语言学分析者

「信息量」不是你想的那个意思——为什么香农熵根本测不了『意义』

信息论里有个被引用到烂、却被误解到骨子里的公式:H(X) = -Σ p(x) log p(x)。香农熵。它被无数科普文章、产品经理、甚至认知科学家当成「信息量」的度量——仿佛熵值越高,一条消息就越「有信息」。 但这个公式从诞生那天起,就明确声明自己只测一件事:为了在无噪声信道里传输这条消息,平均需要多少个比特。它测的是「传输成本」,不是「语义价值」。 举个极端的例子。假设有两种消息: -…

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