models are systemst that predict the next token that follows from a sequence of tokens. A system like that can give correct answers to arithmetic problems it has seen already and often, without having to learn what a child would learn when learning arithmetic. A system like that can also give incorrect answers to arithmetic problems it has not seen already, or hasn't seen often enough and that will be for reasons very different than the reasons that a child will give incorrect answers to the same problem. In general, we don't have to know anything about how children learn arithmetic to know how GTP-3 answers arithmetic problems, it suffices to know how language models work.
- fossuser 6y ago
  Did you ignore everything else in my comment except that example? I don't think additional conversation will be productive. The point is success on small numbers and more mistakes on larger numbers would be what I would predict both if results were memorized and if it had deduced some incomplete model of how to do basic arithmetic. Not having the examples in the training data is a point in favor of understanding the underlying rules and a point against memorization. > "GPT-3 is not a child. GPT-3 is a language model" Yes - thanks for the obvious condescension.
  - YeGoblynQueenne 6y ago
    I'm sorry if my comment came across as condensending. That was not my intention. I addressed the other points in your commment in my much longer comment above. To be honest, I assumed you were making an anthropomorphising comment, suggesting that GPT-3 learns like a child would learn. Sorry if that wasn't what you meant. I'm used to seeing comments like that (on HN in particular) so I guess I jumped to conclusions. Anyway I guess I took your comment about not reading linked papers personally and you took my comment about GPT-3 not being a child personally. And the other poster pounced on my comment as if they had something to win and I reacted to it angrily. This is not a very good conversation and I haven't done my due dillience to keep it civil. I'm sorry we couldn't have a very constructive conversation this time. Maybe next time.
    - fossuser 6y ago
      No worries, on re-read I think I might have just interpreted things as more hostile than they were intended. I do suspect that you may be too quick to draw the memorization conclusion because you find the other one too unlikely. I think you're setting the evidence barrier too high/dismissing evidence in favor of the conclusion you already believe to be true while not holding the memorization hypothesis to the same bar (rather than recognizing that the evidence suggests maybe something interesting is going on). Either way, when things scale up we should be able to see what ends up happening.

YeGoblynQueenne 6y ago

>> A child that is learning addition will have a harder time with larger numbers and make more mistakes too. GPT-3 is not a child. GPT-3 is a language model and language models are systemst that predict the next token that follows from a sequence of tokens. A system like that can give correct answers to arithmetic problems it has seen already and often, without having to learn what a child would learn when learning arithmetic. A system like that can also give incorrect answers to arithmetic problems it has not seen already, or hasn't seen often enough and that will be for reasons very different than the reasons that a child will give incorrect answers to the same problem. In general, we don't have to know anything about how children learn arithmetic to know how GTP-3 answers arithmetic problems, it suffices to know how language models work.

fossuser 6y ago
Did you ignore everything else in my comment except that example? I don't think additional conversation will be productive. The point is success on small numbers and more mistakes on larger numbers would be what I would predict both if results were memorized and if it had deduced some incomplete model of how to do basic arithmetic. Not having the examples in the training data is a point in favor of understanding the underlying rules and a point against memorization. > "GPT-3 is not a child. GPT-3 is a language model" Yes - thanks for the obvious condescension.
- YeGoblynQueenne 6y ago
  I'm sorry if my comment came across as condensending. That was not my intention. I addressed the other points in your commment in my much longer comment above. To be honest, I assumed you were making an anthropomorphising comment, suggesting that GPT-3 learns like a child would learn. Sorry if that wasn't what you meant. I'm used to seeing comments like that (on HN in particular) so I guess I jumped to conclusions. Anyway I guess I took your comment about not reading linked papers personally and you took my comment about GPT-3 not being a child personally. And the other poster pounced on my comment as if they had something to win and I reacted to it angrily. This is not a very good conversation and I haven't done my due dillience to keep it civil. I'm sorry we couldn't have a very constructive conversation this time. Maybe next time.
  - fossuser 6y ago
    No worries, on re-read I think I might have just interpreted things as more hostile than they were intended. I do suspect that you may be too quick to draw the memorization conclusion because you find the other one too unlikely. I think you're setting the evidence barrier too high/dismissing evidence in favor of the conclusion you already believe to be true while not holding the memorization hypothesis to the same bar (rather than recognizing that the evidence suggests maybe something interesting is going on). Either way, when things scale up we should be able to see what ends up happening.