In the interest of pruning this conversation a bit I will not continue the
discussion about GPT-3. Apologies, but this thread is growing too fast and I
don't have the time to give your comments the attention they deserve. I am
happy for you to have the last word in that matter.

>> These techniques were invented from the field of AI, but that does not mean
they remain in the field of AI.

Like I say above, it is pretty uncontroversial that these approaches are part
of the field of AI research. You can consult wikipedia or e.g. the calls for
papers from major AI conferences, AAAI and IJCAI, if in doubt.

So I have to ask again, why do you say these approaches are are not in the
field of AI research? According to whom? And based on what?

I would please like an answer to the above question.

Further, I can certainly point you to successes of symbolic AI, which you say
don't exist. For one thing, the entire fields of automated theorem proving,
planning, search, game playing, knowledge representation and reasoning, etc.
that you say are "not AI", but are like I say still active and still state of
the art in their respective tasks. These are certainly successful- they have
produced systems and techniques that still work best than any alternative and
actually quite well.

For examples of specific systems that were successful in their time, see Logic
Theorist [1] that proved 38 of the first 52 theorems in Principia Mathematica;
Chinook [2], the first computer program to win a world championship against
humans (in checkers/draughts); Deep Blue [3], the first AI system to defeat a
human grandmaster (Garry Kasparov) in chess; MYCIN [4] the first AI system to
outperform human experts in disease diagnosis (specifically, diagnosis of
infections); and so on.

Of course these systems have been superseded - but they were successes
nonetheless. Another reason to learn the history of AI is to become aware of
those systems- they, indeed, were "there".

Again I have to ask you- where does your knowledge of AI come from? When
you make such strong statements about what works and what doesn't, what failed
and what succeeded, are you sure you are well informed? Do you draw your
knowledge from primary sources, or are you trusting the opinions of others who
claim to be experts- but may not be (like in the article above)?

>> How would you tackle this with ILP?

Below I've defined the problem in the format expected by Louise [5]:

?- list_mil_problem(ordered/3).
Positive examples
-----------------
ordered([a],[b,c],[d,e,f]).

Negative examples
-----------------
[]

Background knowledge
--------------------
shorter/2:
shorter(A,B):-length(A,C),length(B,D),C<D.

Metarules
---------
triadic_chain metarule 'P(x,z,y):- Q(x,z), R(z,y)'.
true.

Given this problem definition, Louise can learn the following (Prolog) program:

?- learn(ordered/3).
ordered(A,B,C):-shorter(A,B),shorter(B,C).
true.

To explain, shorter/2 is a predicate defined as background knowledge by me.
triadic_chain is a metarule, a second-order clause that provides inductive
bias. length/2 is an ISO Prolog predicate.

Like I say, this is a trivial problem, not least because its solution is easy
to figure out and the background knowledge and metarules are trivial to define
by hand. Louise can also perform predicate invention to define new
background knowledge (kind of like inventing new features) and also new
metarules. That is to say, Louise can learn the shorter/2 and length/2
programs, also from very few examples- and then reuse them as background
knowledge. But showing how to do that would make for a larger example. I'm
happy to oblige if you are curious.

I should point out that there exists no neural net approach that can learn the
same (or a similar) program from a single positive example- not least because
neural nets cannot make use of background knowledge (i.e. a library of
programs from which to build other programs).

__________________

[1] https://en.wikipedia.org/wiki/Logic_Theorist

[2] https://en.wikipedia.org/wiki/Chinook_(computer_program)

[3] https://en.wikipedia.org/wiki/Deep_Blue_versus_Garry_Kasparo...

[4] https://en.wikipedia.org/wiki/Mycin

[5] https://github.com/stassa/louise/