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Why is AI moving from the cloud to our devices, and what makes on device intelligence finally practical at scale?

In this episode of Eye on AI, host Craig Smith speaks with Christopher Bergey, Executive Vice President of Arm's Edge AI Business Unit, about how edge AI is reshaping computing across smartphones, PCs, wearables, cars, and everyday devices.

We explore how ARM v9 enables AI inference at the edge, why heterogeneous computing across CPUs, GPUs, and NPUs matters, and how developers can balance performance, power, memory, and latency. Learn why memory bandwidth has become the biggest bottleneck for AI, how ARM approaches scalable matrix extensions, and what trade offs exist between accelerators and traditional CPU based AI workloads.

You will also hear real world examples of edge AI in action, from smart cameras and hearing aids to XR devices, robotics, and in car systems. The conversation looks ahead to a future where intelligence is embedded into everything you use, where AI becomes the default interface, and why reliable, low latency, on device AI is essential for creating experiences users actually trust.

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#308 Christopher Bergey: How ARM Enables AI to Run Directly on Devices

Eye On A.I.

#308 Christopher Bergey: How ARM Enables AI to Run Directly on Devices