IRC: #techbytes @ Techrights IRC Network: Friday, May 29, 2026

-TechBytesBot/#techbytes- ( status 403 @ https://www.thelayoff.com/t/1ksnecn6r )

schestowitz[TR2]

"ntil 1993

schestowitz[TR2]

19 hours ago by Anonymous

schestowitz[TR2]

| 1 reaction (+1/-0) | Reply

schestowitz[TR2]

Post ID: @dc+1ksnecn6r

schestowitz[TR2]

@d0 you must mean Indian monkeys, since those are the only ones that Alvind, Krabanaugh and the CIO look to hire. If you pay peanuts, you hire monkeys, of course.

schestowitz[TR2]

IBM is the laughingstock of the tech world these days. It can only acquire clients through deceit and deception.

schestowitz[TR2]

https://www.thelayoff.com/t/1ksj4adk3

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May 29 09:29

schestowitz[TR2]

-TechBytesBot/#techbytes- ( status 403 @ https://www.thelayoff.com/t/1ksj4adk3 )

schestowitz[TR2]

" only 3 badges ?? You must be joking.

schestowitz[TR2]

As a wannbe executive, you must get at least 7 or more badges (worthless or not) in a week or get a PIP immediately. Make sure your devout, church going first line knows about this, or he will be on a PIP too."

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May 29 09:59

schestowitz[TR2]

"Have a goal of inserting undetected backdoors (and other exploitable vulnerabilities) into popular software?

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There's a few things that will dramatically help that goal:

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1) Increase the quantity of code, in a project, written by an unknown party. [Example: AI, & Rust Crates]

schestowitz[TR2]

2) Increase the speed at which new, unreviewed code is introduced into a project... thus rendering future code reviews increasingly difficult and unlikely. [Example: AI]

schestowitz[TR2]

3) Make sure new versions of a compiler can only be built with earlier versions of the same compiler. This makes it possible to inject replicating backdoors not present in the current code base (see "Trusting Trust" by Ken Thompson). [Example: Rust]

schestowitz[TR2]

4) Make sure a programming language has a single prominent compiler. This makes the vulnerability above especially powerful. [Example: Rust]

schestowitz[TR2]

If I wanted to insert undetected backdoors into a software project, I would encourage them to use Rust (the Rustc compiler) along with AI coding "assistants"."

https://www.thelayoff.com/t/1ksr3548x#replies

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schestowitz[TR2]

-TechBytesBot/#techbytes- ( status 403 @ https://www.thelayoff.com/t/1ksr3548x#replies )

schestowitz[TR2]

schestowitz[TR2]

"Why the vitriol for a man who is leading IBM to become more profitable and competitive?"

schestowitz[TR2]

Profitable for the Indian tribe ?

schestowitz[TR2]

At the expense of throwing US based employees under the bus.

schestowitz[TR2]

What are his achievements ? Spewing sh-t from his disgusting mouth ?

https://lists.gnu.org/archive/html/libreplanet-discuss/2026-05/msg00019.html

schestowitz[TR2]

-TechBytesBot/#techbytes-lists.gnu.org | Re: LLM code as public domain and copyleft

schestowitz[TR2]

schestowitz[TR2]

I'm curious if such fear is justified.

schestowitz[TR2]

LLMs are not much more than plagiarism engines.

schestowitz[TR2]

That LLMs are "not much more than plagiarism engines" is gross oversimplification that reveals narrow understanding of how large language models actually work. LLMs are generative synthesis engines that operate on probabilistic reasoning, contextual understanding, and semantic compression. Plagiarism requires intent. LLMs do not have any intent.

schestowitz[TR2]

If you ask an LLM to explain quantum entanglement in simple terms, it doesn’t ‘pull’ a definition from Wikipedia. It constructs a novel explanation using its understanding of the underlying concepts. That’s synthesis, not plagiarism.

schestowitz[TR2]

LLMs are trained on vast corpora of human text. But so are humans. When you read a book and then write an essay inspired by it, are you a ‘plagiarist’? No—you’re learning from context. LLMs do the same, but at scale. The difference is mechanism, not essence.

schestowitz[TR2]

You can use any LLM to generate what you wish to call "plagiarism", and you can use it to be very creative.

schestowitz[TR2]

How do you generate plagiarism by your definition? Ask the LLM to give you literal output of some works. Set the temperature to zero. that specific mode, the LLM acts as a high-speed search-and-retrieve engine, reproducing existing text with minimal variation. It is citation on steroids.

schestowitz[TR2]

Conversely, "authorship" emerges when you use the LLM as an augmentative layer for your own original ideas. You define the core concept, the intent, and the direction. The LLM then refines, expands, and polishes your voice, not its own. It is not generating content from scratch; it is elevating your expression. The difference is not in the tool, but in the source of the initial spark.

schestowitz[TR2]

You’re still mistaking the map for the territory, rather than discovering the territory itself. Try it out. Method is there, in previous paragraph.

schestowitz[TR2]

Thus, in the matter of software, one of the main uses of LLMs is to strip both attribution and licensing information from whole code bases. So while it is correct that machine generated *output* cannot be copyrighted, if it were actually generated from scratch by the LLM. But, one has to raise questions about the input which it is regurgitating minus attribution and licensing information. LLM output is not generated from scratc

schestowitz[TR2]

h, it is instead generated from models trained on licensed code under copyright protection.

schestowitz[TR2]

There are many LLMs today that are not trained on copyrighted code. We talk of millions of published models, like those on huggingface.co

schestowitz[TR2]

I have downloaded 902 models. And I run those which are not trained on copyrighted sets and which are not proprietary. Now you come with such mature looking statement how the main use of the LLM is to strip both attribution and licensing information. Surely you can do that, but it is not main use. For these models, the 'stripping of attribution' narrative falls apart entirely.

schestowitz[TR2]

Yet, you present your statement as if it’s a universal truth. This kind of broad generalization is dangerous. It’s not just an academic error; it misleads people who don’t have the time or expertise to dig into the nuances of these diverse models. They’ll just jump on the bandwagon, protesting a problem that isn’t actually universal.

schestowitz[TR2]

Put more effort in research. It is enough to research the website HF I gave you.

schestowitz[TR2]

So if you wish to use it in the mode of plagiarism, of course, you are free to do so. Same thing with actual books, you could take them and kind of re-write them, without referencing.

schestowitz[TR2]

If you wish to use it in full authorship mode, you can, there will be no plagiarism, and LLM is your augmentation tool.

schestowitz[TR2]

As for software freedom, there is an additional pair of problems caused by LLMs: using the plagiarized output separates potential project collaborators from the very projects which are getting exploited, while at the same time the projects which are getting exploited are getting isolated from any potential collaborators trapped behind LLMs.

schestowitz[TR2]

That is under condition that some user use it as plagiarized output. It simply is not so in majority of cases. I am sure you need to do more experience with it. Basically, run the LLM.

schestowitz[TR2]

If something is plagiarized it means user knew it, and had intent to plagiarize, and would not provide references.

schestowitz[TR2]

So try doing that, practically, then come back with the report. Then we have the fact to talk about.

schestowitz[TR2]

But, yeah, using LLMs to strip the GPL and other software licenses from code, as well as stripping copyright attribution, is a real problem now.

schestowitz[TR2]

For who? Do you have specific case? You can complain. But let us not generalize.

schestowitz[TR2]

The abundance of software created with the LLM also generates more GPL/Apache/Mit/free software. The abundance will soon make the GPL obsolete, because everybody is then able to generate their software, which is in the end free software. It is evolution.

schestowitz[TR2]

There was free software before the GPL.

schestowitz[TR2]

GPL has the purpose to protect free software to remain free software.

schestowitz[TR2]

But once you have free software generated on every corner, every monitor, every computer, the GPL may become obsolete, but users may still have the freedom.

schestowitz[TR2]

So keep working on the freedom, don't judge the temporary momentum of LLm-affairs which you still did not research well.

schestowitz[TR2]

schestowitz[TR2]

Jean Louis

schestowitz[TR2]

schestowitz[TR2]

schestowitz[TR2]

LLMs are generative synthesis engines that operate on probabilistic reasoning, contextual understanding, and semantic compression.

schestowitz[TR2]

No, LLMs have nothing to do with generation. They merely ingest 'tokens' and recombine sets of them into statistically plausible combinations. Lots of people get confused about that, perhaps (to be generous) because of wishful thinking on their part.

schestowitz[TR2]

> Plagiarism requires intent.

schestowitz[TR2]

Intent is not a prerequisite for plagiarism as defined in academia over the ages.

schestowitz[TR2]

> LLMs do not have any intent.

schestowitz[TR2]

Agreed, LLMs have no intent. Thus LLMs just plagiarize despite being automatons. But those who interface with LLMs can have intent. One can question the intent of those interfacing with LLMs because most people know, at least on some level, that the 'tokens' are slurped up verbatim from the WWW at large without attribution.

schestowitz[TR2]

>> But, yeah, using LLMs to strip the GPL and other software licenses

schestowitz[TR2]

>> from code, as well as stripping copyright attribution, is a real

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>> problem now.

schestowitz[TR2]

schestowitz[TR2]

> For who? Do you have specific case? You can complain. But let us not

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> generalize.

schestowitz[TR2]

In the context of code, one recent example is the use of LLMs to try to strip the Chardet project of its license, among quite a few other similar attacks some more public some less public. Noticeably, the original code is in the training set so the stripped version can hardly be described as a cleanroom implementation. "

https://lists.gnu.org/archive/html/libreplanet-discuss/2026-05/msg00014.html

schestowitz[TR2]

-TechBytesBot/#techbytes-lists.gnu.org | Re: LLM code as public domain and copyleft

schestowitz[TR2]

schestowitz[TR2]

In Part II of the report on Copyright and Artificial Intelligence,

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https://www.copyright.gov/ai/

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it concludes with the observation that LLM output, and AI output in general, is ineligible for copyrights unless that output is modified by a human for the purposes of creative expression:

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"As described above, in many circumstances these outputs

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will be copyrightable in whole or in part—where AI is

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used as a tool, and where a human has been able to

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determine the expressive elements they contain. Prompts

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alone, however, at this stage are unlikely to satisfy

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those requirements."

schestowitz[TR2]

https://www.copyright.gov/ai/Copyright-and-Artificial-Intelligence-Part-2-Copyrightability-Report.pdf

schestowitz[TR2]

schestowitz[TR2]

For further clarification, there are written guidelines on the scope of copyright in the context of slop which has been handled meaningfully by humans:

schestowitz[TR2]

"Consistent with the Office’s policies described above,

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applicants have a duty to disclose the inclusion of

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AI-generated content in a work submitted for registration

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and to provide a brief explanation of the human author’s

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contributions to the work"

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However, slop which has not been handled meaningfully by humans remains ineligible for copyright:

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"... a work “autonomously created by artificial intelligence

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without any creative contribution from a human actor” was

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“ineligible for registration”.

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https://www.copyright.gov/ai/ai_policy_guidance.pdf

schestowitz[TR2]

Thus the problem raised in Andy's original message, that LLMs can be and are being misused to strip licensing (and attribution) from projects' code bases. The code goes into the large language model with a license and a copyright holder. Calling that infringement a training set doesn't change its nature. Then the code comes back out of the model as slop, and while slop in general is ineligible for copyright status the original code

schestowitz[TR2]

remains strongly protected by copyright, whether plagiarized by an LLM or not.

schestowitz[TR2]

And, again, as mentioned in an earlier reply, there is the further problem of the LLMs separating users from projects and vice versa. That is a whole other discussion about duplicated effort, missing communications, and general lost opportunities.

schestowitz[TR2]

PS. COPE (Committee on Publication Ethics) writes the following:

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"COPE joins organisations, such as WAME and the JAMA

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Network among others, to state that AI tools cannot

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be listed as an author of a paper."

schestowitz[TR2]

https://publicationethics.org/guidance/cope-position/authorship-and-ai-tools

schestowitz[TR2]

schestowitz[TR2]

It would not be a stretch to apply a similar conclusion to code which has been mangled by an LLM. "

-TechBytesBot/#techbytes-www.copyright.gov | Copyright and Artificial Intelligence | U.S. Copyright Office