Comment by toasty228

That's true, and I am not anti-AI. I was not only thinking about the environmental effects of some single prompt or a certain amount of tokens.

Neither did I want to say that a car is always more wasteful than some alternative.

But defaulting to the behemoth is inefficient, unless everyone is driven to do it: then it's in some way reasonable.

By adding "corrupt" and "dependent", as well as the economic terms, I wanted to offer a broader critique and create an analogy, not just talk about energy usage on its own.

What I had in mind was: it's easier to go many places that are a mile or less from me, by car. Because everything is obstructed by cars. And I'm atrophied by lack of movement. Best would be to drive somewhere to move/walk.

People already do that in masses.

And doing shopping by car, because everything else seems unbearable, also takes away your time, apart from wasting energy compared to more, smaller shops that would be reachable by foot, bycicle etc.

I guess you know the argument.

Today, people's thinking atrophies because their LLM is probably right in their summarization of some Wikipedia article, plus 2-3 other random sources.

Or so.

Using the Wikipedia search function is not expensive.

But, I mostly had a bigger picture in mind than what is the cost of inference.

It's like saying if we didn't have cheap commercial flights people would travel by foot anyways and would consume more resources for food &co. than the plane would consume in fuel...

80% of generative AI queries wouldn't even exist as google searches.

That might be true, but at least I started asking way more questions since we’ve had competent LLMs.

It is exactly this thought, in the form of this sentence, that could replace almost all of my comments in this thread.

It feels depressing, but I think the same. When thinking about the larger world, it becomes increasingly hard to ignore. And of course it is not new.

There were "doomers" already in the midst of the 20th century, but it doesn't mean that they were wrong.

Thanks for asking an open question about my point.

First, because I initially failed to answer your more closed questions (this paragraph is edited in):

> We are getting pretty close to models which can be useful locally in many applications. Or do you mean that at scale running them locally is not possible and hence the infrastructure price is in data centers, which will be expensive to maintain and scale for demand?

I don't think there's a way around making the best of AI capabilities with minimum price and maximum control, and I'd agree this is met by on-prem data centers, just not in a rationally targeted way.

Back to my original comment:

Because it (my conclusion) was not so clear, and maybe I just wanted to highlight some observations without delivering a real argument for or against things [, I thank you for your open question].

The utility/leverage aspect for AI seems more esoteric than the one for cars because, apart from Chatbots, it's more hidden.

And also, similar to cars (or many other phenomena of industrialization), yes, my first vague point was the subsidization of infrastructure. But also, the power gap: that's something not only associated with AI or cars, but with a lot of technologies we all hold dear: sewage, powerline, logistics, etc etc.

What reminds me of cars in the current AI frenzy is the fixation on cementing infrastructure. And also, I think, a lot more people agree on, for example, some kind of universal right to, for example, clean water.

But all of industrialization confronts people with questions of efficiency, inequality, and collective support.

Most people would, for example, support a right to get a minimum amount of clean water when you are living and working in a tradionally inhabited space (if you're on the social-darwinist side) or at least not harming society (if you're more of a social democrat).

And, similar to the buildup of car infrastructure, and the procurement of resources, space etc for maximum building, giant data centers can obstruct people in buying drinking water. Or walking outside (AI obstructs traditional methods of online collaboration).

Charitably the lag time for this technology to have noticeable effects could just be ~5 years away. Similarly to how computers didn't have a big impact for a decade after they were introduced as people got used to using them.

Is the image you provided depicting revenue, or stock value? My point is about revenue.