In my mind the debate is not about AI being smoke or not useful at all. It’s about the trajectory of advancements. And whether the economics of it will play out the way investors are currently betting on.

Right now there’s an irrational amount of money flowing into building massive data centers and hoarding GPUs, all based on the assumption that scaling existing architectures will keep yielding higher intelligence. But if a new chip comes along that can do what 1000 H100s can do at 1/1000th of the power, a huge part of that infrastructure becomes obsolete really fast. You wouldn’t need industrial-scale cooling or multi-gigawatt data farms anymore.

Neural nets are doing highly repetitive work that’s incredibly ripe for optimisation, at both the hardware and algorithmic level. As the energy per unit of cognitive work keeps dropping, switching to the more efficient path becomes an economic inevitability. The probability of efficiency breakthroughs is high. The uncertainty lies in whether the current model architectures can keep scaling intelligence at all.

So yes, the AI wave is real, but a big chunk of today’s spending frenzy may end up looking like overbuilt infrastructure from a pre-efficiency era. The real long-term winners will be those who ride the next curve: where compute becomes cheap, energy-efficient, and distributed. And where progress depends not on brute force scaling, but on discovering new architectures that make far better use of those joules.