disambiguate the objects of in- terest . That allowed us to also eliminate a substantial , up to 95 %, amount of nuisance alarms while maintaining a very high level of detection .
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Another important lesson that we take to heart is the AI-assur- ance .
As the GPUs and batteries are getting cheaper , lower power , and better , certain tasks can be performed at the edge , thus allowing to avoid transmitting a large amount of video to the central C5ISR and deliver only the actionable detections pro- cessed by the AI-enabled em- bedded vision cameras .
It is important that we always remember to continue to vali- date how much confidence we have in the existing system and remind ourselves that AI can do wrong things and it can learn wrong things . Those errors can have big implications .
The decision of whether to use embedded systems , edge de- vices , cloud , or hybrid approach depends on the image reso- lution , speed of networks and
Analytics at the Edge
In the past several years a trend of edge comput- ing is on the rise .
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