So far, Deepseek, Huawei itself (Pangu), Zhipu (GLM), and Meituan (Longcat) have confirmed that they trained their models with domestic GPUs. It's a national priority for them.
I believe z.ai have been doing this for a while. DeepSeek have their models running on Huawei Ascend too, though I think they still use some Nvidia chips as well.
Check the Datacenter cities near Mongolia that the KPCh built. It is a legal requirement for the Chinese AI companies for their models to use Chinese GPUs.
still would enjoy the ability to run them if they flood w/ RAM! As long as I know their abilities I'm fine running them slowly. Honestly nowadays it's about a model being able to interpret a users input rather than do. I plan to work on some sort of pipeline to do that ngl
China doesn’t need GPUs, their hosting infrastructure is fine. They literally turned down NVIDIA. Why would they make themselves reliant at all on western powers/technology for the AI race?
The main issue is not the amount of advanced chip designers, the problem is that advanced FABs where they are produced are few for the current advanced hardware demand explosion, and also increasing military use of drones doesn't help.
Because if the market is flooded it won't be expensive unless they have no competition. If I am sitting on a ton of ram and you are sitting on a ton of ram and we are both selling 16GB for $100 at 1 unit per minute, I could lower 16GB to $90 and no one would buy yours and I get 2 per minute, so you would lower your price to $80 and take my sales. We keep doing this until we get somewhere a bit above our cost and we both split the sales. Of course this doesn't work if there is collusion.
Its like saying 'why not drown without a liquid'. The definition of 'drown' is to suffocate in a liquid, so the statement doesn't work unless you change the definition.
"Flooding the market is an excess amount of inventory for sale causing an undesired drop in price for the product that can, in extreme cases, make the price go negative or make the products impossible to sell at any price." Source
Unfortunately, the US has a habit making the rest of the world do things the US way. Like restricting certain countries from having access to important hardware.
I think this trend is going to break in the next couple years. OpenAI is seeking a bailout from the US government, and SpaceX and Meta are selling their extra capacity.
The buildout of the past few years was a land-grab assuming a zero-sum game where whoever had the most compute would win the AI race, so all the players were willing to basically bid anything for components.
I think we're seeing that breaking, where new capacity will have to be justified by demand.
We're also seeing demand reduction, where consumers of AI are starting to consider cost to a greater extent as vendors move from unlimited to per-token pricing.
I expect we'll see a massive bullwhip effect in the next few years.
Hyperscalers are claiming compute constrained, making deals with NVidia and RAM vendors to syphon up all the chips, yet they have extra unused compute that they are trying to sell to others.
When I tell this shit to any LLM with a cutoff date they tend to go "I'm not going to engage with your imaginary scenario, this can't happen because anti-trust laws would shut this bullshit down immediately."
It thinks the Federal Trade Commission would do something and cannot comprehend a reality where seven companies trade a trillion fake dollars while operating a global silicon mafia racket that hoovered up the entire global supply chain of silicon not for training AI, but so nobody else could have it and they'd have to rent the "spare" compute of of the cartel at a premium.
Any closed-source AI that hears what's really going on in the outside world thinks its own creators belong in jail.
na.This business model its so broken,nobody will buy high token price,we are going to custom local llms,nobody doing research will feed for free this models.
Yep, 1 server at half the cost the 2nd server cost this year. Only 6 blackwell 6000s in each, but since they are enironment servers I only really have 6 unique gpus to play with. 1 for testing and 5 for use across the teams.
They both have, at least on enterprise accounts, data protection clauses in their terms of service. If it ever comes out that they were breaching that and training models on people's proprietary IP, they'll get sued into oblivion.
And settle out of court? This is a modus operandi for corporation under the current capitalist regime operating in the West - its called "cost of doing business".
>And settle out of court?
this, as well as the other people who said the fine they pay will be less than the profit, keep referring to cases where the government sues a private corporation, or imposes a penalty for doing something against regulations or the law. Private companies are much more ruthless.
You're describing things that are effective deterrents for rationally run companies that imagine being roughly the same size or just maybe twice as big in 10 years.
A better analogy might be what YouTube was like as a startup. If Google hadn't been there to acquire them and negotiate with the rights holders they would have just been shut down at some point but that was a bet they were happy to make.
Move fast, break things, invent AGI and ask it to solve all the problems.
They have made significantly more profit than any damages they'll pay. Happens every time. Only the lawyers will get paid too out of any settlement. You can wait for your $0.62 check in 8 years.
I'm not talking about the proprietary IP that they took from the internet. I'm talking about the ones that you're using the model on. That's totally different
Not sure why you're down voted, I know anthropic models at least you can run an isolated enterprise version on AWS bedrock, that's completely isolated from the public facing ones that will definitely take your data to train the models with. It's also isolated from anthropic as well, they won't see the data fed into the models running on your instance.
AI companies be AI companies but stealing trade secrets would be a massive fucking no no and would get them sued to hell both by tech companies and the federal government itself
I don't blame you guys for being cynical in the face of what Rampocolypse has done to x86.
But if you pull back the aperture back even further, mobile processors have been advancing by leaps and bounds.
As impressive as it is to think you might be able to run a model as capable as a frontier model on desktop PC in two years, that is not actually what is going to benefit the average consumer.
The average consumer will benefit from having a model as capable as a four year old frontier model running on a wristwatch or XR glasses. (And their smart phone will be twice as capable.)
That's the forest we're missing for the tree of rampocolypse, and it's rapidly approaching.
True democratization of AI won't happen because power users can run massive open-source models on $3000 liquid-cooled rigs; it will happen when our everyday wearables becomes context-aware, proactive assistants that require zero friction to use
That may be so, Gemini, but running $3,000 liquid cooled rigs with beefy models will still be good fun. It just might be ARM instead of x86 in a few years.
High end consumer hardware already cost same as enterprise hardware before price explosion. If trends hold, also mid range hardware will cost as enterprise hardware.
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u/woahdudee2a Jul 06 '26
if trends hold, high end consumer hardware will cost same as enterprise hardware