Real-World AI Systems

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📝 征稿方向

• The scope of Real-World AI Systems includes, but is not limited to, the following research areas:
• - AI Deployment & Scalability
• - Large-scale AI system integration
• - Edge AI and distributed computing
• - AI in resource-constrained environments
• - Domain-Specific AI Applications
• - AI in healthcare (diagnostics, treatment planning, etc.)
• - AI for smart cities and infrastructure
• - Industrial AI (predictive maintenance, automation, etc.)
• - AI in finance and business analytics
• - Ethical, Legal & Social Implications
• - Fairness, bias, and accountability in AI systems
• - Regulatory and policy frameworks for AI deployment
• - Societal impact and public trust in AI technologies
• - AI System Robustness & Reliability
• - Adversarial robustness and security
• - Explainable AI (XAI) and interpretability
• - Testing, validation, and certification of AI systems
• - Human-AI Collaboration
• - Human-in-the-loop AI systems
• - AI for decision support and augmentation
• - User experience and interaction design for AI applications

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