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