Sam Altman Thinks You're Wasting DRAM
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1. Local inference can cause a large under-utilization of resources from users that do not run local inference hardware at capacity over the hardwares lifespan. This is under-utilization and under-utilization is not optimal from an economics perspective.
2. The concentration of inference hardware to singular providers can aggregate power to single systems or organizations, and their incentives may be at odds with individual users.
The same power dynamic and economics struggle has existed nearly everywhere for all of history. For example, if you want to decide to own or rent a piece of heavy construction machinery for business, you will find a long list of do-not's on the rental contractual terms, but you are more than welcome to buy your own and operate your own machinery at several times the price for the hours used and use it however you want.
Must why people in this HN thread are throwing out so many ad-hominems instead.
Humans simply don't work like that.
I would like to know how “efficient” Altman's $27 million mansion is.
Also, I'd be very surprised if the current rush to build datacenters everywhere is optimal usage of resources. How many companies are building datacenter commons and sharing with other companies to optimize resource usage?
> Two statements can be true
As I general point, because I keep seeing this line on HN: Of course they can in the general case, but more often than not, the reason why this line is written is because there is some tension or contradiction between the statements. In that case, understanding where the tension lies is IMO more useful than shrugging and deciding to "hold two contradictory thoughts in your head" like in 1984.
Sometimes it feels like a rhetoric device to "rescue" an opinion when the opposite opinion is hard to argue against.
A hard rule of life is, if there are resources available, something will consume them. It's interesting that this also ended up being true for compute!
The entire reason SETI@Home started was because people had unused hardware sitting idle at home. Every company I've ever been in has had slides on resource utilization for procured hardware.
In fact not only could the two statements be true, in fact both are true. People want to ignore otherwise because doing so will make local LLM inference sound like the only option when only one is considered.
What they did was to say "hey, we can leverage your idle computer to help process this".
Different perspective.
It seems to me it's economically optimal for inference providers to intentionally close markets that would allow local inference at all, even if that's bad for users as a whole.
And if they're wrong, you'll be able to purchase second hand cheap data centre grade hardware in a couple of years and DRAM prices will return to normal.
There is opportunity theft here.
"Efficient use of resources" is not some absolute based on mere energy or economics calculations, it depends on the goal.
If the goal is "reduce reliance on big tech", "privacy", "autonomy", and so on, then the most efficient use of resources if to say fuck you to Big AI and not let them hoard ram and gpus.
Same with AI. AI use is a colossal waste, for all kinds of frivolous purposes (e.g. some person's ai girfriend chat, or someone asking about K-pop lore, or slop image generation, or slop "dark internet posts"), but also to facilitate "serious" business that we'd be better if it wasn't done at all.
Fixing exactly this has been the constant drumbeat of IT since the early 00's at least. It started with virtualization, to get capacity factor of hardware up in the enterprise. The average server back before VMWare (and HyperV/etc.) became a major thing was probably sitting at 10% utilization or less 95% of the time. Hypervisors were invented to fix this as their primary use case. You'd take a 5-10% performance hit on the raw server performance to gain 90% efficiency back.
Next came the cloud. Which was virtualization at scale. The larger the scale, the better the efficiency.
It's basically almost all anyone has actually accomplished in IT over the past decade or two. Everything else has been largely stagnant compared to the 80's and 90's.
AI inference is in it's infancy, but I imagine we will see more or less the exact same thing play out yet again. Lots of initial on-prem stuff due to cost and freedom, and eventually it becomes virtualized, commoditized, customer segregated, etc. Just like average cloud workloads are today and all the various "small" megawatt-scale builds moved back into the hyperscaler type providers within the next 5-10 years.
> How many companies are building datacenter commons and sharing with other companies to optimize resource usage?
Quite a few that I've seen. Rented inference/token factories are the current new hotness. Plenty of speculative builds being done by hundreds of smalltime providers. These will consolidate per usual and everyone but the last few top percent will remain as the winners. Just like the first hosting providers. Virtualization and fancy schedulers to maximize hardware utilization across a number of end-user customers are a huge topic in this space at the moment. Heck, a lot of these small time players are providing raw compute for the giant AI labs and even hyperscalers.
I don't like that Altman is right on this btw. I much preferred the highly inefficient days of every midsize corporate office having a 200-500kw datacenter in the basement. AWS and their ilk are quite obviously orders of magnitude more hardware efficient though.
And, "waste" has an overtone of moral wrong, of "you shouldn't". When before did anyone say that I shouldn't get a nice PC? Never.
So, yeah, moralizing to individual users that they shouldn't buy DRAM so someone else can have it is new.
No, he absolutely does:
"From a global allocation perspective, actually, it's quite terrible to have everyone have a bunch of the world's limited supply of DRAM sitting in their own computer. And be used 5% of the time," Altman said.
They're all sharing with each other. Anthropic's S-1, for instance, shows $100 billion+ commitments each to renting datacenter space from AWS, xAI, and Google (two of whom compete with Anthropic on AI). None of theme are idly sitting on unused depreciating hardware for no reason.
I've never heard anyone accuse FAANG's of not trying hard enough to optimize their own resource usage.
Not to mention, I bet users will be open to "rent" their hardware for proper utilization, provided he can pay for it.... real question is, will he?
The problem is that this sneaks in a postulate by negating "optimal", which is that underutilization is the opposite of that which is desirable, that it is implicitly undesirable. If we don't take that premise, say that it's value neutral and neither desirable nor undesirable by itself, then the argument doesn't really stand. This neutral valuation is far more reasonable to me. Anybody who works in logistics intuitively already understands this. We don't have cargo ships bow to stern across every single shipping lane, yet this is "underutilization" of those shipping lanes. Sure they're bottlenecked at the ports, but the ports can always be bigger, more numerous and possibly even work faster. The slop turns out doesn't matter. Actually it's beneficial for a few reasons, but my point here is sufficient I think.
You're right this is ultimately a power struggle at the core of it, what I think you could stand to acknowledge is that's all it is. It's just dressed up as economic rhetoric.
also, its a bit weird to say a supply chain fails if you simply order much more than they have.
in stock:100 'i want a million, the supply chain is failing and others need to stop buying so i can get a million'
4. Everything is training data. If that data isn't going to OpenAI, they're not training on it.
Also, it's important to remember OpenAI's failure might actually be the best thing for everyone else in the AI field. e.g. Some new innovation/approach could come out of left field and eat OpenAI's lunch. They've bet the farm (and a lot of other peoples' farms) on a brute force approach. Altman needs your RAM because, if he doesn't control the brute force, the brute force approach might not work only for him.
#2 is true for almost all observers. #1 is only true for a small group of people. #2 is an "is". #1 is a "should". Sam Altman is very, very wrong in the "should" sense of "wrong", by my judgement of value, and I suspect also by the judgement of most people reading this.
Under utilization is not optimal only in one perspective. Maximum utilization of resources. That does not mean it’s not optimal economically.
This kind of underutilization has many other economic benefits. - Decentralization - Separation of ownership - Redundancy - Hedging against certain risks (such as the internet going down)
Economic value is more than just maximum utilization in the minimum amount of time.
It would be more efficient to ban cars in favor of mass transit. It would be more efficient if people only lived in apartment complexes rather than standalone houses. Tons of things can be more "efficient" if you take away people's desire for privacy and ownership.
Citation needed.
OpenAI triggered this ordeal with its order of 900K DRAM wafers per month on october 2025, making everyone panic because it was around 40% of the world production at the time.
We all know that memory providers know what near bankruptcy feels like when they over invest, but right now SK Hynix have 80% margins (ie TSMC ~60%) and choose to pay their shareholders this year the quivalent of ALL their revenues in 2025. It's now common knowledge thanks to Samsung that the rate of factory buidling is not maxmium to portect their margins. And memory providers have already been fined in 2000 for price fixing.
Supply is short because they all choose to make it that way.
Demand has increased for high-bandwidth memory. That increases prices and quantity.
The increase in quantity has happened. Quantity sold has increased. Fabs have increased production and shifted away from other products including consumer products.
Prices increase when there is an increase in price of a substitute in production.
New fabs are planned, consistent with profit-maximizing behavior increasing production in response to increased prices, but they take time.
When e.g. memory manufacturers don't collude, they end up on synchronized boom-and-bust cycles.
But it's also illegal for them for form a cartel, which IIUC would have the benefit of smoothing the supply:demand ratio over time.
Is there any truly good solution to this?
(I'm not an economist, so it's quite possible that my question isn't even cogent.)
Yes, what smart RAM manufacturers (or who've been longer in the business) are doing: ramp up production capacity, but do so gradually.
Those ramp-up timelines tend to be longer than the markets' boom & bust cycles. So they'll be looking at longER-term trends to decide what to invest in & when.
90% perspiration, 10% inspiration.
Also home training and torrenting are a thing now too. Open weight models will never stop being released one way or the other.
mainly because the thing about open weights is folks will just immediately strip it back out.
But I can guarantee you that openai/anthropic/other will absolutely jump at the chance to monetize users by feeding them paid recommendations.
Can you please not do this here? It's not what HN is for, and destroys what it is for.
I actually use both gpt and local qwen and I personally think the question tends to be of what one needs ( speed? privacy? lack of corporate silliness? ).
Still, it is sad that we can predict the future so well based merely on what happened before.
Edit: I certainly hope I don't have to explain to you why the above is relevant. No market participant would dare to argue this if the competition was healthy.
I use my RAM how the hell I want and nobody else better damn well think about telling me otherwise.
I absolutely agree, we should redistribute the wealthness of those hyper extremely wealthy people back to society.
https://cheekypint.transistor.fm/39/transcript#:~:text=quite...
In theory, I don't disagree. He needs it, and he will use it, that's for sure. Moreover, his logical argument should be viewed purely through the lens of his own self-interest: "I need it, I don't have it, it's your fault, and anyway, you don't even use it properly."
But the question I ask myself is: can he use VRAM for something other than what is requested millions of times? "GPT, make me an app to boil eggs," "GPT, make me an app to compare prices," "GPT, make me an app to alert me during Black Friday..."
So many resources used thousands of times... With his VRAM... So the counter-argument we can give him is: Stop thinking like an American picking flowers with a bulldozer (no offense, it's just a metaphor) and learn to conserve your resources.
by the way, why is the post being flagged?
And even in economic terms... the way free markets work is that we let dollars decide which resources go where. That's the "optimal" distribution of scarce resources - they go wherever most values them. So his distribution is in fact economically sub-optimal. I value having some RAM more than he values having one more increment of RAM, so I get some and he doesn't.
He doesn't like it? Not my problem. Not economic theory's problem, either.
ah yes, the classical elitarist gatekeeping. god forbid laymen and paesants can have access to technology! only a small caste of technology priests must be able to use the new technology!
Edit: To be fair, I could have worded my earlier comment differently.
But that's not true. Computers, including RAM, are used for many different things that do not involve AI at all. video games, office work, communications, access to culture, etc.
So, what Altman really says is "AI is the only thing that matter for computing, and thus, for the success of his company, we must allocate all the RAM to his company, and forbid any people from accessing it".
And, IMO, we should not accept that kind of discourse :s