@rayofhk: The smarter AI becomes, the more physical dependencies it may inherit. We often describe AI as if intelligence itself were the product. But once intelligence leaves the screen and enters the physical world, the architecture changes. Training can remain centralized in enormous data centers. Intelligence can increasingly be distributed into smaller machines. But deployment has to survive reality. A humanoid robot doesn’t run on intelligence alone. It depends on chips, sensors, actuators, batteries, materials, manufacturing, electricity, maintenance, supply chains — and ultimately human trust. This is why Physical AI becomes particularly interesting through my Six-Layer AI Ecosystem Model. Intelligence, compute, chips, physical infrastructure, energy, and capital/governance/coordination are no longer separate stories. They have to work together inside one moving machine. And the more capable that machine becomes, the more consequential each dependency can become. This creates an interesting paradox: AI may become more intelligent digitally — while becoming more dependent physically. So perhaps the Physical AI race will not be won simply by whoever builds the smartest model. It may be won by whoever can coordinate the entire stack most effectively. Training can be centralized. Intelligence can be distributed. But deployment must survive reality. #AI #PhysicalAI #HumanoidRobots #Robotics #SixLayerAIModel

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Friday 04 September 2026 05:30:46 GMT