PyTorch DevCon: Facebook AI Bets Big On Optimisation & Privacy

At the recently-concluded PyTorch DevCon, the team released updates that can probably cement PyTorch position as one of the top frameworks for machine learning. The new release includes experimental support for features such as seamless model deployment to mobile devices, model quantization for better performance at inference time, and front-end improvements along with a number of additional tools and libraries to support model interpretability and bringing multimodal research to production. To play down the reputation of ML models as black models, the developers at PyTorch introduced a new tool called Captum. This tool enables the users to visualise what their models are detecting. For example, when an image, say of an animal is given, it visualize the attributions for each pixel by overlaying them on the image as can be seen in the picture above.