Human brains process information in ways traditional computers cannot imitate
the verdict
INSUFFICIENT LEANING
refutedsupported
the weight of evidence
2 sources for · 0 against
The retrieved evidence includes studies noting divergences between machine language models and human brain responses, as well as philosophical arguments for hypercomputation in human cognition, but does not fully establish that human information processing is inherently impossible for traditional computers to imitate.
Do machines and humans process language in similar ways? Recent research has hinted at the affirmative, showing that human neural activity can be effectively predicted using the internal representations of language models (LMs). Although such results are thought to reflect shared computational principles between LMs and human brains, there are also clear differences in how LMs and humans represent and use language. In this work, we systematically explore the divergences between human and machine language processing by examining the differences between LM representations and human brain responses to language as measured by Magnetoencephalography (MEG) across two datasets in which subjects read and listened to narrative stories. Using an LLM-based data-driven approach, we identify two domains that LMs do not capture well: social/emotional intelligence and physical commonsense. We validate these findings with human behavioral experiments and hypothesize that the gap is due to insufficient representations of social/emotional and physical knowledge in LMs. Our results show that fine-tuning LMs on these domains can improve their alignment with human brain responses.
I'm a dualist; in fact, a substance dualist. Why? Myriad arguments compel me to believe as I do, some going back to Descartes. But some sound arguments for substance dualism are recent; and one of these, a new argument so far as I know, is given herein | one that exploits both the contemporary computational scene, and a long-established continuum of increasingly powerful computation, ranging from varieties \beneath" Turing machines to varieties well beyond them. This argument shows that the hypercomputational nature of human cognition implies that Descartes was right all along. Encapsulated, the implication runs as follows: If human persons are physical, then they are their brains (plus, perhaps, other central-nervous-system machinery; denote the composite object by `brains+'). But brains+, as most in AI and related fields correctly maintain, are information processors no more powerful than Turing machines. Since human persons hypercompute (i.e., they process information in ways beyond the reach of Turing machines), it follows that they aren't physical, i.e., that substance dualism holds. Needless to say, objections to this argument are considered and rebutted.
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