This week on PULSE, we chatted with Dino Bekis, Vice President and General Manager of Wearables at Qualcomm.
If you’re unfamiliar with Qualcomm, the company’s Snapdragon processors have largely powered Wear OS smartwatches from the very beginning.
Its latest chips - the W5+ and W5 - have also had a huge hand in the resurgent Google platform, laying the foundation for strong battery life performances from the TicWatch Pro 5 and OnePlus Watch 2.
But Qualcomm’s presence in wearables is much deeper than that.
It also runs the Wearables Ecosystem Accelerator Program, which brings together 200 companies across the wearables industry to exchange knowledge and services - all unified by the Qualcomm platform.
The new challenges of powering the AI features promised by tech companies and wearables makers will come down to companies like Qualcomm providing the processing power.
PULSE got the inside track on how it views this future.
Covered in this podcast:
00:00: Qualcomm's Wearables Philosophy
03:22: The Broad Scope of Wearables and the Qualcomm Wearable Ecosystem Accelerator Program
12:08: AI in Wearables
16:33: Hybrid AI Power
34:48: Snapdragon W5 and W5+ – and how Wear OS could still offer even longer battery life
39:33: RISC-V and Smartwatches
42:23: The Future of Wearables: Advanced Health Monitoring and Improved Connectivity
Key Takeaways
The wearables market is growing in size and complexity, beyond smartwatches. Areas such as pet trackers, kids’ watches, senior’s watches, and health monitoring devices are all making big advances.
Qualcomm is focused on improving battery life and power consumption on wearables, as well as exploring the potential of on-device AI processing.
A big trend is AI in wearables, and having devices blend into the background. On-device processing is crucial to avoid the challenges faced by devices such as the Humane AI Pin.
On-device AI is a big challenge for processor platforms and power management, but hybrid systems offer a way to do this effectively.
The future of wearables will be driven by medical-grade sensors and low-power, always-on connectivity, which can power hybrid AI processing. It will also enable users to use their own devices on a personal device cloud.
