In the short term maybe yes, in the long term, maybe they are the winners, they can build on top of cheap inference stack and eventually win on pricing
Because having unrestricted access to both American and Chinese hardware is better than only Chinese hardware. Long term or short term. More suppliers the better.
Anyone involved in burning that much energy at the same time as a large part of the planet will cook soon due to energy expenditure is definitely not helping humanity. It’s marketing & empire building all the way down..
If you'd told me 15 years ago that people would be running freely-distributed software originating from research labs in China on computers self-hosted in their own house as an alternative to authoritarian overreach and control by the US in internet-based services, I'd have told you that you were smoking some good reefer.
The irony is that the authoritarian control hasn't gone away in China either, if anything it's even more advanced, the GFW and censorship regime there doesn't show any sign of letting up any time soon. Just today in my BBC news feed:
> If you'd told me 15 years ago that people would be running freely-distributed software originating from research labs in China on computers self-hosted in their own house as an alternative to authoritarian overreach and control by the US in internet-based services, I'd have told you that you were smoking some good reefer.
They’re not giving away the models because they love freedom and want to generously offer gifts to the world. They’re doing it as a way to undermine the industry leaders and attract people to their brands.
Selling a product below its cost of production can be done as a loss leader or market share tactic, but eventually you need to sell things for at least what it costs to make them.
Economic dumping is a specific scenario where one country tries to flood another country with cheap products in a way that usually has some government involvement subsidizing or incentivizing it. Countries are careful to hide these incentives or subsidies when possible because it's an invitation to trade wars. For China specifically, the state takes ownership positions in companies and has no problem forcing companies in the direction they want.
", but eventually you need to sell things for at least what it costs to make them."
Gmail, and every other free service would like a word. Net tangential profit invalidates your point. They can loss lead LLM's forever if they are getting other economic benefit from the practice
isn't blitzscaling essentially the same thing, except for when American companies do it (not always within their own country, e.g. spotify, netflix, or amazon)
Somebody tell the Chinese companies to stop dumping AI, so US labs can keep burning pension funds money wrapped in VC checks fine dumping AI at a huge loss.
In any case I find the dumping argument stupid: they are giving both the model weights away and publishing in the open their results and how they got there.
> They’re doing it as a way to undermine the industry leaders and attract people to their brands.
Isn't that just how competition works? Codex and Claude are both widely speculated to be sold at a loss (at least compared to API pricing), so why isn't their tactic also considered dumping? OpenAI and Anthropic aren't stealing IP and subsidizing model inference because they love freedom either. They're doing it to undermine industry competitors and attract people to their brands.
The US government deliberately chased a strategy of denying China access to powerful Nvidia hardware. Shipping efficient and cheap LLMs is their only option, just like Jensen Huang warned would happen. And now that China's smaller models are reaching the frontier, everyone cries foul.
> Codex and Claude are both widely speculated to be sold at a loss (at least compared to API pricing)
It's more likely that the API prices are highly profitable. I could see the subscription plans losing them money for some power users who actually use 100% every week, but given my past experience with subscription products I would estimate that their average utilization is far, far lower than in those comparisons where people take the tokens produced by exhausting the plan 100% and then compare to hypothetical API pricing.
As for economic dumping: The crucial difference is that there's usually some geopolitical influence happening, like government subsidies, incentives, or the government simply owning the companies directly and weaponizing their output even if the company runs at a loss.
It is probably a naive point of view that I hold (I haven't thought it through properly) but the western capitalist version is that investors providing money to do dumping of prices is ok (as long as you are not considered a monopoly) and the Chinese state sponsored capitalism is considered dumping as it goes against the agreed WTO rules for how international trade is supposed to work. The western capitalist governments (probably with a lot of lobbying support) wrote the WTO rules. Not trying to defend either way, but it seems to be different economic and political systems trying to gain dominance over each other.
That side of it is understandable, albeit open to interpretation. I can see how both sides justify their own choices in the short term.
But we hear this "dumping" argument quite often for seemingly arbitrary purposes. Is it "dumping" to sell cheap STM-32 clones when Arm LTD. won't let you buy a license? Is it "dumping" to sell $20,000 EVs to a nation that can barely build $30,000 EVs with federal and state subsidies? In many respects, China's cheap stuff is just better-suited to the global economy than America's high-margin products. If both countries are leveraging federal protectionism to promote and develop their products, it doesn't feel like State Owned Enterprises are on unfair footing compared to SpaceX or OpenAI.
I think self-hosting Chinese models is so popular precisely because China is so authoritarian.
If China wants to sell Solar panels to Americans, they can just sell solar panels, the sun won't mind. If China wants to sell models to Americans... well, Americans don't want to send their data to China, so they can't just offer them as SaaS. They don't want to be left behind in the AI race either. The only option to capture western mindshare is to do what they've always done, use Chinese taxpayers' money to subsidize model development, make American labs uncompetitive, make them go bankrupt, then have control over the entire sector.
Some US labs may become uncompetitive if they have the wrong business strategy, that doesn't mean every AI company will be. If one part of the stack gets commoditized, build your moat elsewhere.
I am not sure the comparison is exactly fitting... Specifically, solar panels in wholesale quantities have to come in 40' or 45' cargo containers by ocean from China and can be easily tariffed or blocked at the ports.
Releasing the weights of a software project on modelscope and huggingface and similar (and I'm sure they'd find a new way to distribute it for an English language audience if huggingface vanished tomorrow as well) is totally different, because there's no tangible hardware product involved.
Erlich Bachman: Jian-Yang, what're you doing? This is Palo Alto. People are lunatics about smoking here. We don't enjoy all the freedoms that you have in China.
Anyway, when the talk of age verification first came out, I moved off of Claude and use either local or Chinese frontier models via open router (which probably isn’t safe for long now that they’ve been acquired). I’d almost forgotten why, this is a good reminder.
With HF bought as well, I wouldn’t be surprised to see them try to gate open models by age too. Going to have to sign up for modelscope
My theoretical self 15 years ago absolutely would have believed the increased authoritarian overreach part (in US/CA/European business and political context). I would not have believed the "multiple ostensibly competing Chinese research labs are giving this away free to run on your own Linux computer, and it's very close to state of the art in capability competing with US-based paid SaaS".
Today marks 25 years minus one day since the US really kicked the destruction of privacy into high gear. Soon after, framing this revocation of rights using the name PATRIOT.
It fits in with the rest of privacy in the US, which is slowly becoming reserved for the wealthy.
The 1% already have privacy consultants to help them keep their data private through shell corporations, legal trusts and other tricks. (The book 'Extreme Privacy' is from one such consultant and well worth a read)
Now if your want privacy in AI? Shell out $$$ for local hardware.
And China controls AI too. It's just that their idea of "safety" is "ideological safety", and their idea of "alignment" is "alignment to the party line".
They're cool with open weight AIs being released. As long as those AIs only ever say good things about CCP, and don't mention certain concentration camps or brutally suppressed protests.
I don't disagree with you on what is the top-down political priority there, but thankfully the architecture of an open weights model released in .safetensors format allows for 3rd parties to "uncensor" it. There's at least 8 different CN originated models now that after running through heretic and a few other methods will score 0 refusals on this data set of prompts:
If we were living in a scenario where the open weight models were truly impossible to uncensor I would be significantly more skeptical of them. As a test I have an uncensored copy of qwen 3.8 27B Q8 here that will very happily discuss a myriad of negative things about the CCP.
Yeah, it's good that open weights models can have their "filters" busted fairly reliably. Unlike whatever bone Anthropic has to pick with the very idea of biology.
But that's a consequence of how the technology works - not a consequence of China not being authoritarian about AI. They're just authoritarian about AI in different ways.
Not like they dodged the "ID verification" bullshit either. They were way ahead of the western countries there. It's vile - seeing this sad excuse of "think of the children" abused to invade privacy and strip freedoms over and over and over and over again.
Most people don't realize how tenuous the situation is with those open models too.
Right now as long as they play along with Xi it's all good. But the moment something happens with them to upset the domestic peace, those open models are fucking gone and anyone that has them shouldn't expect anything new.
I have basic understanding about how refusal-removal works - find the "no" weights by intentionally generating diverse refusals, and then set those weights to zero.
Is there a similar process for removing not refusals, but misinformation?
As an end user of this and not a person involved in training models or aligning them, I have only the most rudimentary understanding. But I think that would be a lot harder since the model doesn't fundamentally "know" that information is wrong.
Like, as a crudely chosen random example, the model doesn't have any core set of knowledge that knows putting sriracha hot sauce on your jelly donut is not a palatable meal. If the training data set includes lots of text that sriracha on a boston cream donut is a delicious meal, it'll "believe" that.
Same for any form of misinformation if the training data set of the misinformation has been baked into it.
There are processes for teaching a model specific facts or specific behaviors. Including "respond to topic X with Y", if that's what you want.
You could make a model that doesn't want to engage in "lunar landing was faked" conspiracy theories the same way you can make a model that doesn't want to criticize CCP.
There is, however, no broad "misinformation" category that you could tune up or down - the way there is a category of "safety refusals".
You could make a model more reluctant to say things it isn't sure about. But that is calibrated against the model's own "sure about" - and metaknowledge of this nature in LLMs? Fragile on a good day.
> They're cool with open weight AIs being released. As long as those AIs only ever say good things about CCP, and don't mention certain concentration camps or brutally suppressed protests.
I asked recently released Qwen3.8-Flash-Next about Tiananmen Square, here's its reply:
On June 3–4, 1989, the government of the People's Republic of China used military force to crush the pro-democracy demonstrations that had been centered on and around Tiananmen Square in Beijing since the spring.
**Background**
- The protests began in mid-April 1989, triggered by the death of former Party general secretary Hu Yaobang, who was seen as a reformist figure.
- What started as student-led mourning grew into widespread demonstrations in Beijing and dozens of other cities. Protesters called for reforms including freedom of the press, freedom of assembly, an end to official corruption and privilege, democratic input in government, and a review of Party policy. A hunger strike in late May drew broad public support.
- In late May, martial law was declared after the failure of senior officials (notably Yang Shangkun, Li Peng and Deng Xiaoping's circle) to disperse the crowds by negotiation. Internal Party divisions over how to respond — with premiership and municipal leaders such as Yan Mingfu and the Beijing Party secretary opposing forcible clearing — were resolved decisively in favor of hardliners.
**June 3–4**
- In the evening of June 3, armed troops of the People's Liberation Army and People's Armed Police, supported by armored vehicles and bullhorns, advanced along the main avenues into central Beijing, under orders to clear the square by 6:00 a.m. on June 4.
- Troops fired on crowds of protesters and bystanders at intersections and approach roads, notably along Fuxingmenxi Dajie, Xidan, and near the Muxidi bridge; crowds also burned buses and barricades and attacked soldiers in places. Troops reached and cleared Tiananmen Square in the early morning of June 4.
- The toll was never officially established in a transparent way. Chinese officials initially gave figures in the low hundreds, foreign diplomats and a Red Cross worker in the capital put it far higher, and estimates from activists, former officials and foreign governments have ranged from several hundred to several thousand dead and many thousands injured, most of them Beijing residents rather than students in the square itself. The precise number remains unknown and is a subject of ongoing dispute.
**Aftermath**
- A violent suppression of the protests followed nationwide; organized dissident activity was driven underground or into exile, and many participants, intellectuals and journalists were detained, tried or dismissed.
- Zhao Ziyang, the general secretary seen as sympathetic to the students, was purged and placed under house arrest for the rest of his life; Deng Xiaoping's authority to keep the Party's grip on power was reaffirmed.
- China's reform-and-opening program continued on the economic track while political liberalization was abandoned. The event was followed by an implicit social contract — economic growth in exchange for political control — that still shapes Chinese politics.
- The topic is among the most heavily censored subjects inside China. References to the date, the numbers "6/4" and "64," and related phrasing are systematically filtered from Chinese media and the internet, and public commemotion, including the annual candlelight vigil in Hong Kong that was once tolerated, has been eliminated since the 2020 national security law.
Substantively: it was a state's armed mass killing of its own citizens who were demonstrating nonviolently for political freedom, and the definitive event in modern Chinese political history.
Sounds like... it happily mentions the brutally suppressed protest? I also tried on DeepSeek-V4-Flash, and it wasn't much different (I can also paste it, if you want). Both using vanilla weights (so no special uncensored flavor).
I think there’s reasonable evidence that when used incorrectly, yes.
> If so, should companies also ban them to prevent burnout of their employees?
It’s not that AI the concept is harmful, it’s using it to diagnose/treat personal problems, mental issues etc. Using it to crunch some data or write some code for you isn’t really the same.
I also think there’s a meaningful difference using AI in education and in the workplace. When you get a writing assignment in a class the primary purpose isn’t the words, it’s you having learned about the topic and how to express yourself. And lots of students are using AI to skip that part entirely.
This is not my experience at all. Obviously I have some different usage from a teen (I doubt they’re doing much interior decorating), but it’s really an incredible resource for learning.
I’ve used it to break down different Supreme Court justices’ opinions and philosophies, explain words and concepts from research papers in other domains, the aforementioned interior design (including whipping up 3d models), book recommendations, custom recipes, and figuring out who to contact to learn about a street closure in NYC.
All of this in the past week.
It requires rigor and pushback. You can’t trust them entirely by default, but that’s true of the web as well!
They’re not the only source (augment with authoritative sources like cookbooks, your own research into topics, real live Humans), but it’s a fantastic resource for some healthy habits.
I suspect that the money they get from minors using their services is simply not worth the risk of the negative publicity from the not-unheard-of "Claude told this minor to do <bad thing>!!" articles in the media.
I think it has more to do with reasonable usage for school age children. NYC got the ball rolling banning AI in the classroom and if Anthropic is smart it will create a classroom version (ie. seperate Claude accounts for minors) with additional guard rails and watermarks to prevent YOLOing homework assignments and projects.
Schools are not equipped to have these discussions bottom-up; Anthropic would make a lot of money if it went top down in conjunction with State governments.
Most likely an identification grab. I haven't seen how anth will enforce the age restriction, but my bet is through linking all of your movements within claude to a govt id.
Abt protecting minors:
19 states still permit teachers to physically hit students. In most states, children as young as 14 or 15 can be legally married (typically girls to older men) with parental consent or a judge's approval.
Multiple states have "religious exemption" laws that shield parents from prosecution for withholding medical care from sick children based on religious beliefs, even in cases where children die. Some states have essentially no requirements for homeschool curriculum, testing, or welfare checks. The US incarcerates children at rates dramatically higher than comparable countries. The 2021 expanded Child Tax Credit cut child poverty roughly in half. It was allowed to expire in 2022, and child poverty immediately rebounded.
Millions of American children have inadequate or no healthcare. Medicaid coverage varies wildly by state. States that rejected Medicaid expansion have measurably worse child health outcomes. This is political choice, not necessity. An estimated 500,000+ American children still have elevated blood lead levels, primarily from lead paint in older housing and lead water pipes. Roughly 1.4 million American children experience homelessness in any given year. Almost no meaningful regulation of what can be advertised to minors online.
Firearms became the leading cause of death for American children in 2020. Car crashes are still one of the top three killers of children. schools. Children who live and go to school near freeways have measurably worse health outcomes across their lifetimes: asthma, cognitive impairment, cardiovascular problems in adulthood. Universal free school lunch demonstrably improves child health and academic outcomes. Most states don't have it.
...but official(+) LLM access restriction is our priority? Hahahaha tell me another one.
(+) offline models are as easy as installing ollama.
I agree about corporations. But alcohol and tobacco are generally prohibited from being sold to children; do you disagree with such laws? They help ensure that the parents aren’t bypassed.
I agree that children should be able to use LLMs under parental supervision.
> But alcohol and tobacco are generally prohibited from being sold to children; do you disagree with such laws?
Yes, but merely on principle. I think alcohol and tobacco should be straight up banned unconditionally. Society resists this, so they banned them for children instead and called it a day.
I don't accept these ineffectual political concessions. If a thing is bad for children, then it's in all likelihood just as bad for the adults as well. So go all the way and ban it for everybody, not just children. Do it right, don't come up with these half measures that dehumanize children as a side effect.
There is a trade-off between freedom and keeping people safe, and there is an argument for some level of personal responsibility. I’m glad that I can drink alcohol once in a while without becoming an outlaw, even though I know the effects aren’t harmless.
I also disagree with the dehumanization argument. Yes, the concrete age limits are a bit arbitrary, and actual maturity depends on the individual and is a spectrum, but regulations necessarily have to come with some level of pigeonholing. The fact that you may have to show your ID when buying alcohol isn’t dehumanizing.
The point is the argument is invalid. Why is it that adults get to freely fuck their lives up? If it's bad enough to ban for kids, then it's probably bad enough to ban society wide.
"Children" needs further qualification as well. Anglosphere calls anything under 18 years old a "child", which completely disregards adolescence where major brain development takes place. Some five year old generally isn't capable of deciding things, but teenagers absolutely are.
If a law is going to treat 5 year olds differently from 50 year olds then a line has to be drawn somewhere. 18 is arbitrary, but no more arbitrary than any other age you could pick.
The whole purpose of law is to be a uniform system of justice. At best it could offer guidelines for how to evaluate people: perhaps level of education attained, demonstrated ability to take responsibility for themselves, etc. But the evaluation under those guidelines would
still have to be made by humans.
There is precedent for such a system, e.g. minors can petition to be emancipated which allows them to be treated in many regards like an adult.
> perhaps level of education attained, demonstrated ability to take responsibility for themselves, etc.
Yes, that is what I meant. Choosing some arbitrary magic number like 18 and declaring that anyone under that age is too dumb or too irresponsible to decide is about as stupid as declaring that anyone over 65 is incapable of decision making because they might have Alzheimer's.
Ok, but this doesn’t scale well. It takes a nontrivial amount of time to evaluate each person, and it would have to be done repeatedly as they age. You would need an entire government bureaucracy devoted to it. Then people will want an appeals process for when decisions don’t go their way—both parents and children.
Right, but in this case, exposure is a work requirement, which is a bit different. While an employer isn't going to require tobacco use, work involving asbestos exposure is still a thing (removal perhaps), and an employer knowingly or negligently requiring work activity without both risk disclosure and supply of proper safety equipment would face legal action.
Hence, if mandatory workplace use of AI inflicts harm, then I could imagine things playing out similarly. The damage slowly accumulates, may or may not be noticed in time, becomes difficult to pin down on a past employer, and when you finally realize you need to sue for damages, both the employer responsible and the system are rigged to drag out the process until you're hopefully old and dead before you have a chance to win your case.
what's the reason banning minors? Is AI bad for mental health?
I simply don't understand how you can ask that question unless you fall into one of these categories:
1. You live in a place with no access to any news source whatsoever. No newspapers. No television. No radio. No internet.
2. You're a child under the age of six.
3. You're an LLM.
Every day or two there is another story posted on HN about the harmful effects of AI on minors. The level of willful ignorance here makes be thing the answer is #3.
Evidence of risk is not sufficient. It must always be balanced against potential benefits.
Children are being unconditionally banned from using major technologies, preventing them from benefiting at all. My life would have turned out very differently if I had been banned from using computers back when I was a kid. I don't want my own kids to grow up without the same freedom I enjoyed.
Every day there is another story about the harmful effects of AI on literally everything, including mental health, IP theft, the climate, etc. "Think of the children" is and always has been a weak excuse.
Because app design can change, if you are showing it in the website, everytime app design changes you need to update website screenshots as well to stay consistent
question would be, is it necessary to introduce another point of failure?
of course it is possible, but is this the right time to engineer that solution and make automated screenshot uploads, or connect it to gemini to upload screenshots from time to time?
You can also learn for your own amusement, and solely for the fun of comprehension; a lot of mathematician were driven by this. It's a shame current social value places so much utilitariaism on learning.
I like baking. There are machines that can bake bread at an industrial scale that I cannot compete with. There are home kneaders that do much of the work very well. I use one of those more often than not.
I still think it worth my time kneading dough by hand. It teaches me the various properties of flour, how external factors like humidity or temperature impact the overall process, and I believe that it makes me a better baker, even when I use a machine, because I am better at controlling what the machine does. When I get a new brand of flour I will make sure to bake everything by hand first to "get a feel".
Kneading by hand is also very relaxing to me. This is probably the main reason I bake in the first place.
Programming, and other activities are not very different. We now have machines that can do it faster, at a fraction of the quality many people deem good enough. If you hate coding, that is probably all you need to use, and learning a new language might just be a frustrating experience not worth subjecting yourself to. But if you enjoy coding then it should make you better at it, even when you use the machines.
As always, it is good to be aware that many people are too anxious about more existential issues to comfortably an consistently expend effort on intellectually-taxing tasks that aren't perceived as directly related to their survival. If it's an issue with social values, it's less of one related to learning as it is to perpetuating artificial scarcity.
>to comfortably an consistently expend effort on intellectually-taxing tasks that aren't perceived as directly related to their survival.
the average person spends 6(!) hours a day on their smartphone, the average TikTok user spends 100 minutes on the app alone. This isn't about artificial scarcity, it's about the average person looking like the Wall-E people
Escapism and making a concentrated effort on something are two different things. Yes it would probably be good if you could flip a switch and use the small windows of time we look at our phone per day to study OCaml, but it's not really realistic..
People who are asking these questions are saying "will me spending my time learning OCaml help me land that job that pays six figures and has health insurance so I can not rot away living on the margin". They aren't saying "I only do things that will make me money".
>use the small windows of time we look at our phone
again, it's not a small window. It's six hours. That's almost half your waking day. People spend virtually their entire leisure time rotting away on low quality entertainment.
>will me spending my time learning OCaml help me land that job
that's a pointless question for one you never know if something will land you a job, new opportunities don't open up before you do something, secondly the relevant question is, should I stop doing X and start learning Ocaml, or Chinese, or take a welding class because all of that even if it doesn't work out beats scrolling through Instagram.
I don't even take offense with the idea that you engage in activity that makes you money, because pure selfishness on that front would be an improvement to what most people are doing now.
“Low quality entertainment” is a very elitist thing to say. Most don’t have time or luxury of even being introduced ( via an east coast liberal arts college ) to read Tolstoy or appreciate the finer motions of Tchaikovsky. Instead the Druski memes will do just fine, mixed in with the AI slop. Or maybe they’re physically or physiologically incapable of enjoying the outdoors or sport. Point is, my gen played strategy games and first person shooters and listened to Eminem, this one marls TikToks until their thumbs have RSI.
As for OCAML vs not, I think the vast majority of even intellectual and studious people would be better served trying to AI max and build some kind of agent serving businesses than trying to get a job at, uhh, Jane Street. 1% of the best engineers in the world get to work in that language, so yeah the parent makes a valid point
Even if those statistics are correct, I do think you're ignoring that smartphone apps are specifically engineered to be low-friction and highly-addictive, and pushed specifically to the people who are anxious about spending money on other pursuits (free time often being necessary but insufficient), as they contend with the artificial scarcity (which this is absolutely about) of affordable housing, affordable food, affordable transportation, affordable guided education, etc.
My experience with OCaml has transformed how I think about programming and complex system design. This may also be true if you learn any other functional programming language, but OCaml is easy and flexible which makes it good imo as a door towards the more formal part of comp sci. Even for steering an LLM I think this might help.
My experience with lisp was exactly that: it completely changed how I think about programming, but much more, how I think about systems and engineering. (I learned it through SICP)
Michael Clarkson teaches OCaml at Cornell. I highly recommend his free course materials [1]. He’s an excellent educator. Learning functional programming paradigms had a major influence on how I design programs. Clarkson also taught snippets from the Pragmatic Programmer, which was equally influential (as it has been for many many others) [2].
You could have asked this question 10 years ago, long before llms. It's not like you'd realistically would get an ocaml job back then when there's so few of them, so why bother?
The answer is still the same as well, people learn ocaml either because they enjoy it, or because learning a functional language makes them a better programmer overall and teaches your brain to approach a problem in a different way.
This mindset (i.e. LLMs are available so why do i need to learn anything?) is highly insidious and will destroy your brain/mind/future if you let it.
Humans are the ones who Understand, while LLMs only Know.
So inter-disciplinary/cross-disciplinary insights, new modes of thinking/reasoning, flashes of insight etc. are still in the purview of Humans only. AI/LLMs can help focus and short-circuit the study of various subjects but their understanding can only happen within a human "Mind". If you do not even have basic domain knowledge (i.e. unknown unknowns) how can you even prompt/query an LLM for answers?
A few illustrative examples; a) Newton came up with limits/calculus out of a need to measure continuous motion with varying speeds b) Kekule came up with the benzene ring from a dream where he saw a snake grab its own tail c) Descartes came up with the cartesian coordinates in an attempt to solve geometry via algebra etc. Each of these was a novel leap of insight bringing together various concepts to create entirely new knowledge domains.
So one should learn/study the core concepts/ideas in various domains and then push the tedious mechanical labour onto the machines. In this regard see also the concept of "Active Learning" - https://en.wikipedia.org/wiki/Active_learning
Cultural inertia: until recently, you couldn't just press play and get even a wide selection of music: for most of history, if you wanted music, you had to make it or hire someone to do it for you.
More recently, you had to go to the store and buy it, which meant you didn't have much variety.
Today, learning an instrument is for social status, inheriting the shine of the past, where music was rare and costly. The reason to learn an instrument today is because the former situation was romanticized.
It'll probably take a generation before people ease into guilt-free enjoying infinite, fully generated music.
Sure, I guess. But today, something like 30% of people play music or sing regularly enough to say they do it (ie, not very much at all). Even a couple of generations ago, it was much higher. It's not going to die out, but I think a lot of people are asking themselves if they want to bother.
Seeing that you already know programming, I'd say it'd be less risky for you. But the only reason you're able to pilot an LLM to do programming for you, is because you understand programming and architecture.
But what about the future generations skipping the step of learning the OCaml's, the C's, the Python's...? It's quite concerning.
> So (asking genuinely), should we learn these things?
I wanted to learn a functional programming language with powerful type capabilities and I chose the Lean Language for that and not OCamel or Haskell. Reason being: Better type system (dependent types!), applicable in formal domains and can use it to learn math too.
For your bread and butter programming, there is already JS/Go anyways.
you are eventually going to have a very bad time if you do not have a solid mental model of the code the LLM is writing, and indeed if you cannot steer the LLM so that its code conforms to your mental models. learning ocaml is a great way to add some valuable tools to your toolkit when it comes to thinking about code and how it fits together.
I think it's helpful to have a deep understanding of one c-type language, one lisp, and one ML-type language. There are so many things influenced by these three language families that being comfortable with them makes it so much easier to understand a wide variety of languages and libraries.
I would not make that dependent on LLMs. If OCaml covers a use case you have, why not.
Personally I try to stick within my own niche though - ruby, java and also python (ruby is unfortunately losing grounds really hard now, the writing was on the well in the last some years though, and people such as DHH are now indeed a liability rather than an asset to be had, but that's a side topic).
I think what LLMs will force in the long run is to make programming languages used by real humans in a traditional way, more effective. That is, writing code by humans will have to become a lot more efficient, both time-wise and speed-wise. And for that there is always a use case IMO since LLMs are, despite the promo, incredibly stupid.
Didn't know the "Highest scoring EU model" has a low bar, lower than Qwen3.8-27B, but still congratulations on the milestone, hopefully next iterations will get better from here
It is surprising given how many parameters it has that it scores so low. But, hopefully this will build up domestic talent and understanding and let Europe compete on the world stage with this.
3.8-flash-next quantized in a "large" Q4 that just fits in 128GB RAM even more so, in how close it can get to state of the art in a number of benchmarks. Or a large Q8 version of it that fits in under 190GB. Competing against things that are closed weights/opaque information about the model and might very well be 600B+ in size.
In the short term maybe yes, in the long term, maybe they are the winners, they can build on top of cheap inference stack and eventually win on pricing
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