How a Low-Power Edge AI Chip Company is Driving Intelligence in Consumer Devices

As home security solutions such as security cameras are now used
in several households, there is an increasing need for AI
(Artificial Intelligence) inferencing at the edge. Typically, the
security solution relies on machine learning models to identify
objects or faces in the CCTV footage – for example
differentiating between a cat and a human. The data is then sent
to the cloud for analysis and sent back to the device. But this
can be problematic when there is poor internet
connectivity. 


Ergo, a tiny 7x7mm AI chip from a company called Perceive, aims
to solve issues with AI inferencing at the edge. The chip enables
rapid processing on edge devices, for example facial recognition,
or alerting to certain sounds, such as glass breaking or a dog
barking. This can trigger actions without resorting to
cloud-based systems. This type of solution can also offer
enhanced data security and user privacy, as the data does not
leave the device. The edge AI inference chips can be used in
connected devices such as smart speakers as well, where many
commands can be processed on the device, rather referring to the
cloud. There can be many other applications in the future
including drones, autonomous vehicles, and much more.  


In the latest episode of ‘The Counterpoint Podcast’, host Peter
Richardson is joined by David McIntyre, VP of Marketing at
Perceive. David talks about AI inferencing at the edge using a
tiny chip called Ergo. He deep dives into problems solved by
inferencing on edge devices over the cloud, use cases, and
savings made related to space onboard, costs and power. The
podcast discussion also focuses on potential applications where
solutions like Perceive’s Ergo chip can be used. 

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