Sam Altman's Case Against Your RAM Is Efficient. That's the Problem

mrkn1 35 points 83 comments November 03, 2026
www.techdirt.com · View on Hacker News

Discussion Highlights (20 comments)

TacticalCoder

His case his "efficient"? What about this one: "People shouldn't be allowed to bicycle for fun. Only utilitarian bicycles should be allowed. For there's too much energy spent manufacturing mountain bikes, tires, converting ski station into bike parks for the summer. That energy and money should instead be directed towards creating more RAM factories and more datacenters for the AI companies" . Where does such an "efficient" argument ends? P.S: as a bonus question: does anyone know how to differentiate a paid shill from a sycophant?

Kevin_Flynn

Altman leaves out of this the fact that OpenAI has basically tried to corner the market on RAM, trying to lock up 40% of the world’s supply without even guaranteeing that it will follow through on the actual purchase orders. I mean, I think that alone would have at least some impact on the current price for RAM, wouldn’t it? Hes going to lobby the federal government to confiscate all your RAM, like FDR did with the gold. :|

jacquesm

Screw Sam Altman. He's the root cause of this shortage, besides that, how does he justify his car having extra seats that he's not using. Sick and tired of these techbros trying to re-centralize computing all over again whilst stealing left, right and center.

krisroadruck

Even putting aside the whole privacy and tuning debates - unless Sam is willing to sell us inference at something near the pre-constrained cost of directly owning the DRAM all he is advocating for is "don't be greedy guys, that's what I'm for. I can be greedy for you!". It's not actually efficient for people to pay huge markups on compute and memory vs letting that same memory site idle some of the time. I mean I guess it's efficient for OpenAIs bank account, but not for anyone else.

hammock

I heard someone say it’s inefficient for Sam to have two kidneys

regularfry

Efficiency and resilience are always in trade-off. Even if there was no other argument it would be worth having local inference as a guard against systemic SPOFs in the big providers.

rhdunn

Sam Altman's argument about RAM utilization is reasonable on a first pass, but misses several key points: 1. people aren't using (GPU) RAM [1] for just running LLMs (in the local model sense), they are using it for other things... games, system displays, other models (Text-to-Speech, Speech Recognition, etc.); 2. being able to run models locally allows them to be used when the internet is down, use them on private data (e.g. medical records, proprietary company data, etc.), including training on that data; 3. the big AI companies are already storing unused GPUs on shelves waiting for their roll-out in data centres, as they can't build the capacity fast enough. With point (3) that goes against Sam Altman's argument about utilization. The big companies have the hardware, but aren't utilizing it themselves. [1] And if the argument extends to RAM in general you have all sorts of applications, especially on developer hardware -- editing and compiling software; running local servers; running CAD and other applications; etc.

zajio1am

A problem of both the Altman post and posts that react on him is that they take efficiency/utility in absolute sense instead of in marginal sense. There is clearly high marginal utility of the first n GB of RAM in your computer, but then its go down probably faster than for RAM in OpenAI's datacenter. And the market just solves for the equilibrium.

solyin

We don't have to hold up paperclips as theoretical anymore. AI needs RAM. All of it. The real life paperclip maximization is RAM chips.

sabas123

I don't understand the backlash against this interview. When listening to the interview it sounded clear that it was just in context of local inference. To me it came across as stating that setting up local inference, when dram is limited, is indeed limiting from a global perspective. I think it's a bit disingenuous to state that his opinion is that we shouldn't have any ram being used for any local purposes.

cadamsdotcom

> if you have a sufficiently powerful AI tool that is told to “maximize” the creation of paperclips, it might decide the best way to do that is to seize control of all resources Hey don't talk about Sam like that!

233mhz

And if we cared even a little bit about efficiency the world would look very different, so we can just stop listening to him anyways

SammyWhiny

How many houses owns Sam? How many rooms in those. Maybe he should let homeless people live in them when he's not there. Or maybe he should live in a one bedroom apartment. That would be way more efficient.

Lerc

I have been finding this quite weird, it seems that the real villany was in what was in Sam Altman's mind when he said something that is basically true. I have seen many explanations of what that was exactly, they are not all agreed on the bad thoughts were, but they are pretty much in agreement that it was a bad thing. It's like saying 'public transport is more efficient than driving your own car', and the person hearing you say 'you shouldn't own a car, you should use the public transport system I will own.'

goalieca

Are LLMs the best use Of ram? Many other extremely beneficial devices for extremely high value use cases are suffering because of this madman trying to corner the market. Show me the value of everything else suffering.

trwhite

What kind of specs would you need on a local machine to be able to run fairly decent (Opus 5.5-level) models on it?

Havoc

In short sound logical argument absolutely zero sense of optics or relatability

bArray

I think the argument being made is fundamentally wrong. It reminds me of the Socialism vs Capitalism models - this idea that centralizing the resources will somehow unlock efficiency. It's also becoming clearly that merely throwing more data, RAM, compute, etc, is not generating significantly better behaviours. We are far better off with millions of people running lots of little experiments, than a handful of super large companies running a subset of experiments. We really need to get agentic LLMs onto local machines at a reasonable price to really accelerate. The likes of qwen3.5-0.8b have been super interesting to me, you have this tiny little model that can run on a CPU that can exhibit agentic behaviours (with a lot of tickling) - in the hands of hobbyists is where I suspect we will see some cool updates.

xnx

This keeps getting posted, but it doesn't seem interesting to discuss. Money is the way we decide how scare resources are allocated. If Sam wants to buy 16GB of 6 year laptop RAM, he can send me a check for $2000.

trwhite

Why did this post get dropped from the homepage?

Semantic search powered by Rivestack pgvector
11,510 stories · 108,877 chunks indexed