Energy Efficiency Evaluation of Artificial Intelligence Algorithms

This article advances the discourse on sustainable and energy-efficient software by examining the performance and energy efficiency of intelligent algorithms within the framework of green and sustainable computing. Building on previous research, it explores the theoretical implications of Bremermann’s limit on efforts to enhance computer performance through more extensive methods. The study presents an empirical investigation into heuristic methods for search and optimisation, demonstrating the energy efficiency of various algorithms in both simple and complex tasks. It also identifies key factors influencing the energy consumption of algorithms and their potential impact on computational processes. Furthermore, the article discusses cognitive concepts and their interplay with computational intelligence, highlighting the role of cognition in the evolution of intelligent algorithms. The conclusion offers insights into the future directions of research in this area, emphasising the need for continued exploration of energy-efficient computing methodologies.