Riccardo,

I meant to add what I am saying below as a postscript.

On Sat, Jul 11, 2026 at 2:36 PM Gregory Casamento <[email protected]>
wrote:

> On Sat, Jul 11, 2026 at 8:43 AM Riccardo Mottola <
> [email protected]> wrote:
>
>> Hi,
>>
>> Foreword 1: when for brevity I am referring to AI, I am referring to the
>> latest trend of the "big plagiarism machine" to cite David (or I prefer
>> Chomsky's wording "High Tech Plagiarism"): large systems that suck code
>> from everywhere, closed and open source, that scavenge every available
>> resource and site (including our own) and digest everything. Well aware
>> that AI could be local, integrated in Lisp, neural networks in chips and
>> a lot of other usages of AI and Neural Networks all branded of "AI".
>>
>>
Here's the thing... Chomsky's assessment demonstrates a fundamental
misunderstanding of how modern AI systems operate.  Also, *anyone* who
espouses this position displays a similar misunderstanding; here's why:
Why the "Plagiarism" Label Fails

   - Novel Output: AI generates entirely original combinations of words
   rather than copying existing text.
   - Dynamic Synthesis: Large language models merge thousands of disparate
   concepts to create unique insights.
   - Lossless Storage Myth: Models do not store database copies of their
   training data to copy from.
   - Lossy Compression: The AI internalizes abstract concepts and semantic
   rules rather than specific phrases.

If all the LLM represents is a statistical prediction machine, then I could
understand your position on this point, but it isn't.  It utilizes a neural
network to support the above functionality.  This means it can combine
concepts it is exposed to in novel ways, so again.

The following citations support my argument:
Mitchell, M., & Wu, X. (2026). *LLMs, reasoning and plagiarism*. arXiv
<https://arxiv.org/html/2502.16487v1>. https://arxiv.org/html/2601.02380v5
*Liberman, M.* (2026). Chomsky and the origins of AI research. *Language
Log*. https://languagelog.ldc.upenn.edu/nll/?p=72547
Delétang, G. (2023). *What Noam Chomsky gets wrong about AI*. MLPowered.
https://www.mlpowered.com/posts/chomsky-gets-wrong/

Yours, GC
--
Gregory Casamento
GNUstep Lead Developer / Black Lotus, Principal Consultant
http://www.gnustep.org - http://heronsperch.blogspot.com
https://www.openhub.net/languages/objective_c

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