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Stochastic Parrots: Frequently Unasked Questions
31–40 of 64 posts
Re: Stochastic Parrots: Frequently Unasked Questions
#32It would have been nice to see some version of “I am very surprised by how far LLMs have come since I wrote the stochastic parrots paper, here is how I have revised my thinking.” But there is nothing like that and the author is just doubling down or trying to correct perceived “misinterpretations” of her work. Meanwhile you have multiple Fields Medalists (Tau, Gowers) saying they’re very impressed by LLMs’ mathematic…
The appeal to authority is strong here. A tool stochastic parrot can be useful too.
Re: Stochastic Parrots: Frequently Unasked Questions
#33Earlier quoted context omitted.
Perhaps actual thinking is not automatically necessary for that either! - and the LLM is proof.
Then what is thinking necessary for? Not for proving novel results; not for coding; not for writing prose; not for arguing a point; not for interpreting artworks; etc.
> not for writing prose; not for arguing a point; not for interpreting artworks
To be fair, LLMs are pretty bad at all of these. They struggle to avoid cliches and to produce prose with actual substance (below a stylistic facade that is undeniably convincing).
Re: Stochastic Parrots: Frequently Unasked Questions
#34It would have been nice to see some version of “I am very surprised by how far LLMs have come since I wrote the stochastic parrots paper, here is how I have revised my thinking.” But there is nothing like that and the author is just doubling down or trying to correct perceived “misinterpretations” of her work. Meanwhile you have multiple Fields Medalists (Tau, Gowers) saying they’re very impressed by LLMs’ mathematic…
The Parrots paper:
"Contrary to how it may seem when we observe its output, an LM is a system for haphazardly stitching together sequences of linguistic forms it has observed in its vast training data, according to probabilistic information about how they combine, but without any reference to meaning: a stochastic parrot."
So perhaps this has always been a negative claim, about what language model AI is not.
Re: Stochastic Parrots: Frequently Unasked Questions
#35I mean, we're pretty deep into Westworld/Blade Runner-style scifi at this point. It's actually a crazy, mind-bending question to try to grasp what is going on with chatclaudini at this point. Regardless of what labels we choose or properties we choose to affirm, we're far too deep into uncanny valley for it to be very helpful.
Re: Stochastic Parrots: Frequently Unasked Questions
#36Earlier quoted context omitted.
Then what is thinking necessary for? Not for proving novel results; not for coding; not for writing prose; not for arguing a point; not for interpreting artworks; etc.
> not for writing prose; not for arguing a point; not for interpreting artworks To be fair, LLMs are pretty bad at all of these. They struggle to avoid cliches and to produce prose with actual substance (below a stylistic facade that is undeniably convincing).
They struggle to avoid cliches and to produce prose with actual substance
I have bad news for you about the writings of most Ph.D.s and University professors...
Re: Stochastic Parrots: Frequently Unasked Questions
#37> Most things we historically do with computing are not well approximated by extruding synthetic text.
I don't understand this point. I feel like almost everything associated with computing is extruding synthetic text.
Re: Stochastic Parrots: Frequently Unasked Questions
#38> Another common trope in the discourse around this phrase is to claim that stochastic parrot is an insult (or even a slur). On one reading, that would require LLMs to be the kind of thing that can take or feel offense, which they clearly aren’t.
isn't that circular reasoning?
"I can call anyone not smart enough to take offense because as I said those anyone aren't smart enough to take offense"?
(also disregarding that being offended has been shifted into "protection of the (perceived) weak (or of the group of your allegiance)" rather than "protection of self" for quite some time now)
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but generally I always felt that this tension around the phrase was somewhat of perscriptive/descriptive difference, or maybe "level of detail in the model" type
just because there is knowledge of a more full understanding of the process doesn't mean other descriptions/modeling of the process are invalid or unuseful
newtonian gravity doesn't describe time dilation - and yet most of the time it is enough to use only it, so it's successfully studied in schools and undergrads
if output of LLM can be modeled (by intuition) as "some other being" for many practical uses *and model works* - then automatical blaming others for "using less precise model" and warning about it feels... strange
Re: Stochastic Parrots: Frequently Unasked Questions
#39It would have been nice to see some version of “I am very surprised by how far LLMs have come since I wrote the stochastic parrots paper, here is how I have revised my thinking.” But there is nothing like that and the author is just doubling down or trying to correct perceived “misinterpretations” of her work. Meanwhile you have multiple Fields Medalists (Tau, Gowers) saying they’re very impressed by LLMs’ mathematic…
The Parrots paper: "Contrary to how it may seem when we observe its output, an LM is a system for haphazardly stitching together sequences of linguistic forms it has observed in its vast training data, according to probabilistic information about how they combine, but without any reference to meaning: a stochastic parrot." So perhaps this has always been a negative claim, about what language model AI is not .
Maybe, but a claim about what and LLM is not is still a claim about what it can or cannot do. And specifically:
> without any reference to meaning
is vague, but I read it as actually quite a strong claim about the limitations of LLMs. I don’t think it would be possible for LLMs to do long chains of correct mathematical reasoning about novel problems that they haven’t seen before “without any reference to meaning.” That simply isn’t possible just by regurgitating and remixing random chunks of training data. Therefore I consider the stochastic parrots picture of LLMs to be wrong.
It might have been an accurate picture in 2020. It is not an accurate picture now. What is often missed in these discussions is that LLM training now looks totally different than it did a couple years ago. RLVR completely changed the game, allowing LLMs to actually do math and code well, among other things.
Re: Stochastic Parrots: Frequently Unasked Questions
#40I think "stochastic parrot" misses the mark as a characterization of LLMs, but so does "artificial intelligence." They're both somewhat helpful and somewhat misleading in complementary ways.
Maybe that's the best one can do when describing something very new and strange. A series of vivid, incompatible metaphors might be the best guide for a while. "Intelligence" as we normally understand it is a significant overstatement, while "parrot" is a massive understatement.