[ExI] GPT-4 on its inability to solve the symbol grounding problem

[Giovanni Santostasi]

*What it does, however, "know" is how these words relate statistically to
one another and in patterns in combination with other words about geometry
and drawing and so on, such that it can construct something resembling an
apple that has meaning to us.*I already gave you reasoning of why it is not
just statistical patterns. Did you follow my reasoning about how stats are
converging (after you analyze a body of text big enough you just add
decimal places to averages) and instead the capability of the LLM seems to
grow exponentially with the growth of the number of parameters they are
trained on.

Also, the idea is that meaning is based both on internal representation but
also on how we communicate with others. Yes, GPT-4 is trying to communicate
with humans so it tries to share its meaning with our meaning. But don't we
do the same? When we determine the meaning of a word, even one that may
invent (Dante invented many Italian words) we want to share it with others
and once they are shared and adopted by others then they start to mean
something. So the fact that GPT-4 tries to come up with a drawing of an
apple that has meaning to us is exactly what any artist would do to try to
communicate the meaning of its work. How can you use that against GPT-4?









On Fri, Apr 14, 2023 at 3:15 PM Gordon Swobe <gordon.swobe at gmail.com> wrote:

> On Fri, Apr 14, 2023 at 3:18 PM Giovanni Santostasi <gsantostasi at gmail.com>
> wrote:
>
>> Gordon,
>> So you got your answer.
>>
>> *Apples are generally round, sometimes with a slightly flattened top and
>> bottom. They may have a small indentation at the top, where the stem
>> connects to the fruit, and a shallow, star-shaped indentation at the
>> bottom, where the apple's calyx is located. The skin of an apple can be
>> smooth or slightly bumpy and comes in various colors, such as red, green,
>> or yellow.*How this is not understanding what the heck an apple is?
>>
>
> To know it if truly understands the shape of an apple, we need now to ask
> it what it means by "round" and "flattened" and "top" and "bottom" and
> "small indentation" and so on, which only leads to more word definitions in
> an endless search for the meanings.
>
> What it *does*, however, "know" is how these words relate statistically
> to one another and in patterns in combination with other words about
> geometry and drawing and so on, such that it can construct something
> resembling an apple that has meaning to *us*.
>
>
> -gts
>
>
>
>>>>>
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