The real difference between float32 and float64
float32 is less accurate but faster than float64, and flaot64 is more accurate than float32 but consumes more memory. If speed accuracy is more important, you can use float64, and if speed is more important than accuracy, you can use float32.
I want to understand the actual difference between float16 and float32 in terms of the result precision. For instance, Numpy allows you to choose the range of the datatype you want (np.float16, np.float32, np.float64). My concern is that if I decide to go with float 16 to reserve memory and avoid possible overflow, would that create a loss of the final results comparing with float32 for instance?
Thank you