It was also frustratingly predictable from the moment the US started trying to limit the sales of the chips. America has slowed the speed of Chinese AI development by a tiny number of years, if that, in return for losing total domination of the GPU market.
That’s not to say I’m brave enough to short NVDA.
At least for me, Google has some real cachet and deserves kudos for not losing money selling Gemini services, at least I think it is plausible that they are already profitable, or soon will be. In the US, I get the impression that everyone else is burning money to get market share, but if I am wrong I would enjoy seeing evidence to the contrary. I suspect that Microsoft might be doing OK because of selling access to their infrastructure (just like Google).
A major reason Deepseek was so successful margins wise was because the team heavily understood Nvidia, CUDA, and Linux internals.
If you have an understanding of the intricacies of your custom ASIC's architecture, it's easier for you to solve perf issues, parallelize, and debug problems.
And then you can make up the cost by selling inference as a service.
> Amazon and I think Microsoft are also working on their own NVIDIA replacement chips
Not just them. I know of at least 4-5 other similar initiatives (some public like OpenAI's, another which is being contracted by a large nation, and a couple others which haven't been announced yet so I can't divulge).
Contract ASIC and GPU design is booming, and Broadcom, Marvell, HPE, Nvidia, and others are cashing in on it.
A long time ago I worked as a contractor at Google, and that experience taught me that they don’t like things that don’t scale or are inefficient.
My opinion, the problems for NVIDIA will start when China ramp up internal chip manufacturing performance enough to be in same order of magnitude as TMSC.
Wont it be enough to just solder on a large amount of high bandwidth memory and produce these cards relatively cheaply?
Perf is important, but ime American MLEs are less likely to investigate GPU and OS internals to get maximum perf, and just throw money at the problem.
> solder on a large amount of high bandwidth memory and produce these cards relatively cheaply
HBM is somewhat limited in China as well. CXMT is around 3-4 years behind other HBM vendors.
That said, you don't need the latest and most performant GPUs if you can tune older GPUs and parallelize training at a large scale.
-----------
IMO, Model training is an embarrassingly parallel problem, and a large enough cluster leveraging 1-2 generation older architectures that is heavily tuned should be able to provide similar performance to train models.
This is why I bemoan America's failures at OS internals and systems education. You have entire generations of "ML Engineers" and researchers in the US who don't know their way around CUDA or Infiniband optimization or the ins-and-outs of the Linux kernel.
They're just boffins who like math and using wrappers.
That said, I'd be cautious to trust a press release or secondhand report from CCTV, especially after the Kirin 9000 saga and SMIC.
But arguably, it doesn't matter - even if Alibaba's system isn't comparably performant to an H20, if it can be manufactured at scale without eating Nvidia's margins, it's good enough.
Cerebras get their chipped fabbed by them. I assume Eucyld will have their chips fabbed by them.
If there's orders, why would they prefer NVIDIA? Customer diversity is good, is it not?
Money talks. Apple asked for first dips a while earlier (exclusively).
AMD are, Cerebras are, I assume OpenChip's and Euclyd's machines will be.
Sure, but in my example Apple got access exclusively for a few months to a newer node, which would make a world of difference if you compete in the same space.
I am a long time fan of Dave Sacks and the All In podcast ‘besties’ but now that he is ‘AI czar’ for our government it is interesting what he does not talk about. For example on a recent podcast he was pumping up AI as a long term solution to US economic woes, but a week before that podcast, a well known study was released that showed that 95% of new LLM/AI corporate projects were fails. Another thing that he swept under the rug was the recent Stanford study that 80% of US startups are saving money using less expensive Chinese (and Mistral, and Google Gemma??) models. When the Stanford study was released, I watched All In material for a few weeks, expecting David Sack’s take on the study. Not a word from him.
Apologies for this off-topic rant but I am really concerned how my country is spending resources on AI infrastructure. I think this is a massive bubble, but I am not sure how catastrophic the bubble will be.
The US is burning good will at an alarming rate, how long will countries keep paying a premium to be spied on by the US instead of China?
This country used to have congressional hearings on all kinds of matters from baseball to the Mafia. Tech collusion and insider knowledge is not getting investigated. The All-in podcast requires serious investigation, with question #1 being “how the fuck did you guys manage to influence the White House?”.
Other notes:
- Many of them are technically illiterate
- They will speak in business talk , you won’t find a hint of intimate technical knowledge
- The more you watch it, the more you realize that money absolutely buys a seat at the table:
https://bloximages.chicago2.vip.townnews.com/goskagit.com/co...
(^ Saved myself another thousand words)
I mean. I think some of us knew this. There's a lot of issues with AI, some psychological, some are risk adverse individuals who would love to save hours, weeks, months, maybe years of time with AI, but if AI screws up, its bad, really bad, legal hell bad, unless you have a model with a 100% success rate for the task, it wont be used in certain fields.
I think in the more creative fields its very useful, since hallucinations are okay, its when you try to get realistic / look reasonably realistic (in the case of cartoons) that it gets iffy. Even so though, who wants to pay the true cost of AI? There's a big uphill cost involved.
It reminds me a lot of crypto mining, mostly because you need an insane amount to invest into before you become profitable.
Anyone who's listened to him (even those who align with him politically) for an extended period of time can't help but to notice so obviously so self interested to the point of total hypocrisy—the examples of which are too many to begin to even wanting to enumerate. Like—take the Trump/Epstein stuff, or the Elon/Trump fallout—topics he would absolutely lose his sh*t over if these were characters on the left. I find it hard to believe anyone actually ever took him seriously. Branding myself as a fan of his would just be a completely self-humiliating insult to my intelligence and my conscience IMO.
Their multiples don't seem sustainable so they are likely to fall at some point but when is tricky.
They've been trying really hard to pivot and find new growth areas. They've taken their "inflated" stock price as capital to invest in many other companies. If at least some of these bets pay off it's not so bad.
I'm open to considering the argument that banning exports of a thing creates a market incentive for the people impacted by the ban to build aa better and cheaper thing themselves, but I don't think it's as black and white as you say.
If the only ingredient needed to support massive innovation and cost cutting is banning exports, wouldn't we have tons of examples of that happening already - like in Russia or Korea or Cuba? Additionally, even if the sale of NVIDIA H100s weren't banned in China, doesn't China already have a massive incentive to throw resources behind creating competitive chips?
I actually don't really like export bans, generally, and certainly not long-term ones. But I think you (and many other people in the public) are overstating the direct connection between banning exports of a thing and the affected country generating a competing or better product quickly.
Apparently that was an issue for them when it came to hiring people to work at their US fabs as well.
That's just one of the ingredients that could help with chance of it happening, far from being "the only ingredient".
The other (imo even more crucial) ingredients are the actual engineering/research+economical+industrial production capabilities. And it just so happens that none of the countries you listed (Russia, DPRK, and Cuba) have that. That's not a dig at you, it is just really rare in general for a country to have all of those things available in place, and especially for an authoritarian country. Ironically, it feels like being an authoritarian country makes it more difficult to have all those pieces together, but if such a country already has those pieces, then being authoritarian imo only helps (as you can just employ the "shove it down everyone's throat until it reaches critical mass, improves, and succeeds" strategy).
However, it is important to remember that even with all those ingredients available on hand, all it means is that you have a non-zero chance at succeeding, not a guarantee of that happening.
South Korea might have the capability to play this game (North Korea certainly doesn't), but it hasn't really had the incentive to.
Which brings us to the real issue: an export ban on an important product creates an extremely strong incentive, that didn't exist before. Throwing significant national resources at a problem to speculatively improve a country's competitiveness is a very different calculation than doing so when there's very little alternative.
Lost months are lost exponentially and it becomes impossible to catch up. If this policy worked at all, let alone if it worked as you describe, this was a masterstroke of foreign policy.
This isn't merely my opinion, experts in this field feel superintelligence is at least possible, if not plausible. This is a massively successful policy is true, and, if it's not, little is lost. You've made a very strong case for it.
doing a lot of heavy lifting in your conjecture
I don't see myself there, but, given that even the faint possibility of superintelligence would be an instant national security priority #1, grinding China into the dust on that permanently seems like a high reward, low risk endeavor. I'm not recruitable via any levers myself into a competitive ethnostate so I'm an American and believe in American primacy.
2. CUDA has been a huge moat, but the incentives are incredibly strong for everybody except Nvidia to change that. The fact that it was an insurmountable moat five years ago in a $5B market does not mean it’s equally powerful in a $300B market.
3. AMD’s culture and core competencies are really not aligned to playing disruptor here. Nvidia is generally more agile and more experimental. It would have taken a serious pivot years ago for AMD to be the right company to compete.
It's the CUDA software ecosystem they have not been able to overcome. AMD has had multiple ecosystem stalls but it does appear that ROCm is finally taking off which is open source and multi-vendor.
AMD is unifying their GPU architectures (like nVidia) for the next gen to be able to subsidize development by gaming, etc., card sales (like nVidia).
Does Nvidia have patents on CUDA? They're probably invalid in China which explains why China can do this and AMD can't.
https://rocm.docs.amd.com/projects/HIPIFY/en/latest/index.ht...
The CUDA moat is extremely exaggerated for deep learning, especially for inference. It’s simply not hard to do matrix multiplication and a few activation functions here and there.
What is this racialized nonsense, have you seen Jensen Huang speak Mandarin? His mandarin is actually awful for someone who left Taiwan at 8.
So for data centers, training is just as important as inference.
Sure, and I’m not saying buying Nvidia is a bad bet. It’s the most flexible and mature hardware out there, and the huge installed base also means you know future innovations will align with this hardware. But it’s not primarily a CUDA thing or even a software thing. The Nvidia moat is much broader than just CUDA.
See, Mojo, a new language to compile to other chips. https://www.modular.com/mojo
Sure, you can keep buying nvidia, but that wasn't what was discussed.
Lol this is how I know no one that pushes mojo on hn has actually ever used mojo.
You're completely wrong here. That's the "what's wrong with it".
To say Mojo doesn't use Python, when clearly that is a huge aim of the project, makes me think you are splitting hairs somewhere on some specific subject that is not clear by your one liners.
Key aspects of Mojo in relation to Python:
• Pythonic Syntax and Ecosystem Integration: Mojo adopts Python's syntax, making it familiar to Python developers. It also fully integrates with the existing Python ecosystem, allowing access to popular AI and machine learning libraries.
• Performance Focus: Unlike interpreted Python, Mojo is a compiled language designed for high-performance execution on various hardware, including CPUs, GPUs, and other AI ASICs. It leverages MLIR (Multi-Level Intermediate Representation) for this purpose.
• Systems Programming Features: Mojo adds features common in systems languages, such as static typing, advanced memory safety (including a Rust-style ownership model), and the ability to write low-level code for hardware.
• Compatibility and Interoperability: While Mojo aims for high performance, it maintains compatibility with Python. You can call Python functions from Mojo code, although it requires a specific mechanism (e.g., within try-except blocks) due to differences in compilation and execution.
• Development Status: Mojo is a relatively new language and is still under active development. While it offers powerful features, it is not yet considered production-ready for all use cases and is continually evolving.
What if I told you I used to work at modular? What would you say then to this accusation that I'm "missing the nuance"?
The rest of this is AI crap.
Do you really think Mojo is not based on Python? Or they are not trying to bypass Cuda? what is the problem?
The rest might be marketing slop. But I'm not catching what your objection is.
what do you mean "do you really". it's not. full stop. what part of this don't you understand?
The marketing and web site materials clearly show how they are using the Python interpreter and extending Python. They promote the use of Python everywhere. Like it is one of the most hyped points.
I think you are trying to quibble with, does the new functions get compiled differently than the rest of Python? So technically, when the Mojo functions are in use, that is not Python at that point?
Or maybe you are saying that they have extended Python so much you would like to not call it Python anymore?
Like IronPython, maybe since that gets compiled to .NET, you disagree with it being called Python?
Or maybe to use the IronPython example, if I'm calling a .NET function inside Python, you would like to make the fine distinction that that is NOT Python at that point? It should really be called .NET?
Here is link to docs. You worked there. So maybe there is some hair splitting here that is not clear.
https://docs.modular.com/mojo/manual/python/
Maybe it is just marketing hype that you disagree with.
But right on the main page it says "Mojo is Python++".
brother you have literally not a single clue what you're talking about. i invite you to go ask someone that currently works there about whether they're "using the Python interpreter and extending Python".
"This is 100% compatible because we use the CPython runtime without modification for full compatibility with existing Python libraries."
At this point you need to either explain your objection, or just admit you are a troll. You haven't actually at any point in this exchange offered any actual argument beyond 'duh, you're wrong'. I'd be ok if you actually pointed to something like 'well technically, the mojo parts are compiled differently', or something. You say you worked there, but you're not even looking at their website.
Creator Chris Lattner discussing why they used Python. https://www.youtube.com/watch?v=JRcXUuQYR90
Start at minute 12. "Mojo is a very extended version of Python".
> using the CPython interpreter as a dynamic library (shown as libpython.dylib in figure 1).
They're embedding the python interpreter not extending it - just like everyone and their mother has been able to do for decades
https://docs.python.org/3/extending/embedding.html
I repeat: you have no idea what you're talking about so in reality you're the troll.
You're problem isn't with me, you are quibbling with there own marketing materials. Go complain to marketing if they are using the words that you disagree with. Everything I've posted is directly from Mojo's website.
You: "Well, technically they are embedding the interpreter, so all the surrounding code that looks exactly like python, and we promote as being compatible with python, and promote as extending python. My good sir, it is not really python. That is just a misunderstanding with marketing. Please ignore everything we are clearly making out as an important feature, totally wrong".
They clearly promote that they are extending python. What is your problem with that? How is that wording causing you to seize up?
I'm aware of what is technically happening. Where did I ever say anything that was not directly from them? Do I really need to write a thesis to satisfy every ocd programmer that wants to argue every definition.
Were you let go because of an inability to think flexibly? Maybe too many arguments with co-workers over their word choice? Does you're brain tend to get single tracked on a subject, kind of blank out in a white flash when you disagree with someone?
Actually, I'm kind of convinced you're just arguing to argue. This isn't about anything.
bro are you really thick? there is zero mojo code that is runnable python; take a look at
https://github.com/modular/modular/tree/main/mojo/stdlib/std...
mojo has zero to do with python. zilch, zero, nada.
what they are doing is simply embedding the python interpreter and running existing python code. literally everyone already does that, ie there are a million different projects that do this same thing in order to be able to interoperate with python (did you notice the heading at the top of the page you linked is *Python interoperability* not *Python compatibility*).
> This isn't about anything.
it's about your complete and utter ignorance in the face of a literal first hand account (plus plenty of contrary evidence).
> Were you let go because of an inability to think flexibly?
let go lololol. bro if you only knew what their turnover was like you would give up this silly worship of the company.
You're bitter.
To be clear, I'm not a fan boy. I don't really know much about Mojo. I've watched some videos, checked out their website, thought it was interesting idea.
The parent post was about alternatives to CUDA.
I posted a 6 word sentence summarizing how Mojo is trying to bypass CUDA, and using Python. -> And you flipped out, that it isn't Python. Really?
I checked out your link, sure does look like Python. But that is the point, all of their promotional materials and every Chris Lattner video, all sales pitches, everywhere.
Everywhere, is Python, Python, Python. Clearly they want everyone one to know how closely tied they are to Python. It is a clear goal of theirs.
But. I see now the pedantic hair splitting. Mojo 'Looks Like Python', they use the same syntax. "Mojo aims to be a superset of Python, meaning it largely adopts Python's syntax while introducing new features".
But you say, they aren't modifying or extending CPython so this is all false, it is no longer technically Python at all.
And I guess I'm saying, Chill. They clearly are focused on Python all over the place, to say that it isn't, is really ludicrous. You're down a rabbit whole of debating what is a name, what is a language. When is Python not Python? How different does it have to be, to not be?
It's all about investment. If you are a random company you don't want to sink millions in figuring out how to use AMD so you apply the tried an true "no one gets fired for buying Nvidia".
If you are an authoritarian state with some level of control over domestic companies, that calculus does not exist. You can just ban Nvidia chips and force to learn how to use the new thing. By using the new thing an ecosystem gets built around it.
It's the beauty of centralized controlled in the face of free markets and I don't doubt that it will pay-off for them.
Also AMD really didn't invest enough in making their software experience as nice as NVIDIA.
Or would china be different because it's a mix of market and centralized rule?
They have never had a focus on top notch software development.
Until 2022 or so AMD was not really investing into their software stack. Once they did, they caught up with Nvidia.
If AMD really wanted to play in the same league as NVidia, they should have built their own cloud service and offered a full stack experience akin to Google with their TPUs, then they would be justified in ignoring the consumer market, but alas, most people run their software on their local hardware first.
HN has a blindspot where AMDs absence in the prosumer/SME space is interpreted as failing horribly. Yet AMDs instinct cards are selling very well at the top end of the market.
If you were trying to disrupt a dominant player, would you try selling a million gadgets to a million people, or a million gadgets to 3-10 large organizations?
A reimplantation would run into copyright issues.
No such problem in China.
And NVIDIA will lose its dominance for the simple reason that the Chinese companies can serve the growing number of countries under US sanctions. I even suspect it won't be long before the US will try to sanction any allies that buy Chinese AI chips!
They are vendor locking industries, i don't think they'll loose their dominance, however, vendor locked companies will loose their competitiveness
Simple example being TikTok.
Its just a matter of time really.
Yet, we see Ford as extremely innovative and revolutionary. I think we can draw lots of parallels between a 19th and early 20th century industrializing US and current China.
Most of Meta's engagement comes from video content. Continuous engagement is how it is able to generate its revenue.
Thats all I need to say!
Russia has none of that at the scale needed.
I believe about 1000 S&P points down - to just above the trade war lows from April.
China shouldn't be buying H20s. Those are gimped 3 year old GPUs. If Nvidia is allowed to sell the latest and greatest in China, I think their revenue would jump massively.
China, admittedly full of smart and hard working people, then just wakes up one day an in a few years covers the entire gap, to within some small error?
How is this consistent? Either:
- The Chinese GPUs are not that good after all
- Nvidia doesn't have any magical secret sauce, and China could easily catch up
- Nvidia IP is real but Chinese people are so smart they can overcome decades of R&D advantage in just s few years
- It's all stolen IP
To be clear, my default guess isn't that it is stolen IP, rather I can't make sense of it. NVDA is valued near infinity, then China just turns around and produces their flagship product without too much sweat..?
No, that's not really why. It is because nobody else has their _ecosystem_; they have a lot of soft lock-in.
This isn’t just an nvidia thing. Why was Intel so dominant for decades? Largely not due to secret magic technology, but due to _ecosystem_. A PPC601 was substantially faster than a pentium, but of little use to you if your whole ecosystem was x86, say. Now nvidia’s ecosystem advantage isn’t as strong as Intel’s was, but it’s not nothing, either.
(Eventually, even Intel itself was unable to deal with this; Itanium failed miserably, largely due not to external competition but due to competition with the x86, though it did have other issues.)
It’s also notable that nvidia’s adventures in markets where someone _else_ has the ecosystem advantage have been less successful. In particular, see their attempts to break into mobile chip land; realistically, it was easier for most OEMs just to use Qualcomm.
I wouldn't exactly say it was a failure, all those chips ended up being used in the Nintendo Switch
There are almost 5 billion smartphone users; sales of 300 million a year would imply that those are only replaced every 16 years, which is obviously absurd.
On a separate note, speaking of the average lifespan of a phone, I'm fairly sure that with how expensive they're becoming, smartphone lifespans are increasing. Especially with:
* hardware performance largely plateauing (not in the absolute sense, that of "this phone can do most of what I need")
* the EU pushing for easy battery and screen replacement and also for 7 years of OS updates
* the vast majority of phones having cases to protect against physical damage
I'm always a little surprised that Nvidia is _so_ highly valued, because it seems inevitable to me that there is a tipping point where big companies will either make their own chips (see Google) or take the hit and build their own giant clusters of AMD or Huawei or whoever chips, and that knowledge will leak out, and ultimately there will be alternatives.
Nvidia to me feels a bit like dot-com era Sun. For a while, if you wanted to do internet stuff, you pretty much _had_ to buy Sun servers; the whole ecosystem was kinda built around Sun. Sun's hardware was expensive, but you could just order a bunch of it, shove it in racks, and it worked and came with good tooling. Admins knew how to run large installations of Sun machines. You could in theory use cheaper x86 machines running Linux or BSD, but no-one really knew how to do that at scale. And then, as the internet companies got big, they started doing their own thing (usually Linux-based), building up administration tooling and expertise, and by the early noughties Linux/Apache was the default and Sun was increasingly irrelevant.
The H200 is the next generation of the H100.
They also weren't starting from scratch, they already had a domestic semiconductor ecosystem, but it was fragmented and not motivated. The US sanctions united them and gave them motivation.
Also "good" is a matter of perspective. For logic and AI chips they are not Nvidia level, yet. But they've achieved far more than what western commentators gave them credit for 4-5 years ago. And they're just getting started. Even after 6 years, what you're seeing is just the initial results of all that investment. From their perspective, not having Nvidia chips and ASML equipment and TSMC manufacturing is still painful. They're just not paralyzed, and use all that pain to keep developing.
With power chips they're competitive, maybe even ahead. They're very strong at GaN chip design and manufacturing.
Western observers keep getting surprised by China's results because they buy into stereotypes and simple stories too much ("China can't innovate and can only steal", "authoritarianism kills innovation","China is collapsing anyway", "everything is fake, they rely on smuggled chips lol" are just few popular tropes) instead of watching what China is actually doing. Anybody even casually paying attention to news and rumors from China instead of self-congratulating western reports about China could have seen this day coming. This attitude and the phenomenon of keep getting surprised is not limited to semiconductors.
However they've also got a fair amount of generality, anything you might want to do that involves huge amounts of matmuls and vector maths you can probably map to a GPU and do a half decent job of it. This is good for things like model research and exploration of training methods.
Once this is all developed you can cherry pick a few specific things to be good at and build your own GPU concentrating on making those specific things work well (such as inference and training on Transformer architectures) and catch up to Nvidia on those aspects even if you cannot beat or match a GPU on every possible task, however you don't care as you only want to do some specific things well.
This is still hard and model architectures and training approaches are continuously evolving. Simplify things too much and target some ultra specific things and you end up with some pretty useless hardware that won't allow you to develop next year's models, nor run this year's particularly well. You can just develop and run last year's models. So you need to hit a sweet spot between enough flexibility to keep up with developments but don't add so much you have to totally replicate what Nvidia have done.
Ultimately the 'secret sauce' is just years of development producing a very capable architecture that offers huge flexibility across differing workloads. You can short-cut that development by reducing flexibility or not caring your architecture is rubbish at certain things (hence no magical secret sauce). This is still hard and your first gen could suck quite a lot (hence not that good after all) but when you've got a strong desire for an alternative hardware source you can probably put up with a lot of short-term pain for the long-term pay off.
Are they as good as Nvidia? No. News reporters have a tendency to hype things up beyond reality. No surprises there.
Are they useless garbage? No.
Can the quality issues be overcome with time and R&D? Yes.
Is being "worse" a necessary interim step to become "good"? Yes.
Are they motivated to become "good"? Yes.
Do they have a market that is willing to wait for them to become "good"? Also yes. It used to be no, but the US created this market for them.
Also, comparing Chinese AI chips to Nvidia is a bit like comparing AWS with Azure. Overcoming compatibility problems is not trivial, you can't just lift and shift your workload to another public cloud, you are best off redesigning your entire infra for the capabilities of the target cloud.
No, I just struggle to reconcile (but many answers here go some way to clarifying) Nvidia being the pinnacle of the R&D-driven tech industry - not according to me but to global investors - and China catching up seemingly easily.
Plus it may not be true, this new Alibaba chip could turn out to be brilliant.
https://www.theguardian.com/technology/2024/jan/02/asml-halt...
Also, they're working hard on replacing ASML DUV machines as well since the US is also sanctioning the higher end of DUV machines. Not to mention multiple parallel R&D tracks for EUV.
You also need to distinguish between design and manufacturing. A lot of Chinese chip news is about design. Lots of Chinese chip designers are not yet sanctioned, and fabricate through TSMC.
Chip design talent pool is important to have, although I find that news a bit boring. The real excitement comes from chip equipment manufacturers, and designers that have been banned from manufacturing with TSMC and need to collaborate with domestic manufacturers.
But that still seems like a huge step behind using EUV + advanced techniques.
Anyway, I'm curious to know how far that gets them in terms of #transistors per square mm.
Also, do we know there aren't secret contracts with TSMC?
It could also happen that all their DUV investment allows them to discover a valuable DUV-derived tech tree branch that the west hasn't discovered yet.
Results are at least good enough that Huawei can produce 7nm-5nm-ish phones and sell them at profit.
A teardown of the latest Huawei phone revealed that the chips produced more heat than TSMC equivalent. However, Huawei worked around that by investing massively into avdanced heat dissipation technology improvements, and battery capacity improvements. Success in semiconductor products is not achieved along only a single dimension, there are multiple ways to overcome limitations.
Another perspective is that, by domestically designing and producing chips, they no longer need to pay the generous margins for foreign IP (e.g., Qualcomm licensing fees), which is a huge cost saving and is beneficial for the economics of everything.
Yes but that doesn't answer the question of how they got so close to nvidia.
> It could also happen that all their DUV investment allows them to discover a valuable DUV-derived tech tree branch that the west hasn't discovered yet.
But why wouldn't the west discover that same branch but now for EUV?
> Results are at least good enough that Huawei can produce 7nm-5nm-ish phones and sell them at profit.
Sidenote, I'd love to see some photos and an analysis of the quality of their process.
Talent pool and market conditions. China was already cultivating a talent pool for decades, with limited success. But it had no market. Nobody, including Chinese, wanted to buy Chinese stuff. Without customers, they lacked practice to further develop their qualities. The sanctions gave them a captive market. That allowed them to get more practice to get better.
> But why wouldn't the west discover that same branch but now for EUV?
DUV and EUV are very different. They will have different branches. The point however is not whether the west can reach valuable branches or not. It's that western commentators have a tendency to paint Chinese efforts as futile, a dead end. For the Chinese, this is about survival. This is why western commentators keep being surprised by Chinese progress: they expected the Chinese to achieve nothing. From the Chinese perspective, any progress is better than none, but no progress is ever enough.
Also to a certain degree you can just throw loads of GPUs at the problem.
So instead of 100k GB200s, you have ~1m of these cards. One thing china _is_ good at is is mass manufacturing.
There's all sorts of caveats to that, but I really think people are overlooking this scenario. I strongly suspect that they could ramp output of (much?) weaker cards far quicker than TSMC can ramp EUV fabrication.
Plus China has vastly superior grid infrastructure. They have a massive oversupply of heavy industry, so even if they hit capacity issues with such gargantuan amounts of cards I can easily see aluminium plants and what not being totally mothballed and supply rerouted to nearby newly built data centres.
In other words, they are working on litography and nanometers, but they're not very worried about those areas because they don't really need them. HN is too myopic, focusing only on single-chip performance and logic chips.
China is known for their countless theft of Europe and especially American IP, selling it for a quarter of the price, and destroying the original company nearly overnight.
Its so bad even NASA has begun to restrict hiring Chinese nationals (which is more national defense, however illegally killing American companies can be seen as a national defense threat as well)
https://www.bbc.com/news/articles/c9wd5qpekkvo.amp
https://www.csis.org/analysis/how-chinese-communist-party-us...
This is the simple explanation. We'll also see European companies matching them in time, probably on inference first.
If China sees an existential risk to getting compute capacity, I can easily see an internal decree to make something happen. Even if it requires designing the hardware + their own CUDA-like stack.
1. An h20 is about 1.5 generations behind Blackwell. This chip looks closer to about 2 generations behind top end Blackwell chips. So ~5ish years behind is not as impressive especially since EUV is likely going to be a major obstacle to catching up which China has no capacity for
2. Nvidia continues to dominate on the software side. Amd chips have been competitive on paper for a while and have had limited uptake. Now Chinese government mandates could obviously correct this after substantial investment in the software stack — but this is probably several years behind.
3. China has poured trillions of dollars into its academic system and graduates more than 3x the number of electrical engineers the US does. The US immigration system has also been training Chinese students but having a much more limited work visa program has transferred a lot of knowledge back without even touching IP issues
4. Of course ip theft covers some of it
This metric is not as important as it seems when they have ~5x the population.
It's certainly non-linear.
Does 5x the number of math graduates increase the number of people with ability like Terrance Tao? Or even meaningfully increase the number of top tier mathematicians? It really doesn't. Same with any other science or art. There is a human factor involved.
Suppose there's more than one. Then sampling from 5x the number of people increases the average number of him that you get (by about 5x).
funny that you mention this because many top AI talent from big tech companies are from chinnese Ivy league graduate
US literally importing AI talent war as highest as ever and yet you still have doubt
You are trying too hard to be right meanwhile 40% top AI talent in big tech is chinnese
so higher number = more chance smart people is indeed true and your argument is just waste of time
AMD literally can't make enough chips to satisfy demand because nVidia buys up all the fab capacity at TSMC.
It's NVIDIA, not nVIDIA. I don't think AMD outperforms NVIDIA chips at price per watt. You need to defend this claim.
NIVIDIA is a very pricey date.
https://wccftech.com/mlperf-v5-1-ai-inference-benchmark-show...
https://semianalysis.com/2024/04/10/nvidia-blackwell-perf-tc...
https://semianalysis.com/2025/06/13/amd-advancing-ai-mi350x-...
There’s a reason no frontier lab using AMD models for training, because the raw benchmarks for performance for a single chip for a single operation type don’t translate to performance during an actual full training run.
Also, anyone doing very large models tend to prefer AMDs because they have 288GB per chip and outperform for very large models.
Outside of these use cases, it’s a toss up.
AMD is also much more aligned with the supercomputing (HPC) world were they are dominant (AMD cpus and GPUs power around 140 of the top 500 HPC systems and 8 of the top 10 most energy efficient)
Take a look at their logo. It starts with a lowercase n.
Virtually all products out of china still are.
If you want something manufacturered the best way is still to fake a successful crowd sourcing campaign.
You'll be able to buy whatever it is on AliExpress (minus any safety features) within 6 months.
If so, can you explain why Nvidia's market cap is much higher than TSMC's? (4.15 trillion versus 1.10 trillion)
- Chinese labs managed to "overcome decades of R&D" because they have been trying for many years now with unlimited resources, government support and total disrespect of IP laws
- Chinese chips may not be competitive at process power/W with Western but they have cheaper electricity and again unlimited loss capacity
- they will probably hit wall at the software/ecosystem level. CUDA ergonomy is something very difficult to replicate and, you know, developers love ease of use
This makes no sense. Market cap is share price times number of shares, there is no analog for a country. It’s also not comparable to the GDP of a country, since GDP is a measure of flow in a certain time period, whereas market cap is a point in time measurement of expected performance.
"According to investors, today's value of Nvidia's expected future profits over its lifetime equals the total monetary value of all final goods and services produced within a medium-sized country in a year."
Don't compare market cap with GDP, when you spell it out it's clear how nonsensical it is.
Nowadays, whenever some Chinese engineers dared to propose using some American parts, the challenges he/she had to face is always "who is going to be responsible if it is not reliable enough for its supply?"
If that happens, China in turn can export those Chips to countries that are in dire need of Chips, like Russia. They can export to Africa, South-America and the rest of Asia. Thus resulting in more competition for Nvidia. I see bright times ahead, where the USA no longer controls all of the worlds chip supply and OS systems.
I see this as an absolute win.
China has managed to monopolise the production (cheap prices) and advance the refinement process, so other domestic projects to extract rare earth minerals were not really profitable. To start it again would take some time.
But them, they do not think the same.
anyway.
VR200 supposedly has 20TB/s HBM, so I wish good luck to all these copy cats to catch up.
I thought that was just the marketing strategy execs employed to get regulatory capture and convince all the AGI pilled researchers to work for them
If you have the most basic understanding of chips its not just design, as that has a high degree of coupling to manufacturing and this article doesn't say where, who or how the chips are being made.
China, at last check was behind Intels home grown chip making efforts when it came to sizes and yields.
Hype and saber rattling to get the US to (Re)act, or possibly ignore the growing black market for Nvidia gear (that also happens to be bi-directional with modified cards flowing back to the US).
Who could have possibly seen this coming? /s
then its just matter of time when SOTA model is produced from china first or not
pixelesque•4mo ago
https://www.ft.com/content/12adf92d-3e34-428a-8d61-c91695119...
MaoSYJ•4mo ago
givemeethekeys•4mo ago
seanmcdirmid•4mo ago
pxc•4mo ago
TrainedMonkey•4mo ago
deadfoxygrandpa•4mo ago
acdha•4mo ago
It’s also an interesting signal to the rest of the world that they’re going to be an option. American tech companies should be looking at what BYD is doing to Tesla, but they’re also dealing with a change in government to be more like Chinese levels of control but with less maturity.
bsder•4mo ago
How big a deal is it to be on the cutting edge with this? Given that models seem to be flattening out because they can't get any more data, the answer is "not as much as you would think".
Consequently, a generation or 2 behind is annoying, but not fatal. In addition, if you pump the memory up, you can paper over a lot of performance loss. Look at how many people bought amped up Macs because the unified memory was large even though the processing units were underpowered relative to NVIDIA or AMD.
The biggest problem is software. And China has a lot of people to throw at software. The entire RISC-V ecosystem basically only exists because Chinese grad students have been porting everything in the universe over to it.
So, the signal is to everybody around this that the Chinese government is going to pump money at this. And that's a big deal.
People always seem to forget that Moore's Law is a self-fulfilling prophecy, but doesn't just happen out of thin air. It happens because a lot of companies pump a lot of money at the engineering because falling off the semiconductor hamster wheel is death. The US started the domestic hamster wheel with things like VHSIC. TSMC was a direct result of the government pumping money at it. China can absolutely kickstart this for themselves if the money goes where it should.
I'm really torn about this. On the one hand, I hate what China does on many, many political fronts. On the other hand, tech monopolies are pillaging us all and, with no anti-trust action anywhere in the West, the only way to thwart them seems to be by China coming along and ripping them apart.
OrvalWintermute•4mo ago
Microchip Inc partnered w US Govt on the aerospace angle and funded Canonical for linux ports. Their Polarfires and now Euro aerospace like Gaisler are heading in the same direction. US Govt/DARPA and others have been funding risc-v ports for years, to include mainly automated porting.
There are big differences between lowend profile-challenged SBCs and the work of NVDA, Microchip Inc, and the US Govt in the much more highend GPU related, and safety critical industries.
With Heavyweights like IBM/Redhat now on risc-v joining canonical and others, the SW side is definitely improving
TSMC btw, has always been about labor arbitrage
belter•4mo ago
"Speaker Johnson says China is straining U.S. relations with Nvidia chip ban" - https://www.cnbc.com/2025/09/17/china-us-nvidia-chip-ban.htm...
Translation: "We are angry with China that they wont let the US undermine itself, and sell its strategic advantages to them..."
littlestymaar•4mo ago
Oh, the irony.
arbuge•4mo ago
tonyhart7•4mo ago
alicloud has many cluster outside china, so they probably can because many friendly country with china has it
but it would be the same with US power play, they only permit anyone that they accept
UltraSane•4mo ago
sameermanek•4mo ago
This is step in good direction for everyone except nvidia and its chinese distribution network
ponector•4mo ago
kimixa•4mo ago
No amount of trade war politics will make up for a lack in infrastructure investment.
xadhominemx•4mo ago
jamiek88•4mo ago
There won’t be 16A manufacturing here in the USA.
Probably ever.
We live in extremely dangerous uncertain times.
Any forecast that long is worthless.
UltraSane•4mo ago
https://wccftech.com/tsmc-cutting-edge-sow-x-packaging-set-f...
xadhominemx•4mo ago