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Philosophers such as Raphaël Millière and Cameron Buckner have argued that LLMs could serve as potential models of certain aspects

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There may also be “parallels” between how LLMs and humans represent language, Ivanova said.

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Silicon Valley has long had its own dialect. “I’ve been telling my wife I have context rot for months,” Conor Bronsdon, the host of an AI-focused podcast, told me. Where the reporter live, in San Francisco, such comparisons are inescapable. “I’ve described myself as high temperature,” a friend recently told me; in AI-speak, this means he is prone to randomness. Such speech easily comes off as unsettling, if not aggressively bleak: Why describe beautiful, tender life in detached, algorithmic terms? The comparisons took off a few years ago, after a group of AI researchers argued that language models are “stochastic parrots” that link together language based on statistical patterns without possessing any understanding of meaning. Language has historically evolved alongside technology.

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