Microsoft Azure, page-295

Great find Uiux!

You're right, this sounds exactly like Akida and on-device learning. It is explicitly talking about spiking neural networks that are capable of learning patterns from remote (edge) devices.

As per the following extract:

[0038] In examples, the modifications to the original dataset may be made based on data that is received from one or more remote devices that are executing the neuromorphic model (e.g., smartwatch 108A, car 110A, smart phone 112A). This new data is illustrated as user data 114. For example, if first neuromorphic model 109A is being utilized to process heart beat signals, and smartwatch 108A receives a new heart beat pattern,that pattern may be sent to the neuromorphic synchronization service where the corresponding model can be can be retrained in the cloud and subsequently sent back out to smartwatch 108 A and other IoT devices hosting first neuromorphic model 109A.

From what I gather, here the device first has to detect / recognise that this is a new pattern. And we know from the Simon Thorpe talks that only Akida is capable of truly learning new patterns on it's own.