2026-10-15 18:25:26
Using #llm to OCR is...interesting. I've been trying it on an old hand written card; and it does very well on stuff I can only just about read; but the mistakes are way more subtle than trad OCR; e.g. one misread a 'standard 6' rack' as a 'standard 19" rack' (the other said '61 rack' which is more obviously wrong). The same one also turned 'M/coil mike'…
"LLMs might have meaningful applications in hybrid warfare, as in the use of chemical weapons as a terror weapon (the recent rise of #LLM-backed cyberattacks and LLM astroturfing bots genuinely concerns me), but remain uncompetitive when it comes to actually doing work of substance" — @…
Claude Code today in an otherwise perfectly normal answer
"The gain would be близко to zero — [...]"
In case you are not proofreading your generated texts.
#AI #ClaudeCode #LLM
funniest thing in #LLM news. One man's month-long research to uncover the secrets of the Frontier Labs is another man's "hey I wrote this python deep_think script":
https://xcancel.com/_can1357/stat…
Current #LLM-driven degradation of software seems to follow an eternal pattern of humans and #technology, where the former seek the latter as a shortcut through reality and experience any resistance and complexity as loss and insult. In my publications I’ve called this “prelapsarian programming” bc it betray…
Je viens de publier « Septembre 2026 - je code avec des open weights pour 10 Š 30 € par mois »
#LLM
"An #LLM absolutely cannot produce work to the highest human standards, or even a good human standard at the moment, and it's unlikely that it ever will. Most human work, however, is not done at a good standard. At best it's mediocre, and at worst it's downright horrible" — @…
Debian developer Antoine Le Gonidec just quit the project over its decision not to ban #LLM-assisted code contributions:
Pretending to have a "neutral stance" when faced with fascism is not neutrality, it’s active collaboration.
AI slop is fascism materialized. Stop it whenever you can!
Source:
Je viens de publier « Qu'est-ce que je dois faire signer Š mes clients pour être autorisé Š analyser leurs données confidentielles avec un LLM ? »
#LLM
RE: #LLM's in coding it won't be long before we start seeing som…
RE: #LLM
Thought experiment: if all LLMs would be required to be public domain by law worldwide, would that change acceptance with respect to #copyright ignoring its other downsides such as its huge environmental damage?
#LLM #ai
« Protecting our FLOSS commons from LLMs »
Are we going back to the nineties? It remembers me when some forges disallowed to have compiled binaries for a proprietary operating system.
#llm #ai #freesoftware
I'm sorry, you still have to think.
#AI
RE: #LLM are already covered, somebody comes up wit…
can anyone advise good methods to cope with the nagging feeling that the customer i'm chatting with is really just the output of an #llm. i'm most triggered by "you are absolutely correct" and my "excellent observations" and similar sycophantic compliments. i never thought i'd miss the denial and passive anger of traditional vendor responses...
Your regular reminder:
ALL LLMs are ultimately just autocomplete. There is no thought, no creativity, no consciousness, no insight. It's just autocomplete with infinite monkeys. What turbocharged autocomplete can do is legit impressive, but it is still just turbocharged autocomplete.
Don't give it more credit than it deserves.
#AI
People often assume that LLM output is some kind of neutral "average" of "all knowledge" (or at least, most of the internet), and that perhaps it picks up and amplifies biases already present in the training data, but these are merely innate human biases to begin with. Already, that shouldn't be comforting, given how biased LLM resume-scanning systems are against female-sounding names, for example, but let's put that aside. We can actually see that LLMs also have intentionally engineered biases added to them in custom training steps:
You know all the LLM syncophancy? The way it agrees with whatever the user says, even if that contradicts itself, or something else the user said earlier? Where did that come from? How often in the internet pre-LLMs did you see someone disagree, only for the other person to immediately apologize and back down? Is that the average behavior on Reddit? On other internet forums? Even in private chat messages or on IRC?
In fact, the internet is legendary for the exact opposite behavior? Where did the collective reply-guy tendency of the training data go? It must have been painstakingly trained out of the model by OpenAI. There's a few viable approaches to this, but likely, it involved optimizing for continued conversation and/or some kind of "pleasantness" score, and that kind of optimization always has side effects. More to the point, if we know the big models are doing this kind of intentional tuning, there probably tuning for other stuff too, and in general, the output of the models is much closer to "things OpenAI wants it to say" than "things the internet would naturally have said" than we might suspect.
#AI #LLMs
🐦 #AlephAlpha released #Kolibri, an open-weight #LLM for German and English under the Apache 2.0 license. A
Continuing from last week's demo on reference data, this week we show off how we handle seed data.
#llm
If the net result of LLMs on education is that homework becomes unworkable and is abandoned in favor of in-school work... I am OK with that.
#Homework #Education #AI
#Atlassian nutzt alle Kundendaten für das Training von #KI. Wir erinnern uns an die zahlreichen Fälle, wo man aus #LLM teilweise die Trainingsdaten rekonstruieren konnte. 😜
Atlassian: Wer zahlt, bleibt verschont | D…
The job of management boils down to deciding where to invest company resources to maximize returns.
But saying yes to one thing means saying no to something else. Deciding what gets cut (and getting buy-in for those decisions) is hard! So instead they started agitating for "velocity" in a foolish belief that they would never have to prioritize one idea over another ever again.
#AI #LLM #tech #softwaredevelopment #UX #UXDesign
🎙️ Quick tip if you're testing #STT / #SpeechToText models locally: before you think "what a stupid #LLM is this?" 🤦♂️🤖 — check your microphone. Your system may be recording from th…
If an #LLM does something illegal who should be criminally liable?
Put in terms that might make sense to people who might disagree, an #LLM is a second order distillation. Reality trains the "models" of cognition via evolution. Those that don't die, evolve emotions to guide them towards or away from things. Humans evolved a complex enough system to construct internal models of reality.
Language jams all this stuff together into a(n extremely lossy) representation for transmitting it to other beings with similar direct access to reality. This becomes the first order distillation of experiential reality. Models trained on that corpus are then second order distillations (they are trained in the artifacts produced by the model trained by reality itself).
A lot of things, like threat modeling, require you to tap into that first order model.
“We need to stop letting a small number of private companies, acting and talking in increasingly erratic ways, dictate how we’re supposed to feel about A.I.” Exactly right. Also, most companies get into serious issues when they wilfully misrepresent their products or are actively harming others. It's long overdue this happens the the LLM labs.
#AI #LLM #Compliance
🔬 Grounded in current research on #LLM laziness, underthinking, premature completion and long-horizon agent degradation
🔧 Zero-dependency Node 16 scripts, works with #ClaudeCode, Codex and #Cursor
@… has developed a number of basic measures to combat prompt injections in document-based LLM workflows: #LLM #PromptInjection #ITSecurity
I like people I can vibe with. Not machines to vibe at.
#Programming #AI #LLM
🔀 #FreeLLMAPI stacks the free tiers of 29 #LLM providers behind one #OpenAI-compatible /v1 endpoint — ~4 billion tokens per month across 251 model families and 358 endpoints.
RE: #AI
And one more thing on the Jacobian Conjecture.
I am certain that at least 10 if not 100 mathematicians have tried this exact problem in Fable and also gpt-5.6 Sol with everything turned to 11. Why did an Anthropic employee get the result?
Is it a low probability and they can just try and try to play again beyond the limits of us mere customers? Did this guy get lucky?
Are professional mathematicians maybe holding back the AI by inputting their own ideas how to do it??
#llm #math #jacobian
now I'm not in a position to fall for the sales circus anyway, and likely neither are you, but it will serve as a useful marker of some people's credibility that we can carry into the After Times.
so that's nice at least.
#OpenAI #facebook #googlegemini #XtheNothingApp #LLM #vibeTruth
My pleasure. 😎
#40c3 Sticker
#AI #LLM #Vibecoding
Sourc…
Let's say you're building a house. Normally this involves hiring a whole bunch of experts (either directly or via some company). You need to pay a fair wage for their labor, and you have to pay for all the material they're going to use. Some of them will be more experienced than others. They will sometimes make a mistake. They will sometimes get sick. The whole construction work will probably take a few months, and may get delayed in the process. Some construction material will be wasted. There's also a risk that over the next years, you'll discover that they screwed something up, and have to fix it. But you'll get a reasonably good house.
Now, a kid comes and tells you you don't have to do this. Instead of paying all these people, you can hire him. He's wearing a suit and sunshades. He never laid a brick in his whole life. But he's got this new great technology that will give you a great house in no time. Of course it will cost you, but not as much as the labor of all these people. You try to learn more, and you discover that the technology actually builds and razes a hundred of house-like things a day, until it gets close enough to something that actually resembles a house. There's a lot of wasted energy and material, but you don't have to worry because it's all subsidized (for the time being). You pay less, you get a house that looks just right on the outside and inside, and that seems to work just right.
Of course, there's a real risk that in a few months you'll discover that something is wrong. You may have to pay a lot for a real expert to figure out how things were done, and how to fix them. Or they may not be able to help you. You may be stuck having to call the suit again, and he'll happily come and fix it for you. And by "fix", I mean he will just raze a whole part of the house and start randomly spitting it out again until he gets something that looks about right, and works about right. Of course, it may not really be a good fit for the rest of the house, but you don't want to pay for replacing the whole thing, do you? It may also introduce a completely new issues that will surface in a few months, but that's just how it is.
Welcome to the glorious world of #AI.
#NoAI #NoLLM #LLM
We had difficulties automatically classifying chats, messaging channels, and forums. So we tested several open-weight large language models for our use case. The benchmark is published below, along with a tool supporting the classification process.
This helps us avoid manually classifying channels collected from dark-web forums and social networks, while reliably identifying which channels can be discarded and which deserve further analysis.
🔗 Publication #ai #llm #cybersecurity #darkweb #osint #opensource
Researchers at ETH Zurich and Anthropic have published an impressive study demonstrating just how fragile online anonymity has become. They show that large language models can be used for de-anonymisation on a large scale. With unrestricted internet access, their agent was able to re-identify users of Hacker News and participants in Anthropic interviews with a high degree of accuracy, based solely on pseudonymous online profiles and conversations: #Anonymity #LLM
"The purpose of AI is to give wealth access to skill without giving skill access to wealth."
Well if that's not spot on perfect...
#AI #LLM #GrandTheftAutocomplete
Yet more proof that synthetic users are bullshit.
As with all #AI products, they do not improve "productivity" but create an excuse not to do the task.
AI participants do not help you do research, but to AVOID research. Research is done to *challenge* our assumptions. Synthetic users' only purpose is to allow those assumptions to remain unchallenged.
They are not "research but faster." They are "going with your gut, but with extra steps to cover your ass."
#LLM
📋 #FreeToken is an edge-native #MoE serving engine for running frontier-scale open-weight models on personal, consumer hardware #opensource
It only takes a very rudimentary understanding of economics to see that, in the long run, the market price of running "agentic AI" (or whatever the latest buzz becomes) and the salary of any kind of knowledge worker can only be separated by a gap that's dependent on *management's* ability to tell their output apart.
There is a cosmic-scale gap between the long-term value to a company in paying a salary to a human vs. getting an LLM to "do" the "same" work, but it's a gap that many people are investing heavily in hiding right now, and CEOs and managers become incredibly gullible when you promise them they won't have to deal with humans who might ask for raises, even though it should be obvious you plan to jack up prices once they're locked in. They also aren't well-known for a deep understanding of how their workers actually generate value, and tend to be easily distracted by shiny but shallow demos, which is exactly what LLMs can produce well.
Even in the most optimistic scenario I can imagine for these developments, the myth of upward mobility that's been a lynchpin for defusing class solidarity among wage laborers is going to take a significant beating. There's a completely obvious game plan underway to try to use fascism to shore up the power of the wealthy against any kind of mass movement, and to play the ancient divide-and-conquer game along race and gender lines just as usual, so the range of outcomes is huge, but every time you use an LLM you're pushing this closer to a sharper conflict.
#AI #LLMs
Be sure to exclude your repositories from HuggingFace here:
#AI
In 1999, we surfed the Web. Now we comb through it like a fantasy hero. Which posts are treasure, and which are deadly Mimics? What's real, and what's an impersonator trying to steal my attention?
Worse: reading all this bland AI monoculture text leads to us thinking bland AI monoculture thoughts.
#AI #llm #ux #uxdesign #tech #softwaredevelopment
AI and being "left behind"
#ai
I've taken #Gentoo Bugzilla down, because it was unusable anyway. No point in feeding the #LLM scrapers that are using thousands of different IPv4 addresses, with no obvious patterns I can see.
EDIT: I'm not looking for hints. I'm not a sysadmin, and I don't have time to deal with this shit. I'm just trying to get some useful job done. I'm not supposed to have to be dealing with this.
#AI #NoAI #NoLLM
Here is another scenario how research #mathematics as we know it will die (or is dead already?): Balkanization!
Without speculating about the future, current agentic AI systems can produce very impressive research math, certainly on PhD level, sometimes on Fields medal level. It needs to be post processed, etc. but I think it is an established fact.
#llm #math #ai 🧵
Reading a lot of Linux projects talking about LLMs now, focusing on if they work well enough or not. No talk about ethics, ideals or politics.
If it continues down this path, FLOSS will end up like the Ed Sheeran of software.
#software #foss #floss #libresoftware #linux #lxqt #desktopEnvironment #openSource #ethics #llm #techbros #tech
The AGENTS.md file simply uses up tokens – nothing else. This was the conclusion reached by researchers at ETH Zurich: ‘Surprisingly, we find that providing context files does not generally improve task success rates, while increasing inference cost by over 20% on average.’
#LLM #AgenticCoding #Claude #Codex #Qwen
Measuring the actual quality of AI applications in your business or organisation doesn't get the attention it deserves. Does AI actual deliver, how reliable is it etcetera, all these things can/should be measured and evaluated. This site is a good starting point.
#AI #evaluation #evals #quality #LLM
The crisis of software development comes from two contradictory rules:
- Up-front thinking is Waterfall; we must only learn by shipping
- There's no time for rework, so everything needs to be done right the first time
Bosses thought #AI could break this contradiction. But synthetic insights and vibe code don't actually enable faster discovery & delivery. They are a (poor) alternative to doing these things AT ALL.
#tech #softwareDevelopment #UX #UXDesign #llm
Execs think that AI can magically fix all their org's problems: their data problem, their PDLC problem, their PMF problem.
But AI is not magic. It's just a technology — and like all novel technologies, incorporating it into your process only expands the number of things that can and will go wrong.
#AI #LLM #softwaredevelopment #tech
Handoffs drool, meetings rule. To fully realize our design vision we MUST coordinate with other people, and therefore deliberately design our meetings to be effective. But instead we are ceding the influence that meetings give us, to focus on LLM-powered solipsism.
#tech #UXDesign #SoftwareDevelopment #AI #LLM #UX #design
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
The idea of a "tech industry" has always relied on "computer" being a special kind of medium, akin to alchemy. And if tech demands to be king, AI hype has now elevated LLMs to a king of kings.
But the solipsism has hit a dead end. The only way forward is to recognize that computers are not special.
#tech #ai #llm #softwareDevelopment #UXDesign #UX
The narrative of AI "inevitability" hit a fever pitch in recent weeks. The announcements have the subtext of press releases: it's here, it's powerful. But what IS here, exactly?
For most of us, what's here is severely uninspiring: a system that is mainly good at proliferating "slop grenades." Less "super-intelligence," more "normal SaaS product."
Don't listen to the hype men. Look with your own eyes, and exercise *your own* agency.
#AI #LLM #tech #software #UX