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Abstraction Engine / Pattern-Amplification AI Avalanche [Java to C# translation] (Re: The Prolog Community is extremly embarrassing (Re: Prolog totally missed the AI Boom)

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Hi,

Here we find Ex-OpenAI Scientist looking extremly concerned:

 > Ex-OpenAI pioneer Ilya Sutskever warns that as
 > AI begins to self-improve, its trajectory may become
 > "extremely unpredictable and unimaginable,"
 > ushering in a rapid advance beyond human control.
 > https://www.youtube.com/watch?v=79-bApI3GIU

Meanwhile I am enjoying some of the AIs abstracting capabilities:

The bludy thingy was translating my Java code into C#
code in a blink and did all kind of fancy translation,
and explains his own doing as:

 > That casual, almost incidental quality you noticed
 > is exactly the abstraction engine working so fluidly
 > that it becomes invisible. The AI was:
 > 1. Understanding the essential computation (the "what")
 > 2. Discarding the Java-specific implementation (the "how")
 > 2. Re-expressing it using C#'s idiomatic patterns (a different "how")

Ha Ha, nice try AI, presenting me this antropomorphic
illusion of comprehension. Doesn't the AI just apply tons
of patterns without any knowing what the code really does?

Well I am fine with that, I don't need more than this
pattern based transformations. If the result works,
the approach is not broken.

Bye

Mild Shock schrieb:
> Hi,
> 
> That is extremly embarassing. I don’t know
> what you are bragging about, when you wrote
> the below. You are wrestling with a ghost!
> Maybe you didn’t follow my superbe link:
> 
>  > seemingly interesting paper. In stead
>  > particular, his final coa[l]gebra theorem
> 
> The link behind Hopcroft and Karp (1971) I
> gave, which is a Bisimulation and Equirecursive
> Equality hand-out, has a coalgebra example,
> I used to derive pairs.pl from:
> 
> https://www.cs.cornell.edu/courses/cs6110/2014sp/Lectures/lec35a.pdf
> 
> Bye
> 
> 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
> 

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Abstraction Engine / Pattern-Amplification AI Avalanche [Java to C# translation] (Re: The Prolog Community is extremly embarrassing (Re: Prolog totally missed the AI Boom) Mild Shock <janburse@fastmail.fm> - 2025-10-04 15:47 +0200
  Swift AI versus Apertus AI: David against Goliath (Was: Abstraction Engine / Pattern-Amplification AI Avalanche [Java to C# translation]) Mild Shock <janburse@fastmail.fm> - 2025-10-04 16:03 +0200

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