* so-called "hallucination" (actually just how generative models work) is a feature, not a bug.
* anyone can easily see the unrealistic and biased outputs without complex statistical tests.
* human intuition is useful for evaluation, and not fundamentally misleading (i.e. the equivalent of "this text sounds fluent, so the generator must be intelligent!" hype doesn't really exist for imagery. We're capable of treating it as technology and evaluating it fairly, because there's no equivalent human capability.)
* even lossy, noisy, collapsed and over-trained methods can be valuable for different creative pursuits.
* perfection is not required. You can easily see distorted features in output, and iteratively try to improve them.
* consistency is not required (though it will unlock hugely valuable applications, like video, should it ever arrive).
* technologies like LoRA allow even unskilled users to train character-, style- or concept-specific models with ease.
I've been amazed at how much better image / visual generation models have become in the last year, and IMO, the pace of improvement has not been slowing as much as text models. Moreover, it's becoming increasingly clear that the future isn't the wholesale replacement of photographers, cinematographers, etc., but rather, a generation of crazy AI-based power tools that can do things like add and remove concepts to imagery with a few text prompts. It's insanely useful, and just like Photoshop in the 90s, a new generation of power-users is already emerging, and doing wild things with the tools.