Bhushan has optimized and deployed more than 1000s of AI models on-device on iOS and Android ecosystem.
Currently, He is building AI Hub at Qualcomm to make on-device journey on Android and Snapdragon platform as seamless as possible.
Previously, he worked on Apple on CoreML framework and helped deployed various system and developer use cases. He also worked at Nvidia in GPU compiler focusing on optimizing code generation for CUDA and graphics load (e.g. Nintendo and Nvidia Shield).
Bhushan Sonawane
Staff ML Engineer, Qualcomm
How to use Qualcomm AI Hub for On-Device AI models
In this workshop we address the common challenges faced by developers migrating AI workloads from the cloud to edge devices. Qualcomm aims to democratize AI at the edge, easing the transition to the edge by supporting familiar frameworks and data types.
In this session, developers can follow along, gaining knowledge and tools to efficiently deploy optimized models on real devices using Qualcomm AI Hub.
We'll walk through how to get started using Qualcomm AI Hub, iterate on your model and meet performance requirements to deploy on device! We'll show examples on how to optimize models and bundle the downloadable target asset into your application.