yep. the word they use is probably 克制 or self-restraint. no need to raise so much cash if you can't use it.

in his article he talks about the negative aspects of getting everything you want. (all the money, brightest minds, biggest share in AI) etc. he says that these are the things that will cause a company to fail.

Yeah, wouldn't it makes sense to increase fundraising, so as to acquire more compute to close the gap?

Perhaps it's akin to a mineshaft gap?

> if the title is conflating

The title is certainly a great conflation. Any seeker of capital would want to regroup after an unfiltered leak of this magnitude, if for no other reason than to secure the forum from future leaks. The comments about the unlikelihood of enormous future profits were at least as consequential with regard to capital investment as anything else that was said.

Because money isn’t free and if you know there is a chokehold in supply, why raise money ar current valuation when things are getting better by the day?

Maybe because if you need more money to catch up with your competitors than anticipated then your ROIC is lower and your valuation changes?

Those could be subsequent developments, but that's not what the linked transcript was about. The transcript was a discussion of the DeepSeek founder (Liang Wenfeng) with investors, and he does not mention any leaks, or any frustration. He simply says that he is constrained by the supply of cards, and he has no problem of getting funding, but has no reason to raise further funding because he can't transform the cash into cards.

  > There is certainly no shortage of funds or resources --- in fact, all these are readily available [...]

  > Within our financial capacity, it's undoubtedly true that the more cards are always better. Our current strategy is to purchase as many cards as possible at a reasonable price --- exactly how many we can afford after using this funding round. The spending pace isn't predetermined; we'll buy whatever is available as long as prices remain competitive. In fact, I'd consider that a positive outcome if we spend the entire amount within six months. [...]

  > In reality, spending such a large sum is no easy task: you can't obtain enough cards, they're hard to come by [...]

  > Therefore, our only concern is whether we can obtain enough cards. If converting all funds into cards were feasible, we would undoubtedly do so without hesitation and are even willing to pay a premium for this benefit --- it's simply to cost effective. Even after paying the premium, however, achieving this goal remains challenging.

Most of that is paywalled, but this one paragraph in the Bloomberg article suggests it might be more to do with investors leaking information:

"The suspension stemmed in part from Liang’s frustration over online reports about his comments to investors during his first financing deal"

The part of the transcript I'd seen floating around online was this part from around 1 hour 26 min:

"With the largest models available today, we simply cannot afford to train them. Even if we spent all five hundred billion yuan, we still wouldn't be able to do so. Even if we could accumulate the resources, we wouldn't have the means to utilize them. The current largest model requires approximately 800 billion activations; domestically, we are still at a scale of several dozen billion activations, and even the largest domestic model may only require several dozen billion activations—a difference of an order of magnitude. To train a model of the same size as an AI system, we would need around 50,000 GB300 GPUs or Huawei 950 GPUs, totaling two hundred thousand cards. This is merely training; research has not yet been considered. Therefore, the biggest gap between us and the United States lies in resources."

I was gonna say, this just puts more pressure to deliver ground breaking research with limited resources. And if history teaches us anything it’s that scarcity produces ingenuity.

> "There's a delusion that what America's AI companies are doing is "best""

Not sure if the word "delusion" is the correct word here? It has not been proven in either direction. We can all see lots of possible issues with it, but it is also possible that it could be what is needed to unlock key capabilities.

We can see that the Chinese models have been getting better, but OpenAI is out there supporting 10 million active users with their frontier models, and now we know that Deepseek can't even get what they need to properly train models.

They'd have to use the gap though to actually kneecap them in that time, or else it is just shoveling money into the fire.

The missile gap for example after all was settled and done, didn't matter at all because not a single missile was ever fired off. All that money, resources, talent, secrecy, lives lost maintaining that secrecy, lives dedicated to furthering that technology and secrecy, it just has not paid off at all for anything at all when you think about it. Maybe you can argue side efforts like nuclear reactor were great or space cargo deployment, but you know you could have just dug into that stuff directly without having to collect it from the drippings of the wmd effort.

I feel like if you showed current frontier models to someone 10 years ago, they'd probably call it AGI. Does AGI have a clear definition or is it just a pair of goalposts on wheels?

All the AGI (which is a misnomer, ASI is preferred) talk is about the moment of singularity, which is where the growth at the third derivative is increasing, so the gap (in the absolute) between first place and others, even if it's one month, will be ever increasing as time progresses. I also have a hard time believing this narrative because limiting factors prevail such as compute and energy. These constraints will take many many years to overcome.

> Jensen Huang disagrees and has said AI is a marathon.

Of course he'd say that; he wants to keep his shovels flying off the shelves.

Reaching AGI would come with so many ethical issues, it feels so absurd that actual adults seem to actually believe it’s something that must be chased as fast as possible

I don't forsee politicians in either country handing over their power to AIs, ever. Unless nukes are dropped, "the other side" will catch up.

> Jensen Huang disagrees and has said AI is a marathon.

We have a saying for that in Italy: "Oste, com'e' il vino?", "Innkeeper, how's the wine?", meaning you should take with a grain of salt assertions that clearly benefit whoever's making them.

It’s kind of true but also kind of silly.

True in that frontier models do have the capability to outperform all other models, but silly because AGI self improvement is itself an iterative process that takes a lot of compute.

So you can imagine a world where all the frontier labs achieve AGI but in order to keep their AGI ahead of other AGIs they have to use more and more compute until all the compute is going to self improvement and there is nothing left for other tasks.

That is just a silly scenario so I think when AGI is around we will still have bottlenecks that force it to grow at a moderate rate instead of asymptomatically.

AGI first mover advantage implies that there is no such bottlenecks.

> U.S. policymakers believe that even if the gap is small—like six months to a year—whoever reaches AGI first [...]

As far as I can tell, the Trump admin has never acknowledged AGI being a goal of theirs. In fact, the admin's "AI advisor" Sriram Krishnan has specifically pushed back on AGI when he called it "a distraction, harmful and now effectively proven wrong."

The ai.gov website says this:

> The United States is in a race to achieve global dominance in artificial intelligence. Whoever has the largest AI ecosystem will set the global standards and reap broad economic and security benefits. Under President Trump, our Nation will win, ushering in a new Golden Age of innovation, human flourishing, and technological achievement for the American people. America’s AI Action Plan has three policy pillars – Accelerating Innovation, Building AI Infrastructure, and Leading International Diplomacy and Security.

Are you sure you're not confusing US policymakers with Silicon Valley CEOs? I'm sure Amodei and Altman wish they could have Claude draft up new policy and EO it into existence, but we're not quite there yet.

> U.S. policymakers believe that even if the gap is small—like six months to a year—whoever reaches AGI first...

From past experience, AGI was never seriously discussed in these kinds of conversations beyond thought experiments, and was basically humoring SBF, Daniela Amodei, and the other EA types (some deep believers, but some who I felt were cynically using it as a way to preempt competition back when OpenAI and Google were the behemoths).

The big worry is applications of AI in C4ISR, OffSec, loitering munitions, Disinfo/social media botting (notice the recent shift towards identification on social media ;)), and other sorts of DefenseTech adjacent usecases.

The second worry is that an AI race turns into an infra buildout race, and HPC is extremely dual use, especially in the simulations space because of the NPT, the CTBT, and the PTBT.

The AGI-pilled people aren't the ones to worry about - it's the people who understand the limits of models and how to integrate with cyberphysical applications.

One word: Focus.

Is there really a valid basis for claims like "state backed enterprises"? My understanding is that's no different than claiming that datacentres in America are "state backed" since they get things like big breaks on property taxes.

All that and so what? Fact is the Chinese have several near peer models, they've released the weights and they are widely available.

You want to sue them or something?

I doubt this is the case. It should be common knowledge at least among the people building these things that a true AGI isn’t possible with LLMs.

Unless I’ve missed some advancement?

It's odd to me to watch so many very rich humans speedrun the destruction of humanity. Like, is there a world where we hit AGI and it actually works out for us?

But this will not be a singular event. And like humans it does not mean that the smartest makes the best decisions.

Who actually believes this nonsense?

Why? If you can reach ASI without ASI, then why can’t multiple companies reach ASI on parallel tracks?

I think that statement is vacuous true for all magical thinking.

Why?

If that is the case, it means one thing only - US labs don't have moat whatsoever and their expectation to have trillion dollar valuation is just laughable.

You think OAI are doing all that out of the goodness of their hearts?

OAI was a market leader until anthropic decided to start placing all their bets on coding agents, they became the leader and now OAI is scrambling and doing everything they can to de-throne. Don't forget that it was OAI that started this whole RAM shortage, instead of being sustainable about it, they just up and decided to buy 40% of all memory production. They are all bad mate, all fighting for this virtual crown that no one cares except for them.

In the end, what matters is pricing, whoever offers sonnet 4.6 quality at the cheapest monthly pricing will win.

I don't know that it's clear that the motivation is that it's "helping" their competitors directly. Maybe the motivation is "if we rely on these, then the next time a US president arbitrarily decides to block us from buying them, we won't have the infrastructure already in place to be able to work around it". It seems more betting on a shorter-term cost with less uncertainty in the long term rather than a shorter-term win with a lot harder to quantify risks in the long term.

They've achieved self-sufficiency in >14nm chips in remarkable timing. Unfortunately for DeepSeek, it's the <14nm chips that are needed for massive training tasks. I wouldn't be surprised if China backs down and lets them purchase the chips given that they are still years away from being able to make them themselves. Either that or the gov't steps in and forces them to share resources

And even if Huawei's Ascend 910C can compete with NVIDIA's H200, CUDA is still a large moat

I think the point is more than by banning the NVIDIA hardware they are forcing local development of potentially competitive hardware, basically giving Huawei a subsidy or leg-up.

Can't they use GlobalFoundries, Intel or TSMC in addition to their own fabs?

They can already make chips economically. Yields are worse than TSCM but good enough since they no longer need to pay the "Qualcomm tax". Huawei's phones are profitable. The issue is rather that Chinese capacity comes from a low quantity, and scaling capacity while simultaneously indigineousizing parts takes time — years. Foreign capacity was too good and too cheap so they never succeeded in scaling capacity, because the demand for Chinese fabs wasn't there. Now the demand for domestic capacity is there and they're scaling like crazy, like 100-200% growth per year. But demand still far outpaces capacity. Fabs are hard to build. You need many more years of 200% growth to even approach the demand.

And yes, I made use of emdash. It's a legit grammar tool. Sue me.

They talk about developing and using TileLang which they ported to Huawei's 950 GPUs.

And it makes sense, as these LLMs become more capable in coding abilities - people will use them to develop their own abstractions to work on different HW. You cannot have it otherwise. If SaaS companies get threatened that their SW doesn't have a moat why do you expect Nividia's SW to have moat ? The computing algorithms are not even proprietary. It is only a matter of whether someones cares about it and is committed. This should be encouraging for new AI chip development companies.

The very progress that Nividia enables also has a negative feedback that threatens it.

And it’s not even reading between the lines and being a conspiracy theorist. The current U.S. regime has made it abundantly clear that they will gladly operate in bad faith.

Being rational and predictable is likely a more important quality than ideology now that the Americans are threatening everyone and forcing us all to pick sides.

Yes the Trump administration acts a lot like the CCP and it is despicable.

This seems like when Indians were super excited about China having castes too. Then, it turned out that they were egregiously incomparable.

US incumbent party criticism is nothing like CCP criticism.

That's not true. First there is still a licensing and quota scheme on the US side for the H200s. Secondly China blocked them for use in inferencing. Thirdly Chinese companies don't want them for training because newer chips are more cost effective.