Engineering Flaws Plague Generative AI Systems

A critical perspective argues that generative AI suffers from fundamental engineering problems, including poor error handling, non-deterministic outputs, and high computational inefficiency. This matters because it underscores the gap between AI's promises and real-world reliability, potentially impacting trust and investment in the technology.

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