[utopiah]

> Some people really do hate AI

That's probably me for a lot of people. The reality is a bit finer than this namely :

- I hate VC funded AI which is actually super shallow (basically OpenAI/Claude wrappers)

- I hate VC funded genuine BigAI that sells itself as the literal opposite of what it is, e.g. OpenAI... being NOT open.

- I hate AI that hides it's ecological cost. Generating text, videos, etc is actually fascinating, but not if making the shittiest video with the dumbest script is taking the same amount of energy I'd need to fly across the globe.

- I hate AI that hides it's human cost, namely using cheap labor from "far away" where people have to label atrocities (murders, rape, child abuse, etc) without being provided proper psychological support.

- I hate AI that embodies capitalist principles of exploitation. If somehow your entire AI business relies on an entire pyramid of everything listed above to capture a market then hike the price once dependency is entrenched you might be a brilliant business man but you suck as a human being.

etc... I could go on but you get the idea.

I do love open source public AI research though. Several of my very good friends are researchers in universities working on the topic. They are smart, kind and just great human beings. Not fucking ghouls riding the hype with 0 concern for our World.

So... yes maybe AI haters have a slightly more refined perspective but of course when one summarize whatever text they see in 3 words via their favorite LLM, it's hard to see.

[pbmonster]

> making the shittiest video with the dumbest script is taking the same amount of energy I'd need to fly across the globe.

I get your overall point, but the hyperbole is probably unhelpful. Flying a human across the globe takes several MWh. That's billions of tokens created (give or take an order of magnitude...).

[utopiah]

Does your comparison include training, data center building, GPUs productions, etc or solely inference? (genuine question I don't know the total cost for e.g. Sora2, only inference which AFAIK is significant yet pale in comparison to everything upstream)

[pbmonster]

No, that's one reason why there's at least an order of magnitude wiggle room there. I just took the first number for J/Token I found on arxiv from 2025. Choosing the exact model and hardware it runs on is also making a large difference (probably larger than your one-time upfront costs, since those are needed only once and spread out across years of inference).

My point is mobility, especially commercial flight, is extremely energy intense and the average westerner will burn much more resources here than on AI use. People get mad at the energy and water use of AI, and they aren't wrong, but right now it really is only a drop in the ocean of energy and water we're wasting anyways.

[utopiah]

> right now it really is only a drop in the ocean of energy and water we're wasting anyways.

That's not what I heard. Maybe it was in 2024 but now data centers have their own categories in energy consumption whereas until now it was "others". I think we need to update our collective understanding in terms of actual energy consumed. It was all fun & games until recently and slop was kind of harmless consequence ecologically speaking but from what I can tell in terms of energy, water, etc it is not negligible anymore.

[pbmonster]

Probably just a matter of perspective. It's a few hundreds of TWh per year in 2025 - that's huge, and it's growing quickly. But again, that's still only a small fraction of a percent of total human primary energy consumption during the same time.

[mlrtime]

You could say the same about the airplane, does the CO2 emissions that the airline states for my seat include building the plane, the R/D, training the pilot.

[utopiah]

Sure and I do, it's LCA https://en.wikipedia.org/wiki/Life-cycle_assessment the problem IMHO being that the AI hype entire ecosystem is literally hiding everything it can about this behind the veil of giving information to competitors. We have CO2eq on model cards but we don't have much datapoints on proprietary models running on Azure cloud or wherever. At best we infer from some research papers that are close enough but we don't know for the most popular models and that's quite problematic. The car industry did everything it could too, e.g. Volkswagen scandal so let's not repeat that.