Overview

""Next-Gen AI: Concepts, Tools, and Research Perspectives"" offers a comprehensive exploration of the evolving landscape of Artificial Intelligence. This work delves into the theoretical foundations that underpin modern AI systems, highlighting advancements in neural networks, deep learning, reinforcement learning, and generative models. It examines cutting-edge tools and platforms shaping AI research and deployment, including frameworks like TensorFlow, PyTorch, and AutoML. The paper emphasizes transformative real-world applications across diverse sectors-healthcare, education, finance, manufacturing, and governance-demonstrating AI's role in automating decision-making, enhancing efficiency, and fostering innovation. It also addresses critical research challenges such as bias, explainability, ethics, and data governance. By bridging theory, tools, and practice, this work provides valuable insights into the future trajectory of AI and its profound impact on both academic research and industry ecosystems.

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