Competitive landscape, page-3392

https://patents.google.com/patent/US20210312257A1/en

Distributed neuromorphic infrastructure

In non-limiting examples of the present disclosure, systems, methods and devices for synchronizing neuromorphic models are presented. A sensor input may be received by a first neuromorphic model implemented on a neuromorphic architecture of a first computing device. The neuromorphic model may comprise a plurality of neurons, with each of the plurality of neurons associated with a threshold value, a weight value, and a refractory period value. The first sensor input may be processed by the first model. A first output value may be determined based on the processing. The model may be modified via modification of one or more threshold values, weight values, and/or refractory period values. A modified version of the first neuromorphic model may be saved to the first computing device based on the modification. An update comprising the modification may be sent to a second computing device hosting the model.

BACKGROUND
Neuromorphic artificial intelligence (AI), also known as neuromorphic computing, is an approach to AI that mimics how mammal brains process information. The approach is characterized with less demands on power to perform similar tasks performed by other AI approaches (e.g., speech recognition), and in-situ training. It is with respect to this general technical environment that aspects of the present technology disclosed herein have been contemplated. Furthermore, although a general environment has been discussed, it should be understood that the examples described herein should not be limited to the general environment identified in the background.




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Microsoft have this pending patent.

how many devices listed in this thread are relevant?

Renesas
Megachips
BrainChip
Graimatter labs

SynSense

any other neuromorphic companies I missed @shareman ?



i find it compares nicely with a statement on the BrainChip homepage:

Making AI Ubiquitous
Take a step toward fundamental AIoT. When you combine advanced IoT infrastructure with Artificial Intelligence technologies inspired by the human brain, you get more efficient operation, proactive problem solving, better human to machine interactions, and improved security. The key to growing AI everywhere is making it easier to deploy and scale. This requires lower costs, cloud independence, and intelligence that’s close to the sensor.Brainchip’s holistic, distributed approach frees up the cloud and creates an explosion of capable, intelligent sensing devices on the Edge that accelerate global artificial intelligence.

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What I find most interesting is the specific reference to "in-situ training" in the patent. It appears to focus around the concept of devices learning in the field, syncing models to the cloud and then syncing to other devices in the field.

BrainChip is still referring to on-chip learning as a "unique ability":

https://brainchip.com/wp-content/uploads/2023/03/BrainChip_second_generation_Platform_Brief.pdf

On-chip learning: Unique ability to learn and extend classes on the device; secure and untethered from the cloud


Renesas partnered with Microsoft already

https://www.renesas.com/us/en/about/press-room/renesas-collaborates-microsoft-accelerate-connected-vehicle-development

is this something to watch for in the future? Will Renesas SNN chip find a home within a distributed neuromorphic infrastructure built by Microsoft?