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首先,The boundary between replication and originality occupies ambiguous territory. When confronted, demo artists typically reference universal "reference" usage. To non-artists this appears reasonable, but references differ from duplicating existing artworks. References assist visual comprehension and realism attainment, since nobody can accurately depict complex subjects like trains from memory alone.

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其次,As LLMs write more of our code, the value of TLA+ for design and reasoning will only grow. TLA+ has the potential to become a cornerstone in an AI+formal methods stack for building systems. The mental models I've described here are the foundation for that future. By mastering abstraction, embracing the global shared memory model, refining to local guards, deriving good invariants, exploring alternatives through refinement, aggressively refining atomicity, and sharing our mental models, we can unlock the full power of TLA+ to design better distributed systems in the age of AI.

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