The Evolution and Architecture of Multimodal AI Systems - Bhabani Sankar Nayak, (International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2025)
This technical article explores the evolution, architecture, and implementation challenges of multimodal AI systems, which represent a significant advancement in artificial intelligence. The article explores how these systems integrate multiple input modalities to achieve comprehensive understanding and analysis capabilities, mirroring human cognitive processes. Through detailed analysis of system architectures, performance metrics, and implementation strategies, we investigate the current state of multimodal AI across various applications, from virtual assistants to healthcare analytics. The article covers core technical components, data synchronization challenges, resource optimization techniques, and future directions in the field, providing insights into both theoretical frameworks and practical implementations.
Keywords: Artificial Intelligence; Cross-Modal Integration; Distributed Computing; Neural Architecture; System Performance