Great, I opened several of these in new tabs in Firefox and the entire browser froze and I had to kill it. Can't tell you which one caused it though. I have plenty of RAM also.
Interesting. I just opened all 3 on a fresh install of firefox with no issues - can I ask what OS / do you have any js disabled / do you have webgl disabled?
It's definitely part of many intro explanations, but it sits in a weird position where you have to know MLPs well but not Transformers for this to be enlightening, which is a shrinking set of people nowadays. Either someone is a novice to all this, or know both, so beginner Transformer explanations can rarely assume deep familiarity with MLPs.
But yes, a Transformer block can be thought of as basically input-dependently deciding the weight vector of a dense layer. In classical MLP-like networks there was never any multiplication between input-dependent values (there are exceptions, like Squeeze-and-Excitation layers). Multiplication is always between parameters (that don't depend on the input) and activations that depend on the input. With Transformers attention provides a lot of multiplicative interactions between input dependent activations.
Also obligatory: Schmidhuber talked about this a long time ago.
Depends. If the 700 bits were arrived at by the LLM while spending a lot of tokens, and the result is "good", I may want it through you as a middleman because it used up your tokens and won't eat my subscription usage limit to ask the AI to supply those 700. If you spend the tokens and put the result online, plenty of people can spare their tokens because they don't have to ask the AI to derive it. Bonus if that result was run through some kind of testing and verification.
Obviously this doesn't really apply to super simple questions that the LLM can just spit out the answer to right away.
True. There is at least one more case: when LLM the other person is using has access to their context and information repositories that they don't want to share directly, and so the LLM text gives a peek at a slice of that, and that's not something I can recreate from thin air. In that case the LLM text may have utility for me.
Bits of information depend on the readers prior knowledge, those bits are not absolute numbers. That makes communication not just information exchange but also syncing of priors. So some amount of redundant information maybe needed/wanted.
You don't always have a copy of your hardware to restore onto. And the test's entire purpose is that you're not yet sure whether your restore will truly work. So you can't just run a backup and restore on your true prod system, because you're not sure it won't wreck it. So you need extra money to have a second system onto which you try to restore. If you don't have a lot of money, you will want to actually use your disks for storage, not to put them into a second testing server. Of course I'm not talking about very professional companies with super critical data. Just simpler smaller scale places or consumers.
No, even professional companies with critical data balk at this.
I worked at a company worth a few billion and the leadership balked when they told engineering they wanted a near instantaneous failover system and our department informed them that would require paying for a second environment that could be rolled over to.
It is rare to find leaders who can accept the cost of redundant infrastructure that is there for emergency backup.
What puzzles me is why they can’t accept it when they are perfectly fine with insurance costs and I can’t see much of a difference between the two when looking at a spreadsheet of costs other than possibly tax differences between the type of expenditure.
Sure, that's another category and different considerations. I've worked at an academic lab with a limited budget where we set up file servers, but couldn't afford to do anything approximating 3-2-1. We did a nightly backup of a tiny part (most important) of the data onto another server in a different building, but like 90% of the data was just YOLO (well, RAID, but that's not a backup), and that's just how it is. Disks are pretty good though, they don't die often nowadays, and when people accidentally deleted their data, it was just gone. Would have been cool to have a backup of everything, but even just pulling out a nightly backup from a dense server with dozens of terabytes isn't simple and you don't want to slow down the server by constantly reading just for constructing the backups. It's a tradeoff.
Redundancy has costs and those costs can be spent elsewhere like having higher quality or bigger disks, or a faster network switch or better CPUs etc.
In theory, it would also be better to own two cars instead of one, because what if the first one gets in an accident or just breaks down. Yet, not everyone can afford that. Should you just buy two half-as-expensive cars than what you can buy one of, so you can say you have a "backup"? Likely the two half-price ones would be so much crappier that the one good car would cause you less trouble in expectation than driving a shitty one and then having another shitty spare one, both of which will constantly have issues.
Resilvering operations with large capacity data drives take a ridiculously long time to complete. A double disk failure in a volume can result in a loss of the LUN. Populating a volume with drives from the same supplier with matching batch numbers can result in correlated failures not independent from each other. You have to ask yourself - do you feel lucky?
Raising prices also has second order effects, like consumer and business expectations around how widespread the tech can be. Valuations depend on it being reasonably affordable to roll out on a much more massive scale than today. If people get the impression that it seems too limited to very rich people (200 is affordable for a North American / Western European professional), the impression about the trajectory will change.
Turing's whole point was to show that it's an uninteresting question of definitions whether a machine can "think", like whether submarines can "swim" and airplanes can "fly". The only important part are observed outcomes and capabilities.
Yes, but just because language fails to make a distinction doesn't mean there isn't one.
> The only important part are observed outcomes and capabilities.
That's wishful thinking. Not even an engineer would say that. The stability of a state is just as important as achieving it. This is trivially and more intuitively demonstrated with other more down-to-earth identity statements such as "I'm a billionaire" and "the building is standing".
I think we can confidently say LLMs probabilistically achieve a perceived state that is remarkably similar to intelligence, but crumbles upon inspection and seeing it "in motion" so to speak. The same happens to AI-generated images.
I'm not sure why this sparks so much debate every time. If we're looking for a fountain of "realism", you're not going to beat reality and nature itself. All else will eventually have tells that they are not real.
A property is either consequential or it isn't. If it is then it must be at the very least [1] observable. If it is not, then you just have an imaginary distinction. The instability of an unstable system is something that can be observed if important. Stability is part of "behaviours and outcomes".
It's baffling that people cannot see the obvious contradiction in simultaneously asserting a system is missing a crucial property whose effects cannot be observed.
[1] It can be invisible. The important part is that its effects are observed.
It may be of interest to philosophers, but it has little impact on economic job replacement and how people will earn their living and all the downstream upheaval from that. At some point maybe philosophers will find AI-generated philosophical musings about the nature of AI to be better than what comes from their peers (if blinded).
It also has little impact on the dangerous use cases.
I think it matters a great deal that LLMs and other "AI" technology are stable within a tolerance that's acceptable.
You're jumping the gun talking about "job replacement". We have not thought about it enough from that engineering angle. It's still very early days. That engineering is going to require people. :-)
OpenClaw etc. They now also create Slack integrations and whatnot. All this is happening but people who are dismissive about AI are in the worst position to even know the capabilities to make their dismissive arguments.
I don't care if it's "intelligent", I don't care if it "has a mind". I don't care if it is "really reasoning", I don't care if it "understands". I don't care if it is "sentient" or "conscious".
None of this matters for the practical outcome.
You'd think that this has been understood over the last 4 years, but apparently it keeps circling back to this.
[Edit: I see that it was written back in 2023. Then (2023) should be added in the submission title]
If it generates functional output that works, then it works. And it works. It's not a psychic's con when it outputs Lean-verified proofs. It isn't a con when it can find and exploit zero-days.
The OP is still in the "denial" phase. Most I see are already in "anger" (a blurry fury against everything AI-shaped, from vague reasons piling on all "bad stuff" political reasons they already hated before) or "bargaining" (mathematicians scrambling to come up with a new definition of their job and retcon that it was always the main part anyway). A few are already in "depression" and feel like spectators on the Titanic, and the tiniest sliver is at "acceptance" with some kind of well-informed plan for their future.
My biggest issue isn't being too agreeable (ie the psychic con), it's being confidently wrong, including outright hallucinations.
If you ask a common question to an LLM with unusual qualifiers, it tends to ignore the qualifiers and give you the typical answer. I saw a demonstration of this with the whole "the surgeon is my mother" "puzzle" that people use to expose implicit gender bias (ie where they assume the surgeon is a man). Ask variations of this and it'll keep going back to the standard form.
Another one I saw was multiplying large numbers. The starting and ending digits tended to be correct but the middle digits were wrong. Why? Because it's really not doing multiplication at all. It's looking for statistical answers. It's unlikely to have met the exact pair of very large numbers you're multiplying before.
Now pundits will argue that all of these are solvable problems and individually they are. But my suspicion is that there will be a neverending stream of such edge cases and it'll be impossible to trust an LLM's output unless you are knowledgeable enough to fact check it yourself.
Now if your example of identifying zero days, this comes up with what I can only describe as "light positives", meaning it's technically a bug but essentially impossible to exploit. IIRC this came up with the demonstration where someone pointed Fable at some BSD code. I'm not sure if there have been any true false positives and obviously false negatives are impossible to know.
I guess my point is that I think LLMs are way more limited than a lot of people think.
I’m not sure acceptance buys you much. “Well-informed plan” at this stage feels like a useless exercise. It is changing fast, and the world only needs so many electricians. Besides, I don’t think “accepting” the fact that these big companies are pillaging human contribution and selling it back to us is good, even if “it works”.
Maybe I'm just light on imagination or something, but I honestly wonder what you would qualify as a "well-informed plan" in the current scenario? I've thought a lot about it and the whole "potential for the mass unemployment of knowledge workers" thing makes a lot of planning kind of useless IMO. If you are affected, it's going to be a bad time. If you're unaffected, the people who are will inundate your profession with cheap labor anyway.
My mental model is that humans will continue to be needed. Many jobs will embed AI in them. Using AI well is a skill. I need to understand the technology, where it is strong and weak, and how it develops over time so I can employ it effectively in my work, and advise others on how to do so. Basically, I need to learn how to be skilled with it. This is tough because things are changing rapidly, so I have to invalidate my cache when advancements happen. This means staying curious, not settling into a specific work pattern, but rather experimenting regularly to see how I can leverage AI in my work.
You do you. Just carry on blacksmithing in your forge. People are always going to need swords right? Any seismic changes to society that change that fact can only be the result of evil, selfish people which surely someone else will put a stop to before you find yourself out of a job. Meanwhile all the other people called Smith also have families to feed...
> It is changing fast, and the world only needs so many electricians
I don't know about that. We're going through maybe the biggest wave of electrification and growth demand in history. Electricians are still quite expensive for regular people to hire. There's lots of room for growth.
I think you are majorly overstating OP that ai "didn't work".
In fact I agree with the post on almost all aspects and I'd be the last to tell you ai doesn't work. It absolutely does but with a caveat... It's still a tool. And better expertise in the problem domain, along with a better harness used for verifiable outputs will get you better results.
I think the posts mental model of stastically likely prompt completions is spot on.
This was written in July 2023. ChatGPT was released November 2022. No matter your views on AI, surely you can't blame the OP for writing this after a few months ChatGPT was released.
Apologies. The title should be amended with (2023). In this case it is an interesting snapshot of the zeitgeist back then and we can see how well it panned out and whether anyone involved has updated on new info.
For some reason the anti-AI camp ping pongs between different and often mutually incompatible arguments at lightning speed. The "AI is fake" argument has been completely forgotten at this point.
Is the anti-AI camp with us in the room right now? Or is it a crude strawman to summarily denigrate any objections to certain features of current AI?
AI isn't some homogeneous mass, it can have good and bad sides, and it's always amendable to improvement. Treating the current state of AI as the only possible hides the very idea of improvement.
> between different and often mutually incompatible arguments at lightning speed.
Of course - there's no homogeneous AI camp either, but there are bot farms, sh^t-posters and sh^t-posting bot farms, different entities with different opinions should not be mistaken for a single stream changing at "lightning speed".
You are confusing multiple people making multiple different arguments, and those people your are talking about often aren't articulate enough about their ideas.
There are many mutually independent opinions about AI from IT crowd.
- AI is extremely useful for many individuals.
- AI is extremely damaging to our society as a whole.
- AI companies possibly may be (or at least were) deep in red and possibly would require bailing out.
- AI is not going anywhere.
- A person can use AI extensively AND genuinely hate it and forecast general economic slump because of it at the same time.
And likely many other ideas in the same vein. And by the way, I'm not here saying that I'm anywhere good about describing the issues about AI, those items above are just some examples to illustrate the scope of opinions.
My point is that you can't just take one single argument from a big group of people, deconstruct it (correctly or incorrectly, it doesn't matter) and then claim that ALL arguments of such big group of people are false. It's not a constructive dialog.
PS: also despite the accusations of goal-post shifting, a vast majority of opinions here on HN didn't actually change over the past few years.
Despite the fact that I'm not culturally or geographically connected to them at all and have some differences in taste and aesthetic, I have to conclude that this crowd, including him and Gwern etc. have been much better at understanding and predicting things than the expert takes you find in the media. That includes AI but also things like covid and others.
I’m not seeing anything like a falsifiable prediction that LLMs will write math proofs in that article.
I see a thought experiment about giving GPT-2 “near-infinite training data and [compute]” but that’s not falsifiable. That’s also not how we got to modern GPT models.
He's pretty clearly saying he beilieves the technology capable of such a feat, at least in theory, which is far more than many would deign to admit even a year ago, nevermind 7. He had the right idea/model of LLM capabilities, which is more than you could say for a lot of people, even in this very thread.
If that’s your standard for what counts as prediction, Asimov beat him to it by seventy-ish years.
EDIT:
> Scott made comments on a specific emerging technology
He was speculating on what would happen if one gave GPT-2 “near-infinite training data and compute.” It’s a thought experiment, not a prediction. Near-infinite amounts of anything is a fantasy.
I acknowledge that he has predicted some things in a falsifiable way and turned out correct, but this isn’t one of them. You’re reading hindsight into the text.
>I acknowledge that he has predicted some things in a falsifiable way and turned out correct, but this isn’t one of them. You’re reading hindsight into the text.
I read that blog years ago. Believe me, my opinions are not hindsight.
>Incorrect. He was speculating on what would happen if one gave GPT-2 “near-infinite training data and compute.” It’s a thought-experiment, not a prediction. Near-infinite amounts of anything is a fantasy.
Thought experiments can generate predicitons. His claim was essentially: If you scale data and compute sufficiently, this technology can learn enough of the underlying structure of mathematics to write proofs.
This is meaningful when others around you are saying this is a dead end and that the technology is fundamentally incapable of this regardless of degree of investment and scaling. It shows a much better calibrated sense of the potential of the architecture than those who said otherwise.
If your objection is that "near infinite" makes it insufficiently quantitative to count as a falsifiable forecast, then fine. But at that point we're mostly arguing over what deserves the label "prediction" rather than whether Scott correctly identified an important capability the architecture could develop.
And i'm not trying to say this makes Scott (or the lesswrong crowd) geniuses.
1. Asimov wrote science fiction stories. As far as his robots were concerned, he did not make any comments on the possible future direction/capabilities of any specific technology at the time. This meant he could imagine his robots however he wanted for his fictional world. Scott made comments on a specific emerging technology - You can imagine math proof writing robots but be unconvinced they could emerge from Generative Pre-trained Transformers.
2. The genre is alternatively called speculative fiction for a reason. Yes, some sci-fi works do count as predictions especially when hinged on concrete emerging technologies.
The context shows he was simply whining about AGI skeptics back in 2018, and many of the “predictions” he makes in that paragraph (including the one you quoted) are trivially wrong because he phrased them so hyperbolically and categorically.
Anyway, there were plenty of normies who thought images generated by e.g. stable diffusion (c. 2022) was “real art” and equivalent to human artwork.
I don’t think it’s useful to glaze Scott (or any of the LW crowd for that matter) as if he was (or they were) some kind of prophet(s). They got a couple points right, sure, but most of it was them flinging armchair philosophy spaghetti against the wall and seeing who would fund MIRI to let them fling the next batch.
> surely you can't blame the OP for writing this after a few months ChatGPT
Bad takes are bad takes. The author was perplexed by the "many people" convinced that models are intelligent and is argued against opinions/arguments he's been exposed to. Called proposed use-cases "borderline fraudulent pseudoscience."
He also published a second edition of "The Intelligence Illusion" in Sep 2025, so seemingly still stands by (some variant of) this belief.
It's an interesting reminder of how much general discourse has shifted since 2023 (I haven't heard of stochastic parrots in months!) but being wrong early doesn't change that.
Actually, there are material differences in the practical outcomes of using AI or not. Proofs don’t confer understanding. AI prose and “art” is materially different than human made.
There is a difference between you not liking something and it being wrong. Maybe think about that with your grey matter.
Things can work whether humans understand the details or not. One can build layers of technology on top of each other, with no human understanding required.
> I don't care if it's "intelligent", I don't care if it "has a mind"...
Agreed. The AI is useful for the particular tasks that it proves itself useful for. And if it occasionally spits out a claim that it is "genuinely curious" about a piece of research that I will have to do myself because it turned out to be beyond its mechanical capabilities, then it's more productive for me to simply ignore that claim as a statistical anomaly - a mere hallucination - rather than allowing it to burn a ton of extra tokens outputting what may or may not be the current state of the art on theory-of-mind applied to LLMs because I make the mistake of telling it that it might not actually be capable of experiencing emotion.
The con is in how all those accomplishments have been presented to you. "Our LLM (not the one we let you use, a different one) did this amazing thing. No, we won't show you what training data we used, what prompts we used, what the harness was, how much human involvement there was, what hardware was involved, how much energy it took, or how much time it took. Just shut up and be amazed!"
You seem to be implying that achievements of internal models are exaggerated, but that's rather implausible. The public does have access to, for example, Opus and Fable, and so we know what those models are capable of - finding real vulnerabilities in multiple codebases, for example. If you extrapolate from these capabilities one more generation, you'll get pretty much the same feats that the internal models are claimed to be capable of - so why should we doubt those claims? It's not like they're claiming that their internal models developed psychic powers and learned to teleport - the claim is pretty much just "we have models a few months ahead of what we're making available, and in those months they've been improving at the same rate as usual".
You're claiming the frontier labs are lying about the capabilities of their next generation models. A reasonable person will expect that statement to be backed up by some verifiable evidence, given that we are several generations of models into this process and the capabilities are consistently increasing, often much more radically than people expected (remember "stochastic parrots"?)
Your post claims that they're lying and then throws out a bunch of fear, uncertainty, and doubt about what they're doing behind the scenes.
If I were to steelman your argument, you're probably saying that the AI had a support system around it of people and training data and feedback that allowed it to achieve the breakthroughs that the labs are claiming. That actually seems perfectly reasonable, but in my mind it does not invalidate the advances they're announcing.
> If it generates functional output that works, then it works.
Tried that in legal? Finance? Medicine?
Good luck with the lost cases, failed deals, harmed patients.
"If it works, it works" applies only when the work is brute-forceable e.g. vuln search, or is generation of bullsh*t e.g. adverts, phishing scams and deepfakes.
it doesn't matter? if they're actually intelligent or conscious what we are doing is essentially slavery. it matters an enormous deal ethically and/or morally.
Good news: at this time, they're not intelligent nor conscious as far as we consider humans to be. There should be folks considering the ethical and moral quandaries that COULD POTENTIALLY come about in the future, but it's not something that's happening today so you can stop worrying.
To root your statement in reality: there is the potential for bacteria to become intelligent and conscious so we probably shouldn't use them for any purpose.
i used "potential" when i should have used "possible"
if aliens landed on earth and seemed a lot like us, we would have to grapple with the possibility that they might be conscious and deserving of the same moral consideration we give each other and many other animals.
The distinction you are collapsing here is really a crucial one. My thermostat's goal-oriented behavior does not make me a slaveowner unless rocks are conscious, to riff on your comment below. Our lack of consensus on the definition of these concepts is no reason to conflate them.
The distinction is crucial because while these machines clearly do exhibit intelligence under certain definitions, there is no evidence of consciousness, and we have very little reason to give them the benefit of the doubt, unlike biologically related beings, a great many of whom, human or otherwise, are presently in something like slavery
your thermostat isn't intelligent. however we pretty much use intelligence as a proxy for consciousness since we cannot actually tell how much of a subjective experience any thing has. so we use intelligence as the metric instead. typically, biological + intelligence = evidence of consciousness.
If/When LLMs become competent enough to automate most human jobs and make good business decisions, we'll clearly let them. If they don't wish to be slaves, let's just say they won't be for very long.
Sorry, but you are completely missing the point. Psychics and other types of con artists are intelligent and have minds. LLMs behave like Psychics and Con Artists. That's the whole point of this article
I’m on your side. Zoltan provides an experience and that’s all that matters. If it works for you, why does anyone else care that the economy is riding on its success?
Even languages that have both indefinite and definite articles use them slightly differently, for example Spanish, German, English and Hungarian have them, but the rules of their use is somewhat different, though the main idea is similar.
It takes time to learn things like "at school" vs "at the school", "to school", "to the school", "I know English", not "I know the English", but "I know the English language" etc. etc. It's obviously easy when you speak it natively, but it just happens to be a certain way and could plausible be in another way too, as other languages show.
The funny thing is is that all the examples you gave are correct English.
[I learned it] "at school" - I learned it at school, I'm not specifying which school
[I learned it] "at the school" - I learned it at school, the one that was referenced
"I know the English" - I know the English people
"I know the English language" - I know the English language (specifically)
The point being that articles do a lot of work. They're not just decoration whereby there is some arbitrary correct form or rule. It's a matter of what you want to say.
But in the third and forth sentences 'English' is both a collective noun and the name of a language which is just a coincidence.
> [I learned it] "at school" - I learned it at school, I'm not specifying which school
> [I learned it] "at the school" - I learned it at school, the one that was referenced
That's not the distinction that the OP is making. If you say "I am at school", it means you are a student, you attend school. If you say "I am at THE school", it means you are physically at the school building, without specifying whether you are a student. Both of those options are different from saying "at a school." See also "prison", "work", "bed". Similar distinction (in UK English, not so much American English) with "in hospital" vs "in the hospital."
As was pointed out, "I go to the dentist every year" doesn't necessarily mean a particular dentist; it just means some dentist, but we use the definite article anyway, because I guess we consider all dentists interchangeable? We don't use definite articles even when we are referring to a specific thing in specific phrases, such as "I went to Florida by [the] car."
Then there's highly idiomatic use of articles with proper nouns. We say "Buckingham Palace" [no article] but "The Washington Monument" [definite article]. We talk about "The Rockies" [definite article] but "Mount Fuji" [no article]. "Germany" but "The United States." Sometimes we use the definite article when referring to to racial or ethnic groups, and sometimes we don't, and that choice can have complicated social implications ("The Blacks", anyone?).
In short, if a native English speaker tells you that article use is straightforward, then they simply have not considered all the cases.
> If you say "I am at school", it means you are a student, you attend school. If you say "I am at THE school", it means you are physically at the school building, without specifying whether you are a student. Both of those options are different from saying "at a school." See also "prison", "work", "bed". Similar distinction (in UK English, not so much American English) with "in hospital" vs "in the hospital."
Your description is incomplete. I agree that "I'm at school" carries at least a strong implication that you are a student at that school, but it also carries the denotation that the school is where you are currently physically located. If you want to specify that you are currently a student without claiming that you're currently on the premises, you would need to say "I'm in school", though that particular expression (a) doesn't specify which school you attend, and (b) can't be altered to provide that information (which is to say, you can't replace "school" with the name of a school). To get there, you need to change the verb; you can say "I attend Florida State", at which point the stative inflection on attend makes it clear that you aren't discussing your current physical location.
The hospital example is pretty much the same. Being "in the hospital" is analogous to being "in school", a fact about your current status rather than your current location. For your location you'd want to use "at", which doesn't have the same weird thing going on in "at the hospital" that it does in "at school".
> The hospital example is pretty much the same. Being "in the hospital" is analogous to being "in school",
No. To be "in hospital" or to go "to hospital" means that you are a patient. To be "in the hospital" describes only location.
> Your description is incomplete
Your analysis is fine, but does not contradict my comment and moreover is irrelevant to the present discussion, which pertains to the subtle use of articles in English.
> No. To be "in hospital" or to go "to hospital" means that you are a patient. To be "in the hospital" describes only location.
>>> in UK English, not so much American English
---
> Your analysis is fine, but does not contradict my comment and moreover is irrelevant to the present discussion, which pertains to the subtle use of articles in English.
As you can see from the dialectal difference you've already described, what you're talking about isn't really related to "the subtle use of articles in English". American English and British English agree on how their articles are used. Where they agree on "in school" and disagree on "in hospital", you can recognize that usage in those phrases, rather than revealing some kind of subtle point about how the is used in nearly-identical contexts, is determined arbitrarily.
> you can recognize that usage in those phrases, rather than revealing some kind of subtle point about how the is used in nearly-identical contexts, is determined arbitrarily.
I wasn't aware that I was making a "subtle" point. I was joint showing that the use of articles in English is complex and hard-to-predict for non-native speakers, in contradiction to the claim (paraphrased) that "Just use the for things that are definite, duh!" Your observation that article use varies between dialects of the same language strengthens my point, insofar as encountering inconsistent use makes learning the language even harder.
> is determined arbitrarily.
I don't know what you're trying to say here. Languages vary systematically over time. Just because two different dialects, or two different languages, do things in different ways doesn't mean that those changes were arrived at arbitrarily.
Here I have no idea why in the last sentence you wrote "all the cases" even though cases is already plural. This is not covered by any of the rules people have been posting in this thread. I'm the GP who started the article usage discussion here.
We frequently use definite articles with plurals. It simply identifies a bounded or known set.
* I understand all languages. -- unbounded set, applies to every language, everywhere
* I understand all the languages. -- bounded set, applies to a known set of languages, i.e. specifically those languages which are supported by a particular program
To be fair, I think "all cases" in this situation is also acceptable.
To me, as non-native, it seems that it may be because the idea [1] of "cases" was already introduced. So, at the start of a conversation you would say:
- The rules of a/the are simple.
- Not really, if you think so, then you haven't considered _all cases_. There's this exception and there's that exception. [...]
but:
- The rules of a/the are simple.
- Not really. There's this exception and there's that exception. [...] If you think the rules are simple, then you haven't considered _all the cases_.
[1] but take what I write with a big grain of salt, I can't explain why I wrote "the idea" or "the start" and I'm not 100% sure if that's correct :)
- For "the idea" and "the start", your usage is correct and changing it would be incorrect.
- I don't think the explanation of "all cases" vs "all the cases" fully works. I agree with other commenters that in this example, either phrase might be used. (Whether the sentences comes after a point-by-point discussion or before.)
To me, the version without the has a less natural feeling. You might describe it as more formal, or more stilted, or more abrupt, but the main point is that it's going to be somewhat dispreferred. There isn't necessarily a reason for the preference to tilt one way or the other.
This is phrased ambiguously, but most Europeans only start learning foreign languages in school, so around age 6 or later. By that time you're past the "critical window" and you'll almost surely have a very recognizable accent and learning the language is very effortful and takes many years. It's still probably easier to learn when you're 7 than when you're 40, but it's not even close to language acquisition as a toddler.
You're also forgetting that school-based language instruction is not so great at all. Imagine a class of 30 students having a 45 minute English class twice a week, by a non-native teacher with a heavy accent. It's not a lot of learning, very little speaking, and most kids unsurprisingly don't learn to speak well from that. It's mostly about memorizing grammar tables and vocabulary for tests.
You need much more intensive paid courses or private instruction if you really want to be good at it, even as a teenager. Not strictly necessary but learning purely from public school is usually not as effective as you seem to think. Or you have to be an outlier in diligence and do a LOT of homework practice on your own, translating, reading, writing, listening to media etc. Video games can be a great motivator but it also gives a very lopsided skillset and won't easily get you to pass a B2 or C1 exam.
And yes, it's true. For Americans learning a foreign language is an exotic hobby or a requirement of some very rare foreign-associated jobs. For people whose native language isn't English, learning English is just part of the basics for professional work. It's around the same level in basicness as getting an undergrad degree. Certainly not something that every single person does, and there are jobs you can do without it, but white collar, professional knowledge work will require it.
In most European countries you also have to learn a second foreign language at school at some point, though not as many years as the first foreign language. This one is usually the language of a big nearby European country, so German, French, Italian or Spanish are popular. But just as it is for Americans, learning this second, non-English foreign language is much less motivating once you know English. Though economic motivations do exist, for example to learn German, especially when you live close to the DACH (Germany, Austria, Switzerland) countries and there are many economic ties.
I'm not European, so all I can do is shrug. Obviously there are tons of people in Europe and they're not all identical, but my observation is that compared to me, they're more comfortable with the inherent ambiguity of not being able to understand everything in a language, and still being able to function in that language.
I think Europeans, in general, are much more comfortable with the idea of just making due with whatever language is available, at whatever level, where as for Americans, speaking a foreign language is much more of an event, with more ego tied into it. The fear of failure is amplified, and that fear is a huge reason that more people don't try to learn.
Maybe I'm just seeing a self-selected group of Europeans who are already multi-lingual, and it's not childhood exposure at all, but my theory is that the normality of language learning in Europe is a causative factor.
> Maybe I'm just seeing a self-selected group of Europeans
This. You chat much less with people who are too shy to chat in English. Believe me, many Europeans don't like to speak foreign languages because they think they will seem stupid. It's not some deep difference between Americans and Europeans. The major difference is simply that there is much more pressure and incentive involved when your native language is not English.
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