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    > The title would be better suited if they included a higher number of HPC/ML/etc software engineers (post PhD) that work on larger scale projects in industry/labs.
If someone needs to be a "post PhD" software engineer working on large scale computation projects in industry to be considered "a developer" whose problems with floating point are worth investigating and dealing with, then we have a problem of definition.

Their premise is that if folks in academia are having a hard time with it, then perhaps the training and tooling around floating point needs some reconsideration. That seems very reasonable to me.




>Their premise is that if folks in academia are having a hard time with it, then perhaps the training and tooling around floating point needs some reconsideration

There's been 50+ years of this reconsideration. Some problems are simply hard, and perhaps nothing will make it easier than to simply learn the nuances.

For some domains, there are some solutions, like BigInt to avoid overflow, but each comes with other tradeoffs.

For general floating-point, it's mathematically quite likely there is no better tradeoff. You cannot stuff infinite values into finite space.




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