IYH ruthless truth for builders, investors, and policymakers:
The real battlefield is the sovereignty stack—vertical-specific fusions of photonic interconnects (0.5 pJ/bit), CXL memory pools, and compliance-baked ASICs. If your AI infrastructure can’t dynamically route workloads by carbon cost and geofenced regulations, you’re already obsolete. Prioritize three moves now:
1. Rip out copper—replace with photonics or forfeit exascale efficiency.
2. Embed governance in silicon—EU’s €35M fines make verifier ASICs non-negotiable.
3. Hoard semiconductor talent—offer 4.2× salaries or lose the 1M-worker gap war.
Hyperscalers will own generic AI, but regulated verticals (healthcare, defense, finance) belong to sovereignty stacks. Build these—or rent your future from Brussels.
> "The next trillion-dollar companies won’t train better models. They’ll build infrastructure that outruns regulators."
Data-backed. No BS.
💠 Sources: EU AI Act Art 71(6) | NVIDIA Blackwell WP | SEMI Foundation | Nature Photonics
IYH ruthless truth for builders, investors, and policymakers:
The real battlefield is the sovereignty stack—vertical-specific fusions of photonic interconnects (0.5 pJ/bit), CXL memory pools, and compliance-baked ASICs. If your AI infrastructure can’t dynamically route workloads by carbon cost and geofenced regulations, you’re already obsolete. Prioritize three moves now:
1. Rip out copper—replace with photonics or forfeit exascale efficiency.
2. Embed governance in silicon—EU’s €35M fines make verifier ASICs non-negotiable.
3. Hoard semiconductor talent—offer 4.2× salaries or lose the 1M-worker gap war.
Hyperscalers will own generic AI, but regulated verticals (healthcare, defense, finance) belong to sovereignty stacks. Build these—or rent your future from Brussels.
> "The next trillion-dollar companies won’t train better models. They’ll build infrastructure that outruns regulators."
Data-backed. No BS.
💠 Sources: EU AI Act Art 71(6) | NVIDIA Blackwell WP | SEMI Foundation | Nature Photonics
Good point about sovereignty.
Where did you get 4.2x from? Just curious.
IYH The multiplier of 4.2x is extrapolated from compensation data from sources like Levels.fyi
Perhaps of interest fuller post https://notes.henr.ee/the-grand-unification-ai-s-control-matrix-9q3wx6