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

[Gordon Swobe]

“5” can be expressed formally also as “V”, I meant. These symbols point to
what we really mean by 5, which is outside of the language of mathematics.
It’s the same with English words.

-gts

On Sun, Apr 16, 2023 at 9:18 PM Gordon Swobe <gordon.swobe at gmail.com> wrote:

>
>
> On Sun, Apr 16, 2023 at 7:43 PM Giovanni Santostasi <gsantostasi at gmail.com>
> wrote:
>
>>
>> *To know the difference, it must have a deeper understanding of number,
>> beyond the mere symbolic representations of them. This is to say it must
>> have access to the referents, to what we really *mean* by numbers
>> independent of their formal representations.*What are you talking about?
>>
>
>
> Talking about the distinction between form and meaning. What applies to
> words applies also to numbers. The symbolic expression “5” for example is
> distinct from what we mean by it. The meaning can be expressed formally
> also as “IV” or ”five.”
>
>
> LLMs have access to and are trained only on the formal expressions of both
> words and numbers, not their meanings.
>
>
> -gts
>
>
>> *“1, 2, 3, 4, Spring, Summer, Fall, Winter” and this pattern is repeated
>> many times.   *
>> Yeah, this is not enough to make the connection Spring==1, Summer==2 but
>> if I randomize the pattern 1,3,4,2, Spring, Fall, Winter, Summer, and then
>> another randomization eventually the LLM will make the connection.
>>
>> On Sun, Apr 16, 2023 at 3:57 PM Gordon Swobe via extropy-chat <
>> extropy-chat at lists.extropy.org> wrote:
>>
>>>
>>>
>>> On Sun, Apr 16, 2023 at 2:07 PM Jason Resch via extropy-chat <
>>> extropy-chat at lists.extropy.org> wrote:
>>>
>>>
>>> To ground the symbol "two" or any other number -- to truly understand
>>>>> that the sequence is a sequence of numbers and what are numbers -- it needs
>>>>> access to the referents of numbers which is what the symbol grounding
>>>>> problem is all about. The referents exist outside of the language of
>>>>> mathematics.
>>>>>
>>>>
>>>> But they aren't outside the patterns within language and the corpus of
>>>> text it has access to.
>>>>
>>>
>>>
>>> But they are. Consider a simplified hypothetical in which the entire
>>> corpus is
>>>
>>> “1, 2, 3, 4, Spring, Summer, Fall, Winter” and this pattern is repeated
>>> many times.
>>>
>>> How does the LLM know that the names of the seasons do not represent the
>>> numbers 5, 6, 7, 8? Or that the numbers 1-4 to not represent four more
>>> mysterious seasons?
>>>
>>> To know the difference, it must have a deeper understanding of number,
>>> beyond the mere symbolic representations of them. This is to say it must
>>> have access to the referents, to what we really *mean* by numbers
>>> independent of their formal representations.
>>>
>>> That is why I like the position of mathematical platonists who say we
>>> can so-to-speak “see” the meanings of numbers — the referents — in our
>>> conscious minds. Kantians say the essentially the same thing.
>>>
>>>
>>> Consider GPT having a sentence like:
>>>>  "This sentence has five words”
>>>>
>>>> Can the model not count the words in a sentence like a child can count
>>>> pieces of candy? Is that sentence not a direct referent/exemplar for a set
>>>> of cardinality of five?
>>>>
>>>
>>> You seem to keep assuming a priori knowledge that the model does not
>>> have before it begins its training. How does it even know what it means to
>>> count without first understanding the meanings of numbers?
>>>
>>> I think you did something similar some weeks ago when you assumed it
>>> could learn the meanings of words with only a dictionary and no knowledge
>>> of the meanings of any of the words within it.
>>>
>>>
>>>>>>
>>>> But AI can't because...?
>>>> (Consider the case of Hellen Keller in your answer)
>>>>
>>>
>>>
>>> An LLM can’t because it has no access to the world outside of formal
>>> language and symbols, and that is where the referents that give meaning to
>>> the symbols are to be found.
>>>
>>> -gts
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>>>
>>
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