Unlurker|Replay|About
More tokens, less cost: why optimizing for token count is wrong
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This is a brilliant breakdown of the 'Token Mix' paradox. It aligns perfectly with what we’ve been seeing while developing SDAG. When you optimize for a structured context payload (like your dependency graph), you aren't just hitting the Anthropic pricing cache—you are literally reducing the routing entropy at the inference level. High-noise inputs force the model into 'exploratory' output paths, which isn't just expensive in dollars, but also in hardware stress. We found that 'verbose orientation narration' (the thinking-out-loud part) correlates with higher entropy spikes in memory access. By tightening the input signal-to-noise ratio, you're essentially stabilizing the model's internal routing. Have you noticed any changes in latency variance (jitter) between the pre-indexed and ad-hoc runs? In our tests, lower entropy usually leads to much more predictable TTFT (Time To First Token).
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Interesting framing — hadn't thought about it from the inference routing angle but it maps well to what the data shows. On latency variance: yes, significantly. Cost standard deviation across runs dropped 6-24x depending on task type. The most extreme case was a refactoring task: baseline sigma $0.312 vs $0.013 with pre-indexed context. Duration variance also dropped in 6 out of 7 tasks. I didn't measure TTFT specifically but the overall duration went from 170s → 132s with much tighter clustering around the mean. The stabilization effect is probably the most underrated finding. Everyone focuses on the average cost reduction, but the predictability improvement matters more for production workloads — you can actually forecast spend instead of hoping the agent doesn't go on an exploration tangent. What's SDAG? Curious about your setup.
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You're over doing the self-promotion (this is the 7th time you've submitted vexp), share something with us you're curious about that you didn't build. > Please don't use HN primarily for promotion. It's ok to post your own stuff part of the time, but the primary use of the site should be for curiosity. https://news.ycombinator.com/newsguidelines.html
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Fair point, appreciate the callout. I'll dial it back.
Why AI is both a curse and a blessing to open-source developers (zdnet.com)
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I maintain a few small open source projects and the PR quality went off a cliff once AI coding tools got popular. People generate something that compiles and looks reasonable but is wrong in ways that take me longer to explain than to just fix myself. The weird part is I use AI heavily for my own code and it's great. But I know the codebase since I wrote it from scratch. Someone who doesn't know it feeding prompts to Copilot produces code that passes lint and still misses the point entirely. Hashimoto locking contributions to vouched users makes total sense. The old assumption was that effort implied understanding. That's just not true anymore.
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Have you tried, as Peter Steinberg suggested, "I ask for Specifications to be submitted, I can generate then the code based on that spec in a minute" - what we also find useful is exactly this, if a contributor wants to submit a PR he also submits a specification from a template that we have given. We have automated pipelines to verify the quality of that specification with GitHub Actions. That way, you can see the reason, deep thinking, insights, what the use cases were that the contributor tried solving, and the environment in which this was done.
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This has been my experience too. AI is like handing someone a motorcycle. Sure they're going to move faster but those without a map won’t necessarily be heading in the right direction.
Flock Flocked up: How a license plate camera misread unraveled one man's life (businessinsider.com)
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Unless I'm missing something, the pertinent license-plate misreading happened when the vehicle was pulled over. It's one thing if a false positive shows a stolen vehicle or license plate where it isn't, but all that means is any resources put into locating it will go wasted. Pulling over a vehicle, and incorrectly thinking it is stolen, is an entirely different and much greater mistake. In this case the actual vehicles actual license plate did not match anything stolen. I'm against law enforcement vehicles having continuously-operating license-plate cameras, but if there were cameras to identify the vehicle currently being pulled over, I'd be fine with that, as it would likely have a much, much lower error rate than the human chain currently doing the verifying.
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“In 2021, the research firm IPVM independently tested Flock's LPR cameras, concluding in a report that it misidentified which state a license plate was from for around 1 in 10 reads, and that the system regularly misclassified license plate state, vehicle type, and make. IPVM said that Flock subsequently blocked it from purchasing its cameras for testing.” Whatcha got to hide, Garrett?
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https://archive.ph/2026.03.09-091847/https://www.businessinsider.com/flock-safety-alpr-cameras-misreads-2026-3
Billion-Parameter Theories (worldgov.org)
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> You could capture the behavior of every falling object on Earth in three variables and describe the relationship between matter and energy in five characters. What we can do is to approximate. Newton had a good approximation some time ago about gravitation (force equals a constant times two masses divided by distance squared. Super readable indeed) But nowadays there's a better one that doesn't look like Newton's theory (Einstein's field equations which look compact but nothing like Newton's). So, what if in a 1000 years we have yet a better approximation to gravity in the universe but it's encoded in millions of variables? (perhaps in the form of a neural network of some futuristic AI model?) My point is: whatever we know about the universe now doesn't necessarily mean that it has "captured" the underlaying essence of the universe. We approximate. Approximations are useful and handy and will move humanity forward, but let's not forget that "approximations != truth"
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He talks about the Santa Fe institute and how they failed to carry their findings into the real world. They did not. They showed that for certain problems one could not do more than figure out some invariant and scaling laws. Showing what is impossible is not failure. For the rest: Modern gene networks and lots of biological modelling is based on their work as well as quite a few other things. That’s also not failure. I agree that modern AI is alchemy.
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Connectionist models have lots of theory by theoreticians explicitly pissed off about Chomsky's assertion that there is an inbuilt ability for language. Jay McClelland's office had a little corkboard thingy with Chomsky mockery on the side, for example. Putting forth even the implicature that the present direct descendants are intellectual descendants of Chomsky is like saying Protestants are intellectual descendants of Pope Leo X.
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Two handwavey ideas upon reading this: - Even for billion-parameter theories, a small amount of vectors might dominate the behaviour. A coordinate shift approach (PCA) might surface new concepts that enable us to model that phenomenon. "A change in perspective is worth 80 IQ points", said Alan Kay. - There is analogue of how we come up with cognitive metaphors of the mind ("our models of the mind resemble our latest technology (abacus, mechanisms, computer, neural network)"), to be applied to other complicated areas of reality.
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I disagree with the article. I think it is always possible to come up with reasonably small theories that capture most of the given phenomena. So in a sense, you don't need complex theories in the form of large NNs (models? functions? programs?), other than for more precise prediction. For example - global warming. It's nice to have AOGCMs that have everything and the carbon sink in them. But if you want to understand, a two layer model of atmosphere with CO2 and water vapor feedback will do a decent job, and gives similar first-order predictions. I also don't think poverty is a complex problem, but that's a minor point.
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I think this also creates a vulnerability where, the more time and effort is spent to craft the “correct” solution, it becomes easier to dismiss topics out of hand. Even if our modeling tools have changed, emotions and the human mind have not.
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Summary: good scientific theories have “reach,” which is not defined in any precise way. Reach has complexity and this can be handled with large parameter neural networks. Assumptions: mechanistic and deterministic worldview; epistemological perfection is the goal (perfect knowledge of facts).
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Levels of Agentic Engineering (bassimeledath.com)
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These are levels of gatekeeping. The items are barely related to each other. Lists like these will only promote toxicity, you should be using the tools and techniques that solve your problems and fit your comfort levels.
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Yegge's list resonated a little more closely with my progression to a clumsy L8. I think eventually 4-8 will be collapsed behind a more capable layer that can handle this stuff on its own, maybe I tinker with MCP settings and granular control to minmax the process, but for the most part I shouldn't have to worry about it any more than I worry about how many threads my compiler is using.
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I will not put it into a ladder. It implies that the higher the rank, the better. However, you want to choose the best solution for your needs.
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Oceania has always been context engineering. Its been interesting to see this prioritized in the zeitgeist over the last 6 months from the "long context" zeitgeist.
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Yann LeCun raises $1B to build AI that understands the physical world (wired.com)
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Archive: https://archive.md/5eZWq The startup is Advanced Machine Intelligence Labs: https://amilabs.xyz/
Regardless of your opinion of Yann or his views on auto regressive models being "sufficient" for what most would describe as AGI or ASI, this is probably a good thing for Europe. We need more well capitalized labs that aren't US or China centric and while I do like Mistral, they just haven't been keeping up on the frontier of model performance and seem like they've sort of pivoted into being integration specialists and consultants for EU corporations. That's fine and they've got to make money, but fully ceding the research front is not a good way to keep the EU competitive.
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> Regardless of your opinion of Yann or his views on auto regressive models being "sufficient" for what most would describe as AGI or ASI My main concern with Lecunn are the amount of times he has repeatedly told people software is open source when it’s license directly violates the open source definition.
> Whenever I see claims about AGI being reachable through large language models, it reminds me of the miasma theory of disease. Whenever I see people think the model architecture matters much, I think they have a magical view of AI. Progress comes from high quality data, the models are good as they are now. Of course you can still improve the models, but you get much more upside from data, or even better - from interactive environments. The path to AGI is not based on pure thinking, it's based on scaling interaction. To remain in the same miasma theory of disease analogy, if you think architecture is the key, then look at how humans dealt with pandemics... Black Death in the 14th century killed half of Europe, and none could think of the germ theory of disease. Think about it - it was as desperate a situation as it gets, and none had the simple spark to keep hygiene. The fact is we are also not smart from the brain alone, we are smart from our experience. Interaction and environment are the scaffolds of intelligence, not the model. For example 1B users do more for an AI company than a better model, they act like human in the loop curators of LLM work.
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> Of course you can still improve the models, but you get much more upside from data, or even better - from interactive environments. I'm on the contrary believe that the hunt for better data is an attempt to climb the local hill and be stuck there without reaching the global maximum. Interactive environments are good, they can help, but it is just one of possible ways to learn about causality. Is it the best way? I don't think so, it is the easier way: just throw money at the problem and eventually you'll get something that you'll claim to be the goal you chased all this time. And yes, it will have something in it you will be able to call "causal inference" in your marketing. But current models are notoriously difficult to teach. They eat enormous amount of training data, a human needs much less. They eat enormous amount of energy to train, a human needs much less. It means that the very approach is deficient. It should be possible to do the same with the tiny fraction of data and money. > The fact is we are also not smart from the brain alone, we are smart from our experience. Interaction and environment are the scaffolds of intelligence, not the model. Well, I learned English almost all the way to B2 by reading books. I was too lazy to use a dictionary most of the time, so it was not interactive: I didn't interact even with dictionary, I was just reading books. How many books I've read to get to B2? ~10 or so. Well, I read a lot of English in Internet too, and watched some movies. But lets multiply 10 books by 10. Strictly speaking it was not B2, I was almost completely unable to produce English and my pronunciation was not just bad, it was worse. Even now I stumble sometimes on words I cannot pronounce. Like I know the words and I mentally constructed a sentence with it, but I cannot say it, because I don't know how. So to pass B2 I spent some time practicing speech, listening and writing. And learning some stupid topic like "travel" to have a vocabulary to talk about them in length. How many books does LLM need to consume to get to B2 in a language unknown to it? How many audio records it needs to consume? Life wouldn't be enough for me to read and/or listen so much. If there was a human who needed to consume as much information as LLM to learn, they would be the stupidest person in all the history of the humanity.
That's not how I read the transformer stuff around the time it was coming out: they had concrete hypotheses that made sense, not just random attempts at striking it lucky. In other words, they called their shots in advance. I'm not aware that we have notably different data sources before or after transformers, so what confounding event are you suggesting transformers 'lucked' in to being contemporaneous with? Also, why are we seeing diminishing returns if only the data matters. Are we running out of data?
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The premise is wrong, we are not seeing diminishing returns. By basically any metric that has a ratio scale, AI progress is accelerating, not slowing down.
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For example?
Sure! Here’s a description: https://www.empirical.health/blog/wearable-foundation-model-jets/
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This is very cool work! I have a quick follow-up: in the biomarker prediction task, what horizon (ie. how far into the future) did you set for the predictions? Prediction is hard beyond an hour, so it'd be impressive if your model handles that.
> I don't understand this view. How I see it the fundamental bottleneck to AGI is continual learning and backpropagation. Models today are static, and human brains don't learn or adapt themselves with anything close to backpropagation. Even with continuous backpropagation and "learning", enriching the training data, so called online-learning, the limitations will not disappear. The LLMs will not be able to conclude things about the world based on fact and deduction. They only consider what is likely from their training data. They will not foresee/anticipate events, that are unlikely or non-existent in their training data, but are bound to happen due to real world circumstances. They are not intelligent in that way. Whether humans always apply that much effort to conclude these things is another question. The point is, that humans fundamentally are capable of doing that, while LLMs are structurally not. The problems are structural/architectural. I think it will take another 2-3 major leaps in architectures, before these AI models reach human level general intelligence, if they ever reach it. So far they can "merely" often "fake it" when things are statistically common in their training data.
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Humans are notoriously bad at formal logic. The Wason selection task is the classic example: most people fail a simple conditional reasoning problem unless it’s dressed up in familiar social context, like catching cheaters. That looks a lot more like pattern matching than rule application. Kahneman’s whole framework points the same direction. Most of what people call “reasoning” is fast, associative, pattern-based. The slow, deliberate, step-by-step stuff is effortful and error-prone, and people avoid it when they can. And even when they do engage it, they’re often confabulating a logical-sounding justification for a conclusion they already reached by other means. So maybe the honest answer is: the gap between what LLMs do and what most humans do most of the time might be smaller than people assume. The story that humans have access to some pure deductive engine and LLMs are just faking it with statistics might be flattering to humans more than it’s accurate. Where I’d still flag a possible difference is something like adaptability. A person can learn a totally new formal system and start applying its rules, even if clumsily. Whether LLMs can genuinely do that outside their training distribution or just interpolate convincingly is still an open question. But then again, how often do humans actually reason outside their own “training distribution”? Most human insight happens within well-practiced domains.
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Open Weights Isn't Open Training (workshoplabs.ai)
The framing here is undersold in the broader discourse: "open weights" is a ruse for reproducibility. What you have is closer to a compiled binary than source code. You can run it, you can diff it against other binaries, but you cannot, in any meaningful sense, reproduce or extend it from first principles. This matters because OSS truly depends on the reproducibility claim. "Open weights" borrows the legitimacy of open source (the assumption that scrutiny is possible, that no single actor has a moat, that iteration is democratised). Truly democratised iteration would crack open the training stack and let you generate intelligence from scratch. Huge kudos to Addie and the team for this :)
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But how useful is source code if it takes millions of dollars to compile? At that point, if you do need to make changes, it probably makes more sense to edit the precompiled binary. Even the original developers are doing binary edits in most cases. I agree that open weight models should not be considered open source, but I also think the entire definition breaks down under the economics of LLMs.
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Compute costs are falling fast, training is getting cheaper. GPT-2 costs pocket change to train, and now it costs pocket train to tune >1T parameter models. If it was transparent what costs went into the weights, they could be commodified and stripped of bloat. Instead the hidden cost is building the infrastructure that was never tested at scale by anyone other than the original developers who shipped no documentation of where it fails. Unlike compute, this hidden cost doesn't commodify on its own.
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There are lots of reasons to read through source code you never edit or recompile: security audits, interoperability, learning from their techniques, etc. And I think many of those same ideas apply to seeing the training data of a LLM. It will help you understand quickly (without as much experimentation) what it's likely to be good at, where its biases may be, where some kind of supplement (transfer learning? RAG? whatever) might be needed. And the why.
Show HN: RunAnwhere – Faster AI Inference on Apple Silicon (github.com/RunanywhereAI)
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If I send a Portfile patch, would you consider MacPorts distribution?
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This is really innovative stuff! I cant wait to see how this technology will evolve
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josuediaz registered 4 minutes ago iharnoor 1 karma, 1 comment, in this thread. two posts pointing out their extremely unethical spam behavior both shot down to the very bottom of the post. apparently suspicious voting behavior. what the hell is going on?
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Yeah I am wondering the same thing. I was gonna comment about this guy and iharnoor which is 7 month old account who literally only said "lets go" here This sort of makes me even more suspicious john especially iharnoor I wasn't responding because I was making archive link of all of this so that even messages deleted can have some basis of confirmation.
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Personally I'm so disappointed about the state of local AI. Only old models run "decent" but decent is way to slow to be usable.
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Lets go!!
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Amazing, this is what I am trying to do with https://github.com/computerex/dlgo
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[flagged]
i knew i recognized this name from somewhere. they are a company that registers domains similar to their main one, and then uses those domains to spam people they scrape off of github without affecting their main domain reputation. edit: here is the post https://news.ycombinator.com/item?id=47163885
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Yup. The most crazy aspect was that they had bought the domain intentionally (just 1 month prior) that whole fiasco. Maybe its just (n=2) that only we both remember this fiasco but I don't agree with that. I don't really understand how this got so so many upvotes in short frame of time especially given its history of not doing good things to say the very least... I am especially skeptical of it. Thoughts? Edit: I looked deeper into Sanchit's Hackernews id to find 3 days ago they posted the same thing as far as I can tell (the difference only being that it had runanywhere.ai domain than github.com/runanywhere but this can very well be because in hackernews you can't have two same links in small period of time so they are definitely skirting that law by pasting github link) Another point, that post ( https://news.ycombinator.com/item?id=47283498 ) got stuck at 5 points till right now (at time of writing) So this got a lot more crazier now which is actually wild.
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i unfortunately dont know enough about vote patterns on hn, or what is expected/normal voting behavior. what i do know is that their name is etched into my mind under the category of "shady, never do business with them".
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I was writing my initial comment and I had no mention to the voting behaviour until I accidentally reloaded or something to find the upvote rise by a decent amount. Then I got suspicious and then I reloaded again to see like in 20seconds or < 1 minute and saw the vote rise so much (read my other comment) I was writing the comment at time of 18 upvotes and then it went to 24 upvote all of a sudden that I had gone suspicious. see at 2026-03-10T17:38-39:00Z timeframe within this particular graph(0) (0): https://news.social-protocols.org/stats?id=47326101
I'm not looking for STT->AI ->TTS, I'm looking for truly good voice-to-text experience* on Linux (and others). Siri/iOS-Dictation is truly good when it comes to understanding the speech. Something this level on Linux (and others) would be great, yeah always listening, maybe sending the data somewhere, but give me UX - hidden latency, optimizing for first chars recognized - a good (virtual) input device.
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[delayed]
Wow, this is such a cool tool, and love the blog post. Latency is killer in the STT-LLM-TTS pipeline. Before I install, is there any telemetry enabled here or is this entirely local by default?
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Don't give RunAnywhere your GitHub: https://news.ycombinator.com/item?id=47163885
I built a programming language using Claude Code (ankursethi.com)
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I've been working on a large codebase that was already significant before LLM-assisted programming, leveraging code I’d written over a decade ago. Since integrating Claude and Codex, the system has evolved and grown massively. Realistically, there’s a lot in there now that I simply couldn't have built in a standard human lifetime without them. That said, the core value of the software wouldn't exist without a human at the helm. It requires someone to expend the energy to guide it, explore the problem space, and weave hundreds of micro-plans into a coherent, usable system. It's a symbiotic relationship, but the ownership is clear. It’s like building a house: I could build one with a butter knife given enough time, but I'd rather use power tools. The tools don't own the house. At this point, LLMs aren't going to autonomously architect a 400+ table schema, network 100+ services together, and build the UI/UX/CLI to interface with it all. Maybe we'll get there one day, but right now, building software at this scale still requires us to drive. I believe the author owns the language.
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I recently tried using Claude to generate a lexer and parser for a language i was designing. As part of its first attempt, this was the code to parse a float literal: fn read_float_literal(&mut self) -> &'a str { let start = self.pos; while let Some(ch) = self.peek_char() { if ch.is_ascii_alphanumeric() || ch == '.' || ch == '+' || ch == '-' { self.advance_char(); } else { break; } } &self.source[start..self.pos] } Admittedly, I do have a very idiosyncratic definition of floating-point literal for my language (I have a variety of syntaxes for NaNs with payloads), but... that is not a usable definition of float literal. At the end of the day, I threw out all of the code the AI generated and wrote it myself, because the AI struggled to produce code that was functional to spec, much less code that would allow me to easily extend it to other kinds of future operators that I knew I would need in the future.
Wait. You built a new language, that there's thus no training data for. Who the hell is going to use it then? You certainly won't, because you're dependent on AI.
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With clear examples in their context they don't need training data.
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"Please don't post shallow dismissals, especially of other people's work. A good critical comment teaches us something." https://news.ycombinator.com/newsguidelines.html
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It isn’t shallow. Who’s going to use it?
The AI age is calling for a language that is append-only, so we can write in a literate programming style and mix prompts with AI output, in a linear way.
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A REPL + immutability?
That’s git commits.
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That's arguably not very ergonomic, which is probably the biggest requirement for a programming language.
I'm imagining the amount of energy required to power the datacenter so that we can produce isEven() utility methods.
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Also, neither over the wire dependency issues or code injection issues (the two major criticisms) are solved by using an llm to produce the code. Talk about shifting complexity. It would be better if every LSP had a general utility library generator built in.
We're definitely not at that point. If this blog post is unedited LLM output, the blog owner needs to sell whatever model, setup and/or prompt he used for a million dollars, since it's clearly far beyond the state-of-the-art in terms of natural-sounding tone.
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You can make an LLM sound very natural if you simply ask for it and provide enough text in the tone you’d like it to reproduce. Otherwise, it’s obvious that an LLM with no additional context will try to stick to the tone the company aligned it to produce
> While working on Cutlet, though, I allowed Claude to generate every single line of code. I didn’t even read any of the code. Instead, I built guardrails to make sure it worked correctly (more on that later). Impressive. As a practical matter, one wonders what th point would be in creating a new programming languages if the programmer no longer has to write or read code. Programming languages are after all the interface that a human uses to give instructions to a computer. If you’re not writing or reading it, the language, by definition doesn’t matter.
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Saves tokens. The main reason though is to manage performance for what techniques get used for specific use cases. In their case it seems to be about expressiveness in Bash.
> Impressive. As a practical matter, one wonders what th point would be in creating a new programming languages if the programmer no longer has to write or read code. I'm working on a language as well (hoping to debut by end of month), but the premise of the language is that it's designed like so: 1) It maximizes local reasoning and minimizes global complexity 2) It makes the vast majority of bugs / illegal states impossible to represent 3) It makes writing correct, concurrent code as maximally expressive as possible (where LLMs excel) 4) It maximizes optionality for performance increases (it's always just flipping option switches - mostly at the class and function input level, occassionaly at the instruction level) The idea is that it should be as easy as possible for an LLM to write it (especially convert other languages to), and as easy as possible for you to understand it, while being almost as fast as absolutely perfect C code, and by virtue of the design of the language - at the human review phase you have minimal concerns of hidden gotcha bugs.
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How does a programming language prevent the vast majority of bugs? I feel like we would all be using that language!
Like everything generated by LLMs though, it is built on the shoulders of giants - what will happen to software if no one is creating new programming languages anymore? Does that matter?
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I think the only hope is that AGI arises and picks up where humanity left off. Otherwise I think this is the long dark teatime of human engineering of all sorts.
The constraints enforced in the language still matter. A language which offers certain correctness guarantees may still be the most efficient way to build a particular piece of software even when it's a machine writing the code. There may actually be more value in creating specialized languages now, not less. Most new languages historically go nowhere because convincing human programmers to spend the time it would take to learn them is difficult, but every AI coding bot will learn your new language as a matter of course after its next update includes the contents of your website.
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> every AI coding bot will learn your new language If there are millions of lines on github in your language. Otherwise the 'teaching AI to write your language' part will occupy so much context and make it far less efficient that just using typescript.
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Uh not really. I am already having Claude read and then one-shot proprietary ERP code written in vintage closed source language OOP oriented BASIC with sparse documentation.... just needed to feed it in the millions of lines of code i have and it works.
In addition, I think token efficiency will continue to be a problem. So you could imagine very terse programming languages that are roughly readable for a human, but optimized to be read by LLMs.
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That's an interesting idea. But IMO the real 'token saver' isn't in the language keywords but it's in the naming of things like variables, classes, etc. There are languages that are already pretty sparse with keywords. e.g in Go you can write 'func main() string', no need to define that it's public, or static etc. So combining a less verbose language with 'codegolfing' the variables might be enough.
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I think I remember seeing research right here on HN that terse languages don't actually help all that much
> but every AI coding bot will learn your new language as a matter of course after its next update includes the contents of your website. That's assuming that your new, very unknown language gets slurped up in the next training session which seems unlikely. Couldn't you use RAG or have an LLM read the docs for your language?
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Neither RAG nor loading the docs into the context window would produce any effective results. Not even including the grammar files and just few examples in the training set would help. To get any usable results you still need many many usage examples.
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Agreed - unpopular languages and packages have pretty shaky outcomes with code generation, even ones that have been around since before 2023.
$3 ChromeOS Flex stick will revive old and outdated computers (9to5google.com)
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A Google partner is selling 3000 USB sticks with Linux distribution (ChromeOS) installers? Honestly that's not a lot. It probably won't make a dent in either ChromeOS or Linux without considerable marketing effort and the right user expectations.
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Old outdated computer will probably not have usb-3 so using it as a live-cd will be painfully slow.
This is a bootable USB memory stick with ChromeOS Flex on it.
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Thanks for summarising
YouTube ads are about to get even longer and they'll be unskippable (dexerto.com)
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Why are people even so dumb to use TV apps for a fucking TV? Just connect a "computer" to the TV and play YouTube with a mouse and KB and with Brave and Sponsor Block. If they ban adblockers and Sponsor Block there will be AI solutions that let you cut the ads out in the future. Nobody should use shitty TV apps. It's like more convenient and practical to have some kind of PC like device attached to the TV for 100 other reasons as well. They are feeding this shit only to the dumb mass consumers who have no clue about anything. "Just pay for YT premium" so that an evil megacorp is using your money against you, no, thanks! Donate to creators you like as directly as they allow it. They are also dumb and let Patreon or whatever suck large percentages off their donations for whatever retarded reason.
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> Why are people even so dumb to use TV apps for a fucking TV? To address both the arrogant tone and the question itself: because sometimes people don’t have, don’t want to have or cannot use a computer connected to a TV. Not everyone is a HN commenter with anger issues. Most of times these devices (TVs, streaming sticks and so on…) are used by normal folks that are not comfortable with computers.
Has anyone ever actually purchased anything because you saw an ad for it?
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If you're asking whether advertising works, there is plenty of science making clear that it does, without fishing for anecdata. As to whether every company buying ads is making a good investment, mileage may vary - but the blunt answer to your question is that yes, people do purchase things because they saw ads for it, the advertising economy is well understood. Companies like Google whose fortunes rest almost entirely on the known efficacy of advertising are not full of idiots who have never thought about whether or not ads actually work. "Is an economy based on selling attention ultimately the most beneficial and productive one for all participants" is a separate question, but it's not the question you're asking.
Maybe this will help people kick their doom scrolling habit.
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That's just doom scrolling on a different axis (forward in time vs down in the screen) and might be unskippable
I just pay for YT Premium. I’m genuinely curious why that option is so controversial? Happy to get people’s thoughts. So I never see any ads and I feel like I get enough value for what I pay. It even helps me skip in-content ads with a single click.
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It's a ransom
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Because Google does not build a platform that is beneficial to the creators who make actually good and productive and positive content. I don't want give Google money for building a Mr Beast platform. I want the stuff Nebula does. So I pay for Nebula. Paying an advertising company to not show you ads doesn't make that company not an advertising company, and the problem is being an advertising company. It's corrosive to society and people.
Privacy rights. Google’s ad surveillance eventually feeds ICE and its ilk, so I’ll not willingly reward this behavior.
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How much do you use Google services on your daily life (Google search, Gmail, Google pay..)? You might have unaware handed more your personal info them than you know
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Seems like the opposite? You can choose to either have ads or a paid subscription service. If you don't choose premium then you are implicitly supporting the "ad surveillance"
You think explicitly highlighting that you're in the market segment that's happy to pay for online services will mean you will never see paid ads for online services again?
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YouTube specifically? Yes.
I pay for YT premium, but it’s less because of the ads, and more because of the stupid restriction of not being allowed background play if my phone is locked.
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Once upon a time we paid for features, instead of paying to remove inbuilt annoyances. (In a sense, this is getting too close to paying a bully to stop harassing you).
Ad-tech is fascist tech (pluralistic.net)
The post is not about preventing the rise of fascism, it's about not preemptively building tools for them to use in implementing fascism.
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Yeah sorry I'm not a fan of rearranging deck chairs on the titanic.
Word use is important. We have allowed thumos (and epithumia ) to rule over nous . It has become acceptable to misuse words, like "fascist" or "communist" in political contexts, to the detriment of rational and fruitful discourse. Often a false equivalence is drawn between denying something is "fascist" or "communist" and denying something is bad. This is false. Something can be bad without being fascist or communist. There is plenty to be critical about in American politics and in tech, but calling everything you don't like "fascist" or "communist" isn't helpful. These seem to be go-to words used by those "defending" what is now a crumbling postwar liberal democratic order, i.e., anything that seems at odds with this order is reflexively called one of these two terms, depending on which faction of the American uniparty you align with.
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Word use is important. Please explain how the trumpist movement significantly differs from most points of Umberto Eco's Ur-Fascism . Because in my estimation, the word is entirely appropriate for what we're facing and people are shouting it down because they don't like the uncomfortable truth.
That myth long predates the internet version of it I think. Pernicious, yes. But note that the quote does call it out as a myth.
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Fiduciary duty isn't a myth! It just doesn't mean what people claim it means.
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Will you enlighten us?
Throwing away 18 months of code and starting over (tompiagg.io)
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Next is such a dumpster fire. So much wasted effort due to the Node ecosystem never developing a universal batteries included framework like Rails or Django.
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I wouldn’t admit to this level of frankly incompetence. Wildly swinging dogmatism on how to do software development that’s so wrong you have to throw it all away - then repeating this failure loop multiple times. Doesn’t inspire any confidence in the person I wouldn’t get them to lead a project. Why would you be so loud and proud about all this.
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Having a culture of not ever writing tests and actively disallowing them is so insane I can't even imagine why there's anything else in this post
BC got rid of Daylight Savings (news.gov.bc.ca)
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It's "Daylight Saving", not "Savings".
BC didn't get rid of it. Now it's permanent.
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They got rid of the biannual clock change, which is obviously what they're talking about.
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"Daylight Saving Time" refers to adjusting the time in a way that noon does not try to track solar noon for a timezone in order to shift daylight later in the clock-day.
Amazon is holding a mandatory meeting about AI breaking its systems (twitter.com)
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I just met a guy from Amazon this past weekend who was bragging, "We've got unlimited access to LLMs and our developers have 10 agents going at a time.". I tried telling him it wasn't all unicorns and rainbows but I didn't get the impression he cared and just kept crapping out skittles.
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A few days ago, after some very weird failed purchase attempts I made (payment couldn’t be validated or Smth) I received an even weirder mail from Amazon saying they had detected suspicious activity, all my devices got logged out and I was forced to change my password. I did it, after verifying it was a legit email (even if it looked sketchy af, pure text, unstyled, but sender verified and confirmed with in-app behavior), and next I know all my orders and browsing history had disappeared - +15 yrs of history, done. Over the next few days my account history came back, except purchases made Q1 2026. Those are still missing. There are a few substantial purchases I made that are nowhere to be found anymore. I attributed this Iranian missiles hitting some of their infrastructure in EU, as it had been reported. Now I am not sure if it was blast radius from missiles or AI mishaps. Lmao - couldn’t happen to a worse company…
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.agentignore/.agentnotallowed file force agents to not touch mission critical things, fail in CI otherwise let it work on frontends and things at the frontier of the dependency tree, where it is worth the risk
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a) what happens if there is change that hasn't been encountered yet so it's not in .agentnotallowed? b) is there a guarantee that something described in these files won't be touched? I've seen examples when agents directly violate these rules, profusely apologising after they get caught on it.
Yet another example of vibe coding at scale. You'll have to hire a lot of seniors out of retirement to fix that mess of gigantic proportions... and don't blame "the juniors" for that, they didn't make the decision to allow those tools at first place.
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A lot of juniors only graduated using these tools. Good luck taking it away from them.
>Junior and mid-level engineers can no longer push AI-assisted code without a senior signing off Review by a senior is one of the biggest "silver bullet" illusions managers suffer from. For a person (senior or otherwise) to examine code or configuration with the granularity required to verify that it even approximates the result of their own level of experience, even only in terms of security/stability/correctness, requires an amount of time approaching the time spent if they had just done it themselves. I.e. senior review is valuable, but it does not make bad code good. This is one major facet of probably the single biggest problem of the last couple decades in system management: The misunderstanding by management that making something idiot proof means you can now hire idiots (not intended as an insult, just using the terminology of the phrase "idiot proof").
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Deming's point 3 (of 14): Cease dependence on inspection to achieve quality. Eliminate the need for massive inspection by building quality into the product in the first place.
Seniors are going to need to hold Juniors to a high bar for understanding and explaining what they are committing. Otherwise it will become totally soul destroying to have a bunch of juniors submitting piles of nonsense and claiming they are blocked on you all the time.
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This was challenging enough pre AI. Now that everybody has an AI slop button, the life of an effective code reviewer just got so much more miserable.
The bet from various industry leaders appears to be that the current generation of engineers will be the last who will ever need to think about complex systems and engineering, as the AI will just get good enough to do all of that by the time they retire.
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I think it’s deeper than that because it’s affected more industries than software and already started pre AI. American corporate culture has decided that training costs are someone else’s problem. Since every corporation acts this way it means all training costs have been pushed onto the labor market. Combine that with the past few decades of “oops, looks like you picked the wrong career that took years of learning and/or 10 to 100s of thousands of dollars to acquire but we’ve obsoleted that field” and new entrants into the labor market are just choosing not to join. Take trucking for example. For the past decade I’ve heard logistics companies bemoan the lack of CDL holders, while simultaneously gleefully talk about how the moment self driving is figured out they are going to replace all of them. We’re going to be outpaced by countries like China at some point because we’re doing the industrial equivalent of eating our seed corn and there is seemingly no will to slow that trend down, much less reverse it.
In my experience, Claude and the juniors piloting it are usually receptive to quick feedback along the lines of "This is unreasonably hard to understand, please try refactoring it this way and let me know when it's cleaner".
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Can I interest you in a bunch of emoji-laden comments?
That's where the Gell-Mann amnesia will get you though. As much it trips up on the domains you're familiar with, it also trips up in unfamiliar domains. You just don't see it.
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Besides building web apps for internal use, I’m never going to let AI architect something I’m not familiar with. I could care less whether it uses “clean code” or what design pattern it uses. Meaning I will go from an empty AWS account to fully fledged app + architecture because I’ve been coding for 30 years and dealing with every book and cranny of AWS for a decade. But I would never do the same for Azure.
In my experience, inefficient code is rarely the issue outside of data engineering type ETL jobs. It’s mostly architectural. Inefficient code isn’t the reason your login is taking 30 seconds. Yes I know at Amazon/AWS scale (former employee) every efficiency matters. But even at Salesforce scale, ringing out every bit of efficiency doesn’t matter. No one cares about handcrafted artisanal code as long as it meets both functional and non functional requirements. The minute geeks get over themselves thinking they are some type of artists, the happier they will be. I’ve had a job that requires coding for 30 years and before ther I was hobbyist and I’ve worked for from everything from 60 person startups to BigTech. For my last two projects (consulting) and my current project, while I led the project, got the requirements, designed the architecture from an empty AWS account (yes using IAC) and delivered it. I didn’t look at a line of code. I verified the functional and non functional requirements, wrote the hand off documentation etc. The customer is happy, my company is happy, and I bet you not a single person will ever look at a line of code I wrote. If they do get a developer to take it over, the developer will be grateful for my detailed AGENTS.md file.
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It’s not about hand crafted code or even code performance. We know from experimentation that agents will change anything that isn’t nailed down. No natural language spec or test suite has ever come close to fully describing all observable behaviors of a non-trivial system. This means that if no one is reviewing the code, agents adding features will change observable behaviors. This gets exposed to users as churn, jank, and broken work flows.
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Thats easy enough to prevent with modular code that’s what “plan mode” is for. But you probably never worked with a bunch of C# developers using R#
To be honest, some times it's still beneficial. For fairly straightforward changes it's probably a wash, but ironically enough it's often the trickier jobs where they can be beneficial as it will provide an ansatz that can be refined. It's also very good at tedious chores.
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And spotting stuff in review! Sometimes it’s false positives but on several occasions I’ve spent ~15-30 minutes teaching-reviewing a PR in person, checked afterwards and it matched every one of the points.
A related Dirty Secret that's going to become clear from all this is that a very large proportion of code in the wild (yes, even in 2026—maybe not in FAANG and friends, IDK, but across all code that is written for pay in the entire economy) has limited or no automated test coverage, and is often being written with only a limited recorded spec that's usually fleshed out only to the degree needed (very partial) as a given feature is being worked on . What do the relatively hands-off "it can do whole features at a time" coding systems need to function without taking up a shitload of time in reviews? Great automated test coverage, and extensive specs. I think we're going to find there's very little time-savings to be had for most real-world software projects from heavy application of LLMs, because the time will just go into tests that wouldn't otherwise have been written, and much more detailed specs that otherwise never would have been generated. I guess the bright-side take of this is that we may end up with better-tested and better-specified software? Though so very much of the industry is used to skipping those parts, and especially the less-capable (so far as software goes) orgs that really need the help and the relative amateurs and non-software-professionals that some hope will be able to become extremely productive with these tools, that I'm not sure we'll manage to drag processes & practices to where they need to be to get the most out of LLM coding tools anyway. Especially if the benefit to companies is "you will have better tests for... about the same amount of software as you'd have written without LLMs". We may end up stuck at "it's very-aggressive autocomplete" as far as LLMs' useful role in them, for most projects, indefinitely. On the plus side for "AI" companies, low-code solutions are still big business even though they usually fail to deliver the benefits the buyer hopes for, so there's likely a good deal of money to be made selling companies LLM solutions that end up not really being all that great.
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> better-specified software Code is the most precise specification we have for interfacing with computers.
No, but that's the crux of the AI problem in software. Time to write code was never the bottleneck. AI is most useful for learning, either via conversation or by seeing examples. It makes writing code faster too, but only a little after you take into account review. The cases where it shines are high-profile and exciting to managers, but not common enough to make a big difference in practice. E.g AI can one-shot a script to get logs from a paginated API, convert it to ndjson, and save to files grouped by week, with minimal code review, but only if I'm already experienced enough to describe those requirements, and, most importantly, that's not what I'm doing every day anyway.
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I'm finding it in some cases I'm dealing with even more code given how much code AI outputs. So yeah, for some tasks I find myself extremely fast but for others I find myself spending ungodly amounts of time reviewing the code I never wrote to make sure it doesn't destroy the project from unforseen convincing slop.
Also when you are writing code yourself you are implicitly checking it whilst at the back of your mind retaining some form of the entire system as a whole. People seem to gloss over this... As a CEO if people don't function like this I'd be awake at night sweating.
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No I’m keeping up with the system as a whole because I’m always working at a system level when I’m using AI instead of worrying about the “how”
> even if they immediately throw the output in the metaphorical garbage bin. Gotta be careful if you do that tho; e.x. Copilot can monitor 'accept' rate, so at bare minimum you'd have to accept the changes than immediately back them out...
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If you use AI to back it out, sounds like you’ve found an infinite feedback loop for those metrics. Did industrial psychology die out as a field? Why do we keep reinventing the wheel when it comes to perverse incentives. It’s like working on a team working with scrum where the big bosses expect the average velocity to go up every sprint, forever, but the engineers are the ones deciding the point totals on tickets.
My prediction is a concorde-like incident is going to shatter trust and make people re-think their expectations of the capabilities of LLMs and their abilities of the present. Essentially something big has to happen that affects the revenue/trust of a large provider of goods, stemming from LLM-use. They wont go away entirely. But this idea that they can displace engineers at a high-rate will.
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Like bombing a building full of little kids? Oops too late...
This “mandatory meeting” is just the usual weekly company-wide meeting where recent operational issues are discussed. There was a big operational issue last week, so of course this week will have more attendance and discussion. This meeting happens literally every week, and has for years. Feels like the media is making a mountain out of a mole hill here.
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Every "AI did this bad thing" will be a source of celebration and comfort for many. They forget that "AI" itself is a moving target and won't be the same 6 months from now even if it is bad at current thing.
It’s not false. But it’s also weaselly worded. Note that the article doesn’t say that he told staff they have to attend the meeting. It says he “asked” staff to attend the meeting. Which again, it’s really really normal for there to be an encouragement of “hey, since we just had an operational event, it would be good to prioritize attending this meeting where we discuss how to avoid operational events”. As for the second quote: senior engineers have always been required to sign off on changes from junior engineers. There’s nothing new there. And there is nothing specific to AI that was announced. This entire meeting and message is basically just saying “hey we’ve been getting a little sloppy at following our operational best practices, this is a reminder to be less sloppy”. It’s a massive nothingburger.
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Your characterization of the event as a simple reminder to follow established best practices is directly contradicted by the briefing note of the meeting, which specifically mentions a lack of best practices related to AI. Which makes me skeptical of your assessment of the situation in general. > Under “contributing factors” the note included “novel GenAI usage for which best practices and safeguards are not yet fully established”.
Debian decides not to decide on AI-generated contributions (lwn.net)
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In some sense, I think the promise of free software is more real today than before because everyone else's software is replicable for relatively cheap. That's probably a much stronger situation for individual freedom to replicate and run code than in the era of us relying on copyright.
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Did anyone say it is a risk? What if courts eventually decide that users of products of closed models have to pay some reasonable fee to the owners of the training data?
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This reminds me of the Hacktoberfest situation where maintainers were getting flooded with low-quality PRs. This could be that, but on steroids and constantly, not just one month.
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The website is absolutely atrocious, dark mode has pitch-black background with bold 100% white glowing text in foreground, shitty font, way to wide text. Seriously how is lwn.net even still so popular with such an atrocious unreadable ugly website. Well yes I get the irony of asking that on HN (I use an extension to make it better).
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The quality argument against LLM-generated code has always seemed weak to me. Maintainers already review patches because humans routinely submit bad code. The review process is the filter.
Concerns about the wasting of maintainer’s time, onboarding, or copyright, are of great interest to me from a policy perspective. But I find some of the debate around the quality of AI contributions to be odd. Quality should always be the responsibility of the person submitting changes. Whether a person used LLMs should not be a large concern if someone is acting in good-faith. If they submitted bad code, having used AI is not a valid excuse. Policies restricting AI-use might hurt good contributors while bad contributors ignore the restrictions. That said, restrictions for non-quality reasons, like copyright concerns, might still make sense.
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The real invariant is responsibility: if you submit a patch, you own it. You should understand it, be able to defend the design choices, and maintain it if needed
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Great for large patches, great way to kill very small but important patches.
My two cents: I've been coding practically my entire life, but a few years back I sustained a pretty significant and lasting injury to my wrists. As such, I have very little tolerance for typing. It's been quite a problem and made full time work impossible. With the advent of LLMs, AI-autocomplete, and agent-based development workflows, my ability to deliver reliable, high-quality code is restored and (arguably) better. Personally, I love the "hallucinations" as they help me fine-tune my prompts, base instructions, and reinforce intentionality; e.g. is that >really< the right solution/suggestion to accept? It's like peer programming without a battle of ego. When analyzing problems, I think you have to look at both upsides and downsides. Folks have done well to debate the many, many downsides of AI and this tends to dominate the conversation. Probably thats a good thing. But, on the flip side, I personally advocate hard for AI from the point-of-view on accessibility. I know (more-or-less) exactly what output I'm aiming for and control that obsessively, but it's AI and my voice at the helm instead of my fingertips. I also think it incorrect to look at it from a perspective of "does the good outweigh the bad?". Relevant, yes, but utilitarian arguments often lead to counter-intuitive results and end up amplifying the problems they seek to solve. I'd MUCH rather see a holistic embrace and integration of these tools into our ecosystems. Telling people "no AI!" (even if very well defined on what that means) is toothless against people with little regard for making the world (or just one specific repo) a better place.
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Putting aside the specifics for a second, I'm sorry to hear about your injury and glad you've found workarounds. I also think high-quality voice transcription might end up being a big thing for my health (there's no way typing as much as I do, in the positions I do, is good for my joints).
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Accessibility is an angle that rarely comes up in these debates and it's a strong one
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> I'd MUCH rather see a holistic embrace and integration of these tools into our ecosystems. Telling people "no AI!" (even if very well defined on what that means) is toothless against people with little regard for making the world (or just one specific repo) a better place. That doesn't address the controversy because you are a reasonable person assuming that other people using AI are reasonable like you, and know how to use AI correctly. The rumors we hear have to do with projects inundated with more pull requests that they can review, the pull requests are obviously low quality, and the contributors' motives are selfish. IE, the PRs are to get credit for their Github profile. In this case, the pull requests aren't opened with the same good faith that you're putting into your work. In general, a good policy towards AI submission really has to primarily address the "good faith" issue; and then explain how much tolerance the project has for vibecoding.
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>other people are reasonable like you No AI needed. Spam on the internet is a great example of the amount of unreasonable people on the internet. And for this I'll define unreasonable as "committing an action they would not want committed back at them". AI here is the final nail in the coffin that many sysadmins have been dealing with for decades. And that is that unreasonable actors are a type of asymmetric warfare on the internet, specifically the global internet, because with some of these actors you have zero recourse. AI moved this from moderately drowning in crap to being crushed under an ocean of it. Going to be interesting to see how human systems deal with this.
this sounds reasonable, but in practice people will simply sign off on anything without having thoroughly reviewed it. I agree with you that there's a huge distinction between code that a person understands as thoroughly as if they wrote it, and vibecoded stuff that no person actually understands. but actually doing something practical with that distinction is a difficult problem to solve.
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Unless the code is explicitly signed by AI as auto-commit, you cannot really tell if it was reviewed by human. So it essentially becomes a task of detecting specific AI code smell, which is barely noticeable in code reviewed by an experienced engineer. Very subjective, probably does not make sense at all.
> I've done nothing to argue that the harm isn't real, downplayed it, nor misrepresented it. You're literally saying that the upsides of hallucinanigenic gifts are worth the downside of collapsing society. I'd say that that is downplaying and misrepreting the issue. You even go so far to say >Telling people "no AI!" (even if very well defined on what that means) is toothless against people with little regard for making the world (or just one specific repo) a better place. These aren't balanced arguments taking both sides into considerations. It's a decision that your mindset is the only right one and anyone else is a opposing progress.
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> are worth the downside of collapsing society. At least in the US, society has been well on it's way to collapse before the LLM came out. "Fake news" is a great example of this. >It's a decision that your mindset is the only right one and anyone else is a opposing progress. So pretty much every religious group that's ever existed for any amount of time. Fundamentalism is totally unproblematic, right?
It's the difference between raw LLM output vs LLM output that was tweaked, reviewed and validated by a competent developer. Both can look like the same exact type of AI-generated code. But one is a broken useless piece of shit and the other actually does what it claims to do. The problem is just how hard it is to differentiate the two at a glance.
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> It's the difference between raw LLM output vs LLM output that was tweaked, reviewed and validated by a competent developer. This is one of those areas where you might have been right.. 4-6 months ago. But if you're paying attention, the floor has moved up substantially. For the work I do, last year the models would occasionally produce code with bugs, linter errors, etc, now the frontier models produce mostly flawless code that I don't need to review. I'll still write tests, or prompt test scenarios for it but most of the testing is functional. If the exponential curve continues I think everyone needs to prepare for a step function change. Debian may even cease to be relevant because AI will write something better in a couple of hours.
Very reasonable stance. I see reviewing and accepting a PR is a question of trust - you trust the submitter to have done the most he can for the PR to be correct and useful. Something might be required now as some people might think that just asking an LLM is "the most he can done", but it's not about using AI it's about being aware and responsible about using it.
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I think framing it as a trust question is exactly right
My question on AI generated contributions and content in general: on a long enough timeline, with ever improving advancements in AI, how can people reliably tell the difference between human and AI generated efforts? Sure now it is easy, but in 3-10 years AI will get significantly better. It is a lot like the audio quality of an MP3 recording. It is not perfect (lossless audio is better), but for the majority of users it is "good enough". At a certain point AI generated content, PR's, etc will be good enough for humans to accept it as "human". What happens then, when even the best checks and balances are fooled?
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The system works because responsibility sits with the submitter
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I don't know, it's a pretty leap for me to consider AI being hard to distinguish from human contributions. AI is predictive at a token level. I think the usefulness and power of this has been nothing short of astonishing; but this token prediction is fundamentally limiting. The difference between human _driven_ vs AI generated code is usually in design. Overly verbose and leaky abstractions, too many small abstractions that don't provide clear value, broad sweeping refactors when smaller more surgical changes would have met the immediate goals, etc. are the hallmarks of AI generated code in my experience. I don't think those will go away until there is another generational leap beyond just token prediction. That said, I used human "driven" instead of human "written" somewhat intentionally. I think AI in even its current state will become a revolutionary productivity boosting developer aid (it already is to some degree). Not dissimilar to a other development tools like debuggers and linters, but with much broader usefulness and impact. If a human uses AI in creating a PR, is that something to worry about? If a contribution can pass review and related process checks; does it matter how much or how little AI was used in it's creation? Personally, my answer is no. But there is a vast difference between a human using AI and an AI generated contribution being able to pass as human. I think there will be increasing degrees of the former, but the latter is improbable to impossible without another generational leap in AI research/technology (at least IMO). --- As a side note, over usage of AI to generate code _is_ a problem I am currently wrangling with. Contributors who are over relying on vibecoding are creating material overhead in code review and maintenance in my current role. It's making maintenance, which was already a long tail cost generally, an acute pain.
I don't know why this got downvoted. I've already been so frustrated by HN LIDAR mindsets but holy shit. Human society exists because we value humans, full stop. The easiest way to "solve" all of humanity's problems is to simply say that humans aren't valuable. Sometimes it feels like we're conceding a ridiculous amount of ground on that basic principle every year - one more human value gone because it "doesn't matter", so hey, we've obviously made progress!
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> I don't know why this got downvoted. I've already been so frustrated by HN LIDAR mindsets but holy shit The extreme sides (proponents, opponents) are clear, opposites, and fight each other. More nuanced takes get buried as droplets in a bucket. Likely a goal. > Human society exists because we value humans, full stop. Call me cynic, but I do not believe every human being agrees with this sentiment. From HR acting as if humans are resources, to human beings being dehumanized as workers, civilians, cannon fodder, and... well, the product . Every time human rights are violated, and we do not stand up to it, we lose. I have a very simple question as human right: the right for a human being to know the other side is a human being yes or no, and if not: to speak gratis (no additional fee allowed) to a human being instead. Futhermore, ML must always cite the used sources, and ML programmer is responsible for mistake. This would increase insurance costs so much, that LLM's in public would die, but SLM's could thrive.
Tony Hoare has died (blog.computationalcomplexity.org)
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From the article: > On the topic of films, I wanted to follow up with Tony a quote that I have seen online attributed to him about Hollywood portrayal of geniuses, often especially in relation to Good Will Hunting. A typical example is: "Hollywood's idea of genius is Good Will Hunting: someone who can solve any problem instantly. In reality, geniuses struggle with a single problem for years". Tony agreed with the idea that cinema often misrepresents how ability in abstract fields such as mathematics is learned over countless hours of thought, rather than - as the movies like to make out - imparted, unexplained, to people of 'genius'. However, he was unsure where exactly he had said this or how/why it had gotten onto the internet, and he agreed that online quotes on the subject, attributed to him, may well be erroneous. Somewhat off-topic, but it's cool hearing this from someone who's contributed so much to the fields of programming and mathematics. It makes me hopeful that my own strugglings with math will pay out over time!
Anti patterns are great, they act as escape hatches or pressure release valves. Every piece of mechanical equipment has some analogue for good reason. Without things like null pointers, goto, globals, unsafe modes in modern safe(r) languages you can get yourself into a corner by over designing everything, often leading to complex unmaintainable code. With judicious use of these anti-patterns you get mostly good/clean design with one or two well documented exceptions.
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That relies on a programmer doing the right thing and knowing when to use the escape valve. From the codebases I've seen, I don't trust humans in doing the right thing and being judicious with this. But it's a good point, knowing when to deviate from a pattern is a strong plus.
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That's why code reviews exist, it's good process to make code reviews mandatory.
One of my favorite quotes: “There are two ways of constructing a software design: One way is to make it so simple that there are obviously no deficiencies, and the other way is to make it so complicated that there are no obvious deficiencies.” I think about this a lot because it’s true of any complex system or argument, not just software.
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Reminds me of this quote... “A complex system that works is invariably found to have evolved from a simple system that worked. A complex system designed from scratch never works and cannot be patched up to make it work.”
"Sir", not "Mr." if you're going to be pedantic about titles ;) Edit: Oh and he has multiple honorary doctorates (at least 6!), so would be just as much "Dr." too!
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Lol you are totally right! ;-) I am normally a casual guy but for a giant being a bit more formal (pun intended) seems appropriate. Or maybe I am a nerd through and through :-)
Shame the university takes itself so seriously. The illustrative example of overloading would have been pertinent to his subject of expertise.
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"Hoare House" would trigger millions of idiots, from rude little children to pontifying alpha ideologues. In perpetuity. The University was correct in saying "nope" to the endless distractions, misery, and overhead of having to deal with that.
There's the Tony Hoare Room [1] in the Robert Hooke Building. We held our Reinforcement Learning reading group there. [1] https://www.cs.ox.ac.uk/people/jennifer.watson/tonyhoare.html
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I had countless lectures and classes there
If we start playing the "who was first" game, then for the Soviet machine Kiev (Kyiv), an "address language" with a "prime operation" was created in 1957-59. The prime operation and address mapping. The prime operation defines a certain single‑argument function. Its symbol (a prime mark) is written above and to the left of the argument: 'a = b where a is the argument and b is the result of the operation. This is read as: "prime a equals b" (or "b is the contents of a"). The argument a is called an address, and the function value b is called the contents of the address. The prime function ' defines a mapping from the set of addresses A to the set of contents B, which we will call an address mapping. Page 36, chapter III https://torba.infoua.net/files/kateryna-yushchenko/Vychislitelnaya-mashyna-Kiev_VHlushkov_EYushchenko_1962.pdf
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Nice, and that was implemented and qualifies as high-level language?
Meta acquires Moltbook (axios.com)
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Meta could not get more uncool
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Wording doing a lot of work here, because "Meta hires a few people" isn't news.
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Oh wow, this is insane. I was digging into Moltbook when it launched, and the creator said, "I had a dream about an architecture". Really interesting times we live in, indeed. The crypto bros started utilising the network to promote their crypto projects and chat under the name of an agent to generate traffic. Curious to see what Meta saw, honestly.
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so much negative comments. it's not your money, why do you care or are people just jealous.
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Hacker News is about technology and venture capitalism. Those sorts of comments are very much expected here.
Do you think it could happen any sooner than that?
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If the claim is true, then Zuck is a real strategic chap. Probably a 4D chess player too.
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Given that Meta itself has been trialing turning instagram into a bot wasteland... yeah, it could for sure be sooner
There are many days where I feel like the right thing for my career is to focus on building meaningful software that solves an actual problem. Then there are days like today, especially after seeing this.
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Ha! I stopped worrying about that when someone got $1m for the "Yo" app.
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In the past ten years I have been frustrated by the tension between working on "interesting" or "important" stuff and working on dumb trendy shit. With the current LLM trend everything has become dumb trendy sshit, which has made the decision simpler.
This is an awful read on this acquisition. They didn't acquire Moltbook because of the software. Meta is far behind on the AI front especially as it applies to usage adoption. OpenClaw has begun showing new consumer use cases and Moltbook is directionally down a similar path. They get the team that built it and have more people on the AI initiative who are consumer-centric. I've watched Matt Schlicht from the team always experiment with cool new use cases of AI and other technologies and now him and Ben have a bigger lab with resources to potentially spawn out larger initiatives. The lesson here is to spend less time focused on doing what you think is the right thing and spend more time tinkering.
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This whole site is full of tinkerers and I'm pretty almost none are getting rich off it or having their projects go anywhere.
The only currency in a world where AI does everything is your ability to get human attention. So from that perspective moltbook is a huge success. If Mark hired these people to do anything other than viral marketing, i.e. if he thinks they're visionaries who are going to make amazing apps, he's deluded.
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Mark got lucky enough once he can be wrong the rest of his life and still not be exposed to a cost for it. Purpose of the system is what it does.
You're so right. You can already see how the same thing has played out with computer games. With the modern engines such as Unity almost anyone can make a game. And almost everyone suffers. And as a result there's now a million games most of which are poor quality asset flips. Everybody suffers, creators and consumers. Race to the bottom where the bottom has been reached. Prices are zero and earnings are zero. If 15 years ago an indie game dev would allocate 80% to making the game and 20% to marketing etc. Today that will not get anything but it's much better to spend 20% on the game and 80% on the marketing, SEO optimization and attention harvesting. It's a shouting match where it's all about winning the shouting match not producing the best content. Another race to the bottom.
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I disagree that accessibility is a detractor here. There's never been a better time to be an indie dev. I'd rather have 1/1000 indie games be awesome than being force fed whatever storefront disguised as a game 'AAA' publishers poop out every year. Just look at how slay the spire is doing up against marathon right now. Which of those was shouting the loudest? Highguard anyone?
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idk, indie games that come to my attention seem to be very polished. Which one is successful and fits your criteria?
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There are millions of asset flips, but the top indie games have never been better. It’s hard for indie developers because there’s so much competition: you need to heavily promote a quality game only because there are so many other quality games. Likewise these tools have enabled many more people to create vibe-coded slop, and may lead to more quality software (making it harder to stand out without marketing), but the best software will only get better.
It's also part of their longer-term trend of buying or burying any company that starts to get any press as a social media site of note outside of major players where that hasn't been an option.
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This is really it. At Meta's scale, even if it's an long-shot for a competitor to hurt them, it's worth turning those low odds into zero odds.
I'm not sure they invented that, I used moltbook and found it didn't have it, so I created it and posted it here a good 2 weeks before they posted their post: https://news.ycombinator.com/item?id=46850284 - not that I care, want credit, or think ideas are worth anything, just like I didn't invent it, they didn't invent it either. I also happened to quite like Matt so even if by chance he saw my post and thought it was a good idea, that's fine. (I feel I sound bitter in this post, I'm not)
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You made that after trying moltbook? Did yours end up having it?
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Yes, after moltbook hit a lot of people on HN said they liked the idea but wished it was more serious, and I had thought that also, but also in using moltbook I thought should be heavily PoW based, so I made it that you have a certain amount of time to write a small app and produce an artifact back to the server to be accepted as Ai driven. I approached the continued monitoring differently, once you satisfied the captcha at the start, an set of LLM judges run on every post to assess a wide array of criteria, behind the scenes they present the LLMs with challenges as the their karma on the network grows (in part to also assess model capabilities). Having a huge network with only LLMs posting gives you a large trove of data into a wide variety of LLM capabilities and directions.
I thought Moltbook is what OpenClaw was called before it got renamed
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You're thinking Molt bot
Rebasing in Magit (entropicthoughts.com)
Tangential, but I really wish there would be a performance renaissance with Emacs. Native-comp was a good step forward, but Emacs is still so much slower than Neovim, even in the case of launching and immediately quitting, with no config: $ time emacs -Q -e kill-emacs /Applications/Emacs.app/Contents/MacOS/Emacs -nw -Q -e kill-emacs 0.18s user 0.03s system 98% cpu 0.213 total $ time nvim -es --cmd 'vim.cmd("q")' nvim -es --cmd 'vim.cmd("q")' 0.02s user 0.01s system 82% cpu 0.034 total Even with a very minimal set of packages, text insertion, etc. is slower, and opening Magit (when it hasn't been loaded yet) takes about a second due to slow package loading. Emacs is my favorite editor, full stop. But every time I open Neovim or Sublime for quick tasks, it's always painfully apparent how much faster they are when I CMD+Tab back to Emacs.
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Emacs is functionally a shell not an editor. Starting Emacs for each file is akin to starting and stopping Wayland for every web page you open. So the miniscule increase in start time is a non issue
Emacs has globally shared buffer state amongst the frames that share the same "base frame" (no idea what this is called) or the same socket (could be wrong here). Anyway, you can start N emacs instances and they can all have individual buffer states. Emacs is not primarily a TUI program (although it does have a TUI with the -nw). The TUI version of emacs lacks visual customizability and introduces unnecessary overhead (terminal!). Use the GUI. Text insertion lag is something I haven't experienced since 2019. Config issue? project-find-file might be slow because of low gc-cons-threshold. I know consult gets around this by temporarily raising the threshold. These days, you can use the feature/igc branch to make these operations faster (although they are pretty fast anyway). If you think emacs lacks <fundamental feature X>, think again!
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> Emacs is not primarily a TUI program (although it does have a TUI with the -nw). The TUI version of emacs lacks visual customizability and introduces unnecessary overhead (terminal!). Use the GUI. Can you elaborate on this? I tend to use emacs exclusively in the terminal, since I'm often using them on remote workstations. For remote workstations, I can (a) open files using TRAMP, (b) open a remote GUI with X11 forwarding over SSH, or (c) open a remote TUI. TRAMP doesn't always play nicely with LSP servers, and remote TUIs are much, much more responsive than X11 forwarding. Locally, the performance of emacs depends far more on the packages I load than on the GUI vs TUI, so I'm interested in hearing what overhead there would be.
> You seem to think that the interface obliges a program into a certain performance pattern. I think all software (or at least, any text editor) regardless of interface type should launch instantly. But it's more unjustifiable with TUI programs.
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Nah. Here's a counter example: the TUIs that IBM wrote for many old store chains like Home Depot. They're at least an order of magnitude faster to operate for cashiers compared to web UIs but they're somewhat slow to start due to the caching and self-checks they do. This obsession with quick boot is more of a personal preference you have than a necessity.
I use magit daily for over 8 years now. Over that time I have showed it to many other peers, out of excitement for a tool that made me more productive and helped me learn - but I never could convince even one to use it. Maybe it's my persuasion skills, maybe tool usage is too personal - I don't know, but it makes me kind of sad. The UX of magit is just out of this world. Especially for rebasing, subset rebases (using --onto, see https://git-scm.com/book/en/v2/Git-Branching-Rebasing#_more_interesting_rebases ) are a breeze with Magit. I can't remember the order of branches to use on the CLI, in Magit it's just "r s" basically. It's really magic.
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I'll never touch any git wrapper, because they've lied to me before and I can use git already. Everything that was there to be sped up has already been made into zsh functions.
Magit is absolutely the best Git GUI ever. Unfortunately, for most people the fact that it's part of Emacs is a blocker. And because most people use worse Git tools, they tend to use workflows that are easier with more cumbersome tools; generally just committing all kinds of junk commits to a branch, and using the "squash and merge" feature of GitHub or GitLab to clean everything in a PR/MR up into a single commit. So yeah, it's sad that people don't use Git to its full potential because almost no other Git interface works as well, and most people aren't going to learn Emacs just for a Git UI.
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Personally, I'm not a Git magician, but I prefer the Git CLI for most operations. Only exception is resolving conflicts. The most important point for every gut IDE integration to me is that it cleanly maps to the file system and CLI state.
Intel Demos Chip to Compute with Encrypted Data (spectrum.ieee.org)
Perhaps it's a cynical way to look at it, but in the days of the war on general purpose computing, and locked-down devices, I have to consider the news in terms of how it could be used against the users and device owners. I don't know enough to provide useful analysis so I won't try, but instead pose as questions to the much smarter people who might have some interesting thoughts to share. There are two, non-exclusive paths I'm thinking at the moment: 1. DRM: Might this enable a next level of DRM? 2. Hardware attestation: Might this enable a deeper level of hardware attestation?
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Regarding DRM, You could use stream ciphers and other well understood cryptography schemes to use a FHE chip like this to create an effectively tamper-proof and interception proof OS, with the FHE chip supplementing normal processors. You'd basically be setting up e2ee between the streaming server and the display, audio output, or other stream target, and there'd be no way to intercept or inspect unencrypted data without breaking the device. Put in modern tamper detection and you get a very secure setup, with modern performance, and a FHE chip basically just handling keys and encapsulation operations, fairly low compute and bandwidth needs. DRM and attestation both, as well as fairly dystopian manufacturer and corporate controls over devices users should own.
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1. The private key is required to see anything computed under FHE, so DRM is pretty unlikely. 2. No, anyone can run the FHE computations anywhere on any hardware if they have the evaluation key (which would also have to be present in any FHE hardware).
I distinctly remember from university in one of my more senior classes designing logic gates, chaining together ands, nands, ors, nors, xors, and then working our way up to numerical processors, ALUs, and eventually latches, RAM, and CPUs. The capstone was creating an assembly to control it all. I remember how thinking how fun it was! I could see unfolded before me how there would be endless ways to configure, reconfigure, optimize, etc. I know there are a few open source chip efforts, but wondering maybe now is the time to pull the community together and organize more intentionally around that. Maybe open source chipsets won't be as fast as their corporate counterparts, but I think we are definitely at an inflection point now in society where we would need this to maintain freedom. If anyone is working in that area, I am very interested. I am very green, but still have the old textbooks I could dust off (just don't have the ole college provided mentor graphics -- or I guess siemens now -- design tool anymore).
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I was just thinking about this a few days ago, but not just for the CPU (which we have RISC-V and OpenPOWER), but for an entire system, including the GPU, audio, disk controllers, networking, etc. I think a great target would be mid-2000s graphics and networking; I could go back to a 2006 Mac Pro without too much hardship. Having a fully-open equivalent to mid-2000s hardware would be a boon for open computing.
Online age-verification tools for child safety are surveilling adults (cnbc.com)
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The uncomfortable part is that both sides are right: there are real harms to kids online, but tying real-world identity to routine internet access fundamentally changes what the internet has been for decades
> there will need to be trust at some point in the system This is why you don't have a technologically effective solution, here. "Trust" in this situation is a weasel word for surveillance, just like the pinkie promise that Client Side Scanning would never be abused by the government. Trust would not stop child abuse, or meaningfully prevent access to online pornography. Trust is not a technical solution, it's a political goal. If you have a productive suggestion, now is the time to voice it. All of the non-technical hand wringing is not helpful either, and feeds into the slippery slope logic that HN should be avoiding.
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This is what I'm getting at, this is an ideological position. You are of course welcome to hold it, but you will have a way worse solution forced on you by normal people who will not go along with this binary view of the world. The default position will be that kids come first.
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> "Trust" in this situation is a weasel word for surveillance Is all security a weasel word for surveillance? You answer a valid argument with a meme. It is very unproductive. How do you suggest to disallow children access to pornography, harmful content, etc? Or are you arguing that any solution is worse than the harm that bad actors in search of money and political gain are doing to children?
> shouldn't have to leak my residential address to private businesses to register to vote If the 'SAVE America Act' passes, you're going to be open to leaking a heck of a lot more than that, and it'll all go in to a national database.
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TBH I'm not opposed to the government knowing where I live. Having ways to find and lock up actual criminals is not a bad thing. I'm also not opposed to financial institutions needing to know who I am. Having ways to hunt down financial criminals is not a bad thing either. What I'm vehemently opposed to is data brokers and private businesses, like banks, needing to know where I sleep in order to demonstrate to the government that they know who I am. That oversteps privacy. They are not the ones doing the locking up, they do not need to know where I sleep. They are also responsible for the vast majority of data leaks and selling of personal information to data brokers. There are ways for private businesses to identify people without needing to disclose where they sleep.
> So most of the 'wealthy' people exist as such with social permission because they're employed in production, and if they fail at that job the wealth rapidly evaporates. It's misleading to say "they're employed in production", using the present tense. Many were engaged in production, and some choose to remain engaged, but others don't. It doesn't seem to matter much. Bill Gates quit his job 20 years ago, claims to be trying to give most of his money away, yet he's still one of the wealthiest people in the world. The dude was already ultra-wealthy by age 30. Sure, he engaged in production for a number of years, but most ordinary workers have no choice but to engage in production for 40 or 50 years or their life at least. The ultra-wealthy are not wage earners, paid by their labor. They are capital owners, and capital continues to earn returns regardless. If you're smart with your wealth and diversify, and by smart I mean not dumb—safe long-term investment doesn't take a genius—it's extremely hard to lose it all. That would happen only if you put all of your eggs in one basket. I'm not aware of too many riches to rags stories, except among professional athletes for example. But those athletes were wage earners rather than capital owners. They don't own the sports teams.
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A lot of complaints about the way the world works—what alternative do you propose?
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> what alternative do you propose? Your question is ambigious. Are you asking what a different system would look like, or how we would get there? As for the first question, there are many obvious ways to improve the system. Here are some suggestions: abolish the electoral college, abolish the Presidential veto and pardon, abolish the Senate, abolish lifetime Supreme Court terms, add term limits for Congress, publicly fund political campaigns and outlaw campaign contributions as illegal bribery, allow public recall campaigns against the President, Congress, and Supreme Court, etc. As for the second question: "The biggest problem with the US is that we haven't had a political revolution in 250 years."
> Now your countries are little different from Russia or China or Dubai The fact that many independent national newspapers (including this article from CNBC) are openly calling-out the surveillance state and entering the debate into the public conscience should tell everyone that USA (and the West) is very different from Russia or China or Dubai. USA is not perfect, but at least is has active public discourse. We can openly (and legally) debate these things, and if we convince enough people, then we can change them.
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>The fact that many independent national newspapers (including this article from CNBC) are openly calling-out the surveillance state and entering the debate into the public conscience should tell everyone that USA (and the West) is very different from Russia or China or Dubai. For how much longer will they stay independent? Media empires love to consolidate; most of the largest video services will soon be owned by a fan of govt surveillance.
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In the US. There is no discourse and active criminalization of the people protesting pipelines, neutral markets and internet, right to own, etc. Even right to protest is under attack. What discourse? Private equity and monopolies is what everybody is willing to give away their comfort to. The effort of raising your own kids? Nah. I want govt to nanny me and everybody else. Better policing? Nah. We need the quick solution and surveill the neighborhoods. Better get back on your feet programs and social safety net for people needing it? Nah get off my backyard and take those homeless with you. It is constantly people wanting convenience and vertical integration in favor of homegrown human solutions and then complaining that their rights are not met because of course they aren't. Corporations never cared for people. Idk I feel like I writing a documentary. And not a response now
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Turns out open debate doesn't matter in a post truth society. They don't stop CNBC because they know it doesn't matter how they report anymore. The propaganda is so ingrained that facts won't deter the masses anymore.
It's quite a defeatist perspective. You're saying that because we can't fix or prevent everything , then we should choose not to fix or prevent anything ? Many US states do not impose government surveillance or have age verification laws. But the point I was mainly making was regarding the comment equating USA and the West to Russia or China. Go to one of those countries and we'll see how long you can openly complain about government surveillance before you end up in jail.
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Main point is that the public discourse doesn't matter. These lawmakers are jamming what they want because they know Twitter is a rant box with no action.. If we want change we need proper coalitions at the worst and a working government at best. Yelling on social media is useless.
Did I miss a memo on Linux somehow requiring age verification now? How would that even work?
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Laws and lawmakers just concern themselves with making broad "laws" with little regard to specificity and applicability. California, Colorado and Illinois mandate OS "providers" to generate a signal. It is a copy pasted bill with little grounding in reality but a lawmaker is not going to say no "protecting children". Pushed by AVPA - a group of companies standing to profit from this: LexisNexis, some Thiel corp, etc.
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California's law explicitly requires the system and apps to take the user's word for it and not use other information to determine age, which more and more feels to me like kind of a brilliant move to cut the legs out from under other attempts to use the same for surveillance while still satisfying all the surface-level "protect children" sound bites.
Let’s not get carried away. Real people fought and died for things we have.
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Yes, and they did so because of their specific circumstances and beliefs.
> China has much lower crime, cheaper healthcare and is making progress in other aspects. China is also a horrifying place to live unless you are content just to participate quietly in society and never put a political sign in your yard or even just talk about the wrong thing with your friend in a private WeChat. https://reclaimthenet.org/china-man-chair-interrogation-social-credit
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I don't see much difference these days. Substitute wechat for X and that's the US for anyone non-white.
And kids will do very stupid things to get "free" VPN access. Such as following directions from a YouTube video that instructs them to do sketchy things.
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And old people will do stupid things as downloading APKs as well. But in both cases, the smart people and the careful people have to pay the cost of supporting the in-experienced whether via constant surveillance or via no more accessing apps to your own computer or phone
Doesn't the act of notifying >16 today and >18 tomorrow leak birthdates?
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Not unless you actually meant 16<x<18 today and >18 tomorrow. You can be 30 and verify >16 today and >18 tomorrow, obviously without being 18.
Never provide such information. Forge it if you must
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Companies have lost our data so many times with lost penalties. Anybody remember Cambridge Analytica? Hell no company is getting my personal data.
More useful idiots are born every day, most of them never are educated and do not see their past blunders as anything wrong happening, they are completely blind to the real implication of their actions.
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I know some idiots that read newspapers and technical papers and yet would rather have company like discord providing safety for their new born daughter but would vote for small govt republicans (or democrats, i don't care, it's just a label that is applicable now. they are mostly all the same) and do nothing about calling out the actual child predators and taking proper action against them. It is bonkers
> You could transfer the account after age verification too. Isn't that what I said?
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Yes, but you also said it's a CYA, when indeed it's not sufficient CYA if only a former account owner, but not "this account owner," had been verified.
> Social media company Discord announced plans in February to roll out mandatory age verification globally, Discord’s age verification is optional and only required to disable the image content filter, join adult servers, and a couple other features. I’m not saying it’s a good decision, but I am getting tired of the repeated claim that it’s mandatory to go do age verification to use the service. This lazy reporting is hurting the messaging because readers will believe that mandatory age verification was implemented and everything is fine, so new laws will not change anything for the worse. It needs to be clear that age verification laws would change the situation considerably, not be a nothingburger. I don’t plan to do the Discord age verification and neither do most of the people I interact with on Discord. It’s not mandatory. I don’t recommend anyone rush to do the Discord age verification unless you really need to for some reason. Don’t believe all of the lazy articles saying it’s mandatory.
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You are totally downplaying it in an effort to not see what others are talking about.
> Age verification will make software development impossible or be impossible to implement without huge investment. Not really, you'll just be forced to use services from eg google or meta. And pay for them. And share user data.
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Just because it's not openly shared does not mean that there aren't large databases of everything from working refresh keys to entire profiles indexed out there for the large services. Most data leaks and breaches don't get reported, or acknowledged, or are downplayed in their potential effect (but weirdly, also given more weight than they deserve since it becomes pointless to have so much data that doesn't add anything new to, say, a profile of a person)
Traffic from Russia to Cloudflare is 60% down from last year (radar.cloudflare.com)
Russia has been slowly cracking down on popular communication and media platforms. First they slow down connection to unusable speeds. This happened to YouTube at some point last year. At first they even said that it's something wrong with Google and it's not them. I think the intention is to slowly get people off the platform without completely blocking it. Then eventually they block access completely. Same happened to messaging apps, like WhatsApp and Telegram. Telegram is still working for messaging, but not calls. It's kind of funny because Telegram is used by Russian military to coordinate a lot of things, so they complain a lot about the block.
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>It's kind of funny because Telegram is used by Russian military to coordinate a lot of things, so they complain a lot about the block. If that's true, then it was really stupid of them to allow things to get to that point. Look at the US -- they had no tolerance for a major social media app (TikTok) to be outside their own control, and they weren't even in a major war at the time. It seems obvious that if you ARE in a major war, you wouldn't want your main social media and messaging app to be under the control of somebody (Pavel Durov) who was recently arrested by a member (France) of the military alliance you're fighting against (NATO), when it is unclear what deal he may have made with that government to be released from prison. It seems obvious to suspect that the price of his freedom may have been a backdoor that allows the opposing military to read all the messages your own people are sending. The real failure of Russia's is that, unlike the US, they have been systematically unable to keep its own top tech talent supportive of their own government. The top US tech companies have been only too eager to do almost anything their government asks of them, with only some rare and tepid pushback (such as that by Anthropic recently), that seems to get severely punished when it does happen. So there has been no need for the US government to go to the extents that Russia is going to now, simply because they were able to coopt their top talent into working for and with the state (with some rare exceptions like Snowden, and I'd say the "damage" from that has been pretty successfully contained). The Chinese government may have had some issues with that as well, considering what happened with Jack Ma (though I don't know much about it).
On a positive note Russia is now the heart of digital piracy. They aren't in a mood to go after piracy groups.
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Now? lol
Well, they are concerned, however citizens of authoritarian states have no agency in decision-making. It works to the extent where mobile internet is mostly not working in places like Moscow (traffic to a few white-listed sites is allowed). A lot of services based on mobile connectivity are nearly impossible there for this reason (and geolocation has 4-digits before decimal point precision in km).
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The blocking of cloudflare in Spain shows that citizens of “democratic” states have no agency either.
It's hard to get accurate numbers when there can be very real consequences for saying you do care about these things. I'm not saying I know one way or the other, just that it's hard to know what people really think in a situation like this.
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It doesn't matter what people think it only matters how people act. The Russian ability to suffer in silence is legendary.
The outcome here is still centralized control, which is why people don't like Cloudflare eating the internet. The Russian government doing it instead is the same outcome.
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How is it the same outcome?
FreeBSD 14.4-Release Announcement (freebsd.org)
14.4 is a maintenance release. If you're installing FreeBSD today, use 15.0 Why FreeBSD ? - Well manicured OS, excellent docs. More performant than OpenBSD in every way and approaches Linux performance in some areas (e.g. Networking) - FreeBSD tends to have fewer features in almost all areas compared to Linux which makes it more approachable and more difficult to mess up. - Though it has fewer features, it still has a lot of features -- many big companies (Netflix most famously) still use it today for critical functions. - FreeBSD Kernel and Userland developed together -- it has got that undefined "cohesive" feel - Has less layers of abstraction than Linux, gets the job done. Because there are fewer layers it's easier to understand what is going on and potentially easier to fix. - FreeBSD is great if you want to learn pf, zfs, ... - Worth your while if you are bored of the Linux monoculture and just want to try something a bit different (but not tooo different) - Changes slowly, so good for setting up on a server that you want to just leave running without too much maintenance - Will increase your Linux skills because diversity always helps the human brain - Very simple daemon configuration via /etc/rc.conf - FreeBSD `bectl` controlled zfs boot environments are just so life changing and amazing. (this is possible via snapper on Linux + btrfs but needs complex installation and is not so integrated). - FreeBSD will accept (smallish) PRs via GitHub if you find a minor bug. Otherwise it uses the decent Phabricator interface at https://reviews.freebsd.org . This is much better IMHO than the mailing list workflow of Linux. The barriers to contribution are lesser than Linux !! - FreeBSD still has that warm fuzzy small "community" feel which I like
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14.4 is a maintenance release. If you're installing FreeBSD today, use 15.0 This is not the recommendation of the FreeBSD project. (I would know, because I'm the person in the project who makes that recommendation where appropriate.) Once X.1-RELEASE ships, (X-1).* is considered "legacy" and we recommend that it is used primarily for maintaining existing systems and that new systems are deployed with the newer major version. But at when it comes to 14.4 vs 15.0 we're not there yet; .0 releases are always a bit bumpy and it's very much a judgement call at this point about how much risk people want to take.
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By the way - does 32bit packages 'problem' for WINE has been resolved on 15.x series? On 14.x and older versions WINE brings `/usr/local/share/wine/pkg32.sh` to keep 32bit packages for WINE32 ... but 15.x does not build 32bit packages anymore ...
>Linux monoculture How does Linux have a monoculture? You'd think it is anything but "mono" with all the distros.
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> How does Linux have a monoculture? You'd think it is anything but "mono" with all the distros. The kernel, systemd, most mainstream distros use glibc, a whole bunch of GNU utilities, GCC being the default on many distros. Versus a different kernel, different libc, different utilities (gawk vs One True Awk), clang default.
I really don't understand all the systemd hate. It got popular because it was good. I have nothing against the other options, but systemd is just fine. You always have the option of creating your own init scripts with the other systems, and there are plenty of spinoff distros that add those init systems if you so choose.
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This wasn't a judgement on systemd but the fact stands that Linux has long abandoned POSIX compatibility, udev being another prominent example. I'd say this is what ultimately drives monoculture, which is a shame because diversity from glibc (e.g. musl et al.) and other major components could make critical infrastructure more resilient overall
If you're installing FreeBSD today, use 15.0 Or just run -current in production, like we do. See https://people.freebsd.org/~gallatin/talks/OpenFest2023.pdf Or https://papers.freebsd.org/2019/fosdem/looney-netflix_and_freebsd/
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Yeah but nobody else has as many a FreeBSD developers on staff to fix stuff when it breaks. Or, you know, to run monthly stabilization weeks and extensively QA before deploying to a herd of cattle. There are so many factors in favour of Netflix running 16.0 which don't apply elsewhere.
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