We have published a pre print, here we discuss the use of how Quantized Fixed precision weights neural network have more understanding of training dataset than float 32 weights weights achieved 6% less training loss and more generalization on the same dataset.
This is major step towards bridging the gap between silicon intelligence and carbon based intelligence.
