Laziness Fuses Kernels and Cuts Memory Access

Tinygrad uses laziness like Haskell: instead of computing A times B immediately and storing it to memory, it waits until the user realizes the tensor, allowing the plus C operation to be fused into one kernel, which eliminates the excessive loads and stores to memory that PyTorch incurs.