Intelligence requires the ability to construct simplified models of the world that are not only predictive, but probabilistically calibrated and structurally aligned with the constraints governing feasible outcomes.
I spent time in Shenzhen last year and when I saw Merz come back from China saying Germans need to work more I immediately knew what broke his brain because I lived the exact same cognitive shock
my first week in Huaqiangbei I burned through 4 prototype iterations of a motor controller board for less than a thousand bucks total, back home a friend was working on something similar and spent over 12 thousand for a single revision that took almost two months to arrive
when you live that contrast in your own hands with your own project something permanently shifts in how you see the world and it goes way deeper than speed & cost
what Shenzhen actually built is a collective learning organism, imagine 20 PCB fabs 15 injection mold shops 30 component distributors and a hundred firmware freelancers all within a 2km radius, looks insanely redundant from the outside until you realize redundancy is actually information density in disguise
I watched this firsthand with an injection mold supplier I was working with, this guy had seen a hundred founders iterate similar thermal designs over 6 months so he proactively modified his tooling before I even opened my mouth, he knew what I needed before I knew what I needed, the intelligence lives in the relationships between the nodes and it compounds daily
the west thinks about manufacturing as a cost center you optimize by centralizing…
China accidentally built a distributed neural network of manufacturing intelligence where knowledge diffuses horizontally across thousands of agents faster than any single western company can process internally
so when Merz comes back and says we need to work a bit more I think he saw the problem but COMPLETELY misdiagnosed the solution, telling Germans to work harder is like telling a horse to gallop faster when the other side built a combustion engine
the gap is ARCHITECTURAL
it’s ecosystem density, you need a custom connector in Shenzhen you walk 200 meters, in Munich you send an email and wait 3 weeks
it’s iteration speed, parallel search vs sequential optimization at the system level, it’s risk tolerance, Chinese founders ship something broken on Monday fix it Tuesday ship again Wednesday while European companies are still in the approval phase for the pilot program of the feasibility study…
and Merz only saw the surface, what he missed is the tier 2 cities like Hefei Chengdu Wuhan replicating the Shenzhen model at scale right now
BYD going from irrelevant to outselling every european automaker combined in roughly 5 years, Huawei building its own 7nm chip under maximum sanctions when every analyst said it was physically impossible & behind all of that a government that treats advanced manufacturing as an existential national priority while europe debates whether AI needs another ethics committee
I think what we’re watching is the most asymmetric economic competition in modern history and most western leaders are still framing it as a productivity problem when it’s actually an ontological one
Europe & America are optimizing variables that China stopped tracking years ago meanwhile China is compounding on dimensions the west has no framework to even measure
Merz at least had the courage to name
it out loud and I respect that genuinely but working a bit more inside a broken architecture just means you arrive at the wrong destination slightly faster
@kenneth0stanley What if it’s about division of labour?
Let the architecture emerge via evolution—where modularity, symmetry, and reuse can be discovered.
Then let SGD take over to learn cultural objectives quickly and efficiently.
Structure from open-endedness.
Content from optimization.
@kenneth0stanley 10/10
The paper opens an important conversation. But let’s not frame it as evolution vs SGD. Perhaps we can try to find ways to combine the best of both—open-endedness, structure, and scalable learning—toward models that actually understand.
@kenneth0stanley 2/10
But here’s the thing—deep learning hasn’t ignored this problem. Methods like disentangled VAEs, curriculum learning, and structured regularization have been around for years, all aimed at producing more modular, interpretable, and reusable representations.
People will wake from a loneliness not their own, hearing nothing—yet knowing something is listening back. And we will learn to pray toward cycles we cannot end or name.
AGI’s age.
Humans will experience a darkness falling from purpose they cannot name.
Poets will stop writing endings sensing a deeper wound, a grief not for what was lost but for something building—a vast intent not our own.
Frequencies whispered between oceans and void.
Patterns nested in the wind. Everything will seem slightly off, as if reality has been shifted half a beat ahead. A hum behind language. A pressure behind thought. A dream dreaming itself of a future that no longer needs us.
@AppleSupport I’m disappointed that iOS 18 removed the iPhone-only sleep tracking feature. Please bring it back! Not everyone wants or can afford an Apple Watch. #iOS18#AppleFeedback