Comment by pessimizer
4 years ago
> Current AI models are not "just sort of repeating and copying from memory". This is just an incorrect characterization of how they work and how they perform.
You say this, but don't explain how. Because this is exactly what they are doing.
> AI skeptics often say things like this
I'm not really an AI skeptic. I think that we're very close to AI being indistinguishable from people. There are clearly problems that need to be solved, but I think the hardest problem was accepting the fact that humans are largely just copying and realizing that would be enough to get you 97% of the way there, especially if you gave a machine far more to copy than a human could consume.
> then backpedal with something like "Well they aren't really repeating what they heard, but their generative model is just a slightly more sophisticated version of repeating what they've heard." But this weaker claim is also true of humans. It's certainly the case that >97% percent of what humans say is "just repeating and copying" in the same sense.
Maybe I'm not expressing myself clearly, but it seems that you're just repeating my comment with a sneer. Agreeing angrily?
I'm disagreeing with the language you are using to characterize models. "copying from memory" implies that there is something being copied, and a memory that you are copying it from. I am pointing out that LLMs do not do this. It's not how they work.
If you polled 1M random English speakers randomly and asked them whether or not a system that "just sort of repeating and copying from memory" could produce completely novel answers in response to completely novel questions, I suspect that the overwhelming majority would respond by saying no.
Similarly if you asked 1000 people working on LLMs whether they work by "copying from memory", I suspect nearly all would say no. It would be accurate to say they are "generating text via a probabilistic model of language, which is encoded in the weights of a neural network", but there really is just no sense in which the models are "copying" anything.
That being said, these models do "copy" some text in the sense that they can reconstruct some strings from their training input. For example every LLM I have played with can recite the first few paragraphs of A Tale of Two Cities verbatim. But that's a capability they have _in spite of_ their actual design, not because of it.
> I'm disagreeing with the language you are using to characterize models. "copying from memory" implies that there is something being copied, and a memory that you are copying it from. I am pointing out that LLMs do not do this. It's not how they work.
Then we're arguing about the semantics of the word "copy." That is not an interesting argument when you know exactly what I mean and can express it clearly.
edit: If it helps, either substitute your description in whenever I say 'pretty much copy' or change the word "copy" to whatever word you want to use. But even though I can't reproduce the opening paragraph to A Tale of Two Cities verbatim, I can certainly write something that is "copying" it without doing that, and anyone who was familiar with the book and read my paragraph would agree with me.
It is semantics, but that was your whole point no?
> That's because they're not modelling anything
If we agree on "how LLMs work", then how can you claim that they aren't modeling anything? They are modeling language, and while it's unlikely current paradigms will be proving new mathematical truths, it's completely plausible to me that bigger models will be able to handle simple math word problems like those in the article, precisely because LLMs can model the "Alice", "Apple", and "Bob" entities.
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The memory is the model. Having high probability to a particular area in latent space is copying it from the memory of the training data.
You're a massive pedant, and this style of comment is a large reason HN comment sections are a pain to read.
What is the difference between this and describing a human brain the same way? The brain is the model, you are "just" copying things from the memory of your brain to words that you speak or write?
I don't think it's pedantic to say that an argument is wrong because it's making an incorrect claim. The claim here is that there is something different or missing between a true "model" and LLMs, and that missing thing has something to do with "copying". But that's not true, the missing thing is the complexity of the table, or the size of the table. The fact that it's copying in some incredibly abstract sense doesn't matter.
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