This text provides an in-depth analysis of the contemporary paradigm of AI development, known as the scaling doctrine. The author deconstructs the technical assumptions that exponential growth in computing power, data volume, and parameter counts leads to breakthrough moments of emergence. The analysis goes beyond engineering, examining the metaphysical aspects of the pursuit of AGI and the political consequences of the concentration of infrastructure capital in the hands of tech giants. It discusses the mechanisms of the data flywheel, the shift in the scientific paradigm toward statistical correlation epistemology, and the ethical risks associated with iterative model deployment within the global AI arms race. This is crucial reading for understanding the mechanisms shaping the digital future.
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