QUALCOMM
PARTNERSHIP WITH AIZIP
Privacy and intelligence for the user The shift away from using big models and cloud-only AI inference to smaller models and AI run directly on devices is driven by three primary factors:
• The need for real-time responsiveness
• Increasing privacy expectations
• The cost of scaling cloud infrastructure.
Privacy and security is an advantage to edge AI.“ The data stays on device and reduces exposure risk, like a healthcare variable that can process sensitive biometric data locally without sending it to the cloud,” Vinesh explains.“ You have lower latency and better quality of service, especially when you want to have real-time responses. This is critical for use cases like autonomous robots, or even physical AI navigating a factory floor.
Qualcomm Technologies and Aizip have partnered to develop efficient, production-grade AI models, specifically tailored for resourceconstrained edge and endpoint devices. The companies have optimized Aizip’ s machine learning models for Qualcomm Technologies’ hardware, bringing agent-driven experiences and on-deviceintelligence across wearable and IoT devices.
Vinesh says:“ Qualcomm’ s collaboration with Aizip AI highlights the move towards efficient on-device AI. Aizip specialises in compact, highly optimised AI models that can run on resource-constrained devices, especially voice, vision, language capabilities on the edge.
“ Together, the focus is to really make sure that we can bring advanced AI capabilities directly on devices, especially powered by Qualcomm platforms, thereby driving real-time, privacy-preserving experiences without relying on cloud compute, which is extremely important for us to scale.”