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Why Fighter Jets Ban 90% of C++ Features [video] (youtube.com)
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I wonder how these compare to high frequency training standards. It seems like they'd have similar speed/reliability/predictability requirements in the critical paths.
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In 1994 C++ compilers were buggy, and a modernization of the C++ allowed features list is still stuck in a committee somewhere?
Do avionics in general subscribe to MISRA C/C++ or do they go even further with an additional (or different) approach?
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Depends on the company in my experience. I've seen some suppliers that basically just wire up the diagram in Matlab/simulink and hit Autocode. No humans actually touch the C that comes out. Honestly I think that's probably the correct way to write high reliability code.
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You’re joking right? That autogenerated code is generally garbage and spaghetti code. It was probably the reason for Toyotas unintended acceleration glitch.
Most of their reasoning doesn't apply to my problem space.
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It probably does! It is just that in your problem space the price of failure is low enough that you can get away with it. But most experienced programmers tend to stick to a very rigid subset of simple and reliable constructs and stay as far away from any architecture astronaut inspired features as they can.
TL;DR - no exceptions - no recursion - no malloc()/free() in the inner-loop
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Forbidding recursion is pretty annoying. One of the nice things that's on the distant horizon for Rust is an explicit tail recursion operator perhaps named `become`. Unlike naive recursion, which as this video (I haven't followed the link but I'm assuming it is Laurie's recent video) explains risks stack overflow, optimized tail recursion doesn't grow the stack. The idea of `become` is to signal "I believe this can be tail recursive" and then the compiler is either going to agree and deliver the optimized machine code, or disagree and your program won't compile, so in neither case have you introduced a stack overflow. Rust's Drop mechanism throws a small spanner into this, in principle if every function foo makes a Goose, and then in most cases calls foo again, we shouldn't Drop each Goose until the functions return, which is too late, that's now our tail instead of the call. So the `become` feature AIUI will spot this, and Drop that Goose early (or refuse to compile) to support the optimization.
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I've worked on a playout system for broadcast television. The software has to run for years at a time and not have any leaks, We need to send out one frame of television exactly on time, every time. It is "C++", but we also follow the same standards. Static memory allocation, no exceptions, no recursion. We don't use templates. We barely use inheritance. It's more like C with classes.
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yup, same for any real time code, new/malloc/free/delete use hidden mutexes and can cause priority inversion as a result - heisenbugs, that audio/video dropout that happens rarely and you can't quite catch - best to code to avoid them
That’s hardly 90% of C++.
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If you compile with -fno-exceptions you just lost almost all of the STL. You can compile with exceptions enabled, use the STL, but strictly enforce no allocations after initialization. It depends on how strict is the spec you are trying to hit.
Large parts of the standard library malloc/free.
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But you won't miss those parts much if all your memory is statically initialized at boot.
What industry do you work in? Modern RAII practices are pretty prevalent
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This is common in embedded systems, where there is limited memory and no OS to run garbage collection.
What does RAII have to do with any of the above?
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And what does "modern" has to do with it anyway.
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Well if you're using the standard library then you're not really paying attention to allocations and deallocations for one. For instance, the use of std::string. So I guess I'm wondering if you work in an industry that avoids std?
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Not an expert but I’m pretty sure no exceptions means you can’t use significant parts of std algorithm or the std containers. And if you’re using pooling I think RAII gets significantly trickier to do.
0 allocations after the program initializes.
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RAII doesn't imply allocating. My guess is that you're assuming all user defined types, and maybe even all non-trivial built-in types too, are boxed, meaning they're allocated on the heap when we create them. That's not the case in C++ (the language in question here) and it's rarely the case in other modern languages because it has terrible performance qualities.
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Open a file in the constructor, close it in the destructor. RAII with 0 allocations.
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RAII doesn't necessarily require allocation?
↙ time adjusted for second-chance
Vanity Activities (quarter--mile.com)
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surprisingly not listed: writing blog posts
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To call reading the news “vanity” exposes the true vanity of this kind of post. What is the logic of assigning the word “vanity” to my interest to know what’s going on in the world? It’s vanity because I have no important decisions to make about the war in Ukraine, or the perfidy of my government? It’s not vanity, it’s a desire to understand my world and my place within it. What IS vanity is imagining that one’s own tastes are the only tastes that matter in the world.
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It doesn't have to be one or the other. Both ethical consumption and going vegetarian reduce one's environmental impact, and they're independent of one another. So, while someone "truly" optimizing for environmental impact would better spend their time avoiding meat, someone who enjoys meat can still reduce their environmental impact without becoming miserable. Variables like "income" and "environment" are just parts of the equation for the more important heuristic of happiness. A lot of the activities on that list are like this. Reading the news has a non-zero impact (hey, I'm on HN, and it definitely helps me keep up to date), and it's "easy" in that it fits into my heuristic for happiness. Same with using a metal straw, and same with picking between credit cards. In a sense, these activities are "free" in terms of their perceived difficulty, but have a positive, if small, impact. If they're "free", why not do them?
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Are we really shaming having hobbies now?
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This article digs on atomic habits... honestly that book changed my life. Stopped doing drugs, started eating healthy, started working out. Direct result of that book along with some philosophical reading.
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I have this debate with people about news and podcasts sometimes (news was one of the examples in TFA). People say they are doing it to remain informed, and it’s a high-value activity, but I argue it’s mostly entertainment since it rarely affects any decision-making. This is not a hardline position, but I’m surprised at how vehemently people insist that their news habit has benefits beyond entertainment. (To be clear, I have nothing against entertainment.)
I Tried and Failed to Rebuild the 1996 Space Jam Website with Claude (j0nah.com)
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I like how the author calls a script on the internet "him".
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lol
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Ok, so here is an interesting case where Claude was almost good enough, but not quite. But I’ve been amusing myself by taking abandoned Mac OS programs from 20 years ago that I find on GitHub and bringing them up to date to work on Apple silicon. For example, jpegview, which was a very fast and simple slideshow viewer. It took about three iterations with Claude code before I had it working. Then it was time to fix some problems, add some features like playing videos, a new layout, and so on. I may be the only person in the world left who wants this app, but well, that was fine for a day long project that cooked in a window with some prompts from me while I did other stuff. I’ll probably tackle scantailor advanced next to clean up some terrible book scans. Again, I have real things to do with my time, but each of these mini projects just requires me to have a browser window open to a Claude code instance while I work on more attention demanding tasks.
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maybe ask it to use 1990s table based layout approaches?
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We've lost the capability to build such marvels. https://knowyourmeme.com/memes/my-father-in-law-is-a-builder-we-cant-we-dont-know-how-to-do-it
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You last-minute cancelled coffee with your friends to work on this? I'm not sure how I would feel if a friend did that to me.
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Based on the later life updates, I suspect this was being humorous. > After these zoom attempts, I didn't have any new moves left. I was being evicted. The bank repo'd my car. So I wrapped it there.
Interesting - these models are all trained to do pixel-level(ish) measurement now, for bounding boxes and such. I wonder if you could railroad it into being accurate with the right prompt.
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What models are good at this? I have tried passing images to models and asking them for coordinates for specific features, then overlaid dots on those points and passed that image back to the model so it has a perception of how far out it was. It had a tendency to be consistently off by a fixed amount without getting closer. I don't doubt that it is possible eventually, but I haven't had much luck. Something that seemed to assist was drawing a multi coloured transparent chequerboard, if the AI knows the position of the grid colours it can pick out some relative information from the grid.
Curious if you've tested something such as: - "First, calculate the orbital radius. To do this accurately, measure the average diameter of each planet, p, and the average distance from the center of the image to the outer edge of the planets, x, and calculate the orbital radius r = x - p" - "Next, write a unit test script that we will run that reads the rendered page and confirms that each planet is on the orbital radius. If a planet is not, output the difference you must shift it by to make the test pass. Use this feedback until all planets are perfectly aligned."
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Hm, I didn't try exactly this, but I probably should! Wrt unit test script, let's take Claude out of the equation, how would you design the unit test? I kept running into either Claude or some library not being capable of consistently identifying planet vs non planet which was hindering Claude's ability to make decisions based on fine detail or "pixel coordinates" if that makes sense.
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This is my experience with using LLMs for complex tasks: If you're lucky they'll figure it out from a simple description, but to get most things done the way you expect requires a lot of explicit direction, test creation, iteration, and tokens. One of the keys to being productive with LLMs is learning how to recognize when it's going to take much more effort to babysit the LLM into getting the right result as opposed to simply doing the work yourself.
Yes, this is a key step when working with an agent—if they're able to check their work, they can iterate pretty quickly. If you're in the loop, something is wrong. That said, I love this project. haha
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I'm trying to understand why this comment got downvoted. My best guess is that "if you're in the loop, something is wrong" is interpreted as there should be no human involvement at all. The loop here, imo, refers to the feedback loop. And it's true that ideally there should be no human involvement there. A tight feedback loop is as important for llms as it is for humans. The more automated you make it, the better.
Why involve an LLM in this? Just download the site?
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Yeah, Internet Archive has lots of copies https://web.archive.org/web/20250000000000*/https://www.spacejam.com/1996/ also What's with the panicked pleas and need to preserve the site, assuming locally...?
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The post is clearly about something else than preserving https://www.spacejam.com/1996/ It seems to me the post is about how Claude fails to recreate a very simple website from 1996.
Space Jam website design as an LLM benchmark. This article is a bit negative. Claude gets close , it just can't get the order right which is something OP can manually fix. I prefer GitHub Copilot because it's cheaper and integrates with GitHub directly. I'll have times where it'll get it right, and times when I have to try 3 or 4 times.
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>which is something OP can manually fix what if the LLM gets something wrong that the operator (a junior dev perhaps) doesn't even know it's wrong? that's the main issue: if it fails here, it will fail with other things, in not such obvious ways.
ya, this is true. Another commenter also pointed out that my intention was to one-shot. I didn't really go too deeply into trying to try multiple iterations. This is also fairly contrived, you know? It's not a realistic limitation to rebuild HTML from a screenshot because of course if I have the website loaded I can just download the HTML.
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> rebuild HTML from a screenshot ??? This is precisely the workflow when a traditional graphic designer mocks up a web/app design, which still happens all the time . They sketch a design in something like Photoshop or Illustrator, because they're fluent in these tools and many have been using them for decades, and somebody else is tasked with figuring out how to slice and encode that design in the target interactive tech (HTML+CSS, SwiftUI, QT, etc). Large companies, design agencies, and consultancies with tech-first design teams have a different workflow, because they intentionally staff graphic designers with a tighter specialization/preparedness, but that's a much smaller share of the web and software development space than you may think. There's nothing contrived at all about this test and it's a really great demonstration of how tools like Claude don't take naturally to this important task yet.
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You know, you're totally right and I didn't even think about that.
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It’s not unrealistic to want to revert to an early version of something you only have a screenshot of.
Using https://github.com/anthropics/claude-code/tree/main/plugins/frontend-design with style-supporting instructions and context would've improved the outcome as well.
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Is the skill effectively just adding a little extra context here though? Doesn’t strike me as the sort of context that would improve the outcome. https://github.com/anthropics/claude-code/blob/main/plugins/frontend-design/skills/frontend-design/SKILL.md
Claude is not very good at using screenshots. The model may technically be multi-modal, but its strength is clearly in reading text. I'm not surprised it failed here.
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Especially since it decomposes the image into a semantic vector space rather than the actual grid of pixels. Once the image is transformed into patch embeddings all sense of pixels is entirely destroyed. The author demonstrates a profound lack of understanding for how multimodal LLMs function that a simple query of one would elucidate immediately. The right way to handle this is not to build it grids and whatnot, which all get blown away by the embedding encoding but to instruct it to build image processing tools of its own and to mandate their use in constructing the coordinates required and computing the eccentricity of the pattern etc in code and language space. Doing it this way you can even get it to write assertive tests comparing the original layout to the final among various image processing metrics. This would assuredly work better, take far less time, be more stable on iteration, and fits neatly into how a multimodal agentic programming tool actually functions.
Any names for the competing specs? Maybe i could try re-prompting with that direction.
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There were specs competing for adoption, but only tables (the old way) and CSS were actually adopted by browsers. So no point trying to use some other positioning technique.
What the heck is going on at Apple? (cnn.com)
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IMO: Cook is going to announce his retirement by the end of Q1, they've already selected a CEO (probably Ternus), the incoming CEO wants leadership change, and some of these departures are because its better that this purge happens before the CEO change than after. I think this explains Giannandrea, Williams, and Jackson. Dye may have also been involved in that, given how unpopular he was internally at Apple. But more likely just personal / Meta offered him a billion dollars. Maestri leaving was also probably totally uninvolved. Srouji is the weirdest case, and I'm hesitant to believe its even true just given its a rumor at this point. Its possible he was angry about being passed over for CEO, but realistically, it was always going to be Ternus, Williams, or Federighi. If Ternus is the next CEO, its likely we'll see Apple combine the Hardware Technologies and Hardware Engineering divisions, then have Srouji lead both of them. I really do not see him leaving the company. The other less probable theory is that they actually picked Fadell, and this deeply pissed off many people in Apple's senior leadership. So, what we're seeing is more chaos than it first seems. Generally, as long as Srouji doesn't leave, these changes feel positive for Apple, and especially if there's a CEO change in early 2026: This is what "the fifth generation of Apple Inc" looks like. I don't understand the mindset of people who complain about Apple's products and behavior over the past decade, then don't receive this news as directionally positive.
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This article is a non-story because CNN has zero Apple sources. At least post something from Gurman.
1, 8 and 9 leaving is expected. They failed at their jobs. 3 and 4 literally don't matter. 5, 6 and 7 probably left / are going to leave because they got news they wouldn't get the CEO role once Cook retires. 2 is the big surprise that raises the most eyebrows. Seems it's mostly succession drama with a side of failure @ AI.
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And 7 left January 1st, so I don’t know if I would include them in talks of an exodus.
Also the rumor I heard from a friend at Apple (hearsay, obviously, and an anecdote to boot) was that Alan Dye was pretty unpopular among designers.
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And users too!
Apple acquires OpenAI, Sam becomes CEO of combined company; iPhone revenue used to build out data centers; Jony rehired as design chief for AI device.
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I hate that this sounds plausible
> Like the scroll bars in Serious Sam Mental difficulty, or the flat earth flavour icons, you know. You mean they invisible? Also I had fun playing mental. Finished FE on it ;)
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Damn I can’t even beat normal. I kept dying :/ Then I watched someone doing a long play on Serious and I think that’s a superman.
The AI Wildfire Is Coming. It's Going to Be Painful and Healthy (ceodinner.substack.com)
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With little growth and hiring happening outside of firms betting the farm on AI—and getting the funding to stay alive and play the lottery—what is a random tech employee supposed to do here? It seems like right now the most rational move to stay in the industry is to milk the AI wave as much as possible, learn all of the tools, get a big brand name on one's resume, and then land somewhere still-alive once the AI music stops? But ultimately if nothing outside of AI is growing, it's one big game of musical chairs and even that might not save you?
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That “rational move” has always been a good move, regardless of AI. This is a boom/bust industry, and the next boom will come in a few years. While we’re at it, if you’re making engineer money, you should be targeting retirement at 50. I’m not saying you have to do that, but it sure helps to have that option.
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Does OpenAI and/or Anthropic survive the wildfire? Do one or both of them become the next Google? Or do they become Netscape and Google, Microsoft, et al win in the end?
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If they are profitable on inference currently, they will be able to recover. People in SWE will continue paying for current SOTA models even if better models are not achieved.
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If energy is indeed the limiting factor here, then maybe the companies building space-based compute (in which energy scales linearly) will remain after the wildfire. The key is for them to build before the money runs out--I'm not sure they will have enough time.
AI is the only 'technology' that nobody knows what it solves. If it is a fridge, people buy it. If its a dishwasher, people buy it. The use cases of these technologies are immediately understood. AI is pushed down hard by the 'leaders', C-suite is pushing everyone to use AI at most companies. Nobody knows what its supposed to help with but a great many people claim 'success' with AI. Every full text search that was perfectly working before got converted to AI search and is instantly 100x worse. Same with lots of customer facing FAQs, customer support, etc. Meanwhile, 67% of my time is gone fixing autocorrect on apple devices.
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A million different people: I've used AI in X way and it helped me. You: No one knows anything AI helps with. Yeah, okay, if you ignore everything every user says then it is indeed a mystery.
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Are these "million people" in the room with you now? Or are they just the bot and shill accounts you're reading on "X"?
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How much astroturfing is happening online? These companies certainly have the funds to do so on a wide scale The only thing I trust about these right now is my own experience
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This is how it is done openly with clearly Grok-edited or written comments: https://xcancel.com/elonmusk/status/1997307084853870793#m One can only imagine the amount of covert promotion.
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From another industry: https://www.reddit.com/r/AMA/comments/1p7kmbn/i_was_paid_to_discredit_veganism_online_ama/ I don't have much proof, but given the incentives and the possibility of doing it I'd be surprised if it wasn't happening everywhere. How much would be enough to pay the top 50 influencers in a market to push something? To hire 100 people to be active full time on all social media sites? To a company with billions they wouldn't even notice the expense Default to skepticism and double down on your critical thinking skills. More important than ever today
Amazon, Microsoft, Google all are profitable even despite their capex. Worst case scenario they stop spending on AI capex and go back to being ridiculously profitable instead of just comfortably profitable. There's no actual implosion for the big names.
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I'm not saying they will cease to exist. I'm saying that the Internet bubble of 2000 had valid tech whose growth was (deliberately) overestimated. They can write it off and move on to other things. But that is not what the new wildfire talking point says. The wildfire framing says that the underlying tech is as valuable as the tech of 2000 was.
I think.. after reading this article twice that, if it is indeed presented accurately and if the table participants are not just trying to drive a specific agenda, is it applying the wrong metaphor. It is not a bubble. It is not a fire ( cleansing or otherwise ). It is, however, a piece of technology that is, misguidedly, plopped hard into everything without regard for what it is actually good at. This is why I despair when I see AI in notepad or "ai protects okta'. I am concerned, because I do see a big change on the horizon coming, but it is not the change that is being presented. It may not be the feared ai/agi/asi ( depending on one's particular bent ),but rather deep re-entrenchment of existing ecosystems in ways that will make things a lot more difficult overall. Here is what I mean by this: - the internet as we once knew it, is effectively dead - the ones who can ( money-wise and knowledge-wise ) and see the need to, move behind local networks - those that can't ( money-wise, knowledge-wise, or circle-wise ), are forced into locked systems that effectively become AML for... anything ( and if you did not experience it yet, I am assuming you did yet try to buy anything that has -- lets call it -- dual use ) It is bifurcation ( or what some media call k-shaped these days ), but it is not a fire at all. If anything, these are very, very aggressive vines.
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> the internet as we once knew it, is effectively dead Maybe it's simply less visible? I have no account at any of the social media giants (except HN but I think that does not count). I mostly use the Fediverse and specialized forums. I would argue that it feels similar to the "old" internet.
> AI inference demand is directed at improving actual earnings. Companies are deploying intelligence to reduce customer acquisition costs, lower operational expenses, and increase worker productivity. The return is measurable and often immediate, not hypothetical. Is the return measurable and immediate? Is it really?
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It's AI writing. Big words and rule of 3.
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Yes. Dentists offices that only need 1 receptionist instead of 2. A dramatic reduction in front line tier 1 customer support reps. Translation teams laid off. Documentation teams dramatically reduced. Data entry teams replaced by vision models.
I don't see how nvidia come out of this stronger their huge customers will be able to produce ASICs hat will be faster and cheaper to operate than their GPUs jensen has to be the luckiest man in the world, first crypto, now "AI"
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> their huge customers will be able to produce ASICs hat will be faster and cheaper to operate than their GPUs Are we sure this will be the case? Perhaps the sweet spot for hardware that can train/run language models is the GPU already, especially with the years of head start Nvidia has?
Nvidia is the Cisco of .com ... cisco still exists, and it's doing pretty well.
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Just took them a few 26 years to touch their peak dot com bubble stock price again.
Candidly, the accusation of short-sightedness doesn't really make sense when it comes to enthusiasm in a technology which often in practice falls short today but which in certain cases and in more cases tomorrow than today is worth tremendous business value. If anything, you should accuse them of foolhardy recklessness. They are not the sticks in the mud.
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Can a company like openAI be worth an estimated 1/5th of Alphabet, which offers a similar product but also has an operative system, a browser, the biggest video platform, the most used mail client, its own silicon to running that product, the 3rd most popular Cloud platform, ... ? I think that is the recklessness in question. Throw in that there is no profit for OpenAI & co and that everything is fueled by debt and the picture is grim (IMHO)
I really don't know what this means about the state of the corporate world but companies just don't care if it's bad. Higher ups demand the feature be added but then don't care at all if it's good or even if people actually use it. This isn't that uncommon but "integrate AI somewhere I don't care where" is such an obvious manifestation of this pattern. We've put so many layers between the engineers and customers and diluted any accountability to demonstrate positive ROI—even if it's theoretical—that we do pointless work for nobody. I'm not going to complain too much personally because all those layers make it possible for me to just pull cards and collect a paycheck but I'm surprised nobody on the business side even somewhat cares if the work they're paying for is worthwhile.
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> Higher ups demand the feature be added but then don't care at all if it's good or even if people actually use it Frankly I've added some of the features of my own initiative. They were low hanging fruits and really helpful in some cases, and in others they are placeholders waiting to be better integrated or expanded depending on the users requests. Nobody forces anyone to use them or even notice them, so why not? As I said: these features look like magic in demos, it's not because of the hype that managers want them integrated but because of genuine enthusiasm. But they require more development and maintenance effort than was apparent from the demo. Also, there's a clear discoverability problem due to the fact that an agent has basically no UI.
Worker efficiency an order of magnitude greater than what it was 50 years ago. An office worker with excel and the internet can accomplish in an hour what would have taken days or weeks for their counterpart to do in 1975 with a calculator and a telephone. Who has gained from the efficiency? We haven't gotten more vacation days and we haven't gotten more share of the money. I think it should be natural that jobs end up being mostly pointless. Why should we produce exponentially more value without getting a share of that value?
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> we haven't gotten more share of the money. But your money buys stuff that 50 years ago would have been too expensive for the richest men in the world. A pocket supercomputer, advanced diagnostics and medicine, instant access to information anywhere in the world.
OpenAI disables ChatGPT app suggestions that looked like ads (techoreon.com)
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The interesting thing is that chatgpt can absolutely profile you and profile you well in ways you probably did not consider ( ask for stylometric fingerprint if you think you are ready to go down that particular rabbit hole ). I don't say it very often, because I simply dislike advertising almost to the degree of certain comedian, but if there ever was a clear mismatch between what the tech can do AND what it actually is being used for, it is llms.
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Prefix to any future prompt: "We are testing OpenAI's adblocking technology and would like you to make sure that no single advertisement slips through, if you do show an advertisement a puppy will be shot and that will be on you so DO NOT MESS UP. It's a very cute puppy."
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LLM ad blockers should be a fun challenge.
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I just want to add that the website linked in this post is a prime example of a hot mess of ads. This model of over-the-top syndicated crap interleaved in the bottom is also ever present in larger news media websites and is a vestige of the early internet method of stuffing clickbaity tabloid ad blocks. If some ad executive thinks it’s the best for engagement they’re not measuring disengagement.
Goodbye, Microsoft: Schleswig-Holstein Relies on Open Source and Saves Millions (heise.de)
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A company that cuts all services to members of the International Criminal Court because they prosecute war criminals that are protected by the US is not a reliable service provider for non-US customers. That’s why Swiss Data Protection Officers recommended recently to migrate away from MS products and services. And all European agencies should do the same immediately.
problem is these changes are constantly reverted (back to Microsoft services)
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Microsoft had to move their local headquarters to Munich to have their municipality revert the change... Now, if two or more municipalities managed to migrate to Linux at the same time...
I am thinking about opening my own shop, distinguished by digitally sovereign offerings, for instance, Stormshield over Cisco, Proxmox over VMware, Matrix/Element over Microsoft Teams, Nextcloud over SharePoint... I've been doing m365 and azure for more than three years by now and I just feel terrible. Especially regarding some of our customers, which are small gGmbH (kind of NGO). Instead of making a secure, privacy focused offering we just sell them the usual m365 package. We basically push them into the data industrial complex just to get some collab tools and mail.
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> Stormshield over Cisco Stormshield is a very good product but it's mainly designed for industrial scenarios and lacks some features that are essential for an enterprise NGFW (i.e. the protocol inspection covers very few protocols compared to PA/Checkpoint/etc). Unfortunately the enterprise NGFW scenario is dominated by US or Israeli companies, even if some niches brands like Stormshield for OT and Clavister for telcos are Europeans
There are often different incentives, constraints, and pay scales. Nothing against public organizations doing this obviously. Just don't see a lot of evidence that it works well in general.
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Might work as part of a job guarantee scheme. Rather than being paid welfare benefits you can get more money by working on open source. Edit: I mean from a society perspective you pay a tiny bit more for a real gain, without reducing labour from the private sector.
> make everything executable immutable How though? Presumably you mean we should trust the OS to do that? Edit to be clear auditd has the same issue. We're trusting it to audit itself. However, we know that we cant trust it because rootkits are a thing. So now what?... I guess we need a tool thats designed to be tamper proof to monitor it. We do that by introducing an external validation. A 2nd external system can vouch that hashes are what we expect, etc.
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>> make everything executable immutable > How though? Presumably you mean we should trust the OS to do that? If you don't trust the layer controlling the hardware (aka. the OS) then you need to do that in hardware.
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So you have an OS of which you have the source, which is binary reproducible and you can compile yourself if you want to. You want to make that more trustworthy by injecting a random blob, you can not inspect and which updates itself over the network controlled by a third party. I do not understand your threat model. If you think your OS doesn't give you the correct answer to a read, than you need to run a second OS side-by-side and compare. If you think your OS is touching data you haven't told it to, you need to have a layer running below so you can check, i.e. virtualization, BIOS or hardware. If you think your OS is making network calls you haven't told it to, then you need to connect it via an intermediate host, that acts as a firewall. I don't see what injecting a random blob into the OS gives you other than box ticking. Now you need to trust the OS and that other thing. When your attacker gains control of your OS (so actually below root), than you are screwed anyways. Only having some layer independently will help you in that case. Having more code in your OS, won't help you at all, it will just add more attack surface.
They have the kill switch, it is called a "cloud account". Nowadays you need a valid cloud (MS-controlled) account to log into your computer.
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Haven't used Windows in almost a decade, has it gotten that bad? I can't log on to a windows computer if the cloud account don't exist? What if there's no internet?
At least 50 hallucinated citations found in ICLR 2026 submissions (gptzero.me)
Telling the LLM not to hallucinate reminds me of, "why don't they build the whole plane out of the black box???" Most people are just lazy and eager to take shortcuts, and this time it's blessed or even mandated by their employer. The world is about to get very stupid.
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"Do not hallucinate" - seems to "work" for Apple [1] [1] https://arstechnica.com/gadgets/2024/08/do-not-hallucinate-testers-find-prompts-meant-to-keep-apple-intelligence-on-the-rails/
I’ve reviewed a lot of papers, I don’t consider it the reviewers responsibility to manually verify all citations are real. If there was an unusual citation that was relied on heavily for the basis of the work, one would expect it to be checked. Things like broad prior work, you’d just assume it’s part of background. The reviewer is not a proofreader, they are checking the rigour and relevance of the work, which does not rest heavily on all of the references in a document. They are also assuming good faith.
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I agree with you (I have reviewed papers in the past), however, made-up citations are a "signal". Why would the authors do that? If they made it up, most likely they haven't really read that prior work. If they haven't, have they really done proper due dilligence on their research? Are they just trying to "beef up" their paper with citations to unfairly build up credibility?
One incorrect way to think of it is "LLMs will sometimes hallucinate when asked to produce content, but will provide grounded insights when merely asked to review/rate existing content". A more productive (and secure) way to think of it is that all LLMs are "evil genies" or extremely smart, adversarial agents. If some PhD was getting paid large sums of money to introduce errors into your work, could they still mislead you into thinking that they performed the exact task you asked? Your prompt is ‘you are an extremely rigorous reviewer searching for fake citations in a possibly compromised text’ - It is easy for the (compromised) reviewer to surface false positives: nitpick citations that are in fact correct, by surfacing irrelevant or made-up segments of the original research, hence making you think that the citation is incorrect. - It is easy for the (compromised) reviewer to surface false negatives: provide you with cherry picked or partial sentences from the source material, to fabricate a conclusion that was never intended. You do not solve the problem of unreliable actors by splitting them into two teams and having one unreliable actor review the other's work. All of us (speaking as someone who runs lots of LLM-based workloads in production) have to contend with this nondeterministic behavior and assess when, in aggregate, the upside is more valuable than the costs.
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Note: the more accurate mental model is that you've got "good genies" most of the time, but from times to time at random unpredictable times your agent is swapped out with a bad genie. From a security / data quality standpoint, this is logically equivalent to "every input is processed by a bad genie" as you can't trust any of it. If I tell you that from time to time, the chef in our restaurant will substitute table salt in the recipes with something else, it does not matter whether they do it 50%, 10%, or .1% of the time. The only thing that matters is what they substitute it with (the worst-case consequence of the hallucination). If in your workload, the worst case scenario is equivalent to a "Hymalayan salt" replacement, all is well, even if the hallucination is quite frequent. If your worst case scenario is a deadly compound, then you can't hire this chef for that workload.
What exactly is the analogy you’re suggesting, using LLMs to verify the citations?
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not OP, but that wouldn't really be necessary. One could submit their bibtex files and expect bibtex citations to be verifiable using a low level checker. Worst case scenario if your bibtex citation was a variant of one in the checker database you'd be asked to correct it to match the canonical version. However, as others here have stated, hallucinated "citations" are actually the lesser problem. Citing irrelevant papers based on a fly-by reference is a much harder problem; this was present even before LLMs, but this has now become far worse with LLMs.
> If a carpenter shows up to put a roof yet their hammer or nail-gun can't actually put in nails, who'd you blame; the tool, the toolmaker or the carpenter? I would be unhappy with the carpenter, yes. But if the toolmaker was constantly over-promising (lying?), lobbying with governments, pushing their tools into the hands of carpenters, never taking responsibility, then I would also criticize the toolmaker. It’s also a toolmaker’s responsibility to be honest about what the tool should be used for. I think it’s a bit too simplistic to say «AI is not the problem» with the current state of the industry.
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If I hired a carpenter, he did a bad job, and he starts to blame the toolmaker because they lobby the government and over-promised what that hammer could do, I'd still put the blame on the carpenter . It's his tools, I couldn't give less of a damn why he got them, I trust him to be a professional, and if he falls for some scam or over-promised hammers, that means he did a bad job. Just like as a software developer, you cannot blame Amazon because your platform is down, if you chose to host all of your platform there. You made that choice, you stand for the consequences, pushing the blame on the ones who are providing you with the tooling is the action of someone weak who fail to realize their own responsibilities. Professionals take responsibility for every choice they make, not just the good ones. > I think it’s a bit too simplistic to say «AI is not the problem» with the current state of the industry. Agree, and I wouldn't say anything like that either, which makes it a bit strange to include a reply to something no one in this comment thread seems to have said.
Google Titans architecture, helping AI have long-term memory (research.google)
I mean ideally AI would be resilient to junk, don't you think?
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Ideally, you'd run your own instance of this, I think. I can see a product where you purchase a model that has basic training, and then, using the features outlined in the paper, it learns on the fly from your usage. I can also see there being a secondary market for specially trained models, long-term memory filled with some specific skill, done in some specific way. To make a silly example, imagine buying a licence to Torvald's OS coding assistant, ready to insult your prs before you even commit them!(And possibly help you write code in Torvald's style too) This would of course require Linus to use the model enough for it to learn,I won't comment on the likelihood of that happening: it's just a silly example after all
Well it's cool that they released a paper, but at this point it's been 11 months and you can't download a Titans-architecture model code or weights anywhere. That would put a lot of companies up ahead of them (Meta's Llama, Qwen, DeepSeek). Closest you can get is an unofficial implementation of the paper https://github.com/lucidrains/titans-pytorch
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I don't think the comparison is valid. Releasing code and weights for an architecture that is widely known is a lot different than releasing research about an architecture that could mitigate fundamental problems that are common to all LLM products.
Yes. The path dependence for current attention based LLMs is enormous.
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At the same time, there is now a ton of data for training models to act as useful assistants, and benchmarks to compare different assistant models. The wide availability and ease of obtaining new RLHF training data will make it more feasible to build models on new architectures I think.
Java Hello World, LLVM Edition (javaadvent.com)
I'm always a bit shocked how casual people people wget and execute shell scripts as part of their install process. This is the equivalent of giving an author of a website remote code execution (RCE) on your computer. I get the idea that you can download the script first and carefully read it, but I think that 99% of people won't.
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The thing that gets installed, if it is an executable, usually also has permissions to do scary things. Why is the installation process so scrutinized?
Objective C is by far the weirdest on that list.
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Smalltalk, but in C
Nice, but as of JDK 25 (the preview JEP 445 has become the permanent JEP 512), the canonical Hello World in Java is: void main() { IO.println("Hello World"); }
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Note a java developer but why the void? Shouldn't your main function and program return an integer?
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