Hes going to lobby the federal government to confiscate all your RAM, like FDR did with the gold. :|
Dead.
Hands.
the underlying economics are unescapable. when there was a glut of RAM because no profitable uses existed for it manufacturers shoved it into consumer products because "bigger number is good" but it produces very little utility sitting idle in consumer devices.
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.
How so? It's obviously self-serving.
From a pure efficiency point of view it makes sense to have all our resources pooled and used by whoever needs them at the time. So long as there is always enough to go around, and all the benefits of local computing are kept (though how that works practically if your internet goes offline I don't know) then theoretically, home computers are suboptimal.
But that argument isn't really based on reality. Privacy, offline access, access when you need it, cost... the list goes on. There's many reasons he's wrong, but the core point that it is technically more efficient in the perfect world seems sound.
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.
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.
Local inference is like buying a house even if it's more expensive than renting, because you (often quite reasonably) don't want to live under the heel of the landlord-tenant power relationship.
Hey don't talk about Sam like that!
Or maybe he should live in a one bedroom apartment.
That would be way more efficient.
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.'
They have no credibility as an impartial analyst.
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.
If Sam wants to buy 16GB of 6 year laptop RAM, he can send me a check for $2000.
Sources for this would be appreciated.
Running all those lines, people don't even use it all that much.
Much more efficient to put everybody into camps, and simply have the people take turns using electrical appliances operating at 100% duty cycle.
Freight delivery speeds need to be brought down too, 35 MPH maximum.
Food? Give me break, get everyone on a Soylent Green diet.
TacticalCoder•1h ago
"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?
rosseitsa•53m ago
emil-lp•45m ago
bux93•41m ago
entrope•29m ago
I think that's about where the argument ends.