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

Brent Allsop brent.allsop at gmail.com
Mon Apr 3 18:07:15 UTC 2023

Yes, it is very exciting to see this much discussion about
colerness qualities, again.  In the old days, the term 'qualia' became a
dirty word on this list, and most people would just filter out any thread
containing that word.  Chat GPT is making it necessary that we explicitly
understand the difference between abstract systems and phenomenal systems
that represent knowledge with physical qualities (ok phenomenal qualities
for those of you that think qualities are not physical,  or not
approachable/sharable via science, apparently the majority of you?)

But I disagree with your assertion that GPT4 has no idea about what it is
talking about, and I don't think GPT4 is saying that at all in these
answers.  Its large language model clearly has the ability to model, at
least abstractly, a large subset of what humanity talks about in very
powerful ways, and is on the verge of General Intelligence.  Just because
it doesn't know what redness is like, doesn't mean it can't know more about
redness than most humans.  Just like Black and White Marry, it can clearly
indicate in these kinds of answers that it has a very powerful grasp of
reality, and the difference between itself and us, and what Mary will learn
when she experiences redness  It is only a matter of time till an abstract
AI helps us discover which of all our descriptions of stuff in the brain is
a description of redness, then endows itself with that so it can finally
say: 'oh THAT is what redness is like." and thereby finally having a
grounded understanding, making it also, phenomenally conscious like us.

I so look forward to the day when we finally have an interest to do the
same.  Finally discovering new phenomenal qualities no human has ever
experienced before, and endowing ourselves with those.  I'm so tired of
only knowing the qualities things seem to be.  Am I the only one that wants
to know what all that stuff out there is really like, and what phenomenal
uploading to phenomenal avatars will really be like in a few more years?

On Fri, Mar 31, 2023 at 5:41 AM Gordon Swobe via extropy-chat <
extropy-chat at lists.extropy.org> wrote:

> Many people here seem interested in the question of whether LLMs can have
> conscious understanding of the words/symbols that it takes as inputs and
> generates as outputs. It seems that most people here want to think GPT4 has
> something like a conscious mind, but I agree with GPT4  below that it has
> no idea what it is talking about.
> On Thu, Mar 30, 2023 at 1:55 PM Gordon Swobe <gordon.swobe at gmail.com>
> wrote:
> GPT-4 explained to me that it could not solve the symbol grounding problem
>> for itself (I reported this in another thread). I asked it to explain the
>> significance.
>> My prompt: What is the significance of the fact that ChatGPT cannot solve
>> the symbol grounding problem for itself and can only simulate that it has
>> solved it? How does this put ChatGPT at a disadvantage compared to humans?
>> GPT-4: The symbol grounding problem refers to the difficulty in
>> connecting abstract symbols (such as words or concepts) to their real-world
>> referents. While ChatGPT can simulate understanding by generating
>> human-like text based on its training data, it doesn't possess the direct
>> experience or sensory input that humans have to ground these symbols in
>> reality.
>> The significance of this limitation has several implications:
>> Lack of true understanding: ChatGPT doesn't have a genuine understanding
>> of the world, as it relies on patterns and associations found in the text
>> it was trained on. It can't form new connections based on direct
>> experience, which may result in limitations in problem-solving or abstract
>> reasoning.
>> Difficulty with context: Without grounding in real-world experiences,
>> ChatGPT may struggle to fully understand context or cultural nuances. It
>> may provide answers that are technically correct but inappropriate or
>> irrelevant in a specific situation.
>> Inability to learn from sensory input: Humans learn through direct
>> experience and sensory input, which allows them to adapt and understand new
>> situations better. ChatGPT can't update its knowledge through real-world
>> experiences, making it less adaptable to novel contexts.
>> Absence of common sense: Although ChatGPT can generate text that appears
>> to show common sense understanding, it might still make errors that a human
>> would easily avoid. This is because its responses are based on patterns in
>> the data, rather than a true comprehension of the concepts.
>> Limited creativity: ChatGPT's creativity is confined to the scope of its
>> training data. While it can generate new text based on patterns it has seen
>> before, it can't create truly novel ideas or solutions in the same way that
>> humans, with their real-world grounding, can.
>> In summary, the inability to solve the symbol grounding problem puts
>> ChatGPT at a disadvantage compared to humans in terms of true
>> understanding, adaptability, context-awareness, common sense, and
>> creativity. However, it is essential to remember that ChatGPT is an AI
>> language model designed to assist and augment human capabilities, not to
>> fully replicate human cognition.
>> ---
> -gts
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