From the course: Edge AI: Tools and Best Practices for Building AI Applications at the Edge
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Benefits and challenges of edge AI
From the course: Edge AI: Tools and Best Practices for Building AI Applications at the Edge
Benefits and challenges of edge AI
- [Instructor] What are the benefits and challenges with Edge AI? How does it compare with the challenges we discussed for general Edge computing? The benefits and challenges of Edge computing we discussed in the earlier video also accrue to Edge AI. In many cases, they are magnified. What are the special benefits? We can predict and trigger actions in real time at the Edge devices without dependencies on the central compute center or connectivity. This is especially useful when low latency is needed and action need to be taken at real time. Edge AI requires low or no bandwidth to connect to the cloud, so predictions are not impacted by its availability. AI can perform independently without dependency on the cloud. Also, input data used for inference stays private and is not shared to cloud resources. This helps in building AI use cases that use personal data without having to deal with security and privacy…
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