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Neuroscientist Anil Seth proposes the hypothesis that certain forms of intelligence depend on consciousness embedded in time, and that algorithms may be unable to escape infinite loops. The evidence he gives is this: Turing proved in 1936 that no algorithm exists that can determine whether an arbitrary program will halt; life, by contrast, relies on metabolism and the free energy principle to reduce entropy, with the pressure to survive serving as a selection mechanism. Seth points out that digital computation concerns only state transitions and ignores the thermodynamic arrow; maintaining 0s and 1s requires error correction, leading to enormous AI energy consumption, and AI may terminate because it runs out of time or power first. He also doubts that approaches such as analog computing, dead computation, and neuromorphic computing will still find it difficult to achieve biologically-style open-ended intelligence, and holds that the imminent arrival of artificial general intelligence and AI consciousness is more like a pipe dream.
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Anil Seth proposes the hypothesis that algorithms cannot escape infinite loops
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Oct 23
Huxiu
Why don't humans get stuck in infinite loops? Neuroscientist Anil Seth on the infinite-loop limitations of AI
Neuroscientist Anil Seth argues that AI may never escape the risk of infinite loops, and the root cause lies in how Turing computation and biological brains differ in their relationship to time and entropy: Turing proved in 1936 that no algorithm can determine whether an arbitrary program will halt, whereas life reduces entropy through metabolism and the free energy principle, with survival pressure serving as a selection mechanism. Digital computation concerns only state transitions and ignores the thermodynamic arrow; maintaining 0s and 1s requires error correction, which makes AI enormously energy-hungry and may cause it to terminate first because time or battery power runs out. He doubts that paths such as analog computation, dead computation, and neuromorphic computation will still find it hard to achieve biologically-style open-ended intelligence, and that the imminence of artificial general intelligence and AI consciousness looks more like a pipe dream.