Edge AI Ecosystem Shaping: Constructing New Software Service Channels (pre-order)

Edge AI Ecosystem Shaping: Constructing New Software Service Channels (pre-order)

Table of Contents
1. The Drive for Timeliness: Shaping Edge AI
1.1 Natural Technological Evolution and Practical Demands in Edge AI
1.2 Edge AI's Resemblance to Edge Computing and Its Advantages
1.3 Edge AI Weaknesses Compared to Cloud AI
2. Global Hardware and Software brands' Aggressive Expansion into Edge AI
2.1 Chipmakers' Strategies in Edge AI
2.2 Startups in the Edge AI Space
2.3 Major Cloud Providers' Involvement in Edge AI
3. Edge AI Development Adapting to Multiple New Software Models
3.1 Cloud-Based Edge AI Development Tools
3.2 Diverse Approaches to Edge AI Inference Software: Embedded and Marketplace Routes
3.3 Diverse Approaches and Billing Methods in Edge AI Deployment
4.MIC Perspective
Appendix
List of Companies
List of Tables
Table 1: A Comparison of Characteristics between Cloud AI and Edge AI
List of Figures
Figure 1: Evolutionary Timeline of Edge Artificial Intelligence Technologies
Figure 2: Architecture and Principles of Horizontal Federated Learning Systems
Figure 3: Intel's Integration of OpenVINO Software to Support AI Acceleration Chips
Figure 4: Illustration of AWS IoT Greengrass ML Inference Service
Figure 5: SensiML SaaS Billing Model
Figure 6: Edge AI Utilizing Cloud Application Marketplace Delivery and Update Mechanisms

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