Mastering Multi-Modal AI: From Vision Transformers to Real-World MLOps

What if your next AI project could see, read, and understand—just like a human? 🤖 In this episode, we go beyond plug-and-play APIs to unlock the true power of Multi-Modal AI. Whether you're decoding computer vision, exploring vision transformers, or fusing images and text using models like CLIP, this podcast breaks down what it really takes to build production-ready AI with MLOps-first thinking. Guys, for getting more deepdive, follow the detailed article below https://open.substack.com/pub/iitmeng... Ready to go from AI hobbyist to full-stack multimodal architect? This podcast is your blueprint. We cover: The fundamentals of Computer Vision (CV): from pixels to object segmentation Deep learning architecture: CNNs vs. Vision Transformers (ViTs) Model explainability and trust Multi-modal learning: combining images and text with models like CLIP Step-by-step guide to deploying production-grade multi-modal systems MLOps, data pipelines, and deployment best practices Whether you're a machine learning engineer, data scientist, or a founder looking to operationalize AI, this is your complete guide to building smarter, scalable, multi-modal apps. 👉 Don’t forget to like, subscribe, and share if this helped sharpen your edge in AI! #BuildWithMultiModalAI