Running a 180B parameter LLM on a single Apple M2 Ultra

Historically average RAM has grown far faster than linear, and there really hasn't been anything pressing manufacturers to push the envelope here in the past few years... until now.

It could be that LLM model sizes keep increasing such that we continue to require cloud consumption, but I suspect the sizes will not increase as quickly as hardware for inference.

Given how useful GPT-4 is already. Maybe one more iteration would unlock the vast majority of practical use cases.

I think people will be surprised that consumers ultimately end up benefitting far more from LLMs than the providers. There's not going to be much moat or differentiation to defend margins... more of a race to the bottom on pricing

Unless I'm misunderstanding, doesn't OpenAI have a very vested interest to keep making their products so good/so complex/so large that consumer hobbyists can't just `git clone` an alternative that's 95% as good running locally?

The magic of openai is their training data and architecture.

There is a real risk that a model gets leaked.