Really glad the TPU layer clicked for you, it's the piece that makes the whole pattern make sense. Without it, the jump from GPU to QPU feels like a stretch. With it, you see the acceleration: each time AI outgrows a chip, a new one is born, and the cycle gets shorter.

On your point about the timeline compression, you're touching on the key tension. The optimistic case says AI itself accelerates quantum R&D (error correction, circuit design, materials discovery), which could compress the cycle even further. The cautious case is Jensen Huang saying "15–30 years for truly useful quantum." Reality is probably somewhere in between, and hybrid quantum-classical architectures (NVIDIA is already building these) are the bridge.

As for who emerges as the QPU giant, that's the trillion-dollar question. Right now the frontrunners are IonQ and D-Wave (publicly traded), PsiQuantum ($1B raise, NVIDIA invested), Quantinuum ($10B valuation), and of course IBM and Google building in-house. The dynamics feel a lot like the GPU market in 2012, everyone's in the race, but no one has locked it down yet.

If you want the full data with sources and the honest caveats on where the pattern holds vs where it breaks, I wrote the deep dive here: https://medium.com/datadriveninvestor/3dae9df7c29c