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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