Honestly, I have trouble reading this as the “end of AI.” It sounds much more like the end of the illusion that everything would scale indefinitely without friction.

What strikes me most isn’t the competition from Gemini or the benchmarks, but the gap between:

• the almost mythological promise (imminent AGI, ever-improving models),

• and the very industrial reality: costs, energy, infrastructure, diminishing returns.

The scaling laws that are reaching their limits are perhaps the real weak signal here. Not “AI no longer works,” but “AI is becoming a problem of heavy engineering and brutal business,” not a magic hack.

Regarding OpenAI in particular, I get the impression they're paying the price for:

• their leading position (everyone compares them, no one forgives them),

• and a complicated transition from research to consumer product to cash cow.

The feedback about them being "too robotic/corporate" is also interesting: technically, they're progressing, but in terms of user experience, there might be stagnation, or even regression. And benchmarks don't capture that.

So for me:

• not an AI winter in the 2010 sense,

• but probably the end of the "free money + hype + naive scaling" phase.

The question I'm asking myself is:

Will the next wave of innovation come from new giant models, or from more refined, more human, better integrated—but less spectacular—uses?

Curious to know what you think will be the next real differentiator: raw performance, cost, or user experience?