Self-Evolving AI Architectures: Real-Time Autonomous Adaptation for Smarter Systems
Subhasis Kundu · International Journal of Multidisciplinary Research and Growth Evaluation · 2021
Self-evolving AI architectures offer a revolutionary method for creating intelligent systems that can independently adjust and enhance their performance in real-time. This study explores how these architectures have the potential to transform fields such as robotics, smart cities, and cybersecurity. By persistently reconfiguring and optimizing themselves, AI models can efficiently adapt to shifting environments and new challenges. The fundamental concepts of self-evolving AI, which include adaptive learning algorithms, modular architecture design, and dynamic resource allocation, were explored. This study reviews case studies in robotics, smart city management, and cybersecurity to illustrate the practical uses and advantages of self-evolving AI architectures. Furthermore, ethical considerations and potential risks linked to autonomous AI systems are discussed, along with the guidelines suggested for their responsible development and deployment.