Post #2450314

2026-04-25 11:39 UTC

@steven_pigeon@mstdn.ca @BoydStephenSmithJr@hachyderm.io @rk@mastodon.well.com For this kind of topic especially, and at this stage in your research, I would suggest Gemini and ChatGPT, just because you can phrase your query into something harder to find than a search engine can handle. The LLMs can get you URLs for research and further reading if that’s how you work with them. Treat them as junior researchers — but there’s multiple talents, and multiple variants within each brand.

Replies (2)

@edwiebe@scribili.masto.host 2026-04-25 14:46

@whophd@ioc.exchange @steven_pigeon@mstdn.ca @BoydStephenSmithJr@hachyderm.io @rk@mastodon.well.com Good grief no.

Open ##2450315
@steven_pigeon@mstdn.ca 2026-04-25 17:59

@whophd@ioc.exchange @BoydStephenSmithJr@hachyderm.io @rk@mastodon.well.com I do not use AI because you spend more time verifying the output (or being annoyed at it) than actually using it. But just for the sake of argument, I tried. The answer I got: [starts by repeating the question, but getting it from the wrong end] The statistical distribution of floating-point magnitude in computation is influenced by the precision and range of the floating-point representation used. [Follows:] The IEEE 754 Standard, [then 10 more irrelevant lines, and 5 more about how floats work] [ends with] Understanding the statistical distribution of floating-point magnitude is crucial for developers to design code that is less susceptible to the pitfalls of floating-point computation and to implement techniques for statistical analysis to ensure numerical stability in scientific software. [True, but that given the question is the converse...] Then gives me a link to an unpublished, unreviewed paper that looks at how many projects use floats on github.

Open ##2450317