Building Edge AI Stack and AI-as-a-Service in Cloud Native Way

Building Edge AI Stack and AI-as-a-Service in Cloud Native Way

Linux Foundation via YouTube Direct link

KubeEdge-AI

9 of 16

9 of 16

KubeEdge-AI

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Building Edge AI Stack and AI-as-a-Service in Cloud Native Way

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  1. 1 Intro
  2. 2 Problem and Challenges
  3. 3 Background
  4. 4 KubeEdge Architecture
  5. 5 Akraino KubeEdge Edge Service Blueprint
  6. 6 KubeEdge ML Offloading Functional Block Diagram
  7. 7 Use Case: Device App ML model inference offloading workflow
  8. 8 Edge Al Challenges
  9. 9 KubeEdge-AI
  10. 10 Service Architecture
  11. 11 Edge-cloud Collaborative JOINT INFERENCE Improve the inference performance, when edge resources are imited
  12. 12 Edge-cloud Collaborative INCREMENTAL LEARNING The more models are used the smarter they are
  13. 13 Edge-cloud collaborative FEDERATED LEARNING Raw data is not transmitted out of the edge, and the model is generated by
  14. 14 Developer perspective: JOINT INFERENCE
  15. 15 Developer perspective: FEDERATED LEARNING
  16. 16 Resource Information

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