Earlier quoted context omitted.
I don’t think that’s true. The US is China’s most valuable trade partner.
edit: misread parent
The comment you replied to is talking about China's trading partners, not the US's trading partners.
China’s open-weights AI strategy is winning
331–340 of 978 posts
Re: China’s open-weights AI strategy is winning
#332Earlier quoted context omitted.
China wants the US economy to flounder. Building our entire growth model on software that can be copied and taken by a small group of people will have no possible consequences.
> China wants the US economy to flounder. Why would they possibly want their largest customer to flounder?
I think lot of Americans overestimate how much China needs them. (Understandable, I suppose, since the UK made a similar mistake vis-a-vis the EU about 10 years back.)
From a Chinese perspective I expect China’s largest customer is China. These days it’s actually kind of wild how many Chinese consumer products aren’t (and won’t be) available at US retailers. And a lot of them are quite good.
For a while now China’s wanted to reduce its dependence on the US for a variety of reasons. And undermining the US tech industry, whose products the US government likes to use as a cudgel, may serve that goal quite nicely.
Re: China’s open-weights AI strategy is winning
#333Re: China’s open-weights AI strategy is winning
#334So, I've been working on infinite context models (think fixed size state with a few tricks) and I think this will eventually lead to a kind of lock-in by vendor. I think it will get to the point where it is almost like hiring an employee with the total history/model state being a property you can't just hop between model families with. Clearly open weights still allow you to do this if you have access to that state b…
How are you storing the data that it can't be exported? Or that I can't use an interface or proxy that logs all my conversations locally for import?
Re: China’s open-weights AI strategy is winning
#335I do think open-weights models are going to "win" in the sense that they're probably going to be dominant when the hardware to run them becomes affordable. (which might be a while). Although I guess you could probably rent the GPU's yourself to hypothetically save on costs. (I'm a little skeptical -- I've heard of companies doing this and the inference bills are surprisingly high -- assuming the sources are correct.…
If you're NVIDIA then open-weight models are a classic example of commoditizing your complements; cheaper models mean more people buying GPU's to run them. [1] Your guess is as good as mine for China though. [1] https://www.joelonsoftware.com/2002/06/12/strategy-letter-v/
There’s export controls on nvidia. According to Jensen, they expect that Chinese models will start being optimized for Huawei
Re: China’s open-weights AI strategy is winning
#336This is a very strange article considering that Llama, the mother of all open-weight models, has led to anything but success for Meta. Also, enterprises don't give a rip if models are open. They care about zero data retention (and sticking with whatever vendor they're already using). This blog post is suspiciously close to being a restatement of what Alex Karp recently said on CNBC[0]. It's important to remember he's…
Isn’t it basically impossible to run the newer high quality Chinese models locally, even for a corporation? The better they get, the more they need a data center. So, the ‘better’ Chinese AI gets , the more it will just be a service run on Chinese hardware competing with ‘our’ lower latency AIs . The open source character of the models is irrelevant if you need a nuclear powered data center for inference. In the end…
The cost of inference is not insurmoutable for many corporations who may run a small datacenter out of their headquaters or branch offices.
Larger models absolutely have a higher barrier of entry, but its a cost under a few hundred thousand as opposed to the millions necessary for a datacenter built as core revenue generating infrastructure.
Cost of inference is small when compared to the cost of training new models. Which is the real advantage these Chinese models have. Someone else has already spent the capital needed to create the model.
With a reasonable upfront investment and a few trained staff, its very possible to run these larger Chinese models in a well managed fashion. The real calculus is if this up-front investment and associated lifecycle costs are over or under the costs a corporation may simply wish to dump into a cloud managed service like OpenAI.
Re: China’s open-weights AI strategy is winning
#337Earlier quoted context omitted.
If you're NVIDIA then open-weight models are a classic example of commoditizing your complements; cheaper models mean more people buying GPU's to run them. [1] Your guess is as good as mine for China though. [1] https://www.joelonsoftware.com/2002/06/12/strategy-letter-v/
Nvidia selling more GPU's at the cost of it's datacenter business is pretty close to Kodak selling digital cameras at the cost of film. The data center side is so bloated anything that eats into it is a huge negative. Their data center business brings in 20x the gpu market. Local open weight models will be what pops the bubble and China will do anything in it's power to enable that pop.
> Nvidia selling more GPU's at the cost of it's datacenter business is pretty close to Kodak selling digital cameras at the cost of film.
This assumes a) AI is a zero-sum game, and b) we're actually talking about on-prem AI will replace cloud-based AI. I think neither statements are true.
AI is like compute: we'll need all sorts of it, in various sizes, everywhere. I'm sure Nvidia whats to own all the workloads.
On the other hand, I do think open weight, like open source, will win in general.
Re: China’s open-weights AI strategy is winning
#338I do think open-weights models are going to "win" in the sense that they're probably going to be dominant when the hardware to run them becomes affordable. (which might be a while). Although I guess you could probably rent the GPU's yourself to hypothetically save on costs. (I'm a little skeptical -- I've heard of companies doing this and the inference bills are surprisingly high -- assuming the sources are correct.…
'Libre Office' did not 'win'.
People are happy to pay $50/year per seat to have the extra features and to not have to deal with stuff.
There's an issue at the margins here:
$1000/employee is a massive cost - it has to be deeply justified. $50/employee is like ... $2 out of your pocket. It's an incremental cost. The CFO is happy to pay it if there is a lot of value.
A lot of software is in that later category.
Imagine if gasoline was 1 cent per litre - and there was 'free gas' but it was a pain to use, and you had to check a bunch of things. You may just pay the 1 cent.
AI is not quite that yet, but these dynamics will play out eventually, for a lot of things.
Re: China’s open-weights AI strategy is winning
#339Earlier quoted context omitted.
There very little reason to use OpenRouter to access closed models, instead of just using the provider directly.
One big reason I can think of is to avoid vendor lock-in. This is why most enterprises use a multi-cloud setup, despite the increased complexity.
>This is why most enterprises use a multi-cloud setup
Going to have to say citation needed on this, if you're suggesting most enterprises have infra-as-code that would allow them to switch their entire infra between vendors within a month.
Re: China’s open-weights AI strategy is winning
#340Earlier quoted context omitted.
I think part of it is definitely to weaken US providers and the US economy as a whole. China has a completely different domestic economic structure and motivations from western cultures... it's probably closest to a fascist economy mixed with a Maoist cultural ideology behind it. There's definitely winners and losers and the state tends to have tight controls over everything though. I also think the restrictions on O…
Does it weaken the US though? It weakens the big providers but most of the economy is in companies buying and this helps them save money.
GDP growth in the United States is in AI and healthcare.
AI capital expenditure is around 5% of total US GDP.
Housing right before the 2009 market collapse was around 6.7%.
Biggest issue I see is housing has more real value than AI expenditure. Demand is real and isn't based purely on a few companies valuation or marketing spin. Nearly 2 decades later we still haven't caught up to construction rates before the 2008 collapse. When the bubble pops it's going to really suck.