Qualcomm

This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. In Exploring AIMET’s Post-Training Quantization Methods, we discussed Cross-layer Equalization (CLE), Bias Correction, and AdaRound in AIMET. Using these methods, the weights and activations of neural network models can be reduced to lower bit-width representations, thus reducing […]

This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. Usually, when you’re presented with three options, such as powerful, efficient, and low cost, you’re also faced with the conundrum where you’re only allowed to pick one or two. Machine learning (ML) practitioners developing neural networks for

On-device intelligence provides important benefits. This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. Our latest AI research to personalize and adapt models while keeping data private One size doesn’t fit all. The need for intelligent, personalized experiences powered by AI is ever-growing. Our devices are