Overview
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Learn how to transition multimodal conversational agents from prototype demonstrations to production-ready deployments in this 19-minute conference talk. Explore the fundamental shift toward multimodal AI systems and discover a comprehensive framework for scaling conversational agents that can process text, voice, images, and other data types. Examine production-grade reference architectures and master ingestion and fusion strategies for handling diverse data inputs effectively. Understand evaluation methodologies that extend beyond traditional text-based metrics to assess multimodal performance accurately. Gain insights into observability practices and incident readiness protocols essential for maintaining robust multimodal systems in production environments. Review real-world deployment patterns and identify key success factors that determine whether multimodal conversational agents will thrive in production settings. Access practical guidance for DevOps teams responsible for deploying and maintaining sophisticated AI systems that interact with users through multiple communication channels simultaneously.
Syllabus
Introduction to Multimodal Conversational Agents
Understanding the Multimodal Shift
Framework for Moving from Demo to Deployment
Production Grade Reference Architecture
Ingestion and Fusion Strategies
Evaluation Beyond Text
Observability and Incident Readiness
Real-World Deployment Patterns
Key Success Factors for Production
Final Takeaways and Conclusion
Taught by
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