On Mon, May 22, 2023 at 7:34 PM Stathis Papaioannou <stath...@gmail.com>
wrote:

>
>
> On Tue, 23 May 2023 at 07:56, Terren Suydam <terren.suy...@gmail.com>
> wrote:
>
>> Many, myself included, are captivated by the amazing capabilities of
>> chatGPT and other LLMs. They are, truly, incredible. Depending on your
>> definition of Turing Test, it passes with flying colors in many, many
>> contexts. It would take a much stricter Turing Test than we might have
>> imagined this time last year, before we could confidently say that we're
>> not talking to a human. One way to improve chatGPT's performance on an
>> actual Turing Test would be to slow it down, because it is too fast to be
>> human.
>>
>> All that said, is chatGPT actually intelligent?  There's no question that
>> it behaves in a way that we would all agree is intelligent. The answers it
>> gives, and the speed it gives them in, reflect an intelligence that often
>> far exceeds most if not all humans.
>>
>> I know some here say intelligence is as intelligence does. Full stop,
>> conversation over. ChatGPT is intelligent, because it acts intelligently.
>>
>> But this is an oversimplified view!  The reason it's over-simple is that
>> it ignores what the source of the intelligence is. The source of the
>> intelligence is in the texts it's trained on. If ChatGPT was trained on
>> gibberish, that's what you'd get out of it. It is amazingly similar to the
>> Chinese Room thought experiment proposed by John Searle. It is manipulating
>> symbols without having any understanding of what those symbols are. As a
>> result, it does not and can not know if what it's saying is correct or not.
>> This is a well known caveat of using LLMs.
>>
>> ChatGPT, therefore, is more like a search engine that can extract the
>> intelligence that is already structured within the data it's trained on.
>> Think of it as a semantic google. It's a huge achievement in the sense that
>> training on the data in the way it does, it encodes the *context* that
>> words appear in with sufficiently high resolution that it's usually
>> indistinguishable from humans who actually understand context in a way
>> that's *grounded in experience*. LLMs don't experience anything. They
>> are feed-forward machines. The algorithms that implement chatGPT are
>> useless without enormous amounts of text that expresses actual intelligence.
>>
>> Cal Newport does a good job of explaining this here
>> <https://www.newyorker.com/science/annals-of-artificial-intelligence/what-kind-of-mind-does-chatgpt-have>
>> .
>>
>
> It could be argued that the human brain is just a complex machine that has
> been trained on vast amounts of data to produce a certain output given a
> certain input, and doesn’t really understand anything. This is a response
> to the Chinese room argument. How would I know if I really understand
> something or just think I understand something?
>
>> --
> Stathis Papaioannou
>

it is true that my brain has been trained on a large amount of data - data
that contains intelligence outside of my own. But when I introspect, I
notice that my understanding of things is ultimately rooted/grounded in my
phenomenal experience. Ultimately, everything we know, we know either by
our experience, or by analogy to experiences we've had. This is in
opposition to how LLMs train on data, which is strictly about how
words/symbols relate to one another.

Terren

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