Tootfinder

Protecting our FLOSS commons from #LLMs
https://blog.codeberg.org/protecting-our-floss-commons-from-llms.html

I guess it is kind of nice that #LLMs are just as prone to getting confused by ambiguous wording in architecture specs as I am. I'm looking at you FEAT_FPRCVT.....

Can someone explain to me how the argument “ #LLMs only produce stochastically reasonable output ” is relevant or convincing?
Like… how do you think a human brain forms a sentence? Is this a straight-forward deterministic process? Does it matter?
I use tools and processes to verify my output and so does a coding agent.
I just don't get how this is an argument that would…

In my latest article for Inquirer.net, I look at the possible role that #AI and #LLMs might have in the literary world. Should AI be only limited to spellchecking and copyediting? Or could they be used to write entire paragraphs?

The burden of human authorship in the age of ChatGPT
Contest poster courtesy of the F. Sionil Jose Young Writers Award MANILA, Philippines - Exploring authorship in the age of AI and ChatGPT. The F. Sionil Jose Young Writers Award, first

#LLMs als Chance für die #Linguistik
https://doi.org/10.37307/j.1868-775X.2026.02.08
(Open Access)
Meine Kollegen am @… und der Erstgutachter meiner Diss Lars Konieczny (U Freiburg) haben einen – wie ich finde – feinen Beitrag in der Zeitschrift 'Deutsche Sprache' veröffentlicht.

Replies to comments on my "#LLMs are eroding my career" post
https://human-in-the-loop.bearblog.dev/replies-to-comments-on-my-llms-are-erodi…

One solution here is to make corporate LLMs unprofitable. Local resistance to data center build-outs is already making that happen, as is other resistance. But, honestly, they're already doing a pretty good job of this themselves. The "AI industry" has never been profitable. Local #LLMs can't be monetized and also can't be prevented.
It's simply not possible to recover training investment costs by charging for inference. I guess they can try to make local models illegal, which is totally possible. I can totally see corporations pushing through a bunch of regulation to "control uncensored models" creating a black market for ablated models.
It's gonna be a wild ride. Get your dark nets ready, we're very close to an even more cyberpunk future.

Just wrote yet another piece on LLMs that has been kicking around in my head for a while: "What kinds of conversations can you have with a parrot?"
#AI #LLMs

RE: #LLMs to access the

The thing I love about computers is that I can tell you basically anything about how a computer works, not because I know everything but because I know how to figure it out. I can walk you, over the course of an hour, two, there, maybe more, though every step of typing something into a web form, from the electrical signals that get turned into digital via an ADC, to the USB controller memory, to the kernel driver, to user space, through the application stack, back down to the kernel, to the network driver, through routers, up the server stack, TCP/IP, key exchanges, etc.
I don't mean I have the time to dig into these things. I used to, and it was fun. I've given more than my fair share of interviews talking though variations of this. What I'm talking about isn't pure knowledge, but that, given relatively simple theory, and the right tools, every action of a computer can be understood down to the limits of physics.
The thing I hate about #LLMs is that take something comprehensible and make it something almost completely opaque. Even with a solid understanding of the theory, literally no one understands what's happening. That is shit. It makes playing with technology not fun anymore. The way in which companies are making things even more opaque by running stuff in the cloud is everything I hated about closed source on steroids.

Just realized that the fact that newer large language models keep getting bigger in terms of parameters is kind of a tell about how they work, even as it's also kind of a requirement from the investment standpoint.
Very roughly, models develop complex functional internal state about some sub-domains, and merely memorize many examples in others. In reality it's more complicated than this and even in this simplified metaphor it's a mix between memorization and "real" "understanding" in each domain. But the point is that if companies were really working towards AGI, they'd be feeding more data into models with *fewer* parameters (that's how you force a model not to memorize) instead of building bigger and bigger models (expands the illusion of competence through increased capacity to memorize).
But being the only ones with the hardware to train an even-bigger model is one of their few competitive advantages, and signing new deals for even more hardware is one of the only ways they can signal to investors that they'll retain their advantage and thus not be destroyed by a food of competitors. That's also how they can convince the hardware dealers like NVidia to continue with circular investments. So they have to run in that direction, regardless of the scientific merits.
This is why someone like LeCun would leave that side of things.
#LLMs #AI

Replies to comments on my "#LLMs are eroding my career" post
https://human-in-the-loop.bearblog.dev/replies-to-comments-on-my-llms-are-erodi…

Ich glaube die #LLMs halluzinieren garnicht selber. Das ist alles #Merz.
Schluss mit den #Nebenverdiensten!

Ich glaube die #LLMs halluzinieren garnicht selber. Das ist alles #Merz.
Schluss mit den #Nebenverdiensten!

Mid- (ongoing) -pandemic "back to the office" mandates and "use AI" mandates are two sides of the same coin that illustrate just how much "technology" happens at the whims of the CEO class, and any description of generative AI as an "inevitable" or "here to stay" technology that doesn't account for that is propaganda.
#AI #GenAI #LLMs

This afternoon a couple of my CI/CD pipelines broke because a user deleted all their their public repositories from #Github .
I suppose many people are starting to be fed up with all what's going on with big companies stealing our code to train their #LLMs, or maybe it's something else... who knows. It's not like we have a single reason to be discontent with Github / Microsoft.
Anyway... I started reviewing all my projects to ensure that I mirror all my critical dependencies so I don't suffer the same problem again.
#CICD #AI #GenerativeAI #SupplyChain

Apparently somebody posted a #counterexample to the Jacobian conjecture on X last night (found by an LLM). I won’t link that junk site, but somebody added it to Wikipedia already if you care:
#math #LLMs #ai

Thinking about some things that @… said in another thread, and as someone who advocates against AI hype and against the use of most generative AI in most circumstances, I feel it's important to say: many of the ethical issues with using generative AI mirror almost directly the ethical issues with living/working on land stolen by colonists, except that they're less harmful.
Arguments like "well we don't really know whose work it's ripping off this time" and "artists that post their art online know it's going to be looked at; this is the same thing" and "well it's inevitable and everyone's doing it so it's unreasonable to make a big deal about it" directly echo arguments like "well now we don't know whose land it was any more exactly" (yes, we do; you can literally go look up the website of their descendants), or "the natives weren't really using the land anyways", or "it's all in the past now, and it's unavoidable." That unavoidable one is actually somewhat true of using stolen land, at least compared to LLM usage.
If you can see through those lies in the case of AI hype but choose not to do so in the case of colonialism, that says something about your priorities and allegiances.
This is not at all a call for people to talk less about AI; rather it's a call for those who take opposing AI hype seriously to look around and make some noise about other injustices too (I realize many of you already do this).
#AI #LLMs #LandBack #GenAI