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Except the people spending all this money on them? Dave wants his book proofread more cheaply, Pete wants to ERP, Melanie wants dashboards to show key business insights, John wants some spreadsheets analyzed, Dean wants to fix bugs in his software. Even Johnny Jihadi wants to know how to make use of unexploded munitions left by govt forces in the Sahel and he goes to AI for that.
Why would the opinions of people who don't pay for the product because they don't find it useful outweigh those who do?
How does that address the point? People advocating against data centres do so on the basis that constructing data centres affects the communities they live in. That's why they get a say. People care about things that affect them. People who pay for chatbots don't get some sort of veto over people who don't. That would be lunatic.
That was the point of Sun's comparison to cars. You may grumble at an auto factory, but you do, at least, understand why cars are necessary. Even if you personally don't own a car and rely on public transport to get everywhere, it's obvious that there's real public demand for cars, on the basis of their obvious usefulness. You might not want a factory near you, but you understand why there need to be factories somewhere. LLMs have not cleared that hurdle. It seems that large numbers of people do not see why these things are so necessary that all these data centres should be built. We could just, you know, not have LLMs. That's an option.
The examples you give - proofreading a book, cybersex, reading spreadsheets - are generally all in the 'toy' category. Even the serious one, the hypothetical Jihadist, could just as easily google the munitions. The use cases for LLMs are so marginal that there is no publicly-felt sense of why they are needed, certainly to the extent of justifying the demands that data centre construction make on the public.
LLMs are obviously useful in the same way that businesses obviously need to analyse spreadsheets and obviously need to write code, amongst a myriad of other tasks where LLMs are useful.
The point you were putting forth is that because LLMs aren't very useful (except for some niche fields) and aren't interesting, there is no need to build datacentres. But that's not the case. We can discern that's not the case because people are prepared to pay for these LLMs. The general public. Coders. Companies. Militaries. Governments.
It is abundantly clear that LLM technology is in fact useful and there is an abundance of examples to back this up. Use of LLMs for targeting/ISR in the Iran war, use of LLMs in hacking, use of LLMs in writing code, use of LLMs in mathematics research, chemistry and biology, use of LLMs in entertainment, making images, translation, proofreading, examining legal or financial data. These are not niche fields.
So people are prepared to sacrifice money for these things, which is why these companies are building datacentres. They're not being built without reason. Companies are paying for all this compute and electricity. Sure, the electricity use is an issue for local communities. Industry has been known to require power, make noise and pollution, which should all ideally be minimized.
Again, this is not the case. If googling was just as easy then he'd do that and not waste time jailbreaking AIs instead.
It does seem that many people don't see a use for AI. But they're wrong about that, maybe they haven't looked into it or misunderstand what is going on.
I'm not actually sure they are widely useful. So far the primary use case for them is coding, right? But not very many people are coders, it's a niche field, and as Freddie has argued (disclaimer: I do not wholly agree with him), very little has actually come of this supposed improvement to coding. We haven't seen a flowering of new programs, and neither have existing programs gotten better.
But even if we grant that LLMs are very useful in the handful of niche fields where they are currently used, the problems remain that 1) most members of the public do not understand or care about those uses, and 2) most members of the public do not think those uses are worth the costs they are being asked to bear.
This may still be overly optimistic. I think many people's main impression of modern software is negative experiences like ubiquitous data harvesting, addictive social media algorithms, and frustrating experiences with confusing or buggy new technology.
Promising to deliver more of these faster won't be considered a positive effect of AI.
As far as I can tell, most Americans think that AI is making society worse. More and more Americans have encountered and used the technology, but it is the most widely-despised technological advance in a generation.
For this story I think the key part there is Pew's point 10. Experts are vastly more optimistic about LLMs than the population in general. That divergence is what drives this conflict. If many members of the public believe that the situation is that a small, wealthy elite are forcing a technology on the country that the country does not want... well, those members of the public are correct.
I mean, good? I do not want members of the public to have veto power over what smart engineers are permitted to develop (as long as they're paying for it, of course). Imagine if we'd held a plebiscite on whether universities should continue spending money on this "Internet" thing in friggin' 1973, 4 years after ARPANET began. Imagine if journalists were publishing articles in 1907 asking for the government to shut down research on these new-fangled planes because they're flimsy and dangerous and nobody they know has seen any benefits from them.
Experts have, well, expertise in the subject. They know the technology has a ridiculous number of use cases. But it takes time for it to percolate through society.
If it helps, if you held this retroactively today, I'm still not sure how I'd personally vote. I get a lot out of the Internet, but I do sometimes wonder if it's worth all the downsides.
That's fair. And the same could be said for AI, of course! There's at least an honest debate to be had there. Not like this highly-motivated special scrutiny of datacenters.
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