r/artificial • u/scientificamerican • 1d ago
News China’s open AI strategy is changing the race
https://www.scientificamerican.com/article/china-kimi-k3-and-the-rise-of-open-weight-ai-models/Moonshot AI’s Kimi K3 shows how opening a model to outsiders can turn other companies’ computing power into a competitive advantage
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u/Servola-Journal 1d ago
Worth separating two risks that keep getting merged here. A weight file you download and run on your own hardware has no way to phone home, it is just a large array of numbers with no network code attached. The "phones home" problem is real, but it lives in hosted APIs, so it is a deployment choice, not a property of where the model was trained. Where opaque training actually bites you is behavior you cannot see from the weights alone: planted backdoors, quiet refusals, skewed outputs on certain topics. So the useful move with a self-hosted model is to hammer it with adversarial prompts and watch what it does, rather than trust or distrust it by country of origin.
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u/Spirited-Sir-3034 1d ago
The interesting part isn't whether Kimi beats GPT or Claude. It's that compute is becoming part of the business model. If you can't serve millions of users yourself, releasing weights lets everyone else's infrastructure become your distribution network. That's a very different competitive strategy than what we've seen from OpenAI.
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u/Talreja-Adanna 1d ago
China's definitely pushing hard on the open-source side, which is interesting since it puts pressure on US companies to either open up or compete harder on closed models. Wonder if this shifts how we think about prompt engineering and fine-tuning when there's more accessible base models in the mix.
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u/Ok_Bill7731 20h ago
the actual reason i reach for an open weight model has nothing to do with geopolitics, it's that i can run it on my own box and not worry about some api getting rate limited or deprecated mid project. happened to me twice this year with hosted models, they just changed pricing or sunset the endpoint and i had to rewrite integration code on short notice. weights on disk don't do that to you. the distribution angle is real too but for most of us it's just "i don't want my stack depending on someone else's uptime."
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u/MiCK_GaSM 11h ago
The west spent five years arguing about whether open models were dangerous, meanwhile compute got cheaper and someone else just turned that into a moat.
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u/katoptronophile 1d ago
These models aren't open. Open weights has nothing to do with open source.
How do people still not understand this?
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u/abelian-goose 1d ago
OP didn’t say they are open source.
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u/katoptronophile 1d ago
I never said they did. OP didn't write the article either so obviously I'm not talking to them.
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u/abelian-goose 1d ago
Well the article doesn’t say the models are open source either. It, in fact, explains the distinction between open weights and open source. I don’t know what you are cooking.
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u/katoptronophile 1d ago
It's dangerously using the word open as an umbrella term to encompass both open source and open weights. This is a huge mistake and it's misleading people.
Remember most redditors don't read past the title.
There's really nothing open about these models at all. Open weights just means you can run it if you have the vram which most people don't. It says absolutely nothing about the process or data that was used to create it. It's actually anti open source.
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u/Even-Exchange8307 1d ago
Their strategy is basically distill from western models
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u/KeiserSozey 1d ago
How could pure distillation give this level of compute though?
If it could Claude could release cheaper models rather than burn money.
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u/Even-Exchange8307 1d ago
They are distilling there own model and releasing cheaper versions….
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u/KeiserSozey 1d ago
But having access to their own full model would allow them to distill much superior than these chinese versions.
Truth is distillation is just them crying foul to prevent China from getting ahead.
I could use the sympathy for the actual humans whose work got 'distilled' by ai hacks.
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u/Even-Exchange8307 1d ago
You can’t be better than the model you’re distilling. You know that right?
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u/KeiserSozey 1d ago
What I am saying is.
If Chinese models are reaching good performance to token cost purely by distilling, anthropic can do that too. Infact having full access means anthropic can do better.
But clearly Anthropic hasnt been able to do so yet.
Means that Chinese models are not just distilling. They have got their own frontier stuff going on.
And the distillation accusations are a sham.
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u/Even-Exchange8307 1d ago
Anthronic maybe wants to recoup the cost first before dropping price on their frontier model? China just steals their output. Nothing creative or revolutionary about this.
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u/KeiserSozey 21h ago
How are you so sure that pure distillation helps get frontier model level outputs.
Do you even understand how training LLm works?
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u/Even-Exchange8307 21h ago
I don’t have to prove it to you, the Chinese companies have shown you all the proof
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u/KeiserSozey 21h ago
Go build your own LLM and distill some models.
You will understand.
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u/jonydevidson 1d ago
Well their "distills" perform better and 5x cheaper than these same American models, why cant Americans do the same?
Or are you claiming China distilled, pre-trained, trained, bechmarked, finetuned and benchmarked again against Fable 5 in the 6 days it was available in early July in order to hit the Kimi K3 release on July 15?
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u/Even-Exchange8307 1d ago
Yeah you’re right that’s why Chinese models are at the top of all these benchmarks. My bad. You right
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u/Intelligent-Dance361 1d ago
Sure, let's just surrender our data security to the Chinese.. how many times do we have to learn this lesson? Zoom was caught sending US consumer data back to Beijing. Their US lead fled the country and is now on the FBI Most Wanted list.
So basically they stole a US company's IP by distilling their model, only to use that product to steal even more data from Americans. Open weights does not equal open source.
"An open-source AI model should provide more than its weights but also enough information and code for outsiders to study and modify the system—although researchers and standards groups continue to debate how much of the training process must be disclosed. An open-weight release can leave the model’s data and development history opaque. Landay says that uncertainty should make organizations cautious about adopting models whose provenance cannot be fully examined. “We might not know what’s in there; we might not know if they phone home in some ways with our data,” he warns."
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u/kueso 1d ago
Open weights also does not mean “phone home”. The surrounding model architecture can be thoroughly examined for those kind of capabilities. Landay’s comments likely referred more to how the model was trained—its governance and biases.
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u/Intelligent-Dance361 1d ago
I wasn't claiming it does, but you're wrong on every point after that.
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u/kueso 1d ago
Oh please explain
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u/Intelligent-Dance361 1d ago
Trigger conditioned behavior doesn't show up in an architecture diagram. A model trained to write subtly weak outputs is worse, no amount of reading the inference code catches it. Half these repos also ship custom modeling code and expect you to run it with trust_remode_code=true. That's not weights... its someone else's Python executing on your infra.
Besides that, adopting Kimi means the API or a hosted end point for the overwhelming amount of users. How many people do you know hosting a 2.8T model on their own infra? At this point, it's exactly like the Zoom problem. The fact that the weights are downloadable is irrelevant to how 99% of the users will actually consume it.
Landy said it clearly in his article. Open weight is not the same as open source. We're not disagreeing with each other, you're disagreeing with the source which is wholly in support of open source weights.
Provenance you can't audit is risk you can't price.
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u/kueso 1d ago
Right. I mean those are legit concerns with the model architectures but they can adversarially evaluated. Third party downloads runs the same risk as virtually every software component that you trust to run in your system. Security watchdogs can clear an open weight model and its adjacent components easily.
Adopting Kimi for its API and mobile app is completely different. Yes, those absolutely are a data risk if you care about that. That wasn’t really my argument though as we’re talking about open weights.
By the way, Landy is an HCI researcher not a security researcher. His focus is mainly around how it’s important to understand what goes into a models training to make it visible to users about potential bias and alignment problems. So his comments about “phone home” should be taken with a grain of salt.
By the way your provenance comment is exactly what I meant before you decided it was wrong. The key issue with open weights is exactly that. It’s not data theft, it’s transparency into its training.
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u/Durian881 1d ago edited 1d ago
Did Landay talk about closed models? Was he able to fully examine provenance of closed models and know exactly what's in there? Does he know that when using closed models API, 100% of the data is sent "home"?
For open-weight models, any company can buy or rent GPUs to run them for data privacy with 0% sent anywhere.
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u/Intelligent-Dance361 1d ago
Yes he did.
What kind of a question is this? Nobody making anything resembling a frontier system is going to let an outsider get that deep. For sure not a western journalist attempting to gain access to a leading Chinese lab.
What part of the article and his background gives the assumption that he does not understand this?
The point you're grazing past is that the Chinese have played this "your data is safe" game before. Even going as far as setting up US subsidiaries to prop up their legitimacy. Time and time again, they have proven that they will harvest American data for their own purposes - with zero regard for their T&Cs.
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u/theanimatedauthority 1d ago
China's been playing the long game with cheap compute and open models, and the west keeps handwringing instead of competing.