LLM 回复准确度的波动现象
用户提出了一个关于大语言模型回复质量波动原因的理论：认为运营商在高峰期会逐渐降低处理深度以减轻服务器负载，并提到近几个月在 Claude 上频繁观察到这一现象，希望听取 HN 社区的看法。
相关报道
At Sequoia Ascent 2026, Andrej Karpathy argued LLMs enable new horizons beyond speeding up existing tasks, like fully LLM-native apps and knowledge bases impossible with classical code. He also discussed the "jaggedness" of LLM capabilities and the emerging agent-native economy splitting products into sensors, actuators, and logic.