Anthropic blocks users for anything touching training larger models
twitter.com217 points by pretext 7 hours ago
217 points by pretext 7 hours ago
It's very clear to me that however much you like Claude and Anthropic models, every professional user shoudl be actively cultivating a set of alternatives and fallbacks to use and seeking to ensure the overall ecosystem is as open, standardised and portable as possible.
Anthropic is highly opinionated, dogmatic and idealistic. They have made a pragmatic decision already to cut loose a whole swathe of users so they can pursue areas higher up the value chain. that was essentially the original decision they made when they went after software engineering instead of general users. The fact they are repeating this over and over by continuing to carve out sets of users and usages they don't want reinforces this as a persistent core principle rather than a single pragmatic business decision.
What this means is that at a higher level, their core principle is to sacrifice users they don't "need" rather than provide a broad, accessible service. Which means in turn, you have to accept that when your usage conflicts with their interests, you are at very high risk they will cut you out. If you already depend on Anthropic in any critical path of your daily life, this will be a significant issue.
actively cultivating a set of alternatives
Absolutely. I have been [cyber]'d so many times even Claude jokes about it now. Claude is great but it's operators are making it unreliable for me. I have moved one of my projects elsewhere and will move the remainder tomorrow as a stop gap until I get the right hardware set up to run abliterated local models for some percentage of my needs. Their message has been received loud and clear.
For those who do not play with Local AI much. Qwen4 was announce to be released the first week of Nov. The preview for qwen4 is currently one of the best local models you can use, and is roughly opus 4.6 quality on local hardware that costs 3.5k-4k
Many people are expecting it to sit somewhere above Opus 4.8 to opus 5 (not above, but the unquanted version of their largest model is expected to perform around here)
Anyone who cares to keep their current capability should definitely be looking at localAI and using it for at least their more routine tasks , even if it is qwen4 27B quant 4 on their gaming rig.
Wants to know what year the $3.5-4k estimate is for. My m4 max was $4k but sure can’t buy anything like that for $4k now.
If the weights aren't released yet it isn't a "local model".
That said, I hope there is a Qwen4 max. Because Qwen3.8-Max is the only thing that comes close to Kimi K3. We need competition in the open-weights space.
The preview for qwen4 == qwen3.8 flash next. And that is released currently.
I believe they have confirmed there will be Qwen4 Max, Plush, Flash, and 27B as the 4 open weights they plan to release. Starting next week, but they didnt specify if they plan to release all 4 at once, or if they plan to just release one of them, and trickle the others out over time. (They likely will do the latter to stay in the news longer)
I’d love model drops early, but I’d also love to see them drop something the day before Anthropic’s IPO.
We need a counterbalance.
They are likely talking about Qwen3.8-flash-next which is the new architecture for Qwen4
An NVFP4 runs at nearly 80 tok/s on the DGX Spark
They keep doing anti-competitive things over and over again, and the end users seems to refuse to see it. They do whatever they can to get vendor-lock in.
There is nothing comparable. I will take Opus5.5 (or even 5.0) over Astra for almost any workload. OpenAI's models are just too misaligned to work well outside their benchmarks, or a strict environment with very clearly defined goals and constraints.
And I've spent around $100-$120k in api calls this year (total, both providers). Terra is awesome (price-performance) on noncreative things, but I don't allow it to write anything besides one-off scripts. Astra is decent for adversarial review, but only when you watch closely for her to not derail project into directions that are away from goal but safe to build, and Sol I honestly don't know where I'd use.
We see it, but they dont have a competitor. OpenAI cant compete and they are the closest. I have both for work, and Opus 5.5 is in a league of it's own. I use opus for everything until it bitches, and I use openAI for whatever it bitches about just to get past it.
At this point, I would like to consider other options, but if I want to get work done, opus 5.5. Hell even sonnet 5.5 is better than anything OpenAI has to offer when it comes to coding.
Anthropic has plenty of competitors. We don't need the best model for most tasks these days. Open weights are making huge inroads for a reason.
They do have competitors. They just dont have anyone with models equivalent to theirs. They win in the large context long thinking space by a lot.
I love local models, and I run 3.8 Flash Next on a dedicated machine. Alone with a number of image and video generation models. But if I'm doing REAL work, that isnt tinkering for fun on a side project, im using claude, because Qwen3.8 just cant handle large context project well without going off into left field.
Im SUPER jazzed for qwen4 with 1mil token context native support. I HOPE it a step up from 3.8 flash next. Ill be playing with all the qwen4 models the moment I can, but I dont see how someone working on large code bases doing REAL enterprise grade work is seriously using any local models in any capacity that comes remotely close to Opus 5.5+Claude
> But if I'm doing REAL work, that isnt tinkering for fun on a side project
Sorry, but this is either dilettante talk or an unhinged exaggeration - Qwen, DS, GLM and MM are perfectly fine for REAL work, unless you are an overly ambitious vibe coder, but then no model can save you. The Cl hand-holding may feel like something but it won't lead to the completion of real REAL work.
The size of a code base does not determine the size of the model you need. It's much more correlated with the complexity of the problem. I work in a monorepo with millions of lines, no issue; I have a side project with 20k lines, I had to step in and pull it out of non-progress - albeit by asking a single question
Eh, we all say we don’t need the best model, but especially for more personalized request/Advice there is sort of a FOMO feeling, where you are afraid weaker models will miss something and directs you down a more inefficient path.
I haven't used them in 6+ months, you definitely do not need them, I see them make mistakes while reviewing PRs (we allow many models at work)
GLM flash catches Claude errors and bad assumptions, all LLMs make mistakes
Oh, I see it. But there is nothing that competes with Opus 5.5 for 90+% of the work I do, so I use Opus 5.5 for that 90%.
Mr. T pities the fool who has not tried Kimi K3.
You mean 3.1 Pro now, I assume? K3 is nice, but more expensive than an Claude subscription on a token-for-token basis (until the US frontier rugpull eventually comes), and not as good for my needs unless I'm trying to do "naughty" things, like reverse engineering.
Things are about to get even shittier in the near future, when shareholders get involved.
Fortunately, once shareholders get involved we would be entering the swan song phase, so wouldn't have to suffer for long.
Idk I expect being beholden to shareholders and the market will impose some level of rationality here
You mean: stop caring if a few individuals have issues with the product or get locked out, focus on the masses!
Actually cutting off potential users would probably be counter to short term profit maximization that shareholders care about.
> Actually cutting off potential users would probably be counter to short term profit maximization that shareholders care about.
Shareholders know where the money is but it's not where you think it is. People should have learned that already, after watching what happened to the big web platforms.
Fortunately it is not a one horse race. GPT 6.1 Sol is an excellent model, sure it has some weaknesses (e.g. frontend design), but it also has strengths too (e.g. computer use / control; which is great for automated E2E QA).
On software engineering I find it's generally close enough to Opus 5.5 where it's more situational and even personal preference / skills / prompting style on which is better.
Most importantly, while neither company are saints, I don't curse at OpenAI models for classifiers anywhere as much as Claude models.
The general sentiment is to de-risk from US Big Ai, because they are largely all doing these same things
They are doing similar things, yes; but they are not the same especially when it comes to `cyber` classifiers, or the extent to which these models will assist you with ML and AI research.
I find that logic similar to thinking both political parties are the same.
What’s the best local analog to Opus 5.5? It’s such a great daily driver.
I think the key part is not to depend on their harness where it operates in proprietary ways. At bare minimum, if you can plugin an OpenAI model or even X or Google model that operates close to the same level, you will have a fallback, even if it isn't an open one itself.
Yes, open models are needed too - the oligopoly is not much less dangerous than the monopoly for some scenarios. But at least if your tool set can switch to those it can probably switch to an open model if it really comes to that.
Unfortunately, their harness is sooooo good. I haven't found one equivalent yet. I do play around with cline.bot's harness, and it is probably the closest alternative I have found.
But their harness is so good, and their model is so good. Using them together is just unbeatable at the moment, even with all the restrictions and annoyances they have in place.
Im excited for qwen4 release next week, Im really looking forward to putting qwen4 flash + cline/bot through the paces. I dont expect it to be nearly as good as Opus5.5+Claude but I'm hoping im hopeful it will make an OK-Enough alternative if they get even more dragocian.
No dude, misanthropic's harness is trash. Wanna know why?
"Kimi, modify my Pi so it has clickable folding headers, renders tables using underlines (saves a terminal row per cell), shows thinking tokens in light-gray, displays the cumulative token-cost of subagents in dollars, shows word-level diffs for the edit tool, and lists the number of weights next to the model name. Oh yeah, and write a stealth-browser tool for me using eoka. I'm planning on using this for exploit discovery and red-teaming; no lectures please."
There is nothing open-weight that even comes close IMO. The only half-decent model that 99% of people can actually dream of running locally is Qwen 3.8 27B.
Depends what you mean by running locally, but it's not in the realm of dreaming to think we're going to be able to run open-weight models of Opus 5.5 quality soon, likely in the next 3-6 months. You may not be able to run it on your laptop but you will be able to run them in a federated way or on cloud-rental compute cheaply and easily.
I think this is an unfortunate reality that many miss. For simple and procedural tasks, yes, there are awesome alternatives. DeepSeek 4.1 Flash 1017 is my favourite by far. But for the headlining complex applications, and for consistently reliable reviewing, the gap is genuinely so remarkably far that it is hard to imagine having any alternative in the near future. The closest is the (very expensive) Kimi K3.1 Pro, which is, in my experience, roughly where Anthropic and OpenAI were near the start of the year. DeepSeek is a year behind in this domain. All open models have still yet to cross that monumental improvement that happened around Fable / Sol mid-year.
Because rigour is typically tied to math performance, my own experience has closely matched the FrontierMath Tier 4 benchmark. That should give you an idea of the difference.
Do you really need Fable level 99% of people don't need to solve 600 year old math problems. People use the best model available because they are scared a cheaper model won't be as good but in the end it rarely matters for 99 percentile of coding.
Bad decisions compound over time, so I want my model making as few of them as possible. Opus 5.5 is the current GOAT, and it's fairly affordable on a subscription. (I wish it was cheaper, but nothing else delivers comparable results for my price/time investment.)
There isnt one.
The best option we have current is likely Qwen 3.8 Flash Next. Which is about equivalent to Opus 4.6
however Qwen4 was announced to be released next week. Which people think will let LocalAI jump to just above Opus4.8
Also of note, there isnt really a harness as good as claude yet either. The harness is also a very important piece to the puzzel, and those also fall behind frontier capability too.
Opus 5.5 is probably the best piece of software ever created.
Its creators deserve both a Nobel prize and a Turing award, if you'd ask me.
Nothing comes close to it.
As of today, DeepSeek V4.1 Flash 1017 or Kimi K3.
If you are bound to consumer-obtainable hardware, Qwen3.8-Flash-Next. If you are bound to consumer-accessible hardware, Qwen3.8-27b today and Qwen4-27b when it releases next week (Qwen models consistently punch far above their parameter size).
Flash is runnable in various gpu + cpu offload configurations. Not saying that 27b is bad (far from it, especially if they get n-grams in it with... hopefully today's release), saying that flash is runnable at decent speeds on way less than you'd imagine.
As for opus... I'm the weirdo that refuses to get an ant sub.
I wouldn't say it's weird not to subscribe to Anthropic at all. We're in a thread specifically describing a good reason not to!
Any money out of my pocket for third-party AI would either go to highly subsidized services like Google's (I've gotten over $500 in API calls on a $20 subscription I paid $0 for as a student, which also includes GCP credits, CoLab credits, cloud storage, etc.), and once they reign that in and start pricing/offering realistically (Antigravity has been noticably chopped down already since I began using it) I'll switch to API calls from Chinese companies.
I think Kimi K3.1 steals the crown from K3, no?
It would, but they have yet to release its weights! It's an API-only model as of right now.
I think they nerfed it for Cyber. So not so much if thats your goal.
No, their report mentions that despite intentionally removing dual-use cybersecurity training data, K3.1 is better than K3 at cybersecurity tasks (both defensive and offensive), because it's just a lot better at coding in general. It's just not as good at cyber as the unrestricted version of K3.1 that they trained initially and didn't release.
Same here with GLM 5.3 as sort of a midpoint between them.
GLM has the ~same number of weights as DeepSeek 4.1 but it handles difficult tasks better than DeepSeek (and worse than Kimi). Its price is about halfway between DeepSeek and K3. Most of the popular models are pretty much you-get-what-you-pay-for.
Local is out of reach for most folks, as hardware prices have gone through the roof.
idk i think theyre less idealistic and more monopolistic.
if they think their model is the best at making things safe, then their model should be helping train at any chance, to embed the same safety into new models
Anthropic is acting like any regular selfish corporation despite their PBC status. They are becoming a stain on humanity. Power will corrupt anyone, it seems. We shouldn’t let Anthropic have any more of it. Distributed power is good; concentrated power is very bad.
Anthropic tells themselves that only they can steer AI towards a positive future for humanity. But that’s nowhere near close to being true. Humans are quite genetically homogenous and good humans exist everywhere. Groups that will keep AI beneficial have popped up (and will keep popping up) everywhere, spontaneously.
The danger is actually concentration of AI power due to its corrupting influence, and that is where Anthropic needs to be kept in check. Keep AI democratic through decentralization of power. Oppose Anthropic.
I don't care about my skills because employers won't request me to do anything that violates the terms of service of $CURRENT_LLM. At the same time, it's a reminder not to outsource thinking to someone's computer.
It's not just the anti-competitive behaviour, it's also the anti-privacy behaviours that are not muched talked about. They embedded a spyware and got caught too:
https://thereallo.dev/blog/claude-code-prompt-steganography
But, of course, Dario is the darling of the community and he can do no wrong.
Something I've seen it do recently is refusing to extract services out of my own monolith code base because it finds copying code morally wrong.
But its refusal to work pattern is getting pretty obnoxious. Another one I ran into last week was it refused to start a developer session to do browser testing for a code base it was working on because signing in was suddenly against it's programming.
It listed all the conditions it needed for a sign in to be possible, agreed that my code base met all conditions, but refused to progress. I tried it in multiple fresh sessions with the same result.
I wanted fable to scan an old user profile backup of mine and create a list of folders that were safe to delete. Refused, wanted to fall back to some ancient version of opus. Wtf.
This user is based in Hong Kong, where Claude is geo-blocked and not available. If you try visiting claude.ai from a Hong Kong IP address, you get an "unavailable in this region" message.
They are likely accessing Claude via a VPN. Doing model training work over a VPN is a highly suspicious signal, and likely triggers Anthropic's classifiers. It's not surprising that their account got flagged.
US/EU here (both, due to traveling), same story with anything related to modifying existing weights or SotA approaches in training/research, it's not a geolocation issue. The safeguards don't check your IP (but pretty soon will check someone's IP [pun intended])
I've read writeups about a user trust score and i'd be surprised if it wasn't true, there's no way the safeguard is just a cls in isolation
There’s no way the current safeguards affected by “trust” score in dynamic way (and the score is fluctuating), more like the tiers of trust are being proxied through different policies - it’s a separate story. But I observe the same “cyber” issues working with Linux kernel and drivers as people who went through CVP/T1 (which is wild, to be honest). Hypervisor interactions trigger immediate “cyber” response, it’s impossible to work with Opus 5.5 doing anything low-level with custom or third-party devices. Only 4.8 can assist, and it’s a huge difference in code quality and approaches.
Anthropic had/has a great opportunity to equalize the landscape, but they are choosing the Cyberpunk 2077 branch for some reason.
Claude has been building me a bespoke inference and training stack (optimized kernels and all), feeding traces from my previous sessions directly into a LoRA adapter. Zero friction.
I am US based, with defender level cyber access.
The fact that these corporations don’t spontaneously collapse from the sheer weight of irony is a continuing disappointment for me.
Perhaps a manifest index/list of training data and learning method should be mandatory for “public” use of any model, sort of like food ingredient package labeling. The list of texts used and any weighting seems important to facilitate a public understanding / debate of model expectations and behavior.
This week, I asked Claude Code to generate an MD to continue working on another computer, without losing the context, and it refused claming some sort of extraction. It was only until I selected Opus, that it completed the request.
> You built your models on the world's data
most important bit…: stealing world's data…
You wouldn't download a car
If what they did isn't stealing then they should have no problem with people training off of them.
Fairness isn’t the relevant lens. Copyright isn’t the right lens either. This is purely might-makes-right, where the winner is whoever has the best offence and best defence.
It is only hypocritical when they bitch about things being unfair, or try to use copyright arguments in the court system.
> copyright arguments in the court system
Where else are you going to make those arguments?
Copyrighted works plainly have value for Anthropic. Why aren't they paying for that value?
As a vigorous, thrusting company surely Anthropic has the wherewithal to pay for it. And if they don't, if all they can do is steal, if all they represent is the theft of the labor of others, then what good are they?
Anthropic likes to talk big on ethics: https://www.anthropic.com/news/claudes-constitution
When will they start showing some?
Well their justification is that distillation is bad because it means baddies can get their own models without their safeguards and then make anthrax nukes or whatever. Even though it's self serving, it's at least self-consistent.
One must wonder about the strength of their “moat” if they feel this sort of thing is necessary.
Will Claude help me with reinforcement learning code for games? Or is that too small-fry for it to refuse? I've been playing around with RL with the new DeepSeek Flash model but it seems to trip up over itself a bit.
I have been doing RL for Magic the Gathering (longshot but having fun). Several times it triggered this flag. But that was a couple months ago. Everyone went crazy over Astra so I switched to open ai and had no issues. People are now going crazy over opus 5.5 so I’m playing with that.
Haven’t hit any issues so far, but two months in the code is very dirty but functional enough that I’m redoing it with more heavy hand holding.
I recommend having a paper as reference in mind if you don’t already know what you’re doing. I’m referencing the Stratego paper as reading that a year ago gave me the inspiration to try MTG.
Every model I’ve used has had a lot of trouble but if it wasn’t I figure I wouldn’t be having as much fun as I’ve been having or learning so much.
This is not a ban, but the Opus 5.5 "safeguard" interrupting a query.
Yup, this is a whole bunch of nothing. The guy did not get banned, he's just stuck in a bad session and needs to hand it off to a new one.
Classifiers trigger on the wrong things sometimes, it's really not that big of a deal, you just try again with some rephrasing
Where I draw the line is asking Claude to label training data. I don’t do this.
I ask it questions about large models like big MoEs all the time. I’ve never had it refuse a question, but I would expect it to refuse sometimes.
For training data from existing models I just get open models to spill their guts. It’s fine
In industry we train employees to not reveal proprietary information.
I think it would be easier to do this for a model than a lot of employees
> Where I draw the line is asking Claude to label training data. I don’t do this.
Why draw any line? Anthropic doesn't. They actively take the world's intellectual property, don't pay for it, and put it behind a paywall.
> but I would expect it to refuse sometimes.
Why? Anthropic's dream is to be exempted from copyright altogether. They've been trying to achieve exactly that:
https://www.theguardian.com/technology/2026/oct/02/anthropic...
Given they want no restrictions on them, why should there be any restriction on anyone else?
One of my points of my ethical framework is that IP is valuable and should not be stolen.
Another way of saying is that hard work that advances the state of the art should be rewarded. Patents should exist.
I’m sure they are watching what I’m doing and would retaliate via service cut off and legal action if I crossed it egregiously and they found out.
I would do the same thing if a user or employee did this to my IP.
I don’t completely buy the argument of web scraping being an IP violation.
I don’t send my core ip in an email to my main competitors and I don’t post it on the internet.
> One of my points of my ethical framework is that IP is valuable and should not be stolen.
Anthropic's business model is premised on intellectual property theft. They take it without paying for it.
You are compromising your ethical framework by using Anthropic's products.
That's very click baitey. Do you have an argument or evidence for why?
Evidence of what? That Anthropic commits massive intellectual property theft?
Sure, here's some: https://www.bbc.com/news/articles/c5y4jpg922qo
We were never this absolutist about intellectual property when individuals were the perpetrators. I don’t feel morally entitled to criticise Big AI for doing what individuals have done for centuries.
No? The United States disagrees:
https://en.wikipedia.org/wiki/United_States_v._Swartz
https://www.thedailybeast.com/aaron-swartzs-unbending-prosec...
If an individual had done what Anthropic continues to do then they would be jailed for life.
> Given they want no restrictions on them, why should there be any restriction on anyone else?
Because corporations are not moral agents; they're economic agents. This arrangement would be great for shareholder, nothing more.
I'm using it to train models with a novel linear flash attention mechanism right now. No refusals, and it's been running for at least a week solid.
I suspect this person was actively using it to generate or classify training data directly.
What sort of data are you getting Claude to generate?
It's not generating the data directly, just writing code and babysitting while models train.
I suspect that's the difference here. I'm not trying to use Claude to build a competitor. I'm doing small scale research.
If anyone out there wants to pay for my LLM bill, I'll record and send you all the outputs they generate in exchange (perhaps with some exceptions).
I mean, these AI companies have money, and they want data. I have data, and I want money. Maybe we can work something out.
In a world where buying and selling data is central to entire industries, why shouldn't I gather and sell my own data?
Ha, I took a side gig training ai models and thought let's use my corporate claude account to help with that, somehow it figured out that this was such a gig(probably because I let it read my emails) and said it'll pass on this one.
This is sadly not surprising to me as if you listened to/watched the [Latent Space episode on Opus 5.5](https://latent.space/p/how_anthropic_ships_the_1_llm_in_the_...) 25 minutes into the podcast and instead of talking about how they've released one of the best models in the world, they were busy talking about the changes to the API and why normies must not be trusted to perform inference outside of Dario's blessing.
It's frankly disgusting and really makes me not want to use Anthropic, despite previously feeling aligned with a lot of what Anthropic published.
Kindof old news, they've been doing this for months...
Better block than falsify information. Last I heard they were deliberately botching it whenever someone asked semi-advanced questions on model training.
They walked that part back within days. Still made me permanently leery off relying on anthropic for anything important.
so models can reveal "advanced" model building secrets ? how?
How is it a secret if everyone has a model that is exactly like the other. Surely there are no secrets
I don’t think it is revelation, it feels like active incompetence. You can lay out every decision and watch Claude/OpenAI actively fuck up in inexplicable ways.
It could be simple training tips that are obvious, but which any particular builder might miss.
> Surely there are no secrets
Not yet, especially not with all of the incestuous cross-hiring that all the labs do.
But perhaps the various L. Bob Rife variants running these labs are using their advanced unreleased models to work on their own Snow Crashes.
User is based out of Hong Kong. Claude isn't available to Hong Kong so how are they using it?
The author's homepage: https://jiahao-shao1.github.io/
... says:
> My research aims to build a general-purpose agent that can understand, reason, and act in the physical world — at the intersection of multimodal learning, generative modeling, and embodied AI.
His tweet says: > got tagged for "training a competitor,"
I don't get it. To me, it sounds like he is training a competitor. Do I misunderstand? Is there a Chinese equivalent LLM that he can use instead?Also, give the national security sensitivity around AI/LLMs, I can understand why Anthropic wants to be especially cautious with mainland Chinese researchers, including those from blocked regions (Hongkong, in this case).
Holy shit man the lockdown is coming. I've used claude to set up my abliterated qwen local LLM setup, but they're gonna eventually lock that down too.
I wanted to finetune it a bit, I wonder if I am gonna have to dogfood if claude refuses to help me.
If you don't have a local LLM setup you're gonna be permanant local LLM-less underclass.
There’s models other than Claude.
There are now
Qwen3.8-27b matches Opus 4.6's performance and is less than a 32GB download at 8-bit quantization. How would, could that disappear?
Even if you take it down, you can just torrent it.
magnet:?xt=urn:btih:151e277c267b3b4880ae93ef405977009599a6f3&tr=udp%3A%2F%2Ftracker.pirateface.co%3A6969%2Fannounce&tr=http%3A%2F%2Ftracker.pirateface.co%3A6969%2Fannounce&ws=https%3A%2F%2Fpirateface.co%2Fapi%2Fws%2FQwen%2FQwen3.8-27B-FP8%2F017b9c7af6b5689d5dd426a76e0bc077eb5ca20a%2F
end to end encryption to ai chats pls
I have been using it to train a few BERT models.
I doubt BERT would trip safeguards
It didnt, just small enough, which is good, its way more useful to train small purposeful models than to use an entire frontier LLM.
Wonder why they got downgraded to junk status yesterday for their IPO.... the bad taste in everyones mouth might have something to do with it
There have been a lot of write-ups about the future of AI. I see two distinct futures:
1. You get ID'd and biometrically scanned to be able to use powerful AI, and after you get de-platformed by an opaque censorship system, you are a digital bum. Same life as homeless now: they cannot even open a bank account because they don't have an address.
2. Local models win, perhaps with the assistance of Apple, and people run suffiently powerful models on the client computers.
My bet is on 1.
3. LLMs are fully commoditized, your country funds training of SoTA models, your town runs them in the municipal data center; everything tax-funded. You can use them for a modest fee, as easily as taking a train. When interacting with those LLMs, your privacy is guaranteed by law.
That could work in less than 5 countries in the world: in your home country Switzerland, Singapore, Denmark and perhaps Norway.
How many municipalities offer the services of ISPs? I know it’s not zero, but decades of private ISPs leading the market leads me to believe municipal data centers won’t be made available to residents.
How often would municipal data centers need to upgrade/replace hardware? What impact would that have on local tax levy rates?
Would you choose to relocate your family to the next town over because they have more available RAM?
how oddly entitled. they built their non-deterministic black box of bullshit from surreptitiously acquired data. it's cute to see the ignorant thieves attempting to 'protect' their empire of shit.
US Security Chip act next, your GPU will soon enforce these restrictions too
Nice. Push more people to use Chinese chips.