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Comment by ot | Hacker News Reader

Yeah the number sounds a lot less impressive if you say that you only get 2^61.44 integers out of 2^64. In other words, a 4% entropy loss.

Information quantities are more meaningfully expressed in number of bits.

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Exactly. Being precise about logarithmic vs linear utilizations is key here. I tried making a similar point about the inefficiency of IEEE-754 redundant NaN encodings here: https://arxiv.org/pdf/2508.05621

Having ~a quadrillion redundant bitstrings all mapping to NaN sounds pretty bad, but logarithmic/information utilization-wise, this is actually not too bad.

I've been looking at the 8087 NaN circuitry lately. Having 2^53 (or whatever) values for NaN was supposedly a feature: "the large number of NAN values that are available, provide the sophisticated programmer with a tool that can be applied to a variety of special situations." For example, the different NaN values could hold debugging information to track down errors.

See "8087 Numeric Data Processor" page S-74: https://ethw.org/w/images/2/2f/Intel_8086_family_users_numer...

You'll see some scripting languages (ab)use this. Where the native "number" type is a 64 bit float and only one NaN bit pattern is a real NaN. The others smuggle a pointer to an object in the lower bits. This way you don't spend any memory overhead indicating if a given variable contains a primitive or an object.

> For example, the different NaN values could hold debugging information to track down errors.

Unfortunately IEEE didn't bother specifying NaN propagation semantics so it ended up pretty useless.

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