Well here we go again another train incident dampening productivity and more reports on how this occurred.
I'm positive with the implementation of Akida this would not of occurred.
To quote PVDM,
The design is optimized for high-performance Machine Learning applications, resulting in efficient, low power consumption while performing thousands of operations simultaneously on each phase of the 300 MHz clock cycle. A unique feature of the Akida neural processor is the ability to learn in real time, allowing products to be conveniently configured in the field without cloud access.
And what about Socionext, as shares for brekky posted.
BrainChip’s flexible AI processing fabric IP delivers neuromorphic, event-based computation, enabling ultimate performance while minimizing silicon footprint and power consumption. Sensor data can be analyzed in real-time with distributed, high-performance and low-power edge inferencing, resulting in improved response time and reduced energy consumption.
View attachment 26929
Edge Compute.