Machine Learning (ML) is an application of Artificial Intelligence where a machine learns by itself or under supervision, without explicit programming. The system acquires the ability to learn and progress from experience sans compromising data accuracy spontaneously. Technological advancements enable ML cores to be embedded on a chip with multiple sensors. As discussed in a recent element14 tech spotlight, Learn About Inertial Sensors with a Machine Learning Core , the ML processing capability permits the transference of several algorithms from the host processor to the sensor itself.
Poll Question: How Beneficial Is It To Have Sensors with Machine Learning Cores?
Top Comments
Since adding some sensors doesn't increase the cost of the chips much, there is always the potential for accidental knowledge. Some processes do seem to have a personality. Maybe it's affected by temperature…
It is only beneficial, when there is the option to receive the processed and raw data. AI wanders off into Lala-land sometimes and there would be no way to double-check without the raw sensor data.
Sensors enable you to bring real world sensing applications.
They take you up a step from Hello World and Blinky to put some real useful application of the computer.
DAB