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From: Mild Shock <janburse@fastmail.fm>
Newsgroups: comp.lang.prolog
Subject: Missed the AI Boom because missed the Emojis (Was: Prolog totally
 missed the AI Boom)
Date: Sun, 29 Jun 2025 13:32:25 +0200
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 > Those that use a large part pay a pretty
 > high price in terms of memory and currently
 > also time for code points > 0xffff

Emojis are typically above 0xffff. And from this
announcement its seem, Emojis are a big part with
keeping up with the AI Boom:

 > :rocket: Call for Papers: Integrating Logical
 > Reasoning & Large Language Models (LLMs) :brain:
 >
 > https://swi-prolog.discourse.group/t/9065

But it would cost you nothing to support this here in library(portray_text):

/* SWI-Prolog 9.3.24 */
?- X = [a,b,c]
X = `abc`

It is extremly trivial to implement, its not really
rocket science. It doesn need much brains and
it works also for Emojis:

/* Scryer Prolog 0.9.4-411 */
?- X = [a,b,c].
    X = "abc".
?- X = ['🚀', a, '🧠', b, c].
    X = "🚀a🧠bc".

In Scryer Prolog it shows double quotes and not
back quotes, because of the different default settings
of the Prolog flags double_quotes and back_quotes.

Mild Shock schrieb:
> 
> Inductive logic programming at 30
> https://arxiv.org/abs/2102.10556
> 
> The paper contains not a single reference to autoencoders!
> Still they show this example:
> 
> Fig. 1 ILP systems struggle with structured examples that
> exhibit observational noise. All three examples clearly
> spell the word "ILP", with some alterations: 3 noisy pixels,
> shifted and elongated letters. If we would be to learn a
> program that simply draws "ILP" in the middle of the picture,
> without noisy pixels and elongated letters, that would
> be a correct program.
> 
> I guess ILP is 30 years behind the AI boom. An early autoencoder
> turned into transformer was already reported here (*):
> 
> SERIAL ORDER, Michael I. Jordan - May 1986
> https://cseweb.ucsd.edu/~gary/PAPER-SUGGESTIONS/Jordan-TR-8604-OCRed.pdf
> 
> Well ILP might have its merits, maybe we should not ask
> for a marriage of LLM and Prolog, but Autoencoders and ILP.
> But its tricky, I am still trying to decode the da Vinci code of
> 
> things like stacked tensors, are they related to k-literal clauses?
> The paper I referenced is found in this excellent video:
> 
> The Making of ChatGPT (35 Year History)
> https://www.youtube.com/watch?v=OFS90-FX6pg
>