Thanks, it’s really valuable to untangle these separate claims, and I mostly agree with the taxonomy. That said, my impressions are different in a few places:
First, I don’t see any reason to believe that ‘Stochastic Parrots’ (SP) is arguing that LLMs are equivalent to Markov chains. I take them to be making the related but weaker claim that (pretraining-only) LLMs are solely ‘predicting the likelihood of a token (character, word or string) given...its preceding context’. They talk about there being ‘big steps’ from n-gram models to word vectors to transformers, so they clearly understand that there are important differences. This weaker claim just seems correct, although it no longer applies to models that have undergone post-training.
Second, I think you’re missing one important member of the SP bestiary: connection to an external referent, typically something in the physical world (sometimes called ‘grounding’). We see this clearly in the catapult and bear examples in ‘Climbing Toward NLU’ (by far the more interesting paper in my opinion; it’s a shame that SP was the one to go viral). Common variants are claims that LLMs can’t possibly understand language because they’re not embodied, or because they don’t have senses[1]. This is sometimes paired with the argument that meaning and understanding require embeddedness in a social context, but I think they’re importantly different.
Third, there’s an interesting distinction that I think is prior to this taxonomy: whether a particular claim is descriptive or prescriptive. We see this with the social argument as expressed in SP: ‘human communication relies on the interpretation of implicit meaning conveyed between individuals.’ There’s a reasonable, descriptive version of this claim: prior to LLMs, linguists theorized that language understanding could only meaningfully occur between speakers embedded in a shared social context. LLMs have provided evidence that this theoretical claim is wrong, and reasonable linguists have presumably updated accordingly. There’s also a less reasonable prescriptive version of the claim, under which LLMs are definitionally incapable of language use, and no evidence of capability can show otherwise[2]. You mostly bundle these latter views into the taxonomy as ‘spiritual SP’, but I think this distinction is one level below the taxonomy.
Again, I’m only arguing about specific aspects because I think you’ve basically gotten it right and are doing valuable work (I’ve had vague ambitions of trying to more clearly lay SP to rest, but I think you’ve now basically handled that). Thanks for the post!
A more sophisticated argument that’s related but not really part of this one, and not quite an SP argument, is the claim that understanding causality requires embodiment in the sense of the ability to experiment by intervening in causal chains, and can’t be done solely from static data.
As LLMs have continued to demonstrate capabilities that skeptics didn’t expect[3], I think we’ve seen skeptics increasingly shift to the prescriptive versions of their claims.
My favorite example is in ‘Climbing Toward NLU’, actually, which claims that correctly completing the sentence Three plus five equals is beyond the capability of ‘any pure LM’. Goalposts have since shifted slightly.
Thanks, it’s really valuable to untangle these separate claims, and I mostly agree with the taxonomy. That said, my impressions are different in a few places:
First, I don’t see any reason to believe that ‘Stochastic Parrots’ (SP) is arguing that LLMs are equivalent to Markov chains. I take them to be making the related but weaker claim that (pretraining-only) LLMs are solely ‘predicting the likelihood of a token (character, word or string) given...its preceding context’. They talk about there being ‘big steps’ from n-gram models to word vectors to transformers, so they clearly understand that there are important differences. This weaker claim just seems correct, although it no longer applies to models that have undergone post-training.
Second, I think you’re missing one important member of the SP bestiary: connection to an external referent, typically something in the physical world (sometimes called ‘grounding’). We see this clearly in the catapult and bear examples in ‘Climbing Toward NLU’ (by far the more interesting paper in my opinion; it’s a shame that SP was the one to go viral). Common variants are claims that LLMs can’t possibly understand language because they’re not embodied, or because they don’t have senses[1]. This is sometimes paired with the argument that meaning and understanding require embeddedness in a social context, but I think they’re importantly different.
Third, there’s an interesting distinction that I think is prior to this taxonomy: whether a particular claim is descriptive or prescriptive. We see this with the social argument as expressed in SP: ‘human communication relies on the interpretation of implicit meaning conveyed between individuals.’ There’s a reasonable, descriptive version of this claim: prior to LLMs, linguists theorized that language understanding could only meaningfully occur between speakers embedded in a shared social context. LLMs have provided evidence that this theoretical claim is wrong, and reasonable linguists have presumably updated accordingly. There’s also a less reasonable prescriptive version of the claim, under which LLMs are definitionally incapable of language use, and no evidence of capability can show otherwise[2]. You mostly bundle these latter views into the taxonomy as ‘spiritual SP’, but I think this distinction is one level below the taxonomy.
Again, I’m only arguing about specific aspects because I think you’ve basically gotten it right and are doing valuable work (I’ve had vague ambitions of trying to more clearly lay SP to rest, but I think you’ve now basically handled that). Thanks for the post!
A more sophisticated argument that’s related but not really part of this one, and not quite an SP argument, is the claim that understanding causality requires embodiment in the sense of the ability to experiment by intervening in causal chains, and can’t be done solely from static data.
As LLMs have continued to demonstrate capabilities that skeptics didn’t expect[3], I think we’ve seen skeptics increasingly shift to the prescriptive versions of their claims.
My favorite example is in ‘Climbing Toward NLU’, actually, which claims that correctly completing the sentence Three plus five equals is beyond the capability of ‘any pure LM’. Goalposts have since shifted slightly.