Closes #421

Co-authored-by: jrcavani <[email protected]>

Closes #450

Co-authored-by: Michał Bartoszkiewicz <[email protected]>

This commit exposes the underlying SimSIMD `bf16`
kernels for distance functions, that can be up to 3x faster
than IEEE half-precision floats for different multiplication-
intensive operations. It also brings backwards-compatibility
for older CPUs, that don't yet support `bf16`.

Important to note, NumPy still doesn't support half-precision,
so we can't reliably guess what the name of the `bf16` type
will be in the buffer protocol specifications.
numpy/numpy#19808