> Interesting approach, rather than normalize to 1 it normalizes to the largest whole number. The positives of this are that you don't run into issues with encoding things like .1 that you do in binary
Nonsense. Binary floating-point too normalizes to the largest possible significand. It then omits the leading 1 from the representation, since the leading 1 is by definition a 1. That this trick is simple to pull in binary is only one of the advantages of a base-2 floating-point representation.
The fact that 0.1 is not representable in binary has nothing to do with the choice of representing it as 0x1999999999999a * 2^-56, because it already is, and that does not make it representable.
Nonsense. Binary floating-point too normalizes to the largest possible significand. It then omits the leading 1 from the representation, since the leading 1 is by definition a 1. That this trick is simple to pull in binary is only one of the advantages of a base-2 floating-point representation.
The fact that 0.1 is not representable in binary has nothing to do with the choice of representing it as 0x1999999999999a * 2^-56, because it already is, and that does not make it representable.