This is already not the case for computers. And you’re trying to argue that we might one day be able to run the bigger models on consumer hardware, but I said it’s too expensive to train them. And you know that the cost isn’t just the RAM right?

If you replace everything I said about RAM with compute and replace the Bill Gates quote with Thomas Watson saying that the “world market [has room for] for maybe five computers” then it’s the same argument. They’re all ultimately built on technical advances in lithography and so growth in RAM and compute largely stem from similar sources.

Sure, my saying they will “always” be tied to concentrated capital is slightly hyperbolic. You never know. But it takes a whole lot of optimism to hope that LLMs will be decoupled from the billionaire class, hence why most analyses of the problems LLMs cause discuss them in this context.

I understand why it is done as shorthand.

I know this likely doesn’t apply to you, as you seem to be capable of understanding the nuance, it’s that a lot of people on social media (by people I’m including the bots) don’t make that distinction.

The same vitriol that is, rightfully, directed at OpenAI/Anthropic/Google/NVIDIA is also directed at things completely outside of the corporate LLM hellscape.

I’m mostly frustrated at seeing the sciences, researchers and open source AI projects catching strays and being painted with the same brush.

It’s useful shorthand among people who understand the nuance, but using that shorthand on social media invites misunderstanding and that is causing collateral damage.