Local models and alignment are orthogonal concepts.

I don't think this is entirely true, insofar as non-local models inherently have a "man cannot serve two masters" problem. The end user and the org running the AI may have different goals. That means even if AI alignment were to be in some sense "solved" for local models, you wouldn't be guaranteed an aligned AI using a non-local model because the "owners" of the non-local model may have deliberately misaligned the AI in their favor and against your interests.

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vntok 2 hours ago | parent | prev [-]

How so? If it's not local, it's not yours, a third party owns it.

Why would you expect that third party specifically trained their model to be more aligned to you and your needs than to them and their (business) needs?

	▲	charcircuit 39 minutes ago \| parent [-]
		>Why would you expect that third party specifically trained their model to be more aligned to you and your needs than to them and their (business) needs? That is my point. Why do you think Gemma, a local model trained by Google, is aligned to you and not the values of Google. You can similarly have a model aligned to you which you pay someone to remotely host for you instead of running it locally.