International Journal of Scientific Research and Engineering Development

Generative Artificial Intelligence (AI) has rapidly evolved from text-only models to sophisticated systems capable of producing high-quality images, audio, and video. The current frontier in 2025 is marked by a paradigm shift toward true multimodal integration, where models are designed to simultaneously process and generate across diverse modalities such as text, images, audio, video, 3D environments, and sensor data. This advancement enables richer contextual understanding, more natural human–AI interaction, and cross-domain applications in education, healthcare, entertainment, and robotics. Despite remarkable progress, several challenges remain, including hallucination control, dataset biases, computational efficiency, and the ethical implications of large-scale generative systems. Addressing these issues is crucial for building reliable, transparent, and sustainable multimodal AI. Looking ahead, generative multimodal models are expected to serve as the foundation for next-generation intelligent assistants, immersive virtual and augmented reality experiences, and AI-driven scientific discovery.

Chandan Ankushe, Shravan Saurkar, Dyaneshwar Wankhede, Prapti Pachghare, Neha Meshram,"The Rise of Generative Artificial Intelligence: Technologies, Applications, and Future Directions" International Journal of Scientific Research and Engineering Development, V9(2): Page(711-716) Mar-Apr 2026. ISSN: 2581-7175. www.ijsred.com. Published by Scientific and Academic Research Publishing.