Artificial Intelligence, Machine Learning, and Generative AI: Current Advances, Applications, and Future Perspectives
The rapid evolution of Artificial Intelligence (AI), Machine Learning (ML), and particularly Generative AI has marked a transformative era in technology development. Since the landmark release of ChatGPT in late 2022, generative AI technologies have experienced unprecedented growth, revolutionizing natural language processing, computer vision, and creative content generation. This paper provides a comprehensive review of recent developments in AI/ML and generative AI from 2023 to 2026, examining fundamental architectures including Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Diffusion Models (DMs). We explore cutting-edge applications across diverse domains including healthcare, education, finance, creative industries, and accessibility technology. The paper also addresses critical challenges including ethical concerns, job market implications, data limitations, and regulatory frameworks. Our analysis reveals that 2025 marks a pivotal year with the emergence of agentic AI and innovative approaches like Mixture of Experts (MoE) and reinforcement learning techniques. We conclude with future research directions and recommendations for responsible AI development and deployment.
Paper
The full text of this publication is not hosted on 44B due to licensing.
Read it at OpenAlex