Your framework is extremely strong on supply-chain propagation and infrastructure repricing dynamics. What I keep wondering, though, is whether AI may behave less like a classical industrial cycle and more like a recursive general-purpose technology.
In railways or traditional infrastructure, efficiency improvements mostly optimize an existing function. But with AI and robotics, each new qualitative capability seems to create entirely new layers of demand rather than simply normalizing the previous one. A robot that can fold laundry, cook, or navigate physical environments is not just a “faster model”; it requires different computational architectures, persistent inference, memory, sensing, coordination, and entirely new infrastructure layers.
So I wonder whether the transition from infrastructure phase to application phase may end up being far less sequential than in previous cycles, because the application layer itself continuously expands the infrastructure requirement. Your analysis is one of the clearest I’ve read on the current phase, which is why I’m very curious how you think about this recursive aspect of AI demand.
I agree that AI may not follow a clean industrial-cycle sequence. The transition from infrastructure to applications may overlap, because applications can create new workloads and reopen infrastructure demand.
That is why I separate the current market signal from the full AI cycle. The May 6 market signal still looked sequential, but the full cycle may become a recursive demand loop.
Yes — I think we are largely converging on the same distinction.
In the short and medium term, I fully agree that the market is still pricing identifiable infrastructure constraints and sequential propagation across the supply chain. The May 6 reaction was very clear in that sense.
My point was more about the longer-term character of AI as a potentially recursive demand system once physical-world deployment begins to scale. But I think your framework captures the current phase extremely well.
Your framework is extremely strong on supply-chain propagation and infrastructure repricing dynamics. What I keep wondering, though, is whether AI may behave less like a classical industrial cycle and more like a recursive general-purpose technology.
In railways or traditional infrastructure, efficiency improvements mostly optimize an existing function. But with AI and robotics, each new qualitative capability seems to create entirely new layers of demand rather than simply normalizing the previous one. A robot that can fold laundry, cook, or navigate physical environments is not just a “faster model”; it requires different computational architectures, persistent inference, memory, sensing, coordination, and entirely new infrastructure layers.
So I wonder whether the transition from infrastructure phase to application phase may end up being far less sequential than in previous cycles, because the application layer itself continuously expands the infrastructure requirement. Your analysis is one of the clearest I’ve read on the current phase, which is why I’m very curious how you think about this recursive aspect of AI demand.
Excellent point.
I agree that AI may not follow a clean industrial-cycle sequence. The transition from infrastructure to applications may overlap, because applications can create new workloads and reopen infrastructure demand.
That is why I separate the current market signal from the full AI cycle. The May 6 market signal still looked sequential, but the full cycle may become a recursive demand loop.
Yes — I think we are largely converging on the same distinction.
In the short and medium term, I fully agree that the market is still pricing identifiable infrastructure constraints and sequential propagation across the supply chain. The May 6 reaction was very clear in that sense.
My point was more about the longer-term character of AI as a potentially recursive demand system once physical-world deployment begins to scale. But I think your framework captures the current phase extremely well.