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> Instead we have a majority of society that wants to see AI fail.

Do you talk to regular people? I work out of coffee shops routinely and literally like 90% of laptops have ChatGPT or Claude open. I was shocked at how many of my friends love the silliest of AI features (like Slack bot summarizing your day or your upcoming meetings), and a lot of decks, proposals, SOW's, etc. are (at least in part) generated with AI these days.

LLMs were invented by AI2, before Transformers were a thing - with RNN-based ELMO.

I don't want AI to fail but I would like to see Altman anf Musk fail for example. I'm very uneasy with the power hungry silicon valley freaks that are running the show at these labs/companies. Hassabis seems like the only one that is not actually Evil.

Is there any evidence that "a majority of society wants AI to fail"

Or is it just vibes?

Care to elaborate on this?

Fully agree with this and they were leading robotic learning as well even back to 2019.

IsaacSim was (and might still be) the best robotic learning sim and I ran MLAgents.

Nemotron is vastly different from standard open-weight models. Its entire training pipeline is open-sourced, while other vendors typically only release the model weights.

I live in the USA and I use a European LLM as a daily driver: Proton’s lumo+ that does a good job packaging a Mistral model for general chat, with good searchable chat history — all with adequate privacy guarantees. Well worth the money.

I purchase open model tokens for agent programming assistance, and I like lumo+ for everything else.

Another option is DuckDuckGo’s Duck.ai subscription, but I slightly prefer ProtonMail’s lumo+ packaging as a product.

The law varies from country to country, but at least I vote for the legislators creating the laws governing my local sovereign AI.

Putting aside reliable rule of law, as others have pointed out, it seems unwise to keep your data in a country that has repeated threatened to annex or invade yours.

The rule of law exists in other countries in a way it does not in the US right now.

Iceland and Switzerland are probably the best places to keep your data safe. I'd put Norway, Sweden, Germany, and the Netherlands after that, though I don't have much specifics on how good they are at privacy these days.

I think US is the only country that's asked to limit their frontier model access based on the Citizenship of the user.

Let's say Gemini gets to AGI by tomorrow, will my Google account access, or Gemini apps access and data be blocked if I'm not a US citizen? (Anthropic did it with a 5% better model).

If US is classifying the model access based on citizenship, that's similar to treating it as a Defense capability.

Most people have had to reluctantly accept their own totalitarian state will control them. They do not want another state to have the same or even more power over them.

No country is safe. You need to host your own end to end on your own infrastructure if you want to be free.

Stallman was correct in the 80s and is correct now about libre software

From a legal perspective the US may be safer than other places if the US is the one seeking your data. The US doesn't need legal process to authorize digging into your foreign server.

From a practical perspective, I'm not sure any servers are safe anywhere...depending on who may want your data.

Actually, it isn't all that different. There are only two words separating "how to say X in language Y" from "say X in language Y". And this "vulgar" metric is actually quite relevant for an LLM, which answers based on conversational context.

Is a recipe useful if no one likes it?

There are equally open, much more useful models out there: https://artificialanalysis.ai/?models=nvidia-nemotron-3-ultr...

You don't need a license to scrape the public web and analyze it, turn it into tokens and other transformations. Let's not expand copyright beyond the horrible monster it already is.

Legal consulting.

> A better strategy is to play an assymetrical game IMO. Don't let your would-be master write the rules by which you play.

What do you mean by this? Do you have an example in the given context?

Anyone with an M-series Apple computer can run something very competently. Mac Pro users can run 30B class models which is good enough for the vast majority of practical everyday purposes, far better than the original ChatGPT was. Anyone with a gaming computer is in a similar situation. The rest of us can still run stuff, just not as big or as fast.

They have it, we just haven’t enabled them. The smart model with a chat box is the wrong abstraction for local. Ideally we would have it built into applications as a clear and easy to use opt-in feature. Like allowing a user to index a folder on their hard drive and then search it semantically via embeddings. You could do that on fairly low end hardware these days. Like 2GB of RAM with any processor made within the last 10 years.

They may not right now, but the whole point of Microsoft's Copilot+ PC standard (even though it's somewhat anemic) is to run models locally. Apple Silicon with enough unified memory is capable. Not to mention modern iPhones and Pixels have fairly capable NPUs and routinely run local models. So, we may not be to the point where most normal people have the hardware to run local models, but it is rapidly approaching.

As time goes on, they’re almost certainly will be very capable local models in the long run we (general computer users) aren’t going back to the era of mainframe computing no matter how much OpenAI, Meta or Google would like us to.

Gamers can run Qwen 3.6 quantised models now.

You would also be shocked what's possible on a 64GB Mac Studio, which isn't that unattainable.

Because the local LLMs available today are already fantastic, and the difference between no LLM and an open weights LLM is much smaller than the gap between an open LLM and a so-called "frontier" model.

It's important that people get used to the idea that your interactions with a language model are a highly personal thing. LLMs can perceive and categorize us in ways we can't even imagine, far more violently than the simple algorithmic feeds which have already corroded public discourse so much. LLMs can control us. LLMs warp the information landscape more radically than even the internet did. Even now you are likely underestimating their role in future society.

The principles of software freedom are becoming existentially important.

It does not, but it might encourage more people to care. Worrying about training is a luxury when you are starting from a baseline of "OpenAI spies upon me and controls my access". Let's focus on getting every Tom, Dick and Harry 1) on board with LLMs, because they're happening, 2) habitually using local software.

The same used to be true of being able to program computers and compile software.

Of course the frontier will always be unattainable, but that's like pointing out that I couldn't buy my own Cray supercomputer.

Some hyperbole is useful. The problem is real and serious, though short of the specific verbiage.

Link? You have to tell us if you want to break through the noise!

For coding, Qwen3.6-27B with MTP should fit in 32GB with almost full context length for Unsloth's 5-bit quantization. That's my preferred choice for a local coding agent on similar hardware: the quality delta compared to a MoE model is IMO worth the extra wait. (And I haven't found a model with 70B-120B parameters that works better for coding.) For general chat, maybe gpt-oss-120b? It should have more general knowledge than a 30B-class model; I've used it to suggest itineraries for trips and to review the completeness of small requests for proposals.

I don't have recommendations for images because I haven't played with those.

these days, even completely mainstream distros (Fedora here) include ollama, which leverages a wide range of hardware and range of models. (it's generally useful to install a more recent ollama, though.) there are free coding harnesses too.

True. What France (as an EU member) and Switzerland (not as an EU member) share is a desire for sovereign AI. I am interested how their efforts compare, and how their LLMs thus far compare.

residents of the universe who recognize the US as a supply-chain risk.

no, actually, from the docs it sounds mainly motivated by the country's unique linguistic requirements.

You can run it, but you can't train it. While this type of toy model could actually be trained in Swiss equipment, a state-of-the-art LLM probably could not.

My charitable reading of GP's point is that the bottleneck for true compute sovereignty is the chips, not the models.

It's one of those lies people tell themselves to make themselves feel better. "Oh, they're just copying my stuff."

Chinese labs are basically just telling everyone, out in the open, what they're doing and how to do it, and the answer from American frontier labs is "Well, they couldn't possibly be getting the results they're getting without just distilling our models," and the American labs aren't even trying to do some of the stuff like DS's aggressive caching to get costs down.

I recently watched a video for one of these “Chinese Models” it kept insisting it was Claude when the user asked. Sorry, there’s no “slur” here but legit suspicion.

But have they? I understand that the Chinese side is illuminated and the American side is dark. I disagree that the Chinese labs have created anything that isn't in an American research lab or production dc. Sure the Chinese have published their findings and not for nothing. But are they novel? Unlikely imo

SOTA LLMs is less important than cheap token and Chinese AI labs is releasing model that is only about 6-8 months behind American AI labs.

Chinese's model like GLM is getting better for coding task and its cheaper. Microsoft Github copilot have to switch billing to token based. the cost of AI have increased since agent come into play. whoever can offer cheaper token to do task will win.

even Microsoft is looking into Deepseek for cheap token.

https://www.axios.com/2026/06/16/microsoft-copilot-cowork-to...

Sorry but I think you’re requirement that something only be “the art” if any arbitrary person can critique it is off. The frontier labs are working on the state of the art but it’s just art that you aren’t allowed to see. Unfortunately.