inference is often a static, bounded problem solvable by generic compilers. training requires the mature ecosystem and numerical stability of cuda to handle mixed-precision operations. unless you rewrite the software from the ground up like Google but for most companies it's cheaper and faster to buy NVIDIA hardware

> static, bounded problem

What does it even mean in neural net context?

> numerical stability

also nice to expand a bit.