> Screen size makes little difference for an individual they can just sit closer
This is silly. Most people don’t want to sit in a chair 3 feet from their TV to make it fill more of their visual area. A large number of people are also not watching movies individually. I watch TV with my family far more than I watch alone.
Tell that to every streaming on their tablets sitting on their stomachs. People even watch movies on their phones but they aren’t holding them 15’ away.
No one says the experience of watching on their tablet matches the experience of watching a movie in the theater.
But this isn’t the point. TVs are furniture. People generally have a spot where the TV naturally fits in the room regardless of its size. No one buys a TV and then arranges the rest of their furniture to sit close enough to fill their visual space. If the couch is 8 feet from the TV, it’s 8 feet from the TV.
People watching their tablet on a couch in from of a 55+” TV with a surround sound speaker system says on some level it’s a better experience. I’ve seen plenty of people do this to say it’s common behavior.
> No one buys a TV and then arranges the rest of their furniture to sit close enough to fill their visual space. If the couch is 8 feet from the TV, it’s 8 feet from the TV.
It’s common on open floor plans / large rooms for a couch to end up in a completely arbitrary distance from a TV rather than next to a wall. Further setting up the TV on the width vs length vs diagonal of a room commonly provides two or more options for viewing distance.
> People watching their tablet on a couch in from of a 55+” TV with a surround sound speaker system says on some level it’s a better experience.
It’s a more private/personal experience. Turning on the TV means everyone watches.
> It’s common on open floor plans / large rooms for a couch to end up in a completely arbitrary distance from a TV rather than next to a wall. Further setting up the TV on the width vs length vs diagonal of a room commonly provides two or more options for viewing distance.
You’re essentially arguing that people can arrange their furniture for the best viewing experience. Which is true, but also not what people actually do.
The set of people willing to arrange their furniture for the best movie watching experience in their home are the least likely to buy a small TV.
People still do this while home alone, you’re attacking a straw man.
> least likely to buy a small TV.
People can only buy what actually exists. My point was large TV’s “have been out for decades they really aren’t a replacement” people owning them still went to the moves.
> People still do this while home alone, you’re attacking a straw man.
Maybe? You’re making blind assertions with no data. I have no idea how frequently the average person sits in front of their 60” TV by themselves and watches a movie on their tablet. My guess is not very often but again, I have no data on this.
> My point was large TV’s “have been out for decades they really aren’t a replacement” people owning them still went to the moves.
And we come back to the beginning where your assertion is true but also misleading.
Most people have a large tv in their homes today. Most people did not have this two decades ago, despite then being available.
The stats agree. TV sizes have grown significantly.
> Maybe? You’re making blind assertions with no data.
I’ve seen or talked to more than five people doing it (IE called them, showed up at their house, etc) and even more people mentioned doing the same when I asked. That’s plenty of examples to say it’s fairly common behavior even if I can’t give you exact percentages.
Convince vs using the TV remove was mentioned, but if it’s not worth using the remote it’s definitely not worth going to the moves.
I do. I’ve researched the optimal distance for a smallish tv screen (which fits between the studio monitor stand). I move the tv closer when watching a film, it stands on hacked together wooden box like thing which has some yoga tools and film magazines in it - it has wheels. Crazy stuff.
There is a flipchart like drawing of my daughter covering the tv normally which we flip when watching films.
Living rooms are not that big to start with. I don't think you actually asked anyone's opinion on this! :D
Small TVs are not comfortable to watch. No one I know is okay with getting a smaller TV and moving their sofa closer. That sounds ridiculous. If there's any comfort to this capatilistic economy, it is the availability of technology at throw away prices. Most people would rather spend on a TV than save the money.
As for the theatre being obsolete, I do agree with you, atleast to some extent. I think everyone is right here. All factors combined is what makes going to the theatre not worth the effort for most of the movies. It's just another nice thing, not what it used to be.
Also, the generational difference too. I think teen and adolescents have a lot of ways to entertain themselves. The craze for movies isn't the same as it used to be. And we grew old(er). With age, I've grown to be very picky with movies.
HBO is expensive and most people don't have it. Ergo most people never see or hear about their lower quality content. Only the good stuff that their rich friends rave about.
You not recognizing their shows doesnt mean they are bad. Ive seen most of those and the overwhelming majority are at least solid. I understand netflix's business model, Im just annoyed that theyre buying HBO because they will likely make it worse. Maybe netflix wants more prestige content and will let HBO be HBO but I doubt it.
Yeah until Netflix adds tiered pricing for content and you end up paying more than what Netflix + HBO Max together would have cost because Netflix is the only game in town for that content..
I think like all media consolidation this will send a lot of people back to the seven seas..
Honest question: given all the companies and people working on anti-cheat systems for the last 20+ years of multiplayer video games, don't you think it would all be server-side if it could be, by now?
No, game companies are simply unwilling to pay for the talent and man hours that it takes to police their games for cheaters. Even when they are scanning your memory and filesystem they don't catch people running the latest rented cheat software.
Cheating is a social problem, not a technical issue. Just give the community dedicated server possibility (remember how back in the days games used to ship with dedicated server binaries?) and the community can police for free! Wow!
Yes, I would also prefer that servers were community run as in the hl2 days.
I would still argue that there are technical issues leading to some amount of cheating. In extraction shooters like Hunt Showdown, Escape From Tarkov and a few others, people can run pcie devices that rip player location and other information from the machines memory in order to inject it into an overlay with a 2nd computer, and they do go to these lengths to cheat, giving them a huge advantage. It wouldn't be possible to rip that info from memory for these "ESP cheats" if the server didn't needlessly transmit position information for players that aren't actually visible. IMO this is a technical failure. There are other steps that could be taken as well, which just aren't because they're hard.
Yes, because players want to spend time moderating other players instead of playing the game. Sounds fun!
Community servers literally invented anti-cheat. All current big name anti-cheats started as anti-cheats for community servers. And admins would choose to use them. Game developers would see that and integrate it. Quake 3 Arena even added Punkbuster in a patch.
Modern community servers like FiveM for GTAV, or Face-It and ESEA for CS2 have more anti-cheats, not less.
No, because most companies will make decisions based on time/effort/profitability, and because client-side anticheat is stupid simple and cheap, that's what they go with. Why waste their own server resources, when they can waste the user's?
So it is the company prioritising their bottom line at the expense of their customer's computers. More simply, they move cost from their balance sheet and convert it into risk on the customer's end.
Which is actively customer-abusive behavior and customers should treat it with the contempt it deserves. The fact that customers don't, is what enables such abuse.
This is such a weird take. In an online multiplayer game the cheaters are the risk to the company's bottom line.
If a game is rampant with cheaters, honest paying players stop showing up, and less new players sign up. The relatively small percentage of cheaters cost the company tons of sales and revenue.
It is actively in a company's best interest to do everything they possibly can to prevent cheating, so the idea that intentionally building sub-par anti-cheat is about "prioritising their bottom line" seems totally absurd to me.
Not to mention these abstract "the company" positions completely ignore all the passionate people who actually make video games, and how much most of them care about fair play and providing a good experience to their customers. No one hates cheaters more than game developers.
> because most companies will make decisions based on time/effort/profitability, and because client-side anticheat is stupid simple and cheap, that's what they go with. Why waste their own server resources, when they can waste the user's?
And my comment was a response to that statement. In context of that statement, companies are indeed choosing to prioritise their commercial interests in a way that increases the risk to the computers of their customers.
> Not to mention these abstract "the company" positions completely ignore all the passionate people who actually make video games
Irrelevant. Companies and their employees are two different distinct entities and a statement made about one does not automatically implicate the other. Claiming, for example, that Ubisoft enables a consistent culture of sexual harassment does not mean random employees of that company are automatically labeled as harassers.
Coming to anti-cheat, go ahead and fight them all you want. That's not a problem. Demanding the right to introduce a security backdoor into your customer's machines in order to do that, is the problem.
> pretty much entirely just generalizations of their own experience, but phrased as if they're objective truth
I mean you're describing 90% of blog and forum posts on the Internet here.
This (IMO - so it's not ironic) is the biggest leap most people need to make to become more self-aware and to better parse the world around them: recognizing there is rarely an objective truth in most matters, and the idea that "my truth is not your truth, both can be different yet equally valid" (again in most cases, not all cases).
I think my issue is that the blog post comes across to me as in essence an argument that the person communicating shouldn't be dissuaded by potential reactions to what they say, but it fails to account for the difference between good-faith and bad-faith reactions. There's a huge difference between a bad-faith misinterpretation and a good-faith misunderstanding in my opinion, as the latter seems to come just as often from a failure on the part of the communicator to be clear as from any fault on the listener. It's hard for me not to get the impression that the author either can't or doesn't seen the value in differentiating between those cases based on the fact there's such significant room for improvement in clarifying their views in their paragraph about remote work, which is why I called it out.
A question I don't see addressed in all these articles: what prevents Nvidia from doing the same thing and iterating on their more general-purpose GPU towards a more focused TPU-like chip as well, if that turns out to be what the market really wants.
The big difference is that Google is both the chip designer *and* the AI company. So they get both sets of profits.
Both Google and Nvidia contract TSMC for chips. Then Nvidia sells them at a huge profit. Then OpenAI (for example) buys them at that inflated rate and them puts them into production.
So while Nvidia is "selling shovels", Google is making their own shovels and has their own mines.
on top of that Google is also cloud infrastructure provider - contrary to OpenAI that need to have someone like Azure plug those GPUs and host servers.
The own shovels for own mines strategy has a hidden downside: isolation. NVIDIA sells shovels to everyone - OpenAI, Meta, xAI, Microsoft - and gets feedback from the entire market. They see where the industry is heading faster than Google, which is stewing in its own juices. While Google optimizes TPUs for current Google tasks (Gemini, Search), NVIDIA optimizes GPUs for all possible future tasks. In an era of rapid change, the market's hive mind usually beats closed vertical integration.
Selling shovels may still turn out to be the right move: Nvidia got rich off the cryptocurrency bubble, now they're getting even richer off the AI bubble.
Having your own mines only pays off if you actually do strike gold. So far AI undercuts Google's profitable search ads, and loses money for OpenAI.
So when the bubble pops the companies making the shovels (TSMC, NVIDIA) might still have the money they got for their products and some of the ex-AI companies might least be able to sell standard compliant GPUs on the wider market.
And Google will end up with lots of useless super specialized custom hardware.
It seems unlikely that large matrix multipliers will become useless. If nothing else, Google uses AI extensively internally. It already did in ways that weren’t user-visible long before the current AI boom. Also, they can still put AI overviews on search pages regardless of what the stock market does. They’re not as bad as they used to be, and I expect they’ll improve.
Even if TPU’s weren’t all that useful, they still own the data centers and can upgrade equipment, or not. They paid for the hardware out of their large pile of cash, so it’s not debt overhang.
Another issue is loss of revenue. Google cloud revenue is currently 15% of their total, so still not that much. The stock market is counting on it continuing to increase, though.
If the stock market crashes, Google’s stock price will go down too, and that could be a very good time to buy, much like it was in 2008. There’s been a spectacular increase since then, the best investment I ever made. (Repeating that is unlikely, though.)
How could Google's custom hardware become useless? They've used it for their business for years now and will do so for years into the future. It's not like their hardware is LLM specific. Google cannot lose with their vast infrastructure.
Meanwhile OpenAI et al dumping GPUs while everyone else is doing the same will get pennies on the dollar. It's exactly the opposite to what you describe.
I hope that comes to pass, because I'll be ready to scoop up cheap GPUs and servers.
Same way cloud hardware always risks becoming useless. The newer hardware is so much better you can't afford to not upgrade, e.g. an algorithmic improvement that can be run on CUDA devices but not on existing TPUs, which changes the economics of AI.
> And Google will end up with lots of useless super specialized custom hardware.
If it gets to the point where this hardware is useless (I doubt it), yes Google will have it sitting there. But it will have cost Google less to build that hardware than any of the companies who built on Nvidia.
Right, and the inevitable bubble pop will just slow things down for a few years - it's not like those TPUs will suddenly be useless, Google will still have them deployed, it's just that instead of upgrading to a newer TPU they'll stay with the older ones longer. It seems like Google will experience much less repercussions when the bubble pops compared to Nvidia, OpenAI, Anthropic, Oracle etc. as they're largely staying out of the money circles between those companies.
I think people are confusing the bubble popping with AI being over. When the dot-com bubble popped, it's not like internet infrastructure immediately became useless and worthless.
that's actually not all that true... a lot of fiber that had been laid went dark, or was never lit, and was hoarded by telecoms in an intentional supply constrained market in order to drive up the usage cost of what was lit.
If it was hoarded by anyone, then by definition not useless OR worthless. Also, you are currently on the internet if you're reading this, so the point kinda stands.
Google uses TPUs for its internal AI work (training Gemini for example), which surely isn't decreasing in demand or usage as their portfolio and product footprint increases. So I have a feeling they'd be able to put those TPUs to good use?
Deepmind gets to work directly with the TPU team to make custom modifications and designs specifically for deepmind projects. They get to make pickaxes that are made exactly for the mine they are working.
Everyone using Nvidia hardware has a lot of overlap in requirements, but they also all have enough architectural differences that they won't be able to match Google.
OpenAI announced they will be designing their own chips, exactly for this reason, but that also becomes another extremely capital intensive investment for them.
This also doesn't get into that Google also already has S-tier dataceters and datacenter construction/management capabilities.
Isn’t there a suspicion that OpenAI buying custom chips from another Sam Altman venture is just graft? Wasn’t that one of the things that came up when the board tried to out him?
> Deepmind gets to work directly with the TPU team to make custom modifications
You don't think Nvidia has field-service engineers and applications engineers with their big customers? Come on man. There is quite a bit of dialogue between the big players and the chipmaker.
They do, but they need to appease a dozen different teams from a dozen different labs, forcing nvidia to take general approaches and/or dictating approaches and pigeonholing labs into using those methods.
Deepmind can do whatever they want, and get the exact hardware to match it. It's a massive advantage when you can discover a bespoke way of running a filter, and you can get a hardware implementation of it without having to share that with any third parties. If OpenAI takes a new find to Nvidia, everyone else using Nvidia chips gets it too.
This ignores the way it often works: Customer comes to NVDA with a problem and NVDA comes up with a solution. This solution now adds value for every customer.
In your example, if OpenAI makes a massive new find they aren't taking it to NVDA.
Nvidia has the advantage of a broad base of customers that gives it a lot of information on what needs work and it tries to quickly respond to those deficiencies.
Nvidia doesn't have the software stack to do a TPU.
They could make a systolic array TPU and software, perhaps. But it would mean abandoning 18 years of CUDA.
The top post right now is talking about TPU's colossal advantage in scaling & throughput. Ironwood is massively bigger & faster than what Nvidia is shooting for, already. And that's a huge advantage. But imo that is a replicateable win. Throw gobs more at networking and scaling and nvidia could do similar with their architecture.
The architectural win of what TPU is more interesting. Google sort of has a working super powerful Connection Machine CM-1. The systolic array is a lot of (semi-)independent machines that communicate with nearby chips. There's incredible work going on to figure out how to map problems onto these arrays.
Where-as on a GPU, main memory is used to transfer intermediary results. It doesn't really matter who picks up work, there's lots of worklets with equal access time to that bit of main memory. The actual situation is a little more nuanced (even in consumer gpu's there's really multiple different main memories, which creates some locality), but there's much less need for data locality in the GPU, and much much much much tighter needs, the whole premise of the TPU is to exploit data locality. Because sending data to a neighbor is cheap, sending storing and retrieving data from memory is slower and much more energy intense.
CUDA takes advantage of, relies strongly on the GPU's reliance in main memory being (somewhat) globally accessible. There's plenty of workloads folks do in CUDA that would never work on TPU, on these much more specialized data-passing systolic arrays. That's why TPUs are so amazing, because they are much more constrained devices, that require so much more careful workload planning, to get the work to flow across the 2D array of the chip.
Google's work on projects like XLA and IREE is a wonderful & glorious general pursuit of how to map these big crazy machine learning pipelines down onto specific hardware. Nvidia could make their own or join forces here. And perhaps they will. But the CUDA moat would have to be left behind.
But it's still something grafted onto the existing architecture, of many grids with many blocks with many warps, and lots and lots of coordination and passing intermediary results around. It's only a 4x4x4 unit, afaik. There's still a lot of main memory being used to combine data, a lot of orchestration among the different warps and blocks and grids, to get big matrices crunched.
The systolic array is designed to allow much more fire and forget operations. It's inputs are 128 x 128 and each cell is its own compute node basically, shuffling data through and across (but not transitting a far off memory).
TPU architecture has plenty of limitations. It's not great at everything. But if you can design work to flow from cell to neighboring cell, you can crunch very sizable chunks of data with amazing data locality. The efficiency there is unparalleled.
Nvidia would need a radical change of their architecture to get anything like the massive data locality wins a systolic array can do. It would come with massively more constraints too.
It's not that the TPU is better than an NVidia GPU, it's just that it's cheaper since it doesn't have a fat NVidia markup applied, and is also better vertically integrated since it was designed/specified by Google for Google.
TPUs are also cheaper because GPUs need to be more general purpose whereas TPUs are designed with a focus on LLM workloads meaning there's not wasted silicon. Nothing's there that doesn't need to be there. The potential downside would be if a significantly different architecture arises that would be difficult for TPUs to handle and easier for GPUs (given their more general purpose). But even then Google could probably pivot fairly quickly to a different TPU design.
The T in TPU stands for tensor, which in this context is just a fancy matrix. These days both are optimised for matrix algebra, i.e. general ML workloads, not just LLMs.
If LLMs become unfashionable they’ll still be good for other ML tasks like image recognition.
Nothing in principle.
But Huang probably doesn't believe in hyper specializing their chips at this stage because it's unlikely that the compute demands of 2035 are something we can predict today.
For a counterpoint, Jim Keller took Tenstorrent in the opposite direction. Their chips are also very efficient, but even more general purpose than NVIDIA chips.
How is Tenstorrent h/w more general purpose than NVIDIA chips? TT hardware is only good for matmuls and some elementwise operations, and plain sucks for anything else. Their software is abysmal.
Of course there's the general purpose RISC V CPU controller component but also, each NPU is designed in troikas that have one core reading data in, one core performing the actual kernel work, and the third core forwarding data out.
For users buying H200s for AI workloads, the "ASIC" tensor cores deliver the overwhelming bulk of performance. So they already do this, and have been since Volta in 2017.
To put it into perspective, the tensor cores deliver about 2,000 TFLOPs of FP8, and half that for FP16, and this is all tensor FMA/MAC (comprising the bulk of compute for AI workloads). The CUDA cores -- the rest of the GPU -- deliver more in the 70 TFLOP range.
So if data centres are buying nvidia hardware for AI, they already are buying focused TPU chips that almost incidentally have some other hardware that can do some other stuff.
I mean, GPUs still have a lot of non-tensor general uses in the sciences, finance, etc, and TPUs don't touch that, but yes a lot of nvidia GPUs are being sold as a focused TPU-like chip.
Is it the Cuda cores that run the vertex/fragment/etc shaders in normal GPUs? Where does the ray tracing units fit in? How much of a modern Nvidia GPU is general purpose vs specialized to graphics pipelines?
Except the native width of Tensor Cores are about 8-32 (depending on scalar type), whereas the width of TPUs is up to 256. The difference in scale is massive.
That's pretty much what they've been doing incrementally with the data center line of GPUs versus GeForce since 2017. Currently, the data center GPUs now have up to 6 times the performance at matrix math of the GeForce chips and much more memory. Nvidia has managed to stay one tape out away from addressing any competitors so far.
The real challenge is getting the TPU to do more general purpose computation. But that doesn't make for as good a story. And the point about Google arbitrarily raising the prices as soon as they think they have the upper hand is good old fashioned capitalism in action.
For sure, I did not mean to imply they could do it quickly or easily, but I have to assume that internally at Nvidia there's already work happening to figure out "can we make chips that are better for AI and cheaper/easier to make than GPUs?"
> what prevents Nvidia from doing the same thing and iterating on their more general-purpose GPU towards a more focused TPU-like chip as well, if that turns out to be what the market really wants.
Nothing prevents them per se, but it would risk cannibalising their highly profitable (IIRC 50% margin) higher end cards.
It’s not binary. It’s not existential. What’s at stake for Nvidia is its HUGE profit margins. 5 years from now, Nvidia could be selling 100x as many chips. But its market cap could be a fraction of what it is now if competition is so intense that its making 5% profit margin instead of 90%.
My personal guess would be what drives the cost and size of these chips is the memory bandwidth and the transcievers required to support it. Since transcievers/memory controllers are on the edge of the chip, you get a certain minimum circumference for a given bandwidth, which determines your min surface area.
It might be even 'free' to fill it with more complicated logic (especially one that allows you write clever algorithms that let you save on bandwidth).
Dram alternates between feast and famine; it's the nature of a business when the granularity of investment is so huge (you have a fab or you don't, and they cost billions -maybe trillions by now). So, it will swing back. Unfortunately it looks like maybe 3-5 years on average, from some analysis here:
https://storagesearch.com/memory-boom-bust-cycles.html
(That's just me eyeballing it, feel free to do the math)
I am so glad both top rated and majority of comments on HN finally understands DRAM industry instead of constant DRAM is a cartel that is why things are expensive.
Also worth mentioning DRAM and NAND's profit from Samsung is what keep the Samsung Foundry fighting TSMC. Especially for those who thinks TSMC is somehow a monopoly.
Another things to point out which is not mentioned yet, China is working on both DRAM and NAND. Both LPDDR5 and Stacked NAND are already in production and waiting for yield and scale. Higher Price will finally be perfect timing for them to join the commodity DRAM and NAND race. Good for consumer I suppose, not so good for a lot of other things which I wont go into.
Most of us who've been on Earth for a while know that courts often get it wrong. Even if the particular court decision you mention was correct does not mean that price fixing is the main reason or the underlying reason DRAM prices sometime go up.
And I am 100% sure a lot of other industries in commodities would have been convicted of price fixing if we look into it. And I say this as someone who have witnessed it first hand.
Unfortunately commodity business is not sexy, it doesn't get the press, nor does it get told even in business schools. But a lot of the times these call called price fixing is a natural phenomenon.
I wont even go into what get decided in court doesn't always mean it is right.
I will also add we absolutely want the DRAM and NAND or in fact any industries to make profits, or as much profits as it could. What is far more important is where do they spend not those profits. I didn't look into SK Hynix but both Samsung and Micron spends significant amount of R&D at least try to lower the total production cost of DRAM per GB. We want them to make healthy margin selling DRAM at $1/GB, not losing money and then go bankrupt.
Look man I’m a PhD economist I know the difference between monopolistic competition and collusion. All that price fixing does is transfer monopoly rents from you and me to the DRAM cartel (or whatever industry is doing the price fixing).
The firms can coordinate by agreeing on a strategy they deem necessary for the future of the industry, and that strategy requires significant capital expenditures, and the industry does not get (or does not want) outside investment to fund it, and if any of the firms defects and keeps prices low the others cannot execute on the strategy, so they all agree to raise prices.
Then, after the strategy succeeds, they have gotten addicted to the higher revenues, they do not allow prices to fall as fast as they should, their coordination becomes blatantly illegal, and they have to get smacked down by regulators.
> The firms can coordinate by agreeing on a strategy they deem necessary for the future of the industry.. Then, after the strategy succeeds, they have gotten addicted to the higher revenues, they do not allow prices to fall as fast as they should, their coordination becomes blatantly illegal..
So said and did the infamous Phoebus cartel, to unnaturally "fix" the prices and quality of light bulbs.
For more than a century, one strange mystery has puzzled the world: why do old light bulbs last for decades while modern bulbs barely survive a couple of years?
The answer lies in a secret meeting held in Geneva, Switzerland in 1924, where the world’s biggest light bulb companies formed the notorious Phoebus Cartel.
Their mission was simple but shocking: control the global market, set fixed prices, and most importantly… reduce bulb lifespan.
Before this cartel, bulbs could easily run for 2500+ hours. But after the Phoebus Cartel pact and actions, all companies were forced to limit lifespan to just 1000 hours. More failure meant more purchases. More purchases meant more profit. Any company who refused faced heavy financial penalties.
The most unbelievable proof is the world-famous Livermore Fire Station bulb in California, glowing since 1901. More than 120 years old. Still alive.
While our new incandescent bulbs die in 1–2 years.
Though the Phoebus cartel was dissolved in the 1930s due to government pressure, its impact still shadows modern manufacturing. Planned obsolescence didn’t just begin here… but Phoebus made it industrial.
The Phoebus cartel didn't collude just to make the light bulbs have a shorter lifespan. They upped the standard illumination a bulb emitted so that consumers needed fewer of them to see well. With an incandescent you have a kind of sliding scale of brightness:longevity (with curves on each end that quickly go exponential, hence the longest lasting light bulb that's so dim you can barely read by its light). The brighter the bulb, the shorter the lifespan.
Also, incandescent lightbulb lifespan is reduced by repeated power cycling. Not only is the legendary firehouse bulb very dim, it has been turned off and back on again very few times. Leaving all your lights on all the time would be a waste of power for the average household, and more expensive than replacing the bulbs more frequently.
Also lightbulb dimmers were a thing back in the day, so you could always buy more lightbulbs and lower the brightness of each to take advantage of that exponential curve in lifespan.
I wouldn't be so sure. I've seen analyses making the case that this new phase is unlike previous cycles and DRAM makers will be far less willing to invest significantly in new capacity, especially into consumer DRAM over more enterprise DRAM or HBM (and even there there's still a significant risk of the AI bubble popping). The shortage could last a decade. Right now DRAM makers are benefiting to an extreme degree since they can basically demand any price for what they're making now, reducing the incentive even more.
The most likely direct response is not new capacity, it's older capacity running at full tilt (given the now higher margins) to produce more mature technology with lower requirements on fabrication (such as DDR3/4, older Flash storage tech, etc.) and soak up demand for these. DDR5/GDDR/HBM/etc. prices will still be quite high, but alternatives will be available.
...except current peak in demand is mostly driven by build-out of AI capacity.
Both inference and training workloads are often bottlenecked on RAM speed, and trying to shoehorn older/slower memory tech there would require non-trivial amount of R&D to go into widening memory bus on CPU/GPU/NPUs, which is unlikely to happen - those are in very high demand already.
Even if AI stuff does really need DDR5, there must be lots of other applications that would ideally use DDR5 but can make do with DDR3/4 if there's a big difference in price
I mean, AI is currently hyped, so the most natural and logical assumption is that AI drives these prices up primarily. We need compensation from those AI corporations. They cost us too much.
Do we really think the current level of AI-driven data center demand will continue indefinitely? The world only needs so many pictures of bears wearing suits.
The pop culture perception of AI just being image and text generators is incorrect. AI is many things, they all need tons of RAM. Google is rolling out self-driving taxis in more and more cities for instance.
Congrats on engaging with the facetious part of my comment, but I think the question still stands: do you think the current level of AI-driven data center demand will continue indefinitely?
I feel like the question of how many computers are needed to steer a bunch of self-driving taxis probably has an answer, and I bet it's not anything even remotely close to what would justify a decade's worth of maximum investment in silicon for AI data centers, which is what we were talking about.
Do you know comparatively how much GPU time training the models which run Waymo costs compared to Gemini? I'm genuinely curious, my assumption would be that Google has devoted at least as much GPU time in their datacenters to training Waymo models as they have Gemini models. But if it's significantly more efficient on training (or inference?) that's very interesting.
No, the 10% best scenario return on AI won't make it. The bubble is trying to replace all human labor, which is why it is a bubble in the first place. No one is being honest that AGI is not possible in this manner of tech. And Scale won't get them there.
Doesn't the same factory produce enterprise (i.e. ECC) and consumer (non-ECC) DRAM?
If there is high demand for the former due to AI, they can increase production to generate higher profits. This cuts the production capacity of consumer DRAM, and lead to higher prices in that segment too. Simple supply & demand at work.
Conceptually, you can think of it as "RAID for memory".
A consumer DDR5 module has two 32-bit-wide buses, which are both for example implemented using 4 chips which each handle 8 bits operating in parallel - just like RAID 0.
An enterprise DDR5 module has a 40-bit-wide bus implemented using 5 chips. The memory controller uses those 8 additional bits to store the parity calculated over the 32 regular bits - so just like RAID 4 (or RAID 5, I haven't dug into the details too deeply). The whole magic happens inside the controller, the DRAM chip itself isn't even aware of it.
Given the way the industry works (some companies do DRAM chip production, it is sold as a commodity, and others buy a bunch of chips to turn them into RAM modules) the factory producing the chips does not even know if the chips they have just produced will be turned into ECC or non-ECC. The prices rise and fall as one because it is functionally a single market.
Each memory DIMM/stick is made up of multiple DRAM chip. ECC DIMMs have an extra chip for storing the error correcting parity data.
The bottleneck is with the chips and not the DIMMs. Chip fabs are expensive and time consuming, while making PCBs and placing components down onto them is much easier to get into.
Yes, but if new capacity is also redirected to be able to be sold as enterprise memory, we won't see better supply for consumer memory. As long as margins are better and demand is higher for enterprise memory, the average consumer is screwed.
Does it matter that AI hardware has such a shorter shelf life/faster upgrade cycle? Meaning we may see the ram chips resold/thrown back into the used market quicker than before?
I mean, the only difference we care about is how much of it is actual RAM vs HBM (to be used on GPUs) and how much it costs. We want it to be cheap. So yes, there's a difference if we're competing with enterprise customers for supply.
I don't really understand why every little thing needs to be spelled out. It doesn't matter. We're not getting the RAM at an affordable price anymore.
A LOT of businesses learned during Covid they can make more money by permanently reducing output and jacking prices. We might be witnessing the end times of economies of scale.
The idea is someone else comes in that's happy to eat their lunch by undercutting them. Unfortunately, we're probably limited to China doing that at this point as a lot of the existing players have literally been fined for price fixing before.
It seems more likely that someone else comes in and either colludes with the people who are screwing us to get a piece of the action or gets bought out by one of the big companies who started all this. Since the rare times companies get caught they only get weak slaps on the wrist where they only pay a fraction of what they made in profits (basically just the US demanding their cut) I don't have much faith things will improve any time soon.
Even China has no reason to reduce prices much for memory sold to the US when they know we have no choice but to buy at the prices already set by the cartel.
I expect that if China does start making memory they'll sell it cheap within China and export it at much higher prices. Maybe we'll get a black market for cheap DRAM smuggled out of China though.
I think in part it is a system level response to the widespread just-in-time approach of those businesses' clients. A just-in-time client is very "flexible" on price when supply is squeezed. After that back and forth i think we'll see return to some degree of supply buffering(warehousing) to dampen down the supply levels/price shocks in the pipelines.
Historically, yes. But we haven't had historical demand for AI stuff before. What happens when OpenAI and NVIDIA monopolize the majority of DRAM output?
In a traditional pork cycle there's a relatively large number of players and a relatively low investment cost. The DRAM market in the 1970s and 1980s operated quite similarly: you could build a fab for a few million dollars, and it could be done by a fab which also churned out regular logic - it's how Intel got started! There were dozens of DRAM-producing companies in the US alone.
But these days the market looks completely different. The market is roughly equally divided up between SK Hynix, Micron, and Samsung. Building a fab costs billions and can easily a year of 5 - if not a decade - from start to finish. Responding to current market conditions is basically impossible, you have to plan for the market you expect years from now.
Ignoring the current AI bubble, DRAM demand has become relatively stable - and so has the price. Unless there's a good reason to believe the current buying craze will last over a decade, why would the DRAM manufacturers risk significantly changing their plans and potentially creating an oversupply in the future? It's not like the high prices are hurting them...
Also, current political turbulence makes planning for the long term extremely risky.
Will the company be evicted from the country in 6 months? A year? Will there be 100% tariffs on competitions imports? Or 0%? Will there be an anti-labor gov’t in effect when the investment might mature, or a pro-labor?
The bigger the investment, the longer the investment timeframe, and the more sane the returns - the harder it is to make the investment happen.
High risk requires a correspondingly high potential return.
That everyone has to pay more for current production is a side effect of the uncertainty, because no one knows what the odds are of even future production actually happening, let along the next fancy wiz-bang technology.
No, a wafer is very much not a wafer. DRAM processes are very different from making logic*. You don't just make memory in your fab today and logic tomorrow. But even when you stay in your lane, the industry operates on very long cycles and needs scale to function at any reasonable price at all. You don't just dust off your backyard fab to make the odd bit of memory whenever it is convenient.
Nobody is going to do anything if they can't be sure that they'll be able to run the fab they built for a long time and sell most of what they make. Conversely fabs don't tend to idle a lot. Sometimes they're only built if their capacity is essentially sold already. Given how massive the AI bubble is looking right now, I personally wouldn't expect anyone to make a gamble building a new fab.
* Someone explained this at length on here a while ago, but I can't seem to find their comment. Should've favorited it.
Sure, yes the cost of producing a wafer is fixed. Opex didn’t change that much.
Following your reasoning, which is common in manufacturing, the capex needed is already allocated.
So, where does the 2x price hike come from if not supply/demand?
The cost to produce did not go up 100%, or even 20%
Actually, DRAM fabs do get scaled down, very similar to the Middle East scaling down oil production.
> So, where does the 2x price hike come from if not supply/demand?
It absolutely is supply/demand. Well, mostly demand, since supply is essentially fixed over shorter time spans. My point is that "cost per square mm [of wafer]" is too much of a simplification, given that it depends mostly on the specific production line and also ignores a lot of the stuff going on down the line. You can use to look at one fab making one specific product in isolation, but it's completely useless to compare between them or when looking at the entire industry.
It's a bit like saying the cost of cars is per gram of metal used. Sure, you can come up with some number, but what is it really useful for?
DRAM/flash fab investment probably did get scaled down due to the formerly low prices, but once you do have a fab it makes sense to have it produce flat out. Then that chunk of potential production gets allocated into DRAM vs. HBM, various sorts of flash storage etc. But there's just no way around the fact that capacity is always going to be bottlenecked somehow, and a lot less likely to expand when margins are expected to be lower.
> Sometimes they're only built if their capacity is essentially sold already.
"Hyperscalers" already have multi-year contracts going. If the demand really was there, they could make it happen. Now it seems more like they're taking capacity from what would've been sold on the spot or quarterly markets. They already made their money.
Well, I've experienced both to some degree in the past. The previous long time with very similar hardware performance was when PCs were exorbitantly expensive and commodore 64 was the main "home computer" (at least in my country) over the latter 80s and early 90s.
That period of time had some benefits. Programmers learned to squeeze absolutely everything out of that hardware.
Perhaps writing software for today's hardware is again becoming the norm rather than being horribly inefficient and simply waiting for CPU/GPU power to double in 18 months.
I was lucky. I built my am5 7950x Ryzen pc with 2x48gb ddr5 2 years ago. I just bought 4x48gb kit a month ago with an idea to build another home server with the old 2*48gb kit.
Today my old g.skill 2x48gb kit costs Double what I paid for the 4x48gb.
Furthermore I bought two used rtx3090 (for AI) back then. A week ago I bought a third one for the same price... ,(for vram in my server).
> It's kinda sad when you grow up in a period of rapid hardware development and now see 10 years going by with RAM $/GB prices staying roughly the same.
But you’re cherry picking prices from a notable period of high prices (right now).
If you had run this comparison a few months ago or if you looked at averages, the same RAM would be much cheaper now.
I think that goes to show that official inflation benchmarks are not very practical / useful in terms of buckets of things that people actually buy or desire. If the bucket that measured inflation included computer parts (GPUs?), food and housing - i.e. all that the thing that a geek really needs inflation would be wayy higher...
> If the bucket that measured inflation included computer parts (GPUs?), food and housing - i.e. all that the thing that a geek really needs inflation would be wayy higher...
A house is $500,000
A GPU is $500
You could put GPUs into the inflation bucket and it wouldn’t change anything. Inflation trackers count cost of living and things you pay monthly, not one time luxury expenses every 4 years that geeks buy for entertainment.
Also need to account for the dollar decline vs other currencies (which yes is possibly somewhat factored into dollar inflation so you'd have to do the inflation calculation in Euros then convert to dollars accounting for the decline in value).
I just gave up and built an AM4 system with a 3090 because I had 128G of ddr4 udimms on hand the whole build was for less than just the memory would have cost for an AM5/ddr5 build.
Really wish that I could replace my old skylake-x system but even ddr4 rdimms for an older xeon are crazy now let alone ddr5. Unfortunately I need slots for 3xTitan V's for the 7.450 TFLOPS each of FP64. Even the 5090 only does 1.637 TFLOPS for FP64, so just hopping that old system keeps running.
If you don't need full ieee-754 double precision, ozaki scheme (emulation with tensor cores) might do the trick. It's been added (just a little bit) to cublas recently.
My 64gb DDR5 kit started having stability issues running XMP a few weeks out of warranty. I bought it two years ago. Looked into replacing it and the same kit is now double the price. Bumping the voltage a bit and having better cooling gets it through memtest thankfully. The fun of building your own computer is pretty much gone for me these days.
Such is life. I suggest finding a less volatile hobby, like crocheting.
Actually, the textile market is pretty volatile in the US these days with Joan's out of business. Pick a poison, I guess? There's little room for stability in a privately-owned-world.
Last night, while writing a LaTeX article, with Ollama running for other purposes, Firefox with its hundreds of tabs, multiple PDF files open, my laptop's memory usage spiked up to 80GB RAM usage... And I was happy to have 128GB. The spike was probably due to some process stuck in an effing loop, but the process consuming more and more RAM didn't have any impact on the system's responsiveness, and I could calmly quit VSCode and restart it with all the serenity I could have in the middle of the night.
Is there even a case where more RAM is not really better, except for its cost?
> Is there even a case where more RAM is not really better, except for its cost?
It depends. It takes more energy, which can be undesirable in battery powered devices like laptops and phones. Higher end memory can also generate more heat, which can be an issue.
But otherwise more RAM is usually better. Many OS's will dynamically use otherwise unused RAM space to cache filesystem reads, making subsequent reads faster and many databases will prefetch into memory if it is available, too.
That said, I wholeheartedly agree that "more RAM less problems". The only case I can think of when it's not strictly better to have more is during hibernation (cf sleep) when the system has to write 128GB of ram to disk.
I've got ~5k+ tabs, and I've also seen basically zero crashes in the last decade. I'm on Macos, not very many extensions though one of them is Sidebery (and before that Tree Style Tabs) which seems to slow things down quite a lot.
I likely don't need all the tabs. Some were opened only because they might be useful or interesting. Others get opened because they cover something I want to dig into further later on, but in this case it's the buildup of multiple crash>restore cycles. Eventually I'll get to each tab and close it or save the URL separately until it's back to 0, but even in that process new tabs/windows get opened so it can take time.
On consumer chips the more memory modules you have the slower they all run. I.e. if you have a single module of DDR5 it might run at 5600MHz but if you have four of them they all get throttled to 3800MHz.
Mainboards have two memory channels so you should be able to reach 5600mhz on both and dual slot mainboards have better routing than quad slot mainboards. This means the practical limit for consumer RAM is 2x48GB modules.
Intel's consumer processors (and therefore the mainboards/chipsets) used to have four memory channels, but around the year 2020 this was suddenly limited to two channels since the 12th generation (AMD's consumer processors had always two channels, with exception of Threadriper?).
However this does not make sense, as for more than a decade the processors have only grown increasing the number of threads, therefore two channels sounds like a negligent and deliberately imposed bottleneck to access the memory if one use all those threads (Lets say 3D render, Video postproduction, Games, and so on).
And if one want four channels to surpass such imposed bottleneck, the mainboards that nowadays have four channels don't contemplate consumer use, therefore they have one or two USB connectors with three or four LAN connectors at prohibitive prices.
We are talking about consumer quad-channel DDR4 machines ten years old, wildly spread, keeps being competent compared with current consumers ones, if not better. It is like if all were frozen along this years (and what remains to be seen with such pattern).
Now it is rumoured that AMD may opt for four channels for its consumer lines due to the increased number of pin connectors (good news if true).
It is a bad joke what the industry is doing to customers.
> Intel's consumer processors (and therefore the mainboards/chipsets) used to have four memory channels, but around the year 2020 this was suddenly limited to two channels since the 12th generation (AMD's consumer processors had always two channels, with exception of Threadriper?).
You need to re-check your sources. When AMD started doing integrated memory controllers in 2003, they had Socket 754 (single channel / 64-bit wide) for low-end consumer CPUs and Socket 940 (dual channel / 128-bit wide) for server and enthusiast destkop CPUs, but less than a year later they introduced Socket 939 (128-bit) and since then their mainstream desktop CPU sockets have all had a 128-bit wide memory interface. When Intel later also moved their memory controller from the motherboard to the CPU, they also used a 128-bit wide memory bus (starting with LGA 1156 in 2008).
There's never been a desktop CPU socket with a memory bus wider than 128 bits that wasn't a high-end/workstation/server counterpart to a mainstream consumer platform that used only a 128-bit wide memory bus. As far as I can tell, the CPU sockets supporting integrated graphics have all used a 128-bit wide memory bus. Pretty much all of the growth of desktop CPU core counts from dual core up to today's 16+ core parts has been working with the same bus width, and increased DRAM bandwidth to feed those extra cores has been entirely from running at higher speeds over the same number of wires.
What has regressed is that the enthusiast-oriented high-end desktop CPUs derived from server/workstation parts are much more expensive and less frequently updated than they used to be. Intel hasn't done a consumer-branded variant of their workstation CPUs in several generations; they've only been selling those parts under the Xeon branding. AMD's Threadripper line got split into Threadripper and Threadripper PRO, but the non-PRO parts have a higher starting price than early Threadripper generations, and the Zen 3 generation didn't get non-PRO Threadrippers.
At some point the best "enthusuast-oriented HEDT" CPU's will be older-gen Xeon and EPYC parts, competing fairly in price, performance and overall feature set with top-of-the-line consumer setups.
Based on historical trends, that's never going to happen for any workloads where single-thread performance or power efficiency matter. If you're doing something where latency doesn't matter but throughput does, then old server processors with high core counts are often a reasonable option, if you can tolerate them being hot and loud. But once we reached the point where HEDT processors could no longer offer any benefits for gaming, the HEDT market shrank drastically and there isn't much left to distinguish the HEDT customer base from the traditional workstation customers.
I'm not going to disagree outright, but you're going to pay quite a bit for such a combination of single-thread peak performance and high power efficiency. It's not clear why we should be regarding that as our "default" of sorts, given that practical workloads increasingly benefit from good multicore performance. Even gaming is now more reliant on GPU performance (which in principle ought to benefit from the high PCIe bandwidth of server parts) than CPU.
I said "single-thread performance or power efficiency", not "single-thread performance and power efficiency". Though at the moment, the best single-thread performance does happen to go along with the best power efficiency. Old server CPUs offer neither.
> Even gaming is now more reliant on GPU performance (which in principle ought to benefit from the high PCIe bandwidth of server parts)
A gaming GPU doesn't need all of the bandwidth available from a single PCIe x16 slot. Mid-range GPUs and lower don't even have x16 connectivity, because it's not worth the die space to put down more than 8 lanes of PHYs for that level of performance. The extra PCIe connectivity on server platforms could only matter for workloads that can effectively use several GPUs. Gaming isn't that kind of workload; attempts to use two GPUs for gaming proved futile and unsustainable.
You have a processor with more than eight threads, at same bus bandwidth, what do you choose, dual channeled or four channeled processor.
That number of threads will hit a bottleneck accessing only through to channels of memory.
I don't understand why you brought up the topic of single-threading in your response to the user, given that processors reached a frequency limit of 4 GHz, and 5 GHz with overclocking, a decade ago. This is why they increased the number of threads, but if they reduce the number of memory channels for consumer/desktop...
Larger capacity is usually slower though. The fastest ram is typically 16 or 32 capacity.
The OP is talking about a specific niche of boosting single thread performance. It’s common with gaming pcs since most games are single thread bottlenecked. 5% difference may seem small, but people are spending hundreds or thousands for less gains… so buying the fastest ram can make sense there.
If you are working on an application that has several services (database, local stack, etc.) as docker containers, those can take up more memory. Especially if you have large databases or many JVM services, and are running other things like an IDE with debugging, profiling, and other things.
Likewise, if you are using many local AI models at the same time, or some larger models, then that can eat into the memory.
I've not done any 3D work or video editing, but those are likely to use a lot of memory.
Having recently updated to 192gb from 96gb I'm pretty happy. I run many containers, have 20 windows of vscode and so on. Plus ai inference on CPU when 48gb vram is not enough.
Interesting that Samsung put their prices up 60% today, and a retailer who bought their stock at the old price feels compelled to put their prices up 2.5x.
When the AI bubble bursts we can get back to the old price
The cost of inventory on the shelves basically doesn’t matter. The only thing that matters is the market rate.
If those retailers didn’t increase their prices when the price hike was announced, anyone building servers would have instantly purchased all of the inventory anyway at the lower prices, so there wouldn’t actually have been weeks of low retail RAM prices for everyone.
Every once in a while you can catch a retailer whose pricing person missed the memo and forgot to update the retail price when the announcement came out. They go out of stock very rapidly.
> If those retailers didn’t increase their prices when the price hike was announced, anyone building servers would have instantly purchased all of the inventory anyway at the lower prices
But that retailer would have made a lot of money in a very short time.
In the scenario where they don't raise prices, they sell out immediately. In the scenario where they do raise prices, it's too expensive so you don't buy it. In the scenario where they keep prices low, and do a lottery to see who can buy them, you don't get picked.
No matter what, you are not getting those modules at the old price. There are few things that trip up people harder than this exact scenario, and it happens everywhere. Concert tickets, limited releases, water during crises, hot Christmas gift, pandemic GPUs, etc.
Once understood you can stop getting mad over it like it's some conspiracy. It's fundamental and natural market behavior.
I guess I lucked out. I bought a 768GB workstation (with 9995wx CPU and rtx 6000 Pro Blackwell GPU) in August. 96GB modules were better value than 128GB. That build would be a good bit pricier today looks like.
Yeah you are not alone here being annoyed. I think we need to penalise all who drive the prices up - that includes the manufacturers but also AI companies etc...
Those price increases are not normal at all. I understand that most of it still comes from market demands but this is also skewing the market now in unfair manners. Such increases smell of criminal activity too.
> I think we need to penalise all who drive the prices up - that includes the manufacturers but also AI companies etc...
You want to penalize companies for buying things and penalize companies for selling things are market rate?
There are a lot of good examples through history about how central planning economics and strict price controls do not lead to good outcomes. The end result wouldn’t be plentiful cheap RAM for you. The end result would be no RAM for you at all because the manufacturers choose to sell to other countries who understand basic economics.
I think there's a case for banning the sale of services well below the marginal cost of supplying that service - loss leaders, or "dumping" - when it's done on such a scale as AI marketing.
I think it's somewhat useful long term advice, and I would add that parts prices tend to be asynchronous.
Building a PC in a cost efficient manner generally requires someone to track parts prices over years, buy parts at different times, and buy at least a generation behind.
The same applies to many other markets/commodities/etc...
That is terrible. Only less than half year! If all countries keep building AI centers, it will talk a long time for the price to be back to reasonable status.
Huh, I had not connected those (hypothetical) dots, but I could see it..
Or maybe there's 2 next-gen Steam Decks, an ultra-portable ARM-based one that's as small as can be, and a more performant x86 one with AMD's next-gen APU...
Yeah, there's a real gap in the market for a relatively compact handheld which can play low-spec PC games. The AMD-based handheld PCs available today are all pretty chunky.
You're right, I was mistaken, I've seen some Youtubers playing games on it, but they use GameHub to run Steam games, somehow I thought it was running Steam OS.
There's plenty of "relatively compact" ARM-based handhelds targeting the retro market already, but many of them are shipping with a pitiful amount of RAM (1GB or so) making them an absolute non-starter, while others (selling for significantly higher prices) run crappy Android-based OS's that will never be updated. There is a gap in the market for a good-quality retro-like handheld shipping with a Linux-native OS (or even just enabling one to be installed trivially after-the-fact, with everything working and no reliance on downstream hacked-together support packages).
There are handhelds for less than 200$ with very good screens and controls that can play all of these. Not to mention stream (via Steam or other software) from your PC!
If they did an AMD CPU using the same TSMC node that Apple uses for Arm CPUs it wouldn't be that much less power efficient and have much great compatibility.
They would realistically gain the most efficiency by getting Nvidia to design a modern super power efficient GPU like what was used in the original switch and Nvidia Shield. AMD GPUs can be great for desktop gaming but in terms of power efficiency to performance ratio Nvidia is way ahead
An AMD CPU and Nvidia GPU might be a hard thing to actually negotiate however given that AMD is big in the GPU space as well. As far as I know most "APU" aren't really that special and just a combo of GPU and CPU
APUs have the GPU and CPU on the same package, or sometimes even the same die (with tiling). If there was to be an Nvidia GPU and AMD CPU type system, they would have to be separate packages.
> Apple demonstrated to the world that it can be extremely fast and sip power.
Kinda. Apple silicon sips power when it isn't being used, but under a heavy gaming load it's pretty comparable to AMD. People report 2 hours of battery life playing cyberpunk on Macs, which matches the steam deck. It's only in lighter games where Apple pulls ahead significantly, and that really has nothing to do with it being ARM.
Sure, but Apple isn't selling their silicon to anyone else and Valve, successful as they are, don't have Apples money and economy-of-scale to throw at designing their own state-of-the-art CPU/GPU cores and building them on TSMCs state-of-the-art processes. Valve will have to roll with whatever is available on the open market, and if that happens to suck compared to Apples stuff then tough shit.
I'm definitely dreaming but I think it could be a win-win situation if Apple decided to licence its chips to Valve: the resulting handheld and VR headsets would be power/efficiency monsters and PC devs would finally have a good reason to target ARM, which could finally bring native PC gaming to MACs.
This doesn't feel like anything Apple has done in modern times. The last thing I remember them licensing was the iPod+HP from 2004-2005. Apple barely does enterprise support; they're very focused on selling their products to consumers and I don't think they're at all interested in selling CPUs to others.
Apple waffles and sometimes talks about gaming on Macs, but they lack the commitment that is needed. A lot of people like to buy a game and continue playing it for years, even after the developer went on to something else; or to buy years old games on sale. But you can't expect to run a mac os app compiled three to five years ago that is media and gpu heavy intensive on today's mac os. There will have been mandatory developer updates and it won't work.
Win32 is the only stable desktop ABI... and games need a stable ABI.
The Nintendo Switch already provides >160 million reasons for gamedevs to care about native ARM support, but that hasn't moved the needle for the Mac. Being ARM-based is the least of its problems, the problem is that it's a relatively tiny potential market owned by a company which is actively hostile to the needs of game developers.
The switch is underpowered to the point that most A(AA) games cannot run on it without a ton of effort and compromise, an M chip powered device would be a different story. But anyway it's never going to happen, just daydreaming about a perfect gaming setup...
Valve isn't in the position to make their own best-in-class ARM chips like Apple is. They'd have to find a vendor which can sell them the chip they need.
Which SoC on the market do you think fits the bill?
Large 4k TVs being this accessible/affordable for most households has not been an option for "decades"..
reply