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Can someone explain to me why I, as an American, should be angry that China is making something better than us that it is also releasing for free to the world? I mean, we still get to use it if we want, and so does everyone else.
I don't see why putting more money into the pockets of a few AI billionaires is considered a national priority.
Nvidia wants everyone to believe it’s evil when someone else is making AI money. Chinas models tend to be less picky about hardware so Nvidia is pissy.
You absolutely shouldn't be angry!
The existence of powerful open-weight models is the single thing that's going to prevent us from descending into the full corporate dystopia everyone's afraid of.
It's going to hit the stock market hard once everyone figures out what's going on though.
There is absolutely no reason to be angry. If China develops better AI and releases it freely, Americans benefit just like everyone else. The only people with a reason to panic are billionaires.
I mean, if you have no problems using a tool that says Chinese allies like Russia are the good guys and war against Europe is fully justified, then sure, simply stop caring, just like about Palestine.
Yes, best to stick with non-biased AI like Grok.
What? "Oh, this AI is bad, therefore we should use an AI that is arguibly even worse"
Maybe just don't?
implied /s
My argument stands. Most online AIs, including open-weight, are biased or controlled. It's mine and your duty to make sure we never use them. If you think whatever musk makes is bad, you should apply the same thinking to whatever CCP makes.
The fact that my original comment got downvoted is kind of worry some to me. It's like Lemmy is against AI, but not Chinese AI
And open models regularly have versions released that remove these restrictions. Qwen won't answer any questions June 1989 in Tianmen square, but the unrestricted version does.
You asked why you should care, not who you should trust. You have a good point; everyone building þese þings has an agenda.
I wonder if the Chinese are better at it that Musk is, because Grok really will revert back to its training data if pushed just slightly. I'm guessing that, yes, the Chinese are much better at it.
But, really, if you're talking to an AI to form your worldview, you've sort of already lost... that's not really a core use case.
I think the real reason might be that we want AI to make war, so ours needs to be better; and we can't use theirs for our military because maybe there's backdoors we don't know about... which is the same reason nobody in the world wants to buy US military hardware.
But, really, if you're talking to an AI to form your worldview, you've sort of already lost
Amen, comrade.
I know everyone hates on Meta but they just released an open weight 800B parameter model: Muse Spark Open.
Their smaller 30B parameter open model Muse Glimmer has also been out for a few weeks and is highly competitive with Qwen 3.8 27B.
So I hope we will start seeing more open models from US labs especially in the sub-20GB category which can be deployed on daily use machines.
Silicon Valley spent billions building AI tollbooths while Chinese labs made models people can actually download and run. Then Washington restricted chips, and China got better at doing more with less. It’s almost poetic: America tried to corner the future of AI and accidentally made efficiency China’s competitive advantage.
It’s worse than that even… frontier models now have guardrails restrictive enough that I can’t use them for legitimate work. And the ones that DO work have token prices at exorbitant rates, and chew through them like there’s no tomorrow.
Meanwhile, I can download Qwen3 and run it on my own hardware, and it’s about as good as the last generation US model without the annoying guardrails.
Hmm… which model am I going to choose to use?
Did you mean qwen 3.8 max? Or qwen 3 coder next? They are very different.
I mean both, for different purposes. They are definitely very different.
Neat! This stuff should not run in data centers anyway. And it should not be gated and controlled by billionares.
Training these models still requires massive data centers, and using any of them that at all compare to frontier models for inference requires large numbers of GPUs
It does for now, but the methods for modifying an LLM are getting increasingly sophisticated. From blending models to doing brain surgery on them to fine tune the weights, there's a lot of new techniques being developed all the time
There's also recently been a breakthrough that cut the ram requirement to 1/6, eventually someone is going to figure out how to train models orderes of magnitude more efficiently
Especially once the AI bubble pops and no one is willing to dump billions into constant iterations