Destroying the growth story of overvalued stocks is an interesting investment strategy. It's not even new. Shortsellers understandably get terrible rep from execs, but their actions are more often in the public interest than you'd think. Normally it's exposing fraud, but here we get the really fortunate side benefit of what could eventually amount to the most significant contribution to the general software community since Linux.

Even if they're ahead they don't have enough GPUs to scale. Open sourcing is hence a good strategy to at least get market share (even if not $).

US labs in Google, Meta and SpaceX are not leading, none of them managed to build something on par with GLM 5.2.

Care to explain to me why they still don't collaborate and still choose to do it in private?

I say this because we see the same thing used as an argument against China. "If they overtake us, they'll do imperialism (like us)." Again, it says more about us than them.

A better reading (IMHO) Of the situation is that China believes that AI shouldn't be used simply to mint a few more trillionaires but the benefits should be shared with society. Why do I say this? Because we now have 70+ years of China doing exactly that. The transformation in China all the way from rural villages to Tier 1 cities has been utterly astounding. China has lifted ~800M people out of extreme poverty.

In some ways we're at a similar point to the late 1990s and 2000s when Microsoft execs complained that Linux, being free, destroyed intellectual property value. Linux should be a perfect example of how people can and do act altruistically, or at least not in a way to bait-and-switch to enrich themselves.

[1]: https://www.reddit.com/r/AskHistory/comments/1d26grm/in_the_...

1) The CEO himself 2) Tencent 3) CALT (the battery company) 4) NetEase (internet/media company) 5) JD.com (ecommerce) 6) Chinese investment firms

What are they expecting in return? I'd say the same thing that all those investors in OpenAI and Anthropic are expecting - profit.

[0] https://finance.sina.com.cn/stock/vcpe/2026-06-11/doc-iniazi...

Which will likely help them bolster the sales of the MANY new AI chips in development/use in China to international markets. Dislodging Nvidia.

Kinda the opposite of what Jensen Huang (Nvidia) thinks US is doing: https://www.youtube.com/shorts/u3SY8nvjhQA

Edit: I'm a fan of deepseek and believe it's good to make the technology open/available. And do think that also help business - which I support as well.

Edit 2: No idea why I'm getting downvoted. That's also their official stance https://english.www.gov.cn/news/202601/08/content_WS695f1b55...

???

Profit!

Not suggesting this is it, but you know, one possible angle.

So, despite hiring the cream of the crop of math graduates, who could read the papers of free academia, but whose own result the free world could not access - they fell behind.

I have a theory explaining why. I think it's because science is an interactive process. NSA cryptographers could read papers, but they couldn't talk openly with the authors of those papers, because of secrecy demands - even asking question might indicate what they were working on. You can easily imagine them spending months on something they could have avoided by going to the original authors and getting told "Oh, we tried that for a long time, it doesn't work".

Whether that theory is right or not, cryptography is a concrete example of a domain where public research with fewer resources beat private research with a lot more resources.

The American companies, from my impression don’t involve themselves with such lowly “hacks” because they have so much money to just push forward with doing everything on big heavy models that run on the most cutting edge nvidia chips that they can, the moment, kinda sorta get on demand (I say that in some degree of jest).

MTP is from Meta

Another DeepSeek advance that the west are copying is DeepSeek Sparse Attention (DSA)

More likely is that an AI generated codename is impossible to fix by humans, and SOTA was not able to figure it out until now.

There is a meteor headed towards all this AI investment that I don't think has been properly accounted for and that is, what happens to all the existing hardware investments when NVidia's next architecture comes out. Blackwell (H100/H200) is the current generation. Rubin (R100, presumably R200) is the next and arrives soon. Now a lot of the investment hasn't been spent yet so will likely be spent on Rubin but at that point, what happens when the next iteration comes out and does 3-4x the compute for the same electricity input and same hardware cost?

Also, what happens when people can run way bigger models on consumer hardware in 5 years? The effective limit for useful local LLMs is currently ~31B parameter models because the RTX 5090 has 32GB of VRAM and Apple's shared memory architecture, which can keep bigger models in memory, just doesn't have the raw processing power.

Anyway, why I argue Anthropic is in a better position (than OpenAI) is that they seem to have captured a market that may well be profitable for them as a company, specifically Claude for coding. So they just haven't burnt quite as much cash as OpenAI so aren't in as deep of a hole.

While I think local models are going to improve maassively over the next few years, running them in a data center at scale is always going to be cheaper for a company. Why? Because they can amortize their costs by running 24/7 and powering them and cooling them is simply cheaper at scale when you're talking about 1000+ engineers who otherwise might only be using their hardware ~40 hours a week.

IMHO Google is in the best position here of all the US companies, even though their models aren't the best, because their data centers are ruthlessly efficient, their homegrown TPUs will eventually catch up (and thus avoid the NVidia tax) and they simply haven't bet the farm on winning AI.

Well I can't think of even one at the moment, to be honest might be biased but all Chinese research labs are largely oss except Alibaba now.

I am certain there are lots of American labs that claim to do it, but either they are marketting in hype since they aren't even close to the frontier or contrarily just don't make anything of significant value public/oss.