Now where is the shovel head maker, TSMC?
And then China popping their head out claiming Taiwan is part of China because they want to seize TSMC
deleted by creator
Those things aren’t mutually exclusive. Yes, they are dumping massive resources into SMIC. Yes, they also want to maintain imperialism over Taiwan, and TSMC is a part of that. Some of it is fear-mongering sure, but China is consistently confrontational in the South China Sea and beyond. There’s a reason they enforce an abrasive naval presence there and continue to press against the Philippines.
https://www.ft.com/content/b4ee2e18-3256-4371-8369-9a3118959fca
they also want to maintain imperialism over Taiwan
Not to deny the realities of the tensions there, but liberals are relatively loose with term imperialism. There is a difference between an imperialist state like the US and an anti-imperialist — and until recently imperialized — state like China.
China is consistently confrontational in the South China Sea and beyond
Yeah why so confrontational, China?
Foreign Policy, 2013: Surrounded: How the U.S. Is Encircling China with Military Bases. And that article is a decade old; it’s only gotten worse.
The US has over 750 overseas military bases around the world, and is building more to further encircle China. Meanwhile China has one anti-piracy base in Djibouti.
Once the US have in housed chip manufacturing they will let China too which is the worst part. Profits over everything amirite?
has been part of china for 2000 years, anglo imperialism wont change that
Pretty sure China has actually been a part of Taiwan for 2000 years
It just writes itself lmao
Tankees. Tankees everywhere.
You have an island governed by a democratically elected government, with a population that from what I remember mostly doesn’t want to be assimilated into the PRC. The PRC taking it by force would, in my eyes, be rather imperialistic.
democratically elected? arguable and only for the last few decades at that. it was run as a brutal single party dictatorship backed by amerikkka until fairly recently. And last time i checked the vast majority of people in Taiwan want to maintain the status quo which is that Taiwan is part of China.
Yeah, fuck the KMT. But as you have recognised, they aren’t a dictatorship anymore.
And the status quo is that they are de facto a small independent island nation, that is de jure claiming mainland China.
Eh, they’ll have plenty of demand for their nodes regardless. Non-AI CPUs and GPUs are still going to want them.
Nvidias being pretty smart here ngl
This is the ai gold rush and they sell the tools.
Yes that’s the meme.
Edited the price to something more nvidiaish:
Gotta add a few more 9s to that. This is enterprise cards we’re talking about
Literally about to do same.
Jensen also is obsessed with how much stuff weighs. So maybe he’d sell shovels by the ton.
Nobody expects the “4 elephants” GPU.
Here is an alternative Piped link(s):
https://www.piped.video/watch?v=ugd61cUHbME
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meanwhile i just want cheap gpus for my bideogames again
You can buy them new for somewhat reasonable prices. What people should really look at is used 1080ti’s on ebay. They’re going for less than $150 and still play plenty of games perfectly fine. It’s the budget PC gaming deal of the century.
it probably the best performance per dollar u can get but a lot of modern games are unplayable on it.
Lot of those games are also hot garbage. Baldur’s Gate 3 may be the only standout title of late where you don’t have to qualify what you like about it.
I think the recent layoffs in the industry also portend things hitting a wall; games aren’t going to push limits as much as they used to. Combine that with the Steam Deck-likes becoming popular. Those could easily become the new baseline standard performance that games will target. If so, a 1080ti could be a very good card for a long time to come.
You’re misunderstanding the issue. As much as “RTX OFF, RTX ON” is a meme, the RTX series of cards genuinely introduced improvements to rendering techniques that were previously impossible to pull-off with acceptable performance, and more and more games are making use of them.
Alan Wake 2 is a great example of this. The game runs like ass on 1080tis on low because the 1080ti is physically incapable of performing the kind of rendering instructions they’re using without a massive performance hit. Meanwhile, the RTX 2000 series cards are perfectly capable of doing it. Digital Foundry’s Alan Wake 2 review goes a bit more in depth about it, it’s worth a watch.
If you aren’t going to play anything that came out after 2023, you’re probably going to be fine with a 1080ti, because it was a great card, but we’re definitely hitting the point where technology is moving to different rendering standards that it doesn’t handle as well.
So here’s two links about Alan Wake 2.
First, on a 1080ti: https://youtu.be/IShSQQxjoNk?si=E2NRiIxz54VAHStn
And then on a Rog Aly (which I picked because it’s a little more powerful than the current Steam Deck, and runs native Windows): https://youtu.be/hMV4b605c2o?si=1ijy_RDUMKwXKQQH
The Rog seems to be doing a little better, but not by much. They’re both hitting sub 30fps at 720p.
My point is that if that kind of handheld hardware becomes typical, combined with the economic problems of continuing to make highly detailed games, then Alan Wake 2 is going to be an abberation. The industry could easily pull back on that, and I welcome it. The push for higher and higher detail has not resulted in good games.
I own a 1080ti and there was recently a massive update to Allan Wake 2 that made it more playable on pascal GPUs. Digital foundry did a video on it: http://youtu.be/t-3PkRbeO8A
I don’t know of any current game that can’t run at least 1080p30fps on 1080ti. But of course my knowledge is not exhaustive.
I wouldn’t expect every “next-gen” game to get the same treatment as Alan Wake 2 going forward. But we’re 4 years into the generation and there has probably been less than 10 games that were built to take full advantage of modern console hardware. My 1080ti has got a few more good years in it.
Here is an alternative Piped link(s):
http://piped.video/t-3PkRbeO8A
Piped is a privacy-respecting open-source alternative frontend to YouTube.
I’m open-source; check me out at GitHub.
Can you reference those instructions more specifically
“Instructions” is probably the wrong word here (I was mostly trying to dumb it down for people who aren’t familiar with graphics rendering terminology).
Here’s a link to the Digital Foundry video I was talking about (didn’t realized they made like 5 videos for Alan Wake 2, took a bit to find it).
The big thing, in Alan Wake 2’s case, is that it uses Mesh Shaders. The video I linked above goes into it at around the 3:38 mark.
AMD has a pretty detailed article on how they work here.
This /r/GameDev post here has some devs explaining why it’s useful in a more accessible manner.
The idea is that it allows offloading more work to the GPU in ways that are much better performance-wise. It just requires that the hardware actually support it, which is why you basically need an RTX card for Alan Wake 2 (or whichever AMD GPU supports Mesh Shaders, I’m not as familiar with their cards).
Ah, mesh shaders. Cool stuff. AMD retroactively added them to their old GPUs in drivers. I think same goes for Intel’s post-Ivybridge GPUs(I think
sendopcode can throw primitives into 3d pipeline, if you are interested, you can go read docs). I guess Nvidia can do something similar.And even if they don’t have such straightforward way of implementing them, they probably(my guess, can be wrong) can be emulated in geometry shaders.
What I don’t like is apparent removal of vertex fetcher, but maybe there will be extension that will return it.
Here is an alternative Piped link(s):
Here’s a link to the Digital Foundry video I was talking about
Piped is a privacy-respecting open-source alternative frontend to YouTube.
I’m open-source; check me out at GitHub.
I suspect that’s the exception and will be for most games.
I bought a GTX1080 when it was released. I played Starfield in 4K on medium settings just fine at 50-60 FPS. Not sure what you mean by “unplayable”.
not in my country lol. getting used cards were already the norm before, for a while you could literally only get used ones for a good price on aliexpress.
and now our gvmnt imposed 100% tax on anything from china, so its really just not affordable.
You can still look for used ones locally either through hardwareswap or fb marketplace (unfortunately thats the best secondhand marketplace atm). Other options include liquidation companies, sometimes universities also have a big market (from both staff and students)
Its been pretty rough still though, good luck on your search
no such thing as hardwareswap in my country. our marketplaces are overpriced because we want to resell our shit with prices proportional to what we overpaid for it.
importing used shit is cheaper because the value of, say, an rx580 is much lower outside the country.
Yea lots of the secondhand tech market exists purely in the US. The market outside of there and a couple other countries (uk, ca, de) dont really exist afaik
Could import from Taiwan instead?
not really a good way. we can mostly only afford used and theres no outlet to buy used from taiwan that ships internationally in a trustworthy way.
brand new will probably be taxed too anyway.
Meanwhile I dont think I have played more than 30minutes on my ps5 this year and its june, and I have definitely not played any minutes on the 1080 sitting in my PC…
Oh fuck scratch that I may have played about 2 hours of Dune Spice Wars
How are you finding dune? I watched a few let’s plays of the demo and it looked interesting…
Honestly, I don’t have an opinion on it, it didnt capture me like old world did last year, so probably not as good or I am just preferring more slow, thought out turn based stuff.
But mostly I am just kinda over gaming as a whole, I realized it’s mostly cheap dopamine chasing for me and I don’t really enjoy it.
Crack cocain is 10000x’s more rewarding and less of a come down when you realize you only spent 1/10th of the price of a console or gaming pc.
How about GeForce NOW?
nah, its gonna become the next enshitified netflix. i stream games from my own pc.
good thing about small screens is that you don’t need the best resolution so it does better on older computers.
not to mention the monthly cost instead of being a once every handful of years thing.
not judging though streaming can be fine.
Don’t forget AMD, good potential if they bring out similar technology to compete with NVIDIA. Less so Intel, but they’re in the GPU market too.
Does ARM do anything special with AI? Or is that just the actual chip manufacturers designing that themselves?
As I understand it, ARM chips are much more efficient on the same tasks, so they’re cheaper to run.
I think its largely the chip manufacturers, but ARM is still making money on licensing fees for Nvidia’s new ai chip (with an integrated 72 core arm cpu) for example
ARM is in the perfect place where, if a company using their architecture succeeds, they get tons of money, and if the company fails, they lose nothing.
NPUs
Does ARM make the designs for those also?
Don’t forget Qualcomm either.
They will eat massive shit when that AI bubble bursts.
I mean if LLM/Diffusion type AI is a dead-end and the extra investment happening now doesn’t lead anywhere beyond that. Yes, likely the bubble will burst.
But, this kind of investment could create something else. We’ll see. I’m 50/50 on the potential of it myself. I think it’s more likely a lot of loud talking con artists will soak up all the investment and deliver nothing.
bubbles have nothing to do with technology, the tech is just a tool to build the hype. The bubble will burst regardless of the success of the tech at most success will slightly delay the burst, because what is bursting isnt the tech its the financial structures around it.
It’s looking like a dead end. The content that can be fed into the big LLMs has already been done. New stuff is a combination of actual humans and stuff generated by LLMs. It then runs into an ouroboros problem where it just eats its own input.
I mostly agree, with the caveat that 99% of AI usage today just stupid gimmicks and very few people or companies are actually using what LLMs offer effectively.
It kind of feels like when schools got sold those Smart Whiteboards that were supposed to revolutionize teaching in the classroom, only to realize the issue wasn’t the tech, but the fact that the teachers all refused to learn and adapt and let the things gather dust.
I think modern LLMs should be used almost exclusively as an assistive tool to help empower a human worker further, but everyone seems to want an AI that you can just tell ‘do the thing’ and have it spit out a finalized output. We are very far from that stage in my opinion, and as you stated LLM tech is unlikely to get us there without some sort of major paradigm shift.
only to realize the issue wasn’t the tech
To be fair, electronic whiteboards are some of the jankiest piles of trash I’ve ever had to use. I swear to God you need to re-calibrate them every 5 minutes.
Yeah, I was thinking more if there’s either an evolutionary improvement or revolutionary (or some movement toward AGI). For me it’s better if not, so I get to keep my job for a few more years. But, my general feeling is with the cash injection, there’s some chance of a breakthrough.
No, they won’t. They’ll just jump on making shovels for the next bubble.
Unfortunately you’ve completely switched your entire economy to shovels for this thing and also all your warehouses are full of shovels for this thing and most of your assets are tied up in shovels for this thing. And now suddenly, this thing stops.
NVIDIA has a very diverse portfolio of consumer and enterprise products. They have never switched to one type of shovels.
I doubt it. Regardless of the current stage of machine learning, everyone is now tuned in and pushing the tech. Even if LLMs turn out to be mostly a dead end, everyone investing in ML means that the ability to do LOTS of floating point math very quickly without the heaviness of CPU operations isn’t going away any time soon. Which means nVidia is sitting pretty.
the WWW wasn’t a dead end but the bubble burst anyway. the same will happen to AI because exponential growth is impossible.
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See Sun Microsystems after the .com bubble burst. They produced a lot of the servers that .com companies were using at the time. Shriveled up after and were eventually absorbed by Oracle.
Why did Oracle survive the same time? Because they latched onto a traditional Fortune 500 market and never let go down to this day.
It means having a shot at getting a good gaming gpu for cheap
As far as I understand the tech, those things aren’t really interchangeable :(
one can only hope
No they won’t, this tech isn’t going to go away Even if it plateaus. All the gpus they make will still get used.
The internet didn’t go away but there was still a .com bubble
As far as I understand, the GPUs that LLMs use aren’t exactly interchangeable with your regular GPU. Also, no one needs that many GPUs for any traditional use cases.
Worst one is probably Apple. They just announced “Apple Intelligence” which is just ChatGTP whose largest shareholder is Microsoft. Figure that one out.
Well, most of the requests are handled on device with their own models. If it’s going to ChatGPT for something it will ask for permission and then use ChatGPT.
So the Apple Intelligence isn’t all ChatGPT. I think this deserves to be mentioned as a lot of the processing will be on device.
Also, I believe part of the deal is ChatGPT can save nothing and Apple are anonymising the requests too.
chatgpt won’t save anything? Doubtful.
Brother I do not care about your doubts.
I want hard facts here.
Do you think that if you enter into a contract with a company like Apple they’ll just be like, aww shit they weren’t supposed to do that. Anyway let’s carry on.
No. This would open OpenAi up to potential lawsuits.
Even if they did save stuff. It gets anonymised by Apple before even being sent to ChatGPT servers.
The hard fact is OpenAI is already exposing itself to lawsuits by training on copyrighted material.
So the proof here should be “what makes them trustworthy this time?”
There’s kind of a difference between “we scraped the internet and decided to use copyrighted content anyways because we decided to interpret copyright law as not being applicable to the content we generate using copyrighted content” (omegalul) and “we explicitly agreed to a legally-binding contract with Apple stating we won’t do that”.
Because Apples lawyers will go ham.
I don’t want my comments here to be received as shilling Apple, more that I want them to based on actual information that is provided and not opinion pieces.
The fact is, if they were to caught saving data then Apple would just end the contract. Is it worth it for them to lose out on that cash, for the sake of using it. When they can just use all the other sources where they are allowed to do that.
Anyway, I don’t care what anonymised data they may or may not save. It won’t be tied to me.
Edit: Do you have some information on this existing lawsuits and the contracts they broke?
Because Apples lawyers will go ham.
Google pays Apple $20 billion a year to keep their search on Apple devices. The subtext of “search” is Google pays Apple for your search data.
Apple has sold your data for the right price to Google, so there should be no expectation that they won’t do the same with other companies.
They sell Google the right to keep it as the default, not that they’re selling data.
Again, point me to some proof of it being actually selling data. As to my understanding they pay for the default engine to be Google.
thing is apple doesnt give a shit about ur privacy
Finally, a reasonable comment.
I would concede that they want to keep it all for themselves, although a lot of anonymising of data is done.
My point is Apple are not sharing it with every third party on the Earth.
If you’re using Android then you don’t really have a leg to stand on, unless you’re using GrapheneOS and you’ve sandboxed Google services.
I would rather use a device that maybe keeps it all for themselves. Rather than one where it is shared with Everyman and his dog.
Plenty of things you can shit on Apple for, but this isn’t one of them I’m afraid.
careful, that’s a hardcore tankie troll you replied to.
Well, most of the requests are handled on device
Doubt.
Voice recognition, image recognition, yes. But actual questions will go to Apple servers.
Doubt.
Is this conjecture or can you provide some further reading, in the interest of not spreading misinformation.
Edit: I decided to read the info from Apple.
With Private Cloud Compute, Apple sets a new standard for privacy in AI, with the ability to flex and scale computational capacity between on-device processing, and larger, server-based models that run on dedicated Apple silicon servers. When requests are routed to Private Cloud Compute, data is not stored or made accessible to Apple and is only used to fulfill the user’s requests, and independent experts can verify this privacy.
Additionally, access to ChatGPT is integrated into Siri and systemwide Writing Tools across Apple’s platforms, allowing users to access its expertise — as well as its image- and document-understanding capabilities — without needing to jump between tools.
Say what you will about Apple, but privacy isn’t a concern for me. Perhaps, some independent experts will verify this in time.
Which is exactly what I said. It’s not local.
That they are keeping the data you send private is irrelevant to the OP claim that the AI model answering questions is local.
OP here being me.
Well, most of the requests are handled on device with their own models. If it’s going to ChatGPT for something it will ask for permission and then use ChatGPT.
I feel I was pretty explicit in explaining how some requests will go to ChatGPT.
Apple has published papers on small LLM models and multimodal models already. I would be surprised if they aren’t using them for on-device processing.
If you think that’s the WORST ONE, you have no idea about any of this
Yeah, if anything, Apple is behind the curve. Nvidia/AMD/Intel have gone full cocaine nose dive into AI already.
That’s just not true. Most requests are handled on-device. If the system decides a request should go to ChatGPT, the user is promped to agree and no data is stored on OpenAI’s servers. Plus, all of this is opt-in.
Most requests are handled on-device.
Literally impossible.
“Hey Siri, what’s the weather forecast for tomorrow.”
< The Farmer’s Almanac that is in my local model says it will rain tomorrow. >
I think there’s a larger picture at play here that is being missed.
Getting the weather is a standard feature for years now. Nothing AI about it.
What is “AI” is,
Hey Siri, what is the weather at my daughter’s recital coming up?The AI processing, calculated on-device if what they claim is true, is:
- the determination of who your daughter is
- What is a recital? An event? Are there any upcoming calendar events that match this concept?
- Is the “daughter” associated with this event by description or invitation? Yes? OK, what’s the address?
- Submit zip code of recital calendar event involving the kid to the weather API, and churn out a reply that includes all this information…
Well {Your phone contact name}, it looks like it will {remote weather response} during your {calendar event from phone} with {daughter from contacts} on {event date}.That is the idea between on-device and cloud processing. The phone already has your contacts and calendar and does that work offline rather than educating an online server about your family, events and location, and requests the bare minimum from the internet, in this case nothing more than if you opened the weather app yourself and put in a zip code.
Nothing AI about it.
Voice processing is AI and was done by Apple servers. Previously, only the keyword “Hey Siri” was local. Onboard AI chips will allow this to be local. The actual queries will go to the servers. Phones do not have the power to run useful LLM locally- at least not with the near instantaneous response times phone users expect. A 56 Watt 128GB RAM M3 Max does around 8.5 tokens/second.
Onboard AI chips will allow this to be local.
Phones do not have the power to ~~~
Perhaps this is why these features will only be available on iPhone 15 Pro/Max and newer? Gotta have those latest and greatest chips.
It will be fun to see how it all shakes out. If the AI can’t run most queries on the phone with all this advertising of local processing…there’ll be one hell of a lawsuit coming up.
EDIT: Finished looking for what I thought I remembered…
Additionally, Siri has been locally processed since iOS 15.
https://www.macrumors.com/how-to/use-on-device-siri-iphone-ipad/
Perhaps this is why these features will only be available on iPhone 15 Pro/Max and newer?
I’m not guessing. I linked to the article about the M3 which is much more powerful than the a17 pro in the 15 pro and has the same NPU.
Forgive me, I’m no AI expert to fully compare the needed tokens per second measurement to relate to the average query Siri might handle, but I will say this:
Even in your article, only the largest model ran at 8/tps, others ran much faster, and none of these were optimized for a task, just benchmarking.
Would it be impossible for Apple to be running an optimized model specific to expected mobile tasks, and leverage their own hardware more efficiently than we can, to meet their needs?
I imagine they cut out most worldly knowledge etc/use a lightweight model, which is why there is still a need to link to ChatGPT or Apple for some requests, would this let them trim Siri down to perform well enough on phones for most requests? They also advertised launching AI on M1-2 chip devices, which are not M3-Max either…
The “AI” parts are what they’re saying happens on the device. This isn’t a gotcha.
Literally not what people are talking about. It’s the “AI” part of the task that doesn’t leave the device (unless it prompts to ask chat gpt). Not that it can magically gleam live info without making any request to the web…
Jeeze, fucking… get your shit straight, making me defend Apple… Fucking do better.
Not true. Most if not all requests are handled by apples own models on device or on their own servers. When it does use OpenAI you need to give it permission each time it does.
Admittedly, I bought an Nvidia card for AI. I am part of the problem.
I don’t think it’s a problem, more like a situation. You are not doing anything wrong or stupid, just interested in something new and promising and have the resources to pursue it. Good for you, may you find gold.
Serious Question:
Why is Nvidia AI king and I see nothing of AMD for AI?
I’m an AI Developer.
TLDR: CUDA.
Getting ROCM to work properly is like herding cats.
You need a custom implementation for the specific operating system, the driver version must be locked and compatible, especially with a Workstation / WRX card, the Pro drivers are especially prone to breaking, you need the specific dependencies to be compiled for your variant of HIPBlas, or zLUDA, if that doesn’t work, you need ONNX transition graphs, but then find out PyTorch doesn’t support ONNX unless it’s 1.2.0 which breaks another dependency of X-Transformers, which then breaks because the version of HIPBlas is incompatible with that older version of Python and …
Inhales
And THEN MAYBE it’ll work at 85% of the speed of CUDA. If it doesn’t crash first due to an arbitrary error such as CUDA_UNIMPEMENTED_FUNCTION_HALF
You get the picture. On Nvidia, it’s click, open, CUDA working? Yes?, done. You don’t spend 120 hours fucking around and recompiling for your specific usecase.
Also, you need a supported card. I have a potato going by the name RX 5500, not on the supported list. I have the choice between three rocm versions:
- An age-old prebuilt, generally works, occasionally crashes the graphics driver, unrecoverably so… Linux tries to re-initialise everything but that fails, it needs a proper reset. I do need to tell it to pretend I have a different card.
- A custom-built one, which I fished out of a docker image I found on the net because I can’t be arsed to build that behemoth. It’s dog-slow, due to using all generic code and no specialised kernels.
- A newer prebuilt, any. Works fine for some, or should I say, very few workloads (mostly just BLAS stuff), otherwise it simply hangs. Presumably because they updated the kernels and now they’re using instructions that my card doesn’t have.
#1 is what I’m actually using. I can deal with a random crash every other day to every other week or so.
It really would not take much work for them to have a fourth version: One that’s not “supported-supported” but “we’re making sure this things runs”: Current rocm code, use kernels you write for other cards if they happen to work, generic code otherwise.
Seriously, rocm is making me consider Intel cards. Price/performance is decent, plenty of VRAM (at least for its class), and apparently their API support is actually great. I don’t need cuda or rocm after all what I need is pytorch.
Simple Answer:
Cuda
I think it’s in the pipeline. AMD has bought Xilinx, which builds FPGAs and already had some AI specific cores in their processors. I believe they’re developing that further and integrating it in their GPUs now.
Well Nvidia sure did get rich quick
Nvidia and IA technology are both legit. Those companies need nvidia GPU for their development.
