Artificial intelligence has grown rapidly in recent years, with four key areas leading this progress: Natural Language Processing (NLP), Computer Vision (CV), Deep Learning, and Agentic AI. While each area has seen remarkable advances on its own, they are usually studied separately. This creates a gap in understanding how these technologies can work together to build truly intelligent systems. This paper reviews recent developments across all four areas and proposes the Integrated Multimodal Autonomous Intelligence (IMAI) framework — a six-layer architecture that brings together perception, understanding, reasoning, action, memory, and safety into one unified system. By examining over 30 key contributions and their real-world applications in healthcare, autonomous driving, manufacturing, enterprise systems, and scientific research, the paper shows how combining these AI pillars can produce systems that are more capable, reliable, and safe than any single technology alone.
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