The first computer I ever used had 512K, which was a great deal back then, and by the time I was old enough to learn to type it had 10MB disk too.
My childhood best friend and neighbour had the same kind of computer except they only had something like 384K of memory and I tried to convince them their computer was broken when it didn't count up all the way.
Mine had 4K of RAM and an 800 KHz CPU - and I was living in the future, man. No way I could use that much memory. After all I had to type in whatever program I wanted to run every time I turned it on. Then I got a manual audio cassette recorder and thought "Woah, I don't think it gets better than this!"
The point of my GP post was that due to being one of the world's biggest and longest-term buyers, Apple is already paying very close to actual manufacturing costs + amortized capex because RAM is an undifferentiated commodity. Owning the factory themselves doesn't reduce the actual manufacturing cost + amortized capex that Apple would have to pay their own factory. Apple is already buying RAM at the lowest possible margins. It's similar math to deciding whether to spend your own cash or get a loan. If the loan's interest rate is low enough, it's better take the loan and put your cash to work where it can return a higher margin. And at the incredibly low margins Apple pays for RAM, keeping that cash in long-term investments will actually earn more money than putting it into building RAM factories.
If Apple could go back in time 3.5 years and decide to build their own factory, that would put them in a great position today. But deciding to do it now won't increase their supply 3.5 years from now more than just increasing their long-term orders with existing suppliers. Those suppliers will start building new factories based on Apple's increased orders and they'll do it faster and cheaper than Apple can because they don't have to build some factories in the U.S. for political reasons or worry as much about environmental regulation, permitting and ensuring Apple employees in Penang get benefits similar to employees in Cupertino.
Isn't one of the points of the article that memory manufacturers leave demand unmet for their own financial safety? In which case, nobody (including Apple) is paying close to manufacturing costs. There isn't enough memory to go around and prices are extremely inflated.
You're talking about the "best" things Apple could do with their money, in terms of investment returns, but I think that misses the point that Apple literally can't buy enough memory at any price.
> that misses the point that Apple literally can't buy enough memory at any price.
They can't buy enough today. I think I already explained this as well as I can in my second paragraph above. You seem to not be appreciating that every decision in this business has a 3.5+ year latency. And 3.5 years ago when Apple made the decisions they're living with now, Micron was selling their furniture (euphemistically speaking). Sinking billions into building RAM fabs would not only have gotten you laughed out of the boardroom, Apple shareholders would have rioted (for all the logical reasons I laid out in my prior two posts). The only scenario where the prudently balanced decision Apple made to not vertically integrate RAM manufacturing looks bad is the very unlikely scenario that actually happened this one time - but that 'bad look' is only temporary because the situation will probably look different 12 months from now (which is less than a third-of-a-fab-decision away)).
Back when I first became a strategist for a public F500 tech company whose products you probably use often, a very wise man took me to dinner and counseled me to never post mortem my decisions on the outcomes, but only on the decision process. In other words, knowing what I knew when I made the decision, did I choose the option most statistically likely to get the desired result - regardless if it worked or failed that time? In highly uncertain games, some bets don't pay off. In my work, if 60% of my decisions came out positively, I'd have been the greatest of all time (they weren't that quite that high). If strategists don't think this way we end up leading our companies to doom by "chasing black swans" (aka unlikely outlier outcomes).
> memory manufacturers leave demand unmet
That's not their plan or desire - it's just the inevitable result of trying to predict both future demand and future capacities of unbuilt fabs on new nodes (every new node is an adventure). Both are rough estimates with bell-curve probabilities and wide error bars. You might imagine the Chief RAM Strategist drags the center of the bell curve so the big bump in the middle is right over their best guess of what the fab yields and market demand will actually be three years from now - perfectly slicing the odds in the probabilistic middle. But they don't. Instead, being a smart, experienced strategist, they slide the bell curve a little bit to the low-side - because very profitably selling everything you can possibly make and regretting the 5 or 10% of demand you left unmet is a far, FAR better (and more survivable) problem to have than sitting on 5 or 10% unsold excess capacity from expensive fab space you paid to build but can't monetize. That extra capacity will often force you to take lower margins on ALL your capacity to ensure you sell through the extra 10%. This is how you speed run becoming an ex-strategist, sometimes of an ex-company.
I'm no business expert and Apple is of course in a unique position, but owning your own fabs has rarely worked out long term. They require eye watering amounts of CAPEX that needs to be amortized over a timeframe that's longer than apple's products. Today's bleeding edge fabs become tomorrow's "cheap" fabs that pump out chips that don't need to be bleeding edge for the components that go into everyday products like microwaves, cars, etc.
One of the reasons Intel fell behind is that they couldn't give access to their competitors for business reasons, and therefore could never scale as high as TSMC could.
There are many other reasons, but accounting is a huge one. Unless there is a huge ROI or something else we don't otherwise know, I don't see Apple adding such expensive deprecating assets onto their books as chip fabs.
If 256GB of RAM enables them to run on-device AI models that (for reasons) are a key feature differentiator?
Personally, I think there's no way memory heavy inference moves on-device (vs cloud) due to the economics, but it's not impossible technology + platforms go that way for currently unforeseeable reasons.
I think there’s a realistic chance consumer inference moves on-device. I think it really depends on marketing.
My non-tech friends and family would probably be served perfectly fine by local models today, if they had a working web search tool. Their queries are often “soft” and don’t have an exact answer. My mom and aunt used it to pick a hairstyle, my mom used it to get an image of what a room would look like with particular drapes in it, etc. Stuff I think mid-sized local models like Gemma or smaller Qwens could do without issue. They just don’t have a device that will run them.
Businesses won’t move. They need a huge context so they can stuff a bunch of Confluence pages in it and 300 tools and it needs to read an entire codebase and yada yada. The hardware depreciation and electricity will probably make it a net zero or even cost more than paying for API access.
My argument is predicated on the assumption that mainstream hardware manufacturers will copy the way Apple and Framework have made system memory usable for inference.
In that world, a) we are already at or close to having enough memory in local devices to do inference locally, and b) that memory isn't inference-specific and can be utilized for other things. Most devices come with enough memory to do some level of inference, and some come with plenty (eg a gaming desktop probably has 32GB+ of RAM in it).
You aren't going to run Kimi on it, but I think the reality for a lot of consumer inference is that it doesn't need to be. It's going to be a lot of things that are soft, and easily answered by a search API, so the LLM really just needs to be able to skim and summarize. Going a step further, we may even see some kind of hybrid approach where a local OpenRouter kind of thing decides whether the task is soft enough to do locally with models that fit in RAM or if it needs to be farmed out to a PaaS provider.
Right. I’m not arguing that Apple wouldn’t offer a 256GB model if they could make money doing it; I’m puzzled as to why they wouldn’t offer several lower-spec models as the entry-level into and then progressive upgrades within that line, since only some people need that 256GB feature differentiator of running frontier-level models on their MacBook Pro.
In the same world 8GB used to be unfathomably huge not that long ago?
Hell, an 8GB hard drive was unfathomable when I was a kid in the 90s. I remember getting a 30 megabyte drive for our Mac LC.
The first computer I ever used had 512K, which was a great deal back then, and by the time I was old enough to learn to type it had 10MB disk too.
My childhood best friend and neighbour had the same kind of computer except they only had something like 384K of memory and I tried to convince them their computer was broken when it didn't count up all the way.
> The first computer I ever used had 512K
Mine had 4K of RAM and an 800 KHz CPU - and I was living in the future, man. No way I could use that much memory. After all I had to type in whatever program I wanted to run every time I turned it on. Then I got a manual audio cassette recorder and thought "Woah, I don't think it gets better than this!"
And that Mac LC only had a max of 10MB of ram.
The same world where a MacBook Pro G4 12" came base level with 256MB of RAM.
The same world where a classic Mac came with 128KB of RAM.
We might someday live in a world where entry-level is 256TB of RAM.
That is the timeline I want to live in. Probably.
A world where Apple has invested in their own fabs, so they can sell devices with drastically more RAM than their competition at entry-level prices.
The point of my GP post was that due to being one of the world's biggest and longest-term buyers, Apple is already paying very close to actual manufacturing costs + amortized capex because RAM is an undifferentiated commodity. Owning the factory themselves doesn't reduce the actual manufacturing cost + amortized capex that Apple would have to pay their own factory. Apple is already buying RAM at the lowest possible margins. It's similar math to deciding whether to spend your own cash or get a loan. If the loan's interest rate is low enough, it's better take the loan and put your cash to work where it can return a higher margin. And at the incredibly low margins Apple pays for RAM, keeping that cash in long-term investments will actually earn more money than putting it into building RAM factories.
If Apple could go back in time 3.5 years and decide to build their own factory, that would put them in a great position today. But deciding to do it now won't increase their supply 3.5 years from now more than just increasing their long-term orders with existing suppliers. Those suppliers will start building new factories based on Apple's increased orders and they'll do it faster and cheaper than Apple can because they don't have to build some factories in the U.S. for political reasons or worry as much about environmental regulation, permitting and ensuring Apple employees in Penang get benefits similar to employees in Cupertino.
Isn't one of the points of the article that memory manufacturers leave demand unmet for their own financial safety? In which case, nobody (including Apple) is paying close to manufacturing costs. There isn't enough memory to go around and prices are extremely inflated.
You're talking about the "best" things Apple could do with their money, in terms of investment returns, but I think that misses the point that Apple literally can't buy enough memory at any price.
> that misses the point that Apple literally can't buy enough memory at any price.
They can't buy enough today. I think I already explained this as well as I can in my second paragraph above. You seem to not be appreciating that every decision in this business has a 3.5+ year latency. And 3.5 years ago when Apple made the decisions they're living with now, Micron was selling their furniture (euphemistically speaking). Sinking billions into building RAM fabs would not only have gotten you laughed out of the boardroom, Apple shareholders would have rioted (for all the logical reasons I laid out in my prior two posts). The only scenario where the prudently balanced decision Apple made to not vertically integrate RAM manufacturing looks bad is the very unlikely scenario that actually happened this one time - but that 'bad look' is only temporary because the situation will probably look different 12 months from now (which is less than a third-of-a-fab-decision away)).
Back when I first became a strategist for a public F500 tech company whose products you probably use often, a very wise man took me to dinner and counseled me to never post mortem my decisions on the outcomes, but only on the decision process. In other words, knowing what I knew when I made the decision, did I choose the option most statistically likely to get the desired result - regardless if it worked or failed that time? In highly uncertain games, some bets don't pay off. In my work, if 60% of my decisions came out positively, I'd have been the greatest of all time (they weren't that quite that high). If strategists don't think this way we end up leading our companies to doom by "chasing black swans" (aka unlikely outlier outcomes).
> memory manufacturers leave demand unmet
That's not their plan or desire - it's just the inevitable result of trying to predict both future demand and future capacities of unbuilt fabs on new nodes (every new node is an adventure). Both are rough estimates with bell-curve probabilities and wide error bars. You might imagine the Chief RAM Strategist drags the center of the bell curve so the big bump in the middle is right over their best guess of what the fab yields and market demand will actually be three years from now - perfectly slicing the odds in the probabilistic middle. But they don't. Instead, being a smart, experienced strategist, they slide the bell curve a little bit to the low-side - because very profitably selling everything you can possibly make and regretting the 5 or 10% of demand you left unmet is a far, FAR better (and more survivable) problem to have than sitting on 5 or 10% unsold excess capacity from expensive fab space you paid to build but can't monetize. That extra capacity will often force you to take lower margins on ALL your capacity to ensure you sell through the extra 10%. This is how you speed run becoming an ex-strategist, sometimes of an ex-company.
I'm no business expert and Apple is of course in a unique position, but owning your own fabs has rarely worked out long term. They require eye watering amounts of CAPEX that needs to be amortized over a timeframe that's longer than apple's products. Today's bleeding edge fabs become tomorrow's "cheap" fabs that pump out chips that don't need to be bleeding edge for the components that go into everyday products like microwaves, cars, etc.
One of the reasons Intel fell behind is that they couldn't give access to their competitors for business reasons, and therefore could never scale as high as TSMC could.
There are many other reasons, but accounting is a huge one. Unless there is a huge ROI or something else we don't otherwise know, I don't see Apple adding such expensive deprecating assets onto their books as chip fabs.
Why would they sell a device with 256GB of RAM as the lowest-spec device rather than making 8 32GB or 16 16GB machines as their entry-level?
Apple’s not exactly famous for their low pricing on spec upgrades nor competing based on being the price leader…
If 256GB of RAM enables them to run on-device AI models that (for reasons) are a key feature differentiator?
Personally, I think there's no way memory heavy inference moves on-device (vs cloud) due to the economics, but it's not impossible technology + platforms go that way for currently unforeseeable reasons.
I think there’s a realistic chance consumer inference moves on-device. I think it really depends on marketing.
My non-tech friends and family would probably be served perfectly fine by local models today, if they had a working web search tool. Their queries are often “soft” and don’t have an exact answer. My mom and aunt used it to pick a hairstyle, my mom used it to get an image of what a room would look like with particular drapes in it, etc. Stuff I think mid-sized local models like Gemma or smaller Qwens could do without issue. They just don’t have a device that will run them.
Businesses won’t move. They need a huge context so they can stuff a bunch of Confluence pages in it and 300 tools and it needs to read an entire codebase and yada yada. The hardware depreciation and electricity will probably make it a net zero or even cost more than paying for API access.
The economic argument in favor of cloud inference: higher utilization is always going to have a ROI for inference hardware.
But maybe that hardware becomes so commoditized that it's not difficult to obtain / stuff in a box.
My argument is predicated on the assumption that mainstream hardware manufacturers will copy the way Apple and Framework have made system memory usable for inference.
In that world, a) we are already at or close to having enough memory in local devices to do inference locally, and b) that memory isn't inference-specific and can be utilized for other things. Most devices come with enough memory to do some level of inference, and some come with plenty (eg a gaming desktop probably has 32GB+ of RAM in it).
You aren't going to run Kimi on it, but I think the reality for a lot of consumer inference is that it doesn't need to be. It's going to be a lot of things that are soft, and easily answered by a search API, so the LLM really just needs to be able to skim and summarize. Going a step further, we may even see some kind of hybrid approach where a local OpenRouter kind of thing decides whether the task is soft enough to do locally with models that fit in RAM or if it needs to be farmed out to a PaaS provider.
Right. I’m not arguing that Apple wouldn’t offer a 256GB model if they could make money doing it; I’m puzzled as to why they wouldn’t offer several lower-spec models as the entry-level into and then progressive upgrades within that line, since only some people need that 256GB feature differentiator of running frontier-level models on their MacBook Pro.
And I'm saying, if 256GB of memory is a requirement for running customer-expected local models (and local models are preferred for some reason).
Think past on-device inference... imagine what on-device training could do. And that would need a lot of RAM.