Central planning is unbeatable as a resource allocation mechanism for small systems. As you attempt to scale it up, it becomes terribly ineffective, to such an extent that decentralized control algorithms wastly outperform it, despite being inherently wasteful
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This is tightly related to AI as well: it's the question of local vs. global optimization in a non-differentiable system, open-ended goal-setting, objective propagation from one module to its neighbors, parent, and internal submodules...
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Backprop is a centralized answer, that only applies to differentiable functions where "control" means adjusting some parameters and where the optimization objective is already known. Its range of applicability is minuscule
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Do you think central planning by governments will become more desirable because of technology?
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"government" as we understand it is a specific technology, and it has shown not to be able to do large-scale central planning. I think increasingly centralized systems will be a long-term trend, driven by technology, but it may not look like governments as we know them
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"Communism can work, it just lacked enough GPUs in the past."
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So ... as a person with leftist convictions that started a successful company, I have opinions on this. The experience of markets as decentralized resource allocation has deeply influenced my thinking. Thread:
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The experience of being 23 years old, having no business experience, but building something people wanted, was extremely influential. It would have been near-impossible for me to convince "established" forces to allocate resources to what I was doing.
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Maybe because centralized planers have difficulties at integrating (local) small-scale information and acting towards it separately?
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It is interesting watching blockchain governance playing out..
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The problem of central planning is not only about information processing, it's about information discovery, tacit and dispersed knowledge.
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