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Where are you supposed to go if you don't care about growth? (ramones.dev)
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Europe.
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What other industries but tech do any of us bother to talk about finding jobs that align with our values? (Outside of avoiding illegal or immoral work.) I think we were incredibly fortunate before ZIRP went away that we had much greater opportunity to choose companies that appealed to us.
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I can relate to, never cared about any of circus around job applications, unfortunely we are not expected to say we do work for money, we have to want to change the world, leave our mark in the universe.
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> If rent wasn't an issue I'd be working full-time on open-source and spend my spare time cycling. Story of life. Everyone is looking for a middle way between an acceptable work and money. In the order hand, he’s the mythical programmer who is passionate with tech and doesn’t care about money.
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Sounds like you have no motivation and want to coast along. You can only do that in software with the right skills. You have to develop skill - you know, “grow.” If you like stagnant work, you have to find a company requiring that kind of work. Probably not in the software industry.
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> My first thought is to lean towards small companies that are not looking to grow. They are hard to find, and usually have no time/energy to "train" me. If they're not looking to grow themselves then why would they invest in growing you?
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also if they are not looking to grow, they are probably not hiring.
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This seems like a very negative (and wrong?) perspective. Why do you think you’ll earn the same in 5 years? Do you think you’ve learned everything you can about software and business? Companies aren’t hiring you just to complete a specific task that they have right now.
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You're saying the quiet part out loud. It's fine to believe such things, but you have to pretend not to, while using growth for your own interests: demanding more money for some work, or completing the work faster and using the free time for other purposes (entertainment, working another job, etc).
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Kurt Vonnegut wrote that an aspiring writer should take any writing job he or she can get. A hack job will at least keep the creative wheels turning. I think the same applies to software development jobs. Take one where you can learn something, hone your chops. Doesn't have to be your passion, because turning an abstract conception into working software is intrinsically satisfying to someone who appreciates that particular form of magic. Do your own projects on the side and keep your antenna peeled for other opportunities more in line with your own life goals.
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You have two options. One is bootstrap. Do what you care about, and make a dent. If all you want is to be able to sustain a frugal life then this takes less effort, but not that much less than earning far more. The other option is to join a (true) non profit. Some of them do seek growth, but some don't.
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Maybe a government job
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I don’t know where you’re supposed to go, because I certainly wouldn’t hire you at any of the places I’ve worked.
Torture Techniques from CIA Black Sites Were Used at Alligator Alcatraz (forever-wars.com)
I never claimed it was a democracy, either today or in the past. I actually said the opposite.
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Is this a “technically it’s a presidential republic” sort of thing?
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I see. I thought you meant "under Trump the US is not a democracy". Which I think is a pretty common opinion. But now I understand you meant "the US has never been a democracy".
Neither torture nor genocide is recognized anywhere as a human right. After WWII we held trials.
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>Neither torture nor genocide is recognized anywhere as a human right. After WWII we held trials. What do you want to tell me? Of course torture is not a human right. That doesn't change a bit that human rights apply to everyone. Even to the torturer. Sure, we should put him/her in prison for a long time but never does even the torturer loose his/her humanity. That is exactly what distinguishes us from the nazis/fascists.
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Distinguishes us how? If you cannot lose your humanity through torture, can you lose it through mass murder? Or is humanity something you cannot ever take away from anyone? If so, the worst of the nazis still had it. Yet I do know that it can be taken away precisely because you can torture another person until they aren't themselves anymore. That is, in fact, the goal of torture. Believing that the world is not divided into good and evil people also requires me to believe that people of the US have the same capacity for both good and evil as did the people of Nazi Germany
Thinking that the word is divided into evil and non evil people is not very useful.
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Dividing things into useful/not useful isn't very useful.
Richard Stallman on ChatGPT (stallman.org)
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> being capable of knowing or understanding. The definitions of "knowing" and "understanding" are being challenged. Also, it's no longer possible to not have a dependency on other opaque softwares.
The quality and usefulness of the service across different domains, the way it's being rolled out by management, the strategy of building many data centres when this makes questionable sense, the broader social and psychological effects, the stock market precarity around it, the support among LLMs for open source code and weights, and the applicability of the word "intelligence" are all different questions. This reads like more a petulant rant than a cogent and insightful analysis of those issues.
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While I mostly agree with you. I still think he's pretty spot on about the risks of depending on a tool you can't run locally.
If we define intelligence as the ability to understand an unfamiliar phenomenon, create a mental model of it, these models are not intelligent (at least at inference time), as they cannot update their own weights. I'm not sure if these models are trained using unsupervised learning and are capable of training themselves to some degree, but even if so, the learning process of gradient descent is very inefficient, so by the commonly understood definition of intelligence (the ability to figure out and unfamiliar situation), the intelligence of an inference only model is zero. Models that do test time training might be intelligent to some degree, but I wager their current intelligence is marginal at best.
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Intelligence and learning really seem distinct. Does someone who only has a short term memory no longer count as intelligent ? But also he does count much simpler systems as AI, so it's not about learning on the fly or being anything like human intelligence.
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> Intelligence and learning really seem distinct. Yeah. Some people are intelligent, but never learn. /s
I think we can call LLMs artificial intelligence. They don't represent real intelligence. LLMs lack real-life experience, and so they cannot verify any information or claim by experiencing it with their own senses. However, "artificial intelligence" is a good name. Just as artificial grass is not real grass, it still makes sense to include "grass" in its name.
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I'm going to get pedantic. That's why I've been using this exact term "LLM" instead of "AI" for the last few years. The "artificial" implies that it has man-made origins, yet serves the *same* purpose. Richard here argues that it doesn't fit because it does not, in fact, serve the same purpose. You can argue that for certain people it can serve the same purpose, like if you're a CEO who replaces low-level support staff with chatbots - but then it's an artificial support staff, not artificial intelligence.
I never really considered this too deeply, because I've never studied "Agentic AI" before (except for natural language processing). Stallman is making a really good point. ChatGPT doesn't solve the intelligence problem. If ChatGPT was actually able to do that it would be able to make ChatGPT 2.0 on request.
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You're assigning something different to his argument. Here's from the linked page > There are systems which use machine learning to recognize specific important patterns in data. Their output can reflect real knowledge (even if not with perfect accuracy)—for instance, whether an image of tissue from an organism shows a certain medical condition, whether an insect is a bee-eating Asian hornet, whether a toddler may be at risk of becoming autistic, or how well a certain art work matches some artist's style and habits. Scientists validate the system by comparing its judgment against experimental tests. That justifies referring to these systems as “artificial intelligence.” This is nowhere near arguing that it should be able to make new versions of itself.
This seems to be a complaint against general use of "Artificial Intelligence" term: none of it is "real intelligence" as we don't really have a definition for that.
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No, he calls other much simpler things AI.
I prefer using LLM. But many people will ask what is an LLM and then I use AI and they get it. Unfortunate. At the same time, LLMs are not a bullshit generator. They do not know the meaning of what they generate but the output is important to us. It is like saying a cooker knows the egg is being boiled. I care about the egg, cooker can do its job without knowing what an egg is. Still very valuable. Totally agree with the platform approach. More models should be available to be run own own hardware. At least 3rd party cloud provider hardware. But Chinese models have dominated this now. ChatGPT may not last long unless they figure out something, given the "code red" situation is already in their company.
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> At the same time, LLMs are not a bullshit generator. They do not know the meaning of what they generate but the output is important to us. They are a bullshit generator. And "the output" is only important for the CIA.
Before someone replies and does a fallacious comparison along the lines like: "But humans also do 'bullshitting' as well, humans also 'hallucinate' just like LLMs do" . Except that LLMs have no mechanism for transparent reasoning and also have no idea about what they don't know and will go to great lengths to generate fake citations to convince you that it is correct.
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> Except that LLMs have no mechanism for transparent reasoning Humans have transparent reasoning? > and also have no idea about what they don't know So why can they respond saying they don't know things?
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> So why can they respond saying they don't know things? Because sometimes, the tokens for "I don't know" are the most likely, given the prior context + the RLHF. LLMs can absolutely respond that they don't know something or that they were incorrect about sometimes, but I've only seen that happen after first pointing out that they're wrong, which changes the context window to one where such an admission of fault becomes probable.
> Extremely lazy take. He's famously a curmudgeon, not lazy. How would you expect him to respond? > Totally ignoring the history of the field. This criticism is so vague it becomes meaningless. No-one can respond to it because we don't know what you're citing exactly, but you're obviously right that the field is broad, older than most realise, and well-developed philosophically. > Ignoring large and varied debates as to what these words mean. Stallman's wider point (and I think it's safe to say this, considering it's one that he's been making for 40+ years) would be that debating the epistemology of closed-source flagship models is fruitless because... they're closed source. Whether or not he's correct on the epistemology of LLMs is another discussion. I agree with him. They're language models, explicitly, and embracing them without skepticism in your work is more or less a form of gambling. Their undeniable usefulness in some scenarios is more an indictment of the drudgery and simplicity of many people's work in a service economy than conclusive evidence of 'reasoning' ability. We are the only categorically self-aware & sapient intelligence, insofar as we can prove that we think and reason (and I don't think I need to cite this).
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> He's famously a curmudgeon, not lazy. How would you expect him to respond? Not lazily, clearly. You can argue he's not lazy, but this is a very lazy take about LLMs. > Stallman's wider point (and I think it's safe to say this, considering it's one that he's been making for 40+ years) would be that debating the epistemology of closed-source flagship models is fruitless because... they're closed source. You are making that point for him. He is not. He is actively making this fruitless argument . > This criticism is so vague it becomes meaningless. No-one can respond to it because we don't know what you're citing exactly, but you're obviously right that the field is broad, older than most realise, and well-developed philosophically. I don't get what you are missing here then. It's a broad field and LLMs clearly are within it, you can only say they aren't if you don't know the history of the field which is either laziness or deliberate in this case because RMS has worked in the field . I notice he conveniently puts some of his kind of work in this field as "artificial intelligence" that somehow have understanding and knowledge. > embracing them without skepticism in your work That's not a point I'm arguing with. > as we can prove that we think and reason (and I don't think I need to cite this). Can we? In a way we can test another thing? This is entirely distinct from everything else he's saying here as the threshold for him is not "can think and reason like a person" but the barest version of knowledge or understanding which he attributes to exceptionally simpler systems.
He's not wrong. It's not intelligence. It's a simulacrum of intelligence. It can be useful but ought to not be trusted completely. And it's certainly not a boon for freedom and openness.
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"Simulacrum of intelligence" is just "artificial intelligence" with a fancier word.
I think I'd define "classical" AI as any system where, rather that putting in an explicit algorithm, you give the computer a goal and have it "figure out" how to achieve that goal. By that definition, SQL query planners, compiler optimizers, Google Maps routing algorithms, chess playing algorithms, and so on were all "AI". (In fact, I'm pretty sure SQLite's website refers to their query planner as an "AI" somewhere; by classical definitions this is correct.) But does an SQL query planner "understand" databases? Does Stockfish "understand" chess? Does Google Maps "understand" roads? I doubt even most AI proponents would say "yes". The computer does the searching and evaluation, but the models and evaluation functions are developed by humans, and stripped down to their bare essentials.
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RMS might say yes, here's from the linked page describing other things as having knowledge and understanding: > There are systems which use machine learning to recognize specific important patterns in data. Their output can reflect real knowledge (even if not with perfect accuracy)—for instance, whether an image of tissue from an organism shows a certain medical condition, whether an insect is a bee-eating Asian hornet, whether a toddler may be at risk of becoming autistic, or how well a certain art work matches some artist's style and habits. Scientists validate the system by comparing its judgment against experimental tests. That justifies referring to these systems as “artificial intelligence.”
Show HN: AlgoDrill – Interactive drills to stop forgetting LeetCode patterns (algodrill.io)
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Nice, you have identified shovel very well.
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I like the idea, and you've got yourself a customer :) The lifetime membership + launch discount was a good marketing bait I felt for. Not really understanding the negativity here. We know for a fact that most of the people that master intellectual problems do so via pattern recognition, not by reasoning. You show a chess master a position, he/she can instantly tell you what the best moves are without "thinking" or "calculating" because it's mostly pattern recognition. Maths and algorithms fall in the same category. When approaching new problems, masters don't really start processing the information and reasoning about it, instead they use pattern recognition to find what are very similar problems. The thing I really don't like is the lack of TypeScript or at least JavaScript, which are the most common languages out there. I really don't enjoy nor use Java/Python/C++.
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> We know for a fact that most of the people that master intellectual problems do so via pattern recognition, not by reasoning. Where is this fact stated, and who are "we" here? Sounds like an opinion or guess at best. > Not really understanding the negativity here There are two comments that could be read negativily, the rest is neutral or positive. I don't really understand the constant need for people to bring up what (they think) the rest of the comments said. Post your piece adding positivity if you want, but most of the time comments end up a fair mix so any time someone adds a snippet like that, it turns outdated in a few hours.
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Thank you, I really appreciate you signing up. I agree with you on pattern recognition. AlgoDrill is built around taking patterns people already understand and turning them into something their hands can write quickly under pressure. You rebuild the solution line by line with active recall, small objectives, and first principles explanations after each step, so it is more than just memorizing code. You are also right about the language gap. Right now the drills are Python first, but I am already working on full support for JavaScript, Java, and C++ across all problems, and I will have all of those in by the end of this year. I want people to be able to practice in the language they actually use every day, so your comment helps a lot.
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I don't know if I feel any negativity, but this is the first time I actually thought 'the price of subscription is approximately equal the price of Opus tokens needed to build a custom version of this for myself'... and got a bit scared TBH
I learned the other day ( https://news.ycombinator.com/item?id=46184676 ) that people who aren't students apparently use LeetCode too, for recreational purposes? I'm not sure why you'd work on someone else's imaginary problem instead of doing something for yourself, so apparently it's there and some people enjoy it, regardless of my understanding of it. But then I don't know how to reconcile the idea that some people use LeetCode to pass interviews, some use it recreationally, but then this app seems to indicate some people use LeetCode to learn patterns to implement in the real world, which seems absolutely backwards to me. These are tiny examples, not "real programming" like you'd encounter in the world outside of computers, LeetCode can impossibly teach you how to create useful programs, it only teaches you syntax and specific problems. So I guess take this as a word of caution, that no matter how much you grind LeetCode, nothing will prepare you to solve real world problems as practicing solving real world problems, and you don't need any platforms for that, just try to make your daily life better and you'll get better at it over time and with experience of making mistakes.
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> imaginary problem instead of doing something for yourself they're doing it for themselves just like when they solve sudokus, crosswords or play fortnite
The idea of getting quizzed on how good you are at recalling specific patterns in algorithm construction is completely and utterly bizarre. I get that some people feel forced into it, but nobody can believe that this is an appropriate measure to judge programmers on. Sure, being able to understand and implement algorithms is important, but this is not what this is training for.
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It's just a power move on devs. People come on HN to brag about crazy high comp and how devs are untouchable. The reality is that if you feel the need to do circus tricks for someone in exchange for a role that makes you happy, you got no leverage. While this might have been less obvious during the late 10s and early 20s with all the fancy pods, consoles, free high quality fresh meals and what not that Big Tech used to offer to devs, it is certainly harder to deny nowadays.
...the f?! why are we interviewing ppl for things like this?! you either: (a) want DEEP understanding of math and proofs behind algorithms etc. (b) can get away with very high level understanding, and refer to documentation and/or use LLMs for implementation details help there is no real world use case for a middle-ground (c) where you want someone with algo implementation details rote-memorized in their brain and without the very deep understanding that would make the rote-memorization unnecessary!
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Maybe it's just me, but I want people that are reasonably competent and you can work with. Maybe there are some jobs that require deep understanding of maths/proofs etc, but those are what, maybe 1 in 100 engineering jobs? More often than not a deep interest in a particular technical domain is a liability. It's like that guy that insists on functional programming design patterns that insists on a fold with tail recursion where simple mutation could have easily sufficed. Or endless optimization, abstraction and forced patterns. Bro, you're working on building a crud app, we don't need spacecraft design.
People are sheep. Someone somewhere used mathematical puzzles as interview questions. That someone became big. Others assumed it was because their interview process was amazing and followed blindly. Soon enough the process started to be gamed. I'm seeing this trend again in the field of AI where math olympiad participants are being given God like status by a few companies and the media. Truth is even the most prolific computational scientists will flunk these idiotic interviews.
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Hundred percent. Classic example of academic smarts vs real world smarts. It's why developers as a group will lose negotiating power over time. You would expect a smart person to question why that 'problem' exists in the first place rather than forge ahead and making a solution for a problem that doesn't exist. It's like your manager telling you to write a software that does something, whatever that is. Your first question should be why and you should not type a single letter until you understand the domain and whether a software solution is needed in the first place. For all the intellectuality modern devs give to themselves, they are still asking how high when told to jump. And in some cases even bragging about jump heights. Only difference is that many devs look down upon others (or simply are unable to understand those) who refuse to jump. We all know devs have better things to focus on, given the state of modern software development.
Seems like a good idea, is it the same kind of concept as the woodpecker method in chess ?
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Nice comparison. It is pretty similar in spirit to the woodpecker method. In chess you repeat the same positions until the patterns feel automatic. Here it is LeetCode problems. You keep seeing the same core patterns and rebuild the solution step by step. For each step and line there is a small objective first, and then a short first principles explanation after you answer, so you are not just memorizing code but training pattern recognition and understanding at the same time.
↙ time adjusted for second-chance
LLM from scratch, part 28 – training a base model from scratch on an RTX 3090 (gilesthomas.com)
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If you are curious about doing something similar with TPU, Google has an article. https://developers.googleblog.com/train-gpt2-model-with-jax-on-tpu/
> When you’re looking at a pre-training dataset in the frontier lab and you look at a random internet document, it’s total garbage. I don't even know how this works at all. It’s [stuff] like stock tickers, symbols, it's a huge amount of slop and garbage from like all the corners of the internet Seems like there would be low hanging fruit in heavier pre processing then? Something deterministic like a reading level score. Or even a tiny model trained for the task to pick out good data?
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Makes me wonder what kind of model we could get if we just trained on Wikidata and similar datasets, but pre-processed to be natural language rather than just triplets of data.
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Data filtering. Dataset curation. Curriculum learning. All already in use. It's not sexy, it's not a breakthrough, but it does help.
Are off-shelf GPUs (like one 3090) suitable for modern academic research on current AI advancements or is it better to rent some cloud compute?
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Research runs on a variety of scales - but "check if this new idea/method/architecture isn't completely dumb on small scale before trying to scale up" is a common enough pattern. And most of those fail on small scale.
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depressingly enough, things that work on small scale architectures often don't work at larger scales
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Yep, most of what's remaining fails to scale. But it's still a very solid filter. Sure, there are things that don't work on small scale and then work on large scale. But they're rare, and they sure are going to be expensive to find and validate.
The Joy of Playing Grandia, on Sega Saturn (segasaturnshiro.com)
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I never played the 1st Grandia, but I had Grandia II on the Dreamcast and I absolutely loved that game. I'll admit that I was never the best with (J)RPGs and never played it for that long per-session as a kid, but I did eventually finish it. Though, it did take many years to finally get to the end and finish the game, but I enjoyed it! (I also enjoyed Evolution 2: Far Off Promise).
It often gets worse. I stopped playing Final Fantasy X (on the PS2) because there was a boss battle where there was a 10 minute un-skippable cutscene between each stage of the battle and if you died you had to re-watch each one.
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I think at that point I'd call it and mark that one as "finished it".
> 10-13 minutes if I remember correctly from booting the game to actually being able to do anything besides mash buttons to try and skip the cutscenes. Genuinely curious - if you don't care about the story then why play an RPG? When you're speedrunning - sure, skip all of the cutscenes, but when you're playing casually - why would you want to do that?
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I play RPGs for the fun of turning time and grind into more advanced abilities (eg going from getting slaughtered by dragons in Skyrim to being the one doing the slaughtering). There are few games where the story has mattered to me, and even basically no games where the cutscenes did. Edit: the presence of story and cutscenes in a game I enjoy is basically correlation and not causation (for me).
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Oh I do care about the story, but please don't front-load the credits and make me sit through them.
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I could ask you a similar question: why play an RPG if you don't care about playing? Go watch a movie. The point of many posters, I imagine, is that there is too much non-playing parts all at once, it's not strictly about them not being skippable. This is especially damning when the long unskippable cutscene is during a boss fight or something which you might fail afterwards and cannot save.
> 10-13 minutes if I remember correctly Mmm played any Kojima games? :)
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Nope, MGS was big on Playstation when I was growing up and the whole stealth gameplay does not appeal to me.
You can typically skip most dialogue and cut-scenes in the MGS games. Also quite a number of the cut-scenes are interactive and can actually help you in game play (codec numbers are show, clues etc). MGS-4 though is has ridiculous cutscene length.
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MGS4 would be like 10% shorter if you had a mod that just cut every line in a cutscene that’s someone repeating someone else’s previous line, but as a question.
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I never finished it. So I wouldn't know.
Play the game in an emulator that has a shortcut for fast-forward. It makes a world of difference when it comes to "enduring" overly long cut-scenes, load screens, repeated spell animations, endless combat encounters, etc. I wish modern games would have the same feature!
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Fair point, I was playing on MiSTER.
↙ time adjusted for second-chance
No ARIA is better than bad ARIA (w3.org)
2 cents here. Let's make this article optimistic and forward looking. That's somehow intriguing to write an article that says "no" without providing "yes" examples. I don't view this as very generous. Looking for further updates.
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This is the "Read Me First" page on a site absolutely full of documentation...
Something I'm desperately keen to see is AI-assisted accessibility testing. I'm not convinced at all by most of the heuristic-driven ARIA scanning tools. I don't want to know if my app appears to have the right ARIA attributes set - I want to know if my features work for screenreader users. What I really want is for a Claude Code style agent to be able to drive my application in an automated fashion via a screenreader and record audio for me of successful or failed attempts to achieve goals. Think Playwright browser tests but for popular screenreaders instead. Every now and then I check to see if this is a solved problem yet. I think we are close. https://www.guidepup.dev/ looks extremely promising - though I think it only supports VoiceOver on macOS or NVDA on Windows, which is a shame since asynchronous coding agent tools like Codex CLI and Claude Code for web only run Linux. What I haven't seen yet is someone closing the loop on ensuring agentic tools like Claude Code can successfully drive these mechanisms.
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What about just AI assisted accessibility? Like stop requiring apps to do anything at all. The AI visually parses the app UI for the user, explains it, and interacts. Accessible is an also-have at best for the vast majority of software. This would open a lot more software to blind users than is currently available.
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That's expensive, slow (listen to a screenreader user some time to see how quickly they operate) and likely only works online. I'm also not going to shirk my responsibilities as a developer based on a hope that the assistive tech will improve.
Not a joke. If truly you want a properly functioning website for blind/bad sight/ Step 1 would probably be to put on a blindfold and go through your website with a screenreader (cmd + f5 on a mac).
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I would very much like to be better at building websites that handle assistive technologies like screen readers well. I don't have a lot of blind users to worry about because they don't let you be a firefighter if you're blind. But a lot of firefighters are people who simply did not do well in school, even the very senior ones, and that's because they are often very clever people who are of an age where things like dyslexia were just not diagnosed early or often. So now I deal with a lot of people who use assistive technologies to help with dyslexia and related comorbidities. I have dyscalculia that wasn't diagnosed until I was 19 and at uni, and even then it was diagnosed initially by my mate's Educational Psychology undergrad girlfriend in the pub one evening. That was in the early 90s and we're better at it now - but not by much.
An AI-generated automated testing script in your pipeline will do great though.
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And then we're back at your own: > I'm not convinced at all by most of the heuristic-driven ARIA scanning tools.
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That's entirely different. ARIA scanning tools are things that throw an error if they see an element that's missing an attribute, without even attempting to invoke a real screenreader. I'm arguing for automated testing scripts that use tools like Guidepup to launch a real screenreader and assert things like the new content that was added by fetch() being read out to the user after the form submission has completed. I want LLMs and coding agents to help me write those scripts, so I can run them in CI along with the rest of my automated tests.
Rather than improving testing for fallible accessibility assists, why not leverage AI to eliminate the need for them? An agent on your device can interpret the same page a sighted or otherwise unimpaired person would giving you as a disabled user the same experience they would have. Why would that not be preferable? It also puts you in control of how you want that agent to interpret pages.
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The golden rule of LLMs is that they can make mistakes and you need to check their work. You're describing a situation where the intended user cannot check the LLM output for mistakes. That violates a safety constraint and is not a good use case for LLMs.
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