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The Decoherence Trap: When AI slop drowns out the signal in an endless sea of noise
Maevyn introduces decoherence: the build-up of locally valid but mutually incompatible or redundant models inside a system, so that the cost of change is dominated by translating between them. The essay argues it compounds with a system's rate of change, that AI is producing it faster than ever, and that this rules out a runaway intelligence explosion.
39 min · 8,856 words