You might want to learn what words like reactionary actually mean before using them. We are discussing an open source tool, which by its nature lacks the built-in constraints you are describing. Your argument is a piece of sophistry designed to create the illusion of expertise on a subject you clearly do not understand. You are not engaging with the reality of the technology, but with a simplified caricature of it.

Technology such as LLMs is just automation and that’s what the base is, how it is applied within a society is what’s dictated by the uperstructure. Open source LLMs such as DeepSeek are a productive force, and a rare instance where a advanced means of production is directly accessible for proletarian appropriation. It’s a classic base level conflict over the relations of production.

Nah, I don’t think I’m going to take as gospel what a CIA asset say.

Instead, go read Marx to understand the relationship between the technology and the social relations that dictate its use within a society.

Elections are just the surface of the problem. The real issue is who owns the factories and funds the research. In the West that’s largely done by private capital, putting it entirely outside the sphere of public debate. Even universities are heavily reliant on funding from companies now, which obviously influences what their programs focus on.

or maybe it’s the capitalist relations and not the technology that’s the actual problem here

Right, I think the key difference is that we have a feedback loop and we’re able to adjust our internal model dynamically based on it. I expect that embodiment and robotics will be the path towards general intelligence. Once you stick the model in a body and it has to deal with the environment, and learn through experience, then it will start creating a representation of the world based on that.

It seemed pretty clear to me. If you have any clue on the subject then you presumably know about the interconnect bottleneck in traditional large models. The data moving between layers often consumes more energy and time than the actual compute operations, and the surface area for data communication explodes as models grow to billions parameters. The mHC paper introduces a new way to link neural pathways by constraining hyper-connections to a low-dimensional manifold.

In a standard transformer architecture, every neuron in layer N potentially connects to every neuron in layer N+1. This is mathematically exhaustive making it computationally inefficient. Manifold constrained connections operate on the premise that most of this high-dimensional space is noise. DeepSeek basically found a way to significantly reduce networking bandwidth for a model by using manifolds to route communication.

Not really sure what you think the made up nonsense is. 🤷

I’m personally against copyrights as a concept and absolutely don’t care about this aspect, especially when it comes to open models. The way I look at is that the model is unlocking this content and making this knowledge available to humanity.

Ah yes, they must be stealing IP from the future when they publish novel papers on things nobody’s done before!

I do indeed hate living under capitalism

I’m actually building LoRAs for a project right now, and found that qwen3-8b-base is the most flexible model for that. The instruct is already biased for prompting and agreeing, but the base model is where it’s at.

Yup, and this is precisely why it was such a monumental mistake to move away from GPL style copyleft to permissive licenses. All that achieved was to allow corporations to freeload.

I very much agree there, but think of how much worse it would be if we were stuck dealing with proprietary corporate tech instead.

How is that wishful thinking? Open models are advancing just as fast as proprietary ones and they’re now getting much wider usage as well. There are also economic drivers that favor open models even within commercial enterprise. For example, here’s Airbnb CEO saying they prefer using Qwen to OpenAI because it’s more customizable and cheaper

“We’re relying a lot on Alibaba’s Qwen model. It’s very good. It’s also fast and cheap,” he said. “We use OpenAI’s latest models, but we typically don’t use them that much in production because there are faster and cheaper models.”

I expect that we’ll see exact same thing happening as we see with Linux based infrastructure muscling out proprietary stuff like Windows servers and Unix. Open models will become foundational building blocks that people build stuff on top of.

I mean you can believe whatever you like. I’m obviously not going to convince you of anything here. We’ll just have to wait and see who’s right.

Europe is pretty much entirely dependent on US platforms having failed to develop their own the way China and Russia did. There’s no European Yandex or Baidu equivalent, no European Alibaba, and so on.

A few more

• The US withdraws from NATO causing it to fall apart
• The US annexes Greenland
• The US invades Venezuela
• A country exits the EU
• A major financial crash in the west
• Israel and the US attack Iran
• Far right parties form governments in major European countries
• Organized resistance of the AFU collapses
• Ukraine goes bankrupt due to insufficient funding from the west
• There’s a major break up between the US and Europe

maybe it’s a vacuum lifter :)

Hopefully this stuff pans out. I’d love see it happen.

This is existing high performance hardware that you can buy. I’d love for there to be something equivalent built using RISCV, but there’s not.