It appears good and cheap. But it's actually burning money, energy and water like crazy. I think somebody mentioned to generate a 10 second video, it's the equivalent in energy consumption as driving a bike for 100km.

It's not sustainable. I think the thing the person above you is referring to is if we ever manage to make LLMs and such which can be run locally on a phone or laptop with good results. That would make people experiment and try out things themselves, instead of being dependent on paying monthly for some services that can change anytime.

I'm using "good" in almost a moral sense. The quality of output from LLMs and generative AI is already about as good as it can get from a technical standpoint, continuing to throw money and data at it will only result in minimal improvement.

What I mean by "good AI" is the potential of new types of AI models to be trained for things like diagnosing cancer, and and other predictive tasks that we haven't thought of yet that actually have the potential to help humanity (and not just put artists and authors out of their jobs).

The work of training new, useful AI models is going to be done by scientists and researchers, probably on a limited budgets because there won't be a clear profit motive, and they won't be able to afford thousands of $20,000 GPUs like are being thrown at LLMs and generative AI today. But as the current AI race crashes and burns, the used hardware of today will be more affordable and hopefully actually get used for useful AI projects.