Wtf. Are we actually seeing a push towards being 100percent dependent on the cloud?
Sovereign AI has never been more important.
Controlling AI is so much more powerful and impactful than controlling search or social algorithms.
Centralized AI a 10x on social control over everything we have seen before, and there is no way that a free and open society survives contact with centralised, high capability AI if the system is manipulated towards guiding outcomes. It’s essentially mind control, as people will offload an even greater share of their cognition to AI than they do with search and social.
Build and maintain sovereign AI while you still can.
Yes, we are, the amount of data centers being built doesn't make sense for long-term model improvements. They are definitely planning on licensing us terminals to use instead of our own PCs at the very least as a backup plan if the frontier companies fail and have assets liquidated.
No, we are just seeing a push towards Nvidia wanting to make money.
Nothing stops you from giving Nvidia half a million for their latest and greatest AI GPUs, unless you are in China I guess, but China does very well despite the export control.
It is just classic market segmentation, the thing Nvidia and just about every company that can benefit from it has done for decades. Cloud providers are ready to pay a lot of money, consumers wanting local AI have a lower budget, and gamers even lower. But a low budget is greater than zero, and there is still money to be made on these markets. But they also don't want to compete against themselves, so they are going to find ways of crippling enterprise-class workloads on consumer hardware.
It used to be that they crippled high precision arithmetic on consumer hardware, because it was a differentiating factor, but AI doesn't care about high precision, so now, it is something else.
I can't wait until we have real competition against NVIDIA, whether it is from a Chinese chip maker or someone else. Hopefully then these kinds of intentional crippling of hardware/firmware will be avoidable by buying an equivalent product from another firm.
Even for things like the huawei ascend, what makes them crap for price to perf I think is still dram. They actually cost more than nvidia clusters last I checked. Just like how regular laptops and phones are now being squeezed upwards to become closer (and uncompetitive with) apple devices.
Given the history of prohibition in the past few centuries, it wouldn't surprise me if it is much easier to buy Nvidia products in China than in the US. The price is much higher most likely, but the actual transaction is likely easier.
Unless the US somehow differs from the EU in some major ways, can't you just walk into a store and buy a NVIDIA GPU? Not sure how much easier it can get. And yes, it's as easy in China to, walk into store, point at GPU, fork over the money, you get your GPU. Like everywhere else, except the US I suppose?
NVIDIA probably already figured out that local will be massive part and are preparing to do DRM for AI.
Pay up for license to unlock full capacity, pay up for license to use encrypted models from AI moguls, paid per billion tokens processed or just operations in GPU
I don't see the case for DRM protected local models on either side.
The consumer has access to free and open models for local use.
The supplier has better control and wider market to serve running the models in data centers.
Only way I can see encrypted models being widespread is if they are bundled as part of a software package (OS/Browser/etc) and not sold as the product.
Years ago I would think I was being paranoid to think they would patch hardware retroactively to make it slower so you need to pay more to use your own hardware.
In 2026, I think this is what all car companies are doing after you pay the full car price.
I don't see a reason why they wouldn't do it with so little competition
It smells like something IBM would do. Coming from small computers where you own it, I was flabbergasted to learn that IBM would ship additional processors and ram with their mainframes but you were not allowed to use them until you paid the additional license fee.
So it is something that has been done for a long time now. Still feels like unethical rent-seeking that should not be tolerated by the customer.
See Also: car companies that charge additional fees for hardware already on the car. Additional services, I sort of understand(remote start via cell network), but stuff like heated seats, that is just wrong.
Databases licencing per core is the most ridiculous thing I've heard for me. In this case they have zero marginal cost and still charge you for it. Hilarious.
> See Also: car companies that charge additional fees for hardware already on the car. Additional services, I sort of understand(remote start via cell network), but stuff like heated seats, that is just wrong.
It saves the car manufacturer on logistics cost. The per-unit cost of a seat heater is (much) smaller than the cost related to keeping two variants of seat in stock and to provide spare parts. Say the heating mat costs 100€ per seat including materials and installation, and can be sold to the customer for 400€ permanent, that means as long as 1 in 4 customers buys the seat heating option, the books are balanced, and all money you save on logistics is pure profit.
Adding subscription on top of that is financially even better, if there is one thing companies LOVE thanks to stonk market incentives it is monthly recurring revenue.
The reason why open source couldn't win search and social was because they need network effects which is not possible for open source maintainers.
AI is a software just like operating systems and executables where open source absolutely dominates the industry. Remember when the compiler engineers optimized the shit out of llama.cpp.
Right now the bottleneck for AI software is compute and data. Moore's law is give us compute, StackOverflow, arXiv (and it's children like bioRxiv), gutenberg and others (3lib, anna, internet.org) will give us data.
>Right now the bottleneck for AI software is compute and data. Moore's law is give us compute, StackOverflow, arXiv (and it's children like bioRxiv), gutenberg and others (3lib, anna, internet.org) will give us data.
Tons of stuff happenning behind closed doors today though. No more stackoverflow for the next decade, that could create a problem if all new context only exists in chatgpt conversations only openAI has access to (or whoever).
Wait until the archives are compromised and millions of people's conversation and uploaded data are published. Such context was never before accessible in that scale, but it will become accessible soon, I am pretty sure.
Yes? How is this at all surprising given....everything we've seen tech companies push for for years and years? People are fully embedding themselves and their workflows in the services of big, closed companies, and are going to be surprised when they finally feel able to clamp down? There has been warning sign after warning sign, but people are only increasing their dependence.
> Are we actually seeing a push towards being 100percent dependent on the cloud?
[Hanlon's Razor] This is such a contrived performance drop scenario that I find it hard to believe it was done with the purpose you're inferring.
I'd interpret this as Nvidia not caring that much about Linux desktops/laptops once again (as opposed to Windows desktops/laptops), rather than anything to do with local vs cloud.
No, when people talk about building software they tend to mean building software. Just like "putting together my own training hardware" doesn't imply you're creating your own wafers from sand.
But the original post was about a hardware vendor getting in the way. It's pointless to talk about "sovereign AI" when all you do is run GLM on Nvidia.
This is classical move from Nvidia. They are doing similiar bullshits on their GPUs for decades. I'm very much looking forwars for their competition to rise.
>Oddly, the direction of the problem flips depending on power source. Unplugged, Linux hit around 61 to 67 tokens per second on LM Studio, comparable to Windows. Plugged in, that same test dropped to about 15 tokens per second.
Absolutely hilarious.
This is just incompetence. No reason Nvidia with its TRILLIONS of market cap couldn't of tested and fixed this on Linux before shipping.
Or a day one patch.
I have no doubt that'll it'll work right eventually. Long after RTX Spark laptops flop and can be purchased for half off.
Last night I pulled out my 5070TI laptop and installed CachyOS. I was running various models within about 20 minutes.
That 12GB of VRAM is a hard limitation, Unsloth can't split jobs between vram and system memory.
Nvidia doing what Nvidia has always done; proprietary closed drivers. Weird choice to cryptographically protect the power settings. Key problem is that we've allowed a company that's always been this way to form a monopoly. Other brands exist, perhaps it is now worth the effort to migrate and rebuild elsewhere.
New generations such as Blackwell have open source kernel modules, there is not even a proprietary option. I thought there was a move in this direction?
The total linux-firmware-nvidia package for Archlinux uncompressed (outer, the firmware blobs are also compressed on top of that) is ~160MB (Mb would be Megabit), with the biggest individual compressed blob being ~50MB.
they could make money that way right now but they figured out they can make even more money by doing this. but jokes on them, people will figure it out, unlock / jailbreak and they just lose good will long term
Enumerating 3 things really ..sparks a comment nowadays? Doing that as a rhetorical device has been a thing for generations and of course LLMs mimic it because it is everywhere in their training data.
I just heard a quick J. Talarico speech at some country concert. In the 10 or so sentences he spoke, he had 3 or 4 instances of doing this "Claudism" enumeration. Are you saying Texas just elected Claude for Senate?
Maybe we should stop with such superficial judgements. It's the modern equivalent of not liking the speaker's tie. (Doesn't mean the speaker's speech is good, but it doesn't mean it's bad either.)
There are more Claude-isms in there than just rule of three (Hence -isms and not -ism), and while I'd generally agree that we generally shouldn't be superficial with our judgements, this particular heuristic has served me pretty well so far. I don't know what Talarico speech you are talking about, so i won't comment on that (But I'm not sure if political speeches are the best rebuttal to "I think obviously AI generated text is an indicator of low signal-to-noise ratio").
Edit re "equivalent to not liking the speaker's tie":
This is not equivalent at all, this is a written blog post and I'm put off by the way it is written, not by say the URL or their chosen font. It's more akin to a speaker dropping an inappropriate joke at the start of their talk and leaving because of that
Please be aware that you have been the target of foreign anti-AI influence campaigns. Your comment history makes it clear they have had a strong negative effect on you.
What an odd response, but if by "foreign influence campaign" you mean "masses of badly written blog posts that i regret wasting my time reading" then sure
Not really, because for more than 2 decades the closed-source NVIDIA Linux drivers were at parity of features and performance with the Windows drivers, unlike the AMD drivers before they were open-sourced, which was much more recently.
This is a new thing with the firmware that can be used only by Windows. If this NVIDIA policy continues, then NVIDIA will indeed become a bad choice for Linux, but until now, for graphics and AI applications NVIDIA has been the best choice for Linux, by providing the best performance and reliability.
For pure computational applications, especially for those requiring good FP64 throughput, there are many years since NVIDIA has become a worse choice than AMD and more recently also than Intel, but that is due to poor hardware support, not to bad software support.
We have antitrust laws on the books. They have barely been enforced since Reagan. But that good change if there was political will. How is Nvidia not a monopoly?
Why does the title say DGX spark when the link is the RTX Spark laptop?
Those are very different things as far as I understand, and the whole "doesn't work well with linux" really only makes sense on the RTX Spark laptop I think?
Isn't the DGX spark linux by default?
It should be possible to reverse engineer this, if it works on windows?
> The laptops also support unified memory configurations up to 128GB, shared between CPU and GPU, which is unusual for a laptop and central to why they’re being marketed at AI developers in the first place.
This isn't rare on laptops, pretty default on AMD with iGPU
Not everyone grew up in a situation where home was a stable dependable place. Not everyone has a home to go to. If you have it with you, they can't mess with it or take it away from you when you're not there. If you grew up in a broken home, you would understand.
If the security of your home possessions is an issue, it should be addressed first before you spend thousands on a very stealable laptop that you need to carry everywhere.
Local AI is an expensive hobby. You're paying big money for small performance (so mainly for the feeling of "owning it", which is a great motivator). It can't match cloud services, not absolutely nor bang-for-buck, especially if you look a bit for cheaper and freebie options. As someone who loves and promotes local AI, in the situation you described my plea would be to use that money to improve your situation more directly (move out, get support,...). The cost of a laptop that can run somewhat decent models should buy you at least several months of therapy (@1 session/week).
Exactly. Get yourself a DGX spark and plug it in at home.
I meanwhile, run my ridiculously OP workstation class hardware as a server - 9995wx, 768GiB, rtx pro 6000 w/ 96GiB vram - at home, and my Asus ZenBook is light, cool, and long-lived.
Runs GLM 5.3 flash at 35 tok/sec while consuming only 15 GiB VRAM, and I can run a lot more stuff on there alongside.
I have been saying this for years, and the answer hits a nerve that gets you downvoted into oblivion: people prefer the aesthetics of laptops, simple as that. They will absolutely go to the grave arguing that they need the mobility etc, then just leave it plugged in. They simply prefer how laptops look, and they absolutely hate it when someone dares say it.
I have a laptop for work. 95% of the time i'd prefer a tower or at least a mini PC with proper cooling, but that remaining 5% i have to be around with the laptop is enough. I don't like the idea of having to remember to sync the projects every time (especially while i'm in the middle of testing something new so it's not like i can just pull the latest commit or sync the latest good version of something)
Fortunately that's just a matter of weeks until someone revengs and publishes the fix... even if we need to wait a while for a proper upstreamed solution.
As someone who went down the rabbit hole of local AI, there is so much exhausting debugging already. Even if this is "just" another step you have to find, it's toxic.
You will never stop me. As I and everyone like me, before and after me, have shown, time and time again. And by me, I mean nature. And by nature I mean math and logic unchangeable in any possible universe. You cannot give me a thing without me having it. If a thing exists, I can copy it, know it, and bring it's equivalent into existence. Nothing can be created that is not indelibly written into the the intricate cause and effect chain of history. A perfectly encrypted thing is indistinguishable from the noise of the cosmos, but if I want I thing, it shall soon emerge, free from any control from that noise, which is the weight of all that has happened, just as surely as I can count to a number.
If you want to prosper with the current of nature, provide a thing easily for mutual benefit. The more you try to block a thing, the sooner your demise into uselessness.
So weird that everyone gives Microsoft a complete pass. They probably paid Nvidia to give them a head start so people would be forced into Windows and WSL for awhile.
I am starting to wonder whether CEOs everywhere ( but especially in US ) are simply unable to read the room. I shrugged off nvidia when they did it to gaming and mining ( it annoyed me, but ultimately there were options to deal with it ), but here it is touching a much wider populace with repercussion well beyond crypto and gaming.
Assume I'm naive on this matter, but why wouldn't Nvidia allow its own DGX OS to be a first party OS on these devices? Some sort of MS subsidy? Ecosystem-wise, wouldn't it make sense for Nvidia to keep pushing its own OS on all the devices containing its hardware?
Unrelated to this slowdown, I could imagine this sort of thing being the right application for things like Taalas, although I'm not quite sure whether it can actually offer what I imagine that it can (i.e. ability to make a cheap, physically small card that can run a large model).
A laptop can't run the latest big models, because memory is too expensive. This thing probably can't run models larger than Mistral Small 4. But it'd be a completely different thing to have a hardcoded Mistral Large 4, than a choice of tiny models.
You probably won't be able to run a sota model on a single Talaas card. You probably need a set. It should theoretically be cheaper, faster, more power efficient than Nvidia at running that model. But then you are stuck with a chip that can run only that model. And I understand that context size will also be a problem.
Yeah, that was why I felt that, while Taalas might not be the right thing in general, it could be really appealing in a laptop, that would otherwise not be able to run any big model at all.
I think I misunderstood what the technology could do a little bit, because I imagined these fixed matrix multiplies encoded into hardware as small-ish, as using routing space etc., not just fast.
I think what I really imagined was useful would be more easily achieved by having a big ROM with model weights connected to an ordinary GPU.
This one is allegedly/hopefully a bug but just waiting for it to become a revenue stream / paywall. Uh oh, you want to run locally your dangerous illegal foreign open models, not licensed by Nvidia? Can’t work with you paying for a special security feature unlock on your GPU.
Or maybe just not at all - shell out for OAI tokens and send us all your data - your privacy is very valuable to us and we will make sure to be the only ones to monetize it.
You could say, Nvidia is selling pickaxes and has no business gatekeeping what rocks you hit with it, but I guess it depends on their relationships with major mining companies, and ultimately what pays more.
The attack on reverse engineering of games is a precursor to universal computing lockdown. When you need AI to keep up with programming, the entity controlling the AI controls what software is possible to create. It’s a bid for centralised control and thought censorship at a scale and depth much more ambitious than anything we have ever seen before.
They really got it right on multiple levels - for those who don't know, roller coaster tycoon was infamously written in 99% assembly and meticulously optimized by the developer to run effectively in 16 megabytes of ram.
I'm starting to feel empathy with those people who think bus lanes are coming form their freedom as part of some conspiracy to take away their cars.. I would like private enjoyment of my own RAM to use as I wish please.
Sovereign AI has never been more important.
Controlling AI is so much more powerful and impactful than controlling search or social algorithms.
Centralized AI a 10x on social control over everything we have seen before, and there is no way that a free and open society survives contact with centralised, high capability AI if the system is manipulated towards guiding outcomes. It’s essentially mind control, as people will offload an even greater share of their cognition to AI than they do with search and social.
Build and maintain sovereign AI while you still can.
Nothing stops you from giving Nvidia half a million for their latest and greatest AI GPUs, unless you are in China I guess, but China does very well despite the export control.
It is just classic market segmentation, the thing Nvidia and just about every company that can benefit from it has done for decades. Cloud providers are ready to pay a lot of money, consumers wanting local AI have a lower budget, and gamers even lower. But a low budget is greater than zero, and there is still money to be made on these markets. But they also don't want to compete against themselves, so they are going to find ways of crippling enterprise-class workloads on consumer hardware.
It used to be that they crippled high precision arithmetic on consumer hardware, because it was a differentiating factor, but AI doesn't care about high precision, so now, it is something else.
Pay up for license to unlock full capacity, pay up for license to use encrypted models from AI moguls, paid per billion tokens processed or just operations in GPU
I wonder if this space is explored fully enough at the moment.
Aside from some implementation details, it's conceptually much easier than doing it for a SQL database.
The consumer has access to free and open models for local use.
The supplier has better control and wider market to serve running the models in data centers.
Only way I can see encrypted models being widespread is if they are bundled as part of a software package (OS/Browser/etc) and not sold as the product.
So it is something that has been done for a long time now. Still feels like unethical rent-seeking that should not be tolerated by the customer.
See Also: car companies that charge additional fees for hardware already on the car. Additional services, I sort of understand(remote start via cell network), but stuff like heated seats, that is just wrong.
Yep, "Batterygate"
https://www.npr.org/2020/11/18/936268845/apple-agrees-to-pay...
It saves the car manufacturer on logistics cost. The per-unit cost of a seat heater is (much) smaller than the cost related to keeping two variants of seat in stock and to provide spare parts. Say the heating mat costs 100€ per seat including materials and installation, and can be sold to the customer for 400€ permanent, that means as long as 1 in 4 customers buys the seat heating option, the books are balanced, and all money you save on logistics is pure profit.
Adding subscription on top of that is financially even better, if there is one thing companies LOVE thanks to stonk market incentives it is monthly recurring revenue.
I think more than that, it is probably a lie they tell us that you are not paying for the hardware/equipment.
AI is a software just like operating systems and executables where open source absolutely dominates the industry. Remember when the compiler engineers optimized the shit out of llama.cpp.
Right now the bottleneck for AI software is compute and data. Moore's law is give us compute, StackOverflow, arXiv (and it's children like bioRxiv), gutenberg and others (3lib, anna, internet.org) will give us data.
It's a waiting game. Open source always wins.
Tons of stuff happenning behind closed doors today though. No more stackoverflow for the next decade, that could create a problem if all new context only exists in chatgpt conversations only openAI has access to (or whoever).
[Hanlon's Razor] This is such a contrived performance drop scenario that I find it hard to believe it was done with the purpose you're inferring.
I'd interpret this as Nvidia not caring that much about Linux desktops/laptops once again (as opposed to Windows desktops/laptops), rather than anything to do with local vs cloud.
As in, make your own inference and training hardware?
I stopped using my laptop for dev and switched to talking to claude code on my phone and as you can imagine I am faster at producing code.
100% cloud with a single entry point device to manage dedicated servers + agents
Absolutely hilarious.
This is just incompetence. No reason Nvidia with its TRILLIONS of market cap couldn't of tested and fixed this on Linux before shipping.
Or a day one patch.
I have no doubt that'll it'll work right eventually. Long after RTX Spark laptops flop and can be purchased for half off.
Last night I pulled out my 5070TI laptop and installed CachyOS. I was running various models within about 20 minutes.
That 12GB of VRAM is a hard limitation, Unsloth can't split jobs between vram and system memory.
https://developer.nvidia.com/blog/nvidia-transitions-fully-t...
Point was about the kernel drivers being open-source enabling hackability - they don't, the card hardware is just as closed as before.
Nvidia does something to prevent abuse so that regular people who want the laptops can buy one. Nvidia gets knocked on.
When did "we" have a say in this? I don't get these types of comments from the "open-source as a community."
Nvidia has been doing this for decades, and there are two possible arguments:
1. They are successful despite it.
2. They are successful because of it.
There is no mythical collective "we" representing the open-source community in Nvidia's supply chain of success. It's Nvidia and its consumers.
Man it really is exhausting to read a title that sparks my interest, just to be greeted with the most basic Claude-isms in the subheading.
I see what you did there. ;)
I just heard a quick J. Talarico speech at some country concert. In the 10 or so sentences he spoke, he had 3 or 4 instances of doing this "Claudism" enumeration. Are you saying Texas just elected Claude for Senate?
Maybe we should stop with such superficial judgements. It's the modern equivalent of not liking the speaker's tie. (Doesn't mean the speaker's speech is good, but it doesn't mean it's bad either.)
Edit re "equivalent to not liking the speaker's tie": This is not equivalent at all, this is a written blog post and I'm put off by the way it is written, not by say the URL or their chosen font. It's more akin to a speaker dropping an inappropriate joke at the start of their talk and leaving because of that
This is a new thing with the firmware that can be used only by Windows. If this NVIDIA policy continues, then NVIDIA will indeed become a bad choice for Linux, but until now, for graphics and AI applications NVIDIA has been the best choice for Linux, by providing the best performance and reliability.
For pure computational applications, especially for those requiring good FP64 throughput, there are many years since NVIDIA has become a worse choice than AMD and more recently also than Intel, but that is due to poor hardware support, not to bad software support.
This has been an issue on Linux since 2014, and the gtx980.
Those are very different things as far as I understand, and the whole "doesn't work well with linux" really only makes sense on the RTX Spark laptop I think? Isn't the DGX spark linux by default?
> The laptops also support unified memory configurations up to 128GB, shared between CPU and GPU, which is unusual for a laptop and central to why they’re being marketed at AI developers in the first place.
This isn't rare on laptops, pretty default on AMD with iGPU
If you really want to do DIY inference, plug it in at home and set up tailscale so you can access it on the go.
No huge battery drain or toasty hot laptop required. Lower cost laptop. Lighter laptop. Longer battery life laptop. Win win win win.
I meanwhile, run my ridiculously OP workstation class hardware as a server - 9995wx, 768GiB, rtx pro 6000 w/ 96GiB vram - at home, and my Asus ZenBook is light, cool, and long-lived.
Runs GLM 5.3 flash at 35 tok/sec while consuming only 15 GiB VRAM, and I can run a lot more stuff on there alongside.
unique local data and know how not shared with cloud.
I am not saying don't use a laptop.
I am not saying you have to use cloud inference.
I am saying using a laptop for inference is dumb. If you want private inference:
- use a dgx spark or similar plugged in at home
- set up tailscale so you can connect from anywhere
- use your phone as a hotspot on the go
- work on your laptop, using tailscale to connect to your home inference server if you're on the go
This gets you everything except for the few hours you might be on an airplane.
Also very curious if the NPU is visible in Linux, too.
https://www.xda-developers.com/nvidia-rtx-spark-laptops-same...
If you want to prosper with the current of nature, provide a thing easily for mutual benefit. The more you try to block a thing, the sooner your demise into uselessness.
A laptop can't run the latest big models, because memory is too expensive. This thing probably can't run models larger than Mistral Small 4. But it'd be a completely different thing to have a hardcoded Mistral Large 4, than a choice of tiny models.
I think I misunderstood what the technology could do a little bit, because I imagined these fixed matrix multiplies encoded into hardware as small-ish, as using routing space etc., not just fast.
I think what I really imagined was useful would be more easily achieved by having a big ROM with model weights connected to an ordinary GPU.
But with Nvidia people just expect they nerf all the features.
Still miles ahead compared to Apple, where linux does not even boot on newer macs!
Or maybe just not at all - shell out for OAI tokens and send us all your data - your privacy is very valuable to us and we will make sure to be the only ones to monetize it.
You could say, Nvidia is selling pickaxes and has no business gatekeeping what rocks you hit with it, but I guess it depends on their relationships with major mining companies, and ultimately what pays more.
But, on the other hand, having my DGX Spark stack at hand, I know the solution:
"AI views proprietary components as damage and routes around them."Sovereign AI has never been more important.
But yeah, we do need to make sure the REA cat stays out of the bag.
I, for one, welcome our reverse-engineer-anything overlords.
TIL. Nice word.
EDIT: I don't know why you changed your comment, but yes, it was obvious from reading the article that it was not actually about the DGX Spark.
They really got it right on multiple levels - for those who don't know, roller coaster tycoon was infamously written in 99% assembly and meticulously optimized by the developer to run effectively in 16 megabytes of ram.