[ExI] Bender's Octopus (re: LLMs like ChatGPT)

[Jason Resch]

On Thu, Mar 23, 2023, 8:22 PM Gordon Swobe via extropy-chat <
extropy-chat at lists.extropy.org> wrote:

> On Thu, Mar 23, 2023 at 5:23 PM spike jones via extropy-chat <
> extropy-chat at lists.extropy.org> wrote:
>
> > I really don’t think it thinks, but it makes us think it thinks.
> ChatGPT is wicked cool.
>
> I agree 100%. Also, like Bender and the other author of this paper, I
> object to the language I often see in discussions like these we have on ExI
> about these subjects.
>
> quoted the paper cited in a previous message and below:
>
> --
> "Large LMs: Hype and analysis
> Publications talking about the application of large LMs to
> meaning-sensitive tasks tend to describe the models with terminology that,
> if interpreted at face value, is misleading. Here is a selection from
> academically-oriented pieces (emphasis added):
>
> (1) In order to train a model that *understands* sentence relationships,
> we pre-train for a binarized next sentence prediction task. (Devlin et al.,
> 2019)
>
> (2) Using BERT, a pretraining language model, has been successful for
> single-turn machine *comprehension*. . .(Ohsugi et al., 2019)
>
> (3) The surprisingly strong ability of these models to *re-call factual
> knowledge* without any fine-tuning demonstrates their potential as
> unsupervised open-domain QA systems. (Petroni et al., 2019)--
>
> In linguistics and epistemology and in philosophy in general, usually
> terms like "understand" and "comprehend" and "recall factual knowledge"
> have meanings that are not applicable to these languuge models. They do not
> actually comprehend or understand anything whatosever. They only make us
> think they do.
>
>
> https://docslib.org/doc/6282568/climbing-towards-nlu-on-meaning-form-and-understanding-in-the-age-of-data
>

If that's true how do I know anyone else on this list is actually
comprehending or understanding anything?

Jason




>
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