Re: Ok I made a joke, sorry (Was: 2nd Cognitive Turn ~~> no Bayesian Brain)

BTW: Friedrich Ueberweg is quite good
and funny to browse, he reports relatively
unfiltered what we would nowadays call
forms of "rational behaviour", so its a little
pot purry, except for his sections where he
explains some schemas, like the Aristotelan
figures, which are more pure logic of the form.
And peng you get a guy talking pages and
pages about pure and form:
"Pure" logic, ontology, and phenomenology
David Woodruff Smith
https://www.cairn.info/revue-internationale-de-philosophie-2003-2-page-21.htm
But the above is a from species of philosophy
that is endangered now. Its predator are
abstractions on the computer like lambda
calculus and the Curry Howard isomorphism. The
revue has become an irrelevant cabarett, only
dead people would be interested in, like
may father, grandfather etc...
Mild Shock schrieb:

 My impression Cognitive Science was never
Bayesian Brain, so I guess I made a joke.
 The time scale, its start in 1950s and that
it is still relative unknown subject,
 would explain:
- why my father or mother never tried to
   educated me towards cognitive science.
   It could be that they are totally blank
   in this respect?
 - why my grandfather or grandmothers never
   tried to educate me towards cognitive
   science. Dito It could be that they are totally
   blank in this respect?
 - it could be that there are rare cases where
   some philosophers had already a glimps of
   cognitive science. But when I open for
   example this booklet:
 System der Logic
Friedrich Ueberweg
Bonn - 1868
https://philpapers.org/rec/UEBSDL
    One can feel the dry swimming that is reported
   for several millennia.  What happened in the
   1950s was the possibility of computer modelling.
 Mild Shock schrieb:

Hi,
>
Yes, maybe we are just before a kind
of 2nd Cognitive Turn. The first Cognitive
Turn is characterized as:
>

The cognitive revolution was an intellectual movement that began in the 1950s as an interdisciplinary study of the mind and its processes, from which emerged a new field known as cognitive science.

https://en.wikipedia.org/wiki/Cognitive_revolution
>
The current mainstream believe is that
Chat Bots and the progress in AI is mainly
based on "Machine Learning", whereas
>
most of the progress is more based on
"Deep Learning". But I am also sceptical
about "Deep Learning" in the end a frequentist
>
is again lurking. In the worst case the
no Bayension Brain shock will come with a
Technological singularity in that the current
>
short inferencing of LLMs is enhanced by
some long inferencing, like here:
>
A week ago, I posted that I was cooking a
logical reasoning benchmark as a side project.
Now it's finally ready! Introducing 🦓 𝙕𝙚𝙗𝙧𝙖𝙇𝙤𝙜𝙞𝙘,
designed for evaluating LLMs with Logic Puzzles.
https://x.com/billyuchenlin/status/1814254565128335705
>
making it possible not to excell by LLMs
in such puzzles, but to advance to more
elaborate scientific models, that can somehow
>
overcome fallacies such as:
- Kochen Specker Paradox, some fallacies
   caused by averaging?
- Gluts and Gaps in Bayesian Reasoning,
   some fallacies by consistency assumptions?
- What else?
>
So on quiet paws AI might become the new overlord
of science which we will happily depend on.
>
Jeff Barnett schrieb:

You are surprised; I am saddened. Not only have we lost contact with the primary studies of knowledge and reasoning, we have also lost contact with the studies of methods and motivation. Psychology was the basic home room of Alan Newell and many other AI all stars. What is now called AI, I think incorrectly, is just ways of exercising large amounts of very cheap computer power to calculate approximates to correlations and other statistical approximations.
>
The problem with all of this in my mind, is that we learn nothing about the capturing of knowledge, what it is, or how it is used. Both logic and heuristic reasoning are needed and we certainly believe that intelligence is not measured by its ability to discover "truth" or its infallibly consistent results. Newton's thought process was pure genius but known to produce fallacious results when you know what Einstein knew at a later time.
>
I remember reading Ted Shortliffe's dissertation about MYCIN (an early AI medical consultant for diagnosing blood-borne infectious diseases) where I learned about one use of the term "staff disease", or just "staff" for short. In patient care areas there always seems to be an in-house infection that changes over time. It changes because sick patients brought into the area contribute whatever is making them sick in the first place. In the second place there is rapid mutations driven by all sorts of factors present in hospital-like environments. The result is that the local staff is varying, literally, minute by minute. In a days time, the samples you took are no longer valid, i.e., their day old cultures may be meaningless. The underlying mathematical problem is that probability theory doesn't really have the tools to make predictions when the basic probabilities are changing faster than observations can be turned into inferences.
>
Why do I mention the problems of unstable probabilities here? Because new AI uses fancy ideas of correlation to simulate probabilistic inference, e.g., Bayesian inference. Since actual probabilities may not exist in any meaningful ways, the simulations are often based on air.
>
A hallmark of excellent human reasoning is the ability to explain how we arrived at our conclusions. We are also able to repair our inner models when we are in error if we can understand why. The abilities to explain and repair are fundamental to excellence of thought processes. By the way, I'm not claiming that all humans or I have theses reflective abilities. Those who do are few and far between. However, any AI that doesn't have some of these capabilities isn't very interesting.
>
For more on reasons why logic and truth are only part of human ability to reasonably reason, see https://www.yahoo.com/news/opinion-want-convince-conspiracy-theory-100258277.html >
>
   -- Jeff Barnett

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