Post by @yogthos@lemmy.ml

2026-10-16 02:30 UTC

The reason Chinese companies are making open models is very simple actually, and has fuck all to do with charity. LLMs are a form of a general commodity, and it’s not a viable business model to monetize them directly. Trying to compete on model quality is a race to the bottom. Anything one lab can do, others can figure out a few months later. So, you have to keep investing more and more money just to keep ahead. Chinese companies realized this early, and that’s why they release the model in the open, aiming for the high end of the value chain building customized services and integrations tha capture the market. My expectation is that LLMs will become like Linux where nobody really makes any money off the tech directly. But you’ll see platforms like AWS built on top of it. Meanwhile, you absolutely can inspect the weights and there are now plenty of tools for doing just that. It’s an active area of research, but these things aren’t black boxes people make them out to be. Finally, there are completely open models as well with training data, and source released in the open. None of them are frontier quality, but they are certainly a starting point. There also projects like petals for doing distributed training. There’s absolutely no reason why you can’t have something like SETI@home for training models on a network. This is what people should be putting their energy into instead of whinging endlessly as if OpenAI or Anthropic give a flying fuck that some brave lib made yet another ‘AI slop’ comment on a niche social media platform.

Replies (2)

@usernamesAreTricky@lemmy.ml 2026-10-16 02:41

and has fuck all to do with charity That’s what I said? you absolutely can inspect the weights Current techniques cannot give you anything close to the level of inspection you can with software. Worse still, techniques of frontier AI labs are moving in the opposite direction with it getting harder to understand over time and less going into things like chain of thought There also projects like petals for doing distributed training You always be at a massive disadvantage because of the severally more limited compute available. Additionally, distributed computing not inside the same data center adds massively increased latency Training a model also does nothing for the environmental side of things and just makes things worse instead of whinging endlessly as if OpenAI or Anthropic give a flying fuck that some brave lib made yet another ‘AI slop’ comment on a niche social media platform. That’s 100% missing the point. The point is to not encourage more people to use the tool that gives control to Anthropic, OpenAI, etc. Social stigma and pushback is the point. People use things less when it’s seen as uncool. Normalizing AI use just means it’s going to be used more against your interests

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@oxomoxo@lemmy.world 2026-10-17 01:45

I have given up trying to have this conversation, especially on Lemmy, but even in general. There is a mass hysteria surrounding anything even tangentiality related to AI. I think there must be something innately human that makes people ‘throw the baby out with the bathwater’ when it comes to change and the fear that comes with it. What I find more productive is to just leave the naysayers and doomers to there own devices. Most people just don’t get it, and that’s okay.

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