OpenAI describes GPT-5 Pro as using "scaled but efficient parallel test-time compute." Nathan Lambert on Lex Fridman #490 discusses the broader pattern of inference-time scaling: giving models more compute at generation time to explore multiple reasoning paths. ↩
To be clear: this is just what I think. I’ve found it useful to categorize errors this way. If you think about errors differently, (1) I’d love to hear it (2) I’m glad you’re thinking about error handling in software.
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