Remember when AI was exciting? When ChatGPT felt like magic and Midjourney blew your mind? That was approximately 47 'revolutionary' models ago.

Now we're in the AI equivalent of a Marvel movie franchise—endless sequels with diminishing returns, where every new release promises to change everything but just gives us another slightly different way to generate mediocre marketing copy.

The Absurdity

Your inbox is now a graveyard of AI announcements. "Meet our new multimodal model!" "Introducing AI-powered analytics!" "We've added AI to our AI!" It's like watching someone try to make fetch happen, but instead of fetch, it's another API that hallucinates slightly less.

The tech press has become AI's hype man at a party that ended six months ago. Every minor improvement gets breathless coverage like we've discovered fire again. Meanwhile, actual users are just trying to get the damn thing to stop making up citations.

Startups have pivoted so hard to AI that their original business models are just distant memories. "We used to sell productivity software, but now we sell AI that promises productivity while actually creating more work to fix its mistakes."

Why This Matters

AI fatigue isn't just about being tired of hearing about AI. It's about the cognitive load of pretending every incremental improvement matters. We're experiencing announcement whiplash without actual utility improvement.

The real innovation has shifted from "what can this do?" to "how many ways can we repackage the same underlying technology?" It's the tech equivalent of putting a new label on the same bottle of water and calling it revolutionary hydration.

This fatigue creates a dangerous environment where actual breakthroughs get lost in the noise. When everything is revolutionary, nothing is. We're training ourselves to ignore the signal because the noise is so damn loud.

The Reality

Here's the secret nobody wants to admit: most AI applications are solving problems that either don't exist or were already solved adequately. We're optimizing the wrong things because they're measurable, not because they matter.

The actual useful AI is boring. It's in supply chain optimization, medical imaging analysis, and climate modeling. Not in generating another variation of "corporate synergy" for your LinkedIn post.

We've confused technological capability with human value. Just because we can make an AI do something doesn't mean we should, or that anyone actually wants it.

The Way Forward

First, let's normalize saying "I don't care" about the 47th AI model announcement. Your time is valuable, and not every incremental improvement deserves your attention.

Second, demand actual utility, not just hype. Ask the hard questions: Does this actually solve a real problem? Is it better than existing solutions? Or is it just AI for AI's sake?

Finally, remember that the most revolutionary technology is often the one that quietly works in the background, not the one with the flashiest press release. The future isn't about more AI—it's about better AI that actually makes our lives better, not just more complicated.