The term Scaling refers to "setting the stage to enable and support growth." Here are a few listicles that clearly explains "Top 4 scaling challenges in Edge AI." To know more, feel free to reach us at https://visailabs.com/

1. TOP 4 SCALING
CHALLENGES
IN EDGE AI

2. NETWORK
Cloud has a large Infra to
store data ( Video, Images
etc). But network
bandwidth for transporting
data is not scalable at the
edge esp. in remote and
congested areas
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3. STORAGE
Edge hardware has low
storage limits. Moving all
data to cloud is not
possible due to Bandwidth
problems. Also, in many
cases edge data is needed
only for a short time until
the AI processing is done
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4. PROCESSING
Sensor data such as 4K
video streams pose a heavy
computing workload. Cloud
might solve it. But this is
difficult to scale esp. if you
want real time responses.
We need to do processing
on the edge for low latency
applications
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5. SECURITY
A scalable data privacy
methodology for data
storage on edge networks
esp. in remote areas is the
need of the hour. Secure
storage & transmission of
data will define edges
growth in the near future.
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