It’s funny.  I was reading some commentary on this last week (can’t even 
remember where now; that was _last week_!), and I remember thinking that the 
description reminded me of Williams Syndrome in people.  They have a 
grammatical sense that is at the stronger end of the human range, but their 
train of meaning has come to be characterized (again, a now-tropish short-hand) 
as “word salad”.  

That there should be several somewhat-autonomous processes running in parallel 
in people, and coupled by some kind of message-passing, as Ray Jackendoff 
proposes, seems quite reasonable and in keeping with brain biology, and if 
there is, it would be a compact way to account for the seeming independence in 
refinement of grammatical sense and whatever other part of sentence-coherence 
we have come to term “semantics”.

Last year, too, someone (I think my boss at the time, which would make it two 
years ago) told me about some nature paper saying that a comparative genome 
analysis of domestic dogs and wolves had shown a mutation in the dogs at the 
cognate locus to the one that results in Williams Syndrome in people.  That 
would be an easy indulgent interpretation: the greater affectionateness 
preserved into adulthood, and the increased verbal-or-other communicativeness.  
Though Barry Lopez, I think it was, argues that wolves have higher social 
intelligence, which I guess would be making some claim about a “semantics”.

The chatbot has, however, a knd of pure authentic evil that Philip K. Dick 
tried to mimic (the argument with the door), and came close enough to be 
laughing-through-tears, but could not truly simulate as it shines through in 
the Ginsparg exchange.  Or dealing with the maddening, horrifying computer 
interfaces that every company puts up to its customers, after they have fired 
all the human problem-solvers.  Few things put me in a real dread, because I am 
now fairly old, and getting older as fast as I can.  But the prospect of still 
being alive in a world where that interface is all that is left to any of us, 
is dreadworthy.

Eric



> On Feb 8, 2023, at 11:51 AM, glen <geprope...@gmail.com> wrote:
> 
> I wrote and deleted a much longer response. But all I really want to say is 
> that these *models* are heavily engineered. TANSTAAFL. They are as 
> engineered, to intentional purpose, as a Boeing 777. We have this tendency to 
> think that because these boxes are opaque (more so to some than others), 
> they're magical or "semantic-less". They simulate a human language user 
> pretty well. So even if there's little structural analogy, there's good 
> behavioral analogy. Rather than posit that these models don't have semantics, 
> I'd posit *we* don't have semantics.
> 
> The problem with communication is the illusion that it exists.
> 
> On 2/7/23 14:16, Steve Smith wrote:
>> DaveW -
>> I really don't know much of/if anything really about these modern AIs, 
>> beyond what pops up on the myriad popular science/tech feeds that are part 
>> of *my* training set/source.   I studied some AI in the 70s/80s and then 
>> "Learning Classifier Systems" and (other) Machine Learning techniques in the 
>> late 90s, and then worked with folks who did Neural Nets during the early 
>> 00s, including trying to help them find patterns *in* the NN structures to 
>> correlate with the function of their NNs and training sets, etc.
>> The one thing I would say about what I hear you saying here is that I don't 
>> think these modern learning models, by definition, have neither syntax *nor* 
>> semantics built into them..   they are what I colloquially (because I'm sure 
>> there is a very precise term of art by the same name) think of or call 
>> "model-less" models. At most I think the only models of language they have 
>> explicit in them might be the Alphabet and conventions about white-space and 
>> perhaps punctuation?   And very likely they span *many* languages, not just 
>> English or maybe even "Indo European".
>> I wonder what others know about these things or if there are known good 
>> references?
>> Perhaps we should just feed thesemaunderings into ChatGPT and it will sort 
>> us out forthwith?!
>> - SteveS
>> On 2/7/23 2:57 PM, Prof David West wrote:
>>> I am curious, but not enough to do some hard research to confirm or deny, 
>>> but ...
>>> 
>>> Surface appearances suggest, to me, that the large language model AIs seem 
>>> to focus on syntax and statistical word usage derived from those large 
>>> datasets.
>>> 
>>> I do not see any evidence in same of semantics (probably because I am but a 
>>> "bear of little brain.")
>>> 
>>> In contrast, the Cyc project (Douglas Lenat, 1984 - and still out there as 
>>> an expensive AI) was all about semantics. The last time I was, briefly, at 
>>> MCC, they were just switching from teaching Cyc how to read newspapers and 
>>> engage in meaningful conversation about the news of the day, to teaching it 
>>> how to read the National Enquirer, etc. and differentiate between 
>>> syntactically and literally 'true' news and the false semantics behind same.
>>> 
>>> davew
>>> 
>>> 
>>> On Tue, Feb 7, 2023, at 11:35 AM, Jochen Fromm wrote:
>>>> I was just wondering if our prefrontal cortex areas in the brain contain a 
>>>> large language model too - but each of them trained on slightly different 
>>>> datasets. Similar enough to understand each other, but different enough so 
>>>> that everyone has a unique experience and point of view o_O
>>>> 
>>>> -J.
>>>> 
>>>> 
>>>> -------- Original message --------
>>>> From: Marcus Daniels <mar...@snoutfarm.com>
>>>> Date: 2/6/23 9:39 PM (GMT+01:00)
>>>> To: The Friday Morning Applied Complexity Coffee Group <friam@redfish.com>
>>>> Subject: Re: [FRIAM] Datasets as Experience
>>>> 
>>>> It depends if it is given boundaries between the datasets.   Is it 
>>>> learning one distribution or two?
>>>> 
>>>> 
>>>> *From:* Friam <friam-boun...@redfish.com> *On Behalf Of *Jochen Fromm
>>>> *Sent:* Sunday, February 5, 2023 4:38 AM
>>>> *To:* The Friday Morning Applied Complexity Coffee Group 
>>>> <friam@redfish.com>
>>>> *Subject:* [FRIAM] Datasets as Experience
>>>> 
>>>> 
>>>> Would a CV of a large language model contain all the datasets it has seen? 
>>>> As adaptive agents of our selfish genes we are all trained on slightly 
>>>> different datasets. A Spanish speaker is a person trained on a Spanish 
>>>> dataset. An Italian speaker is a trained on an Italian dataset, etc. 
>>>> Speakers of different languages are trained on different datasets, 
>>>> therefore the same sentence is easy for a native speaker but impossible to 
>>>> understand for those who do not know the language.
>>>> 
>>>> 
>>>> Do all large language models need to be trained on the same datasets? Or 
>>>> could many large language models be combined to a society of mind as 
>>>> Marvin Minsky describes it in his book "The society of mind"? Now that 
>>>> they are able to understand language it seems to be possible that one 
>>>> large language model replies to the questions from another. And we would 
>>>> even be able to understand the conversations.
>>>> 
> 
> 
> -- 
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