Comment by andy99
3 hours ago
What’s the point of having “sovereign” weights that are worse than publicly available ones? Wouldn’t Europe be better off just keeping up-to-date on the Chinese releases? In the event of some schism requiring sovereign capability, or even if the Chinese pulled ahead and stopped releasing the weights, why would Europe be better off because of Mistral? (Or any country’s inferior sovereign effort make them better off?)
I think I understand the incentives that cause this to exist (it would be politically worse to say we’re just going to use Chinese models) but they are misguided. If sovereigns want to have valuable models, they should insist on world class, relevant ones like the Chinese have. Instead they embrace mediocrity in the name of sovereignty.
> In the event of some schism …
In the views of most Europeans, that schism already happened.
Europe was perfectly happy to rely on US software and services for decades. None of the large US tech companies would be nearly as profitable if they hadn’t had a whole continent of wealthy customers, and no competition.
I don’t think Americans are realizing yet how much has changed for us the past two years.
That's your fantasy. Reality is https://news.ycombinator.com/item?id=49607443
Early this year I was thinking "will I still have access to this service if they invade Greenland?"
Never had to do it before. That's how much it has changed.
2 things here, one is related to benchmaxxing, another to being good enough
1. Mistral isn't benchmaxxing. That doesn't mean they're better, but it does mean the benchmark gap not a good reflection of the actual gap
2. I think the "world class or nothing" framing mixes general capability with system capability. Most deployments don't need AGI In RL you need a model that's reliably good at one or two things, thats it. Example: Case of a hospital flooded in emails. You make a system that decides which patient emails needs a human and drafts replies for the rest. If a sovereign model is good enough at that, and you can run it on a hospital's own servers under EU jurisdiction, the frontier gap part has zero importance
Who cares about "beats DeepSeek / GPT11 / Claude Fairytale 8.9"
Agree benchmarks don’t tell the whole story. A better and easier evaluation of capability is whether anyone is using it for anything.
Does Mistral have material market share for any application, including anything that would fall under item 2 above?
Not sure if you are European, but in EU it's a bit taboo to even talk about this in this manner. We like to spend a lot of money to make sure we finish last.
The training data and knowledge is the edge, you need to build that up and maintain it. And of course mine everything you can from the American and Chinese models, like they mined everything from the internet / films / music / games etc.
China's model for decades has been to do it cheaper and then do it better for cheaper. Just accepting this makes you an economic vassal state. We've seen this play out over decades now with other industries. I'm not blaming China for this approach, but if you want to stay relevant, then you need to compete.
You don't need to view China as some scary boogeyman who's going to use AI to attack you or w/e the current conspiracy is. They just need to continue peacefully outperforming while everyone else gets fat and lazy.
We know it's possible to put backdoors into LLMs, we don't have reliable ways to detect them without direct support from whoever inserted it.
Europe is less-worse-off with open weights than with… I guess it's weights-as-a-service? WaaS? The thing Anthropic and OpenAI do.
But that's not enough. As recently demonstrated, being just a few months behind with the power differential between defending with an open weight model while being attacked by a leading model, means losing absolutely.
I do not know if this holds going forward or not. It's not inconceivable that we're just about to get models that make unhackable code, using all the things software developers keep saying you need to do if you really care about security.
But anyone concerned about sovereignty can't bet the farm on this possibility. For the moment, it looks like it's a national security matter to ensure at least core state functionality (including core private sector logistics) gets the absolute best attention money can buy, and that the absolute best money can buy ("can buy" does a lot of heavy lifting here) is currently LLMs, and it's important those LLMs aren't going to get cut off by arbitrary whim like Mythos was, and it's important that those LLMs don't have backdoors like we can't rule out anyone else's from having.
This is true even if Europe was only defending from Russian cyberwarfare and didn't need to plan for the president of the country in which Mythos was developed, attempting to annex two NATO states.
Any model, even an open weight one, is fundamentally an encoding of a way of viewing the world.
What kind of "alignment" are AI labs optimizing for? Ideological alignment is the full term, self-censored into something more technological-sounding.
Every model has people behind it rating what it should and shouldn't say. Every time you ask a model and trust its answer, you become ever-so-slightly ideologically indoctrinated.
I don't want my model to reflect the views of American oligarchs or Chinese cadres. I want European values of enlightenment and humanitarianism to be the default and that's why the sovereign part is important.
Is there a specific concern you have, and what kind of performance penalty is it worth to you on say coding tasks?
Conceptually, sure I understand, but in practice it currently seems like it amounts to just using a worse model without getting anything in return. And if some hypothetical alignment to European values is important, it seems like putting the necessary effort into building a model that’s actually competitive but has this alignment is the solution, rather than accepting an inferior one.
I think for coding tasks, it probably doesn't matter as much. I'm more worried about stuff like chatbots subtly pushing or normalizing a certain world view.
I think I'm not the only one that's had this revelation, recall the Llama4 announcement. [0]
> It’s well-known that all leading LLMs have had issues with bias—specifically, they historically have leaned left when it comes to debated political and social topics. This is due to the types of training data available on the internet.
> Our goal is to remove bias from our AI models
This goal of course is self-defeatingly impossible to achieve. There is no unbiased, there's always only an unbiased relative to the bias of the observer.
Phrased differently, models weren't right leaning enough for the American oligarchy class and they publicly shared their desire to change the ideology they perpetuate.
I think an important perspective to keep in mind here is Zizek, the philosopher who's dedicated his life's work to the functioning of ideology.
> I already am eating from the trashcan all the time. The name of this trashcan is ideology. The material force of ideology - makes me not see what I'm effectively eating. It's not only our reality which enslaves us. The tragedy of our predicament - when we are within ideology, is that - when we think that we escape it into our dreams - at that point we are within ideology.
-- Slavoj Zizek
My concern is that both the Americans and the Chinese will be aligning their models more and more ideologically and that they will function as the perfect propaganda machine - surface-level objective and unthreatening, but answering every question asked from a world view decided elsewhere.
For some tasks (like aforementioned coding), that won't matter and there we can use whatever model is most capable. But as we outsource more and more of our thinking to AI and use it more and more to educate impressionable young people, not having our own models will mean not getting a say in how societies views are shaped and perpetuated.
Imagine for example, the question: "What caused the French revolution?" There's many answers that might be technically correct. Which ones get emphasized is where ideology lives and gets perpetuated.
Since there is no unideological, the best we can do is a pluralism of ideologies building LLMs. To not build one representing your views is for your views to not be represented.
[0] https://ai.meta.com/blog/llama-4-multimodal-intelligence/