Running machine learning (ML) models on Lens Studio and Spectacles can expand creators’ abilities to design powerful and robust AR experiences. However, one of the biggest constraints of running ML models on devices is power consumption. In order to minimize the power consumption of running ML models, running ML models on a digital signal processor (DSP) is the best solution because DSP is the most power efficient IP.
Up until now, SnapML has been supporting float models. For models to run on DSP however, they need to be quantized. We are therefore introducing quantization support through SnapML.
There are three major benefits for creators to use quantized models:
- Fast inference speed
- Small model size
- Increased power efficiency.