2021 BRN Discussion, page-4774

But But

https://www.nextplatform.com/2021/03/30/arms-v9-architecture-explains-why-nvidia-needs-to-buy-it/

Jem Davies, an Arm Fellow and general manager of its machine learning division, gave a perfect example of the economic forces that are driving compute out of the datacenter and into a more diffuse data galaxy, as we called it three years ago.

“In the Armv9 decade, partners will create a future enabled by Arm AI with more ML on device,” Davies explained. “With over eight billion voice assistive devices. We need speech recognition on sub-$1 microcontrollers. Processing everything on server just doesn’t work, physically or financially. Cloud computing bandwidth aren’t free and recognition on device is the only way. A voice activated coffee maker using cloud services used ten times a day would cost the device maker around $15 per year per appliance. Computing ML on device also benefits latency, reliability and, crucially, security.”