AI systems that mimic human perception do not depend on a single sense. Similarly, your systems should integrate multiple modalities such as vision, language, and sensor data. This workshop focuses on the architecture, techniques, and deployment strategies for multimodal AI, enabling the development of more intelligent, responsive, and context-aware solutions.

What You'll Learn

• Architectural blueprints for integrating computer vision, NLP, and sensor data
• Cross-modal learning techniques for knowledge transfer across modalities
• Deployment strategies for edge, IoT, and resource-constrained environments

Key Takeaways

• Reference architectures and integration patterns for production-grade systems
• Evaluation frameworks to ensure coherent, high-performance multimodal behavior

Who Should Attend

• AI system architects and engineers
• IoT and edge computing specialists
• Product managers working on complex AI applications
• R&D teams exploring next-generation AI capabilities