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True, but look at nuclear tests. There used to be around 50 tests every year, for decades. Now the only nuclear tests in the last 27 years were the six done by North Korea[1]. And there's still only nine countries with any nuclear weapons, and none in the past twenty years[2].

That's a bit better than just "it hasn't killed us yet". I think it shows we can at least stop the further development of this kind of technology.

[1] https://www.armscontrol.org/factsheets/nuclear-testing-tally

[2] https://en.wikipedia.org/wiki/List_of_states_with_nuclear_we...

by cortesoft52 minutes ago|

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Nuclear tests are extremely easy to detect worldwide, and enrichment activity is a major industrial process that is also fairly easy to track given the specialized equipment needed.

AI development doesn’t have any of these characteristics. It would be almost impossible to easily distinguish a datacenter that is working on AI development and a datacenter mining cryptocurrency.

It would not be nearly as easy to stop AI development as it is to stop nuclear arms development.

by Analemma_1 hours ago|

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To the extent nuclear arms control works, I think it's only because nuclear weapons are so hard to build-- uranium enrichment is hugely expensive and complicated, and plutonium weapons need actual reactors.

If it was possible for ordinary companies to build nuclear weapons, and also release open-source ones that anyone could use to compete with the paid ones, I suspect we'd all have been dead a long time ago, arms control treaties or no.

by BoppreH1 hours ago|

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Even the (SOTA LLM) open source models are trained with huge clusters. Datacenters are also hugely expensive and complicated.

Or you can take one step back and look at chip allocation. As far as I know there are only three companies on the planet that can make the chips that go in those clusters. One (ASML), if you look back the supply chain to the Extreme Ultraviolet Lithography Systems.

If politicians decided that no more large language models should be trained, it sounds like we could do it.