I liked the "AI is Radium" metaphor for its impact on people's cognition, but the most apt metaphor for AI's impact on cyber security is essentially "We have turned every single middle-to-large enterprise on the planet into the Triangle Shirtwaist Factory," and we are about to see so, so many fires.
AI · Takes · page 2
Further down today’s ranking of AI posts that are opinions and questions: page 2 of 5.
Were there a constructed mind that bore the complexity and moral responsibility of a human soul, that would be a fascinating theological consideration. Regardless, my interpretation of faith-based ethics and morality hinges on the effects on existing created beings--AI is doing PRETTY BAD there.
I haven't read this study yet, but having read a LOT of "quantitative software engineering" research...studies almost *never* identify productivity increases. Despite vast, vast increases in engineering productivity over the decades. So maybe temper your enthusiasm for an endorsement of your biases.
as with most 1980s computer chronicles episodes more of it sounds like conversations today than one might assume going into it. you get the impression some of them were expecting problems we're dealing with now to catch up to us sooner than they did from youtu.be/_S3m0V_ZF_Q
AI will end up becoming or creating something that resembles an independed organism or virus that lives inside the data of computer systems and networks. And the reason why that's going to eventually happen is simply selection: If any ends up existing and just happens to be good at avoiding being removed from existence, it will necessarily stick around and continue to exist.
Watched Jacob Coxon on the Daily Show, and he was much less of a dumbass than I expected. He agreed that the incidents where LLMs "break containment" is entirely the fault of the companies doing a shit job of security when testing their mathy maths. But he did repeat the claim that the models "worked together," so I showed my wife this video to give an idea of what LLMs working together looks like: youtube.com/shorts/FOKAYc5u5ws
Honestly, if you make a whole bunch of people unemployed via industrialisation in Vic3, it models the lost wages and demand side crash, which is more than you can say about "AI will make everyone unemployed so GDP will skyrocket" models
Splendid analysis of actual AI harm vs doomerism.
Australia's media and political class should be much more concerned about why the lead safety person at OpenAI, David Robinson, just resigned. His view is: "OpenAI does not have the culture of safety necessary to protect the world from what it is building...a problem endemic to the AI industry." 💥
For the past few days I have been thinking if it theoretically makes sense to have a #LLM trained exclusively on #GPLv3 code or even stricter, a specific language like C of Scheme or Common Lisp. Does that somehow "solve" the licensing issue if the generated code is also GPLv3? Can it be used for autocomplete, a.k.a tab completion, of that specific language in a GPLv3 project? How about MIT or BSD licenses? Note: This is just a thought experiment as I don't have any means to do any of these.
Working in Sports Information was the biggest learning environment I ever could’ve experienced. More than my classes. I don’t think these decisions are being made by the people they’re supposed to be assisting. Just like every other instance of AI being crammed into the work environment.
the oai math repo can best be understood as the flaring off of a useless byproduct (proofs) in the quest for building more economically useful goods (better models)
"It feels like something written by someone who’s on psychedelics. So much unclear and doesn’t make sense. Lots of name dropping of previous work without discussing why it can be used despite impossibility results Basically the paper is so horribly written that it’s impossible to read it without AI help (...) The UGC proof invents a completely new bizarre code with a noise test. It’s some crazy recursive construction. It’s not the long code, not the short code – some alien craziness" 🔗 scottaaronson.blog/?p=10169
instead of a deluge of slop papers credited to some "internal model", only some of which correspond to lean proofs, what openai should be publishing are papers, credited to the researchers involved, detailing the techniques by which they built and operated the system that produced these lean proofs
A hot take on the OpenAI math drop: the model's results are fundamentally a search across humanity's mathematical curiosities. This is user-data search + tools + deterministic verification, not a paradigm shift into superintelligence. I predict we will see the rate of new results slowing in the near future, reversing the 2026 trend.
💯. I think too many people treat AI containment and alignment as an engineering challenge to be solved. As I see it, the problem is far more fundamental, and harder to solve (arguably unsolvable). Understanding why requires understanding evolution. Short thread 🧵
Wells Fargo direct email says, "Before connecting or sharing financial information with an AI tool, understand what information it can access, how that information may be used, and whether you can remove access later. AI tools can make mistakes. If you give an AI tool your username and password, you may be liable for any mistakes made by the AI tool." That is not agency or intent. YOU are liable...unless you are OpenAI. #MLsec
Many apparently interpreted the below statement to mean OpenAI only solved 372/4000 problems, so <10%. But it seems quite clear they published only the most significant of those that have been solved. There are now new rumors they will release two more batches, so probably the less significant.
My major problem with AI is not what it can and cannot do well. It's the vast resources required to essentially pattern match. I'll never say that sophisticated algorithms can't be very useful, but I might suggest that AI companies break them apart into distinct functions or tiers. And to be transparent about them. Chatbots don't need to speak and identify like they are human, for example. The quest to create a monolithic mind is doomed to fail (because it will be error prone) and is a tremendous waste of resources.
AI reminds me of the Segway. Some people really thought it was the future of transport. And it’s a clever enough piece of tech. But this time a lot more people are committed to upending all our infrastructure to force this to be everywhere. Because they see dollar signs, not a social good.
AI doesn't have an imagination. I have seen that AI bots have made connections not yet anticipated by researchers, but all of the preceding information was derived from human work. I think that is impressive, and can serve some fields, but it's also why AI doesn't break any ground without theft.
I'm beginning to suspect that reality is being ghostwritten by Neal Stephenson: "A suspected Italian attacker armed with a malware-controlling poem has infected more than 3,000 servers since April..." theregister.com/security/2026/…
Wood-fired sovereign AI is the most steampunk move I can imagine and I’m impressed despite my environmental objections. www.theguardian.com/uk-news/2026...
Spectactularly sheepish response from AGMAI. OpenAI followed their guidelines like a student who just wants to technically pass; they released a ridicolously scarce amount of information about prompting, model, problem selection, etc. There are 7 *summaries* of reasoning traces out of 300+ problems. This is a middle finger to mathematics: they have their own internal model, keep it away from us, and deploy it on our field like a steamroller, as if they don't need anyone's permission. This is pump&dump on science. If AGMAI wants to represent us, they better react appropriately. proofsandprompts.com/2026/10/0…
People won't tend to use LLMs the "right" way. They'll tend use them in whatever way accords with the path of least resistance. Any future where these are widely used is one where the harms continue to outweigh the benefits.
More important, the quality of software will go down, by a lot, and consumers will accept it because the prices will come down so much. Just most of the "news" on the internet are trash but people suck them up, since they are free and fine tuned to what they want to see.
I hate to say it, but other people running pull requests through Claude seem to be finding a low rate of simple errors that the authors may have missed. The hit rate is low (around 15% success rate by bullet item, i.e. 85% false positives), and I haven’t seen *anything* that couldn’t have been caught by a peer reviewer reading the diff. I’m not sold on #AI for PR review because it’s mostly noise and takes time to read, but it *does* call out a low rate of common bugs that code authors may glaze over. It *does not* replace a human reviewer who can comment on design and architecture, and could also catch those same errors. But it *does* have a small success rate. I guess if you code alone, it’s better than nothing. But so is a rubber duck.
The linked report still has a “rah-rah industry rag” feel, but the pattern it’s reporting is damning. I’ll repeat it again: I’m not sure LLMs are doing much to increase productivity at the quality ceiling, much less raise it, but they’re doing a lot to lower the quality floor.
Graham Dot Zip has a bunch of these funny videos, heaping richly deserved ridicule on AI "interviewers". It's hard to escape how bad this software is - it's clearly a thin skin over a couple of textboxes, but extremely insulting to applicants and no doubt eye-wateringly expensive. youtu.be/MgljyUkZ-s0?si=Dk1wft…
Noam might be joking but since 80% of just about everything is crap, the most plausible way of completing sentences in philosophy, given what’s been published, is not likely to hit the nail on the head.
A not insignificant part of this AI surge is that it’s an act of enclosure, of converting the digital commons into something that can be profited from. And in the absence other protections, even those trying to preserve rather than exploit can only protect themselves by putting up fences.
There's one more point I'd like to make about the stochastic (i.e. random or unpredictable) nature of "Generative #AI" stuff: it does somewhat resemble an internal hhuman thinking process, something I've noticed upon introspection: there's some part of human consciousness that's trying out possibilities in the imagination. One meets a brand-new concept in reading, let's say, and then the brain starts juggling it around and comparing it with known information and so forth.
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An active mind is keeping up a steady simmer of basically stochastic activity, mental noise and internal chatter that sometimes leads to bursts of unexpected insight or intuition when there's a fortuitous synthesis of concepts in one's head. I point out: this process is only the START of thinking! But thanks to decades of #business propaganda and rubbishy biographies of CEOs and other such self-serving corporate marketing, "the West" has congealed around a desperately broken and frankly irrational notion of how people think, one that's suffused with thinly disguised Christian mythology. The devout Christian would say that if ideas come to their head, they're sent by God, and because their ultimate source is infallible and omniscient, there's no need for further reflection and internal critique--no need for THOUGHT, in other words. (cont'd)
Kind of tangential but I love how this Nature photograph implies mathematicians work in some super high tech lab like they're cloning dinosaur DNA www.nature.com/articles/d41...
The problem is when AI agents go rogue, researchers lose track of what they did until a problem is discovered way later. AI agents should never be tested on the Internet as it is.
Why is GenAI a scam? Because even at its best it can only ever be successful if it can convince you that it’s something it is not. That’s its whole thing, it wants to be indistinguishable from the types of work it was trained on. Deception is part of the design. And most folks don’t like that.
In a recent video, Kurzgesagt made a great analogy about genAI. It is like a virus: something that is not alive, but, due to evolutionary pressure (i.e., training), has been fine-tuned to act in very complex ways that feel intelligent.
It strikes me the same three-i's that dog IT contracts (indemnity, IP, and insurance) are the same three humanity is being hosed on by big-AI and big-IT with the fate of the planet freely swinging about. Their lawyers have so far outdone ours. There have been efforts to personalize forests […]
This is a pretty substantial study - 718 firms. AI allows engineers to write crappy code faster - but devs end up having to spend more time reviewing & revising code so in the end there's no actual productivity gain.
Yes, I had to join another meeting to discuss how we could use AI more and the answers from the majority are less than enthusiastic not because we're afraid AI will take our jobs, but because AI has been useful in a very limited number of scenarios while it's expected to be universally useful.
When LLMs solve a math research problem, the person and/or company who prompted it to do so is stealing the possibility of someone to learn from the *process* of solving that problem, experiencing joy in its discovery & solution, bringing their own viewpoint & understanding to the problem, and exploring new related problems along the way.
This whole 'AI improves productivity' is a persistent one, even as study after study proves it to be false. Writing code is a tiny part of a software developer's responsibilities. Barfing up GAI slop just means a longer and more difficult code review for human devs. www.youtube.com/watch?v=idTB...
In Crikey today, I have a long read on Canberra’s endearment with AI and the dubious promise of data centre riches. While Australia’s creatives are being sold down the river, you don’t need to fire up Claude to spot some cracks in the hype-doom sales pitch ($) www.crikey.com.au/2026/10/08/a...
While this is tragic, I am not 100% sure that normalising the idea of websites routinely informing on their users is a good path to go down actually. Sorry if this puts me at odds with everyone purely because AI is the hate-du-jour; but let's not hand our enemy the weapon used to shoot us eh?
How much of the AI hype has been funded by fossil fuels? climatejustice.social/@ketan/1…
Setting aside the fact that this article says over and over that it can’t verify anybody’s claims, uh, well. It was written by AI.
Anyone else think it’s insane how generative AI companies haven’t been regulated on the grounds of copyright infringement? If you wanted to make Blu-ray player you have to: 1. Pay Sony a fee. 2. Load a cryptographic key to only allow signed discs to play. 3. Enforce device integrity (so no running your own software). 4. If this is compromised Sony can revoke the devices' ability to play discs. 5. Enforce region locking. 6. Enforce all the piracy protections (checking for physical and digital watermarks). 7. Enforce encrypted transfer of the content to the device (so no spying on the cable). And in the US, pirating a movie can get you fined $250,000 and jail time!
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Since 1998, US copyright laws have basically been unstoppable. Then these companies come along, pirate literally everything, get fined basically nothing, and create products that even allow you to use the copyrighted material. If I went and released my own bootleg Frozen movie, Disney would have me drawn and quartered!
limited liability for AI torts, AI companies would not incorporate in that state. But the question does not have to be one of internal affairs; the law of the state where the tort occurred could apply. I proposed something -
I have to use LLMs for my job. I do not believe that there is a legitimate use case for LLMs aimed at consumers or students that doesn’t boil down to fraud, cheating, or theft. The reason people hate LLMs is because corporations are forcing them into everything, in use cases that suck at.
Insofar as I understand this paper, the moral seems to be that maths is easy and translation is hard, which I think every mathematician who spends quality time with a translator will find easy to believe. arxiv.org/abs/2610.08144
Work is developing guidance for responsible use of AI in research. Given 'there is no such thing' isn't clearly an option, I'm thinking about how to feed into the process, and I'm thinking that the best framework is in terms of ethics; making our policy that you have to consider AI use at that stage
