https://aiworldjournal.com/ais-race-to-learn-when-machines-learn-faster-than-nature-intended/

⚡ AI's Rapid Ascent: Energy, Ethics, and Evolution 1 source This article from AI World Journal examines the rapid acceleration of AI learning, noting its ability to achieve complex tasks like language mastery and image recognition far faster than human development. It highlights that AI systems are becoming self-teaching, constantly optimizing their own architectures. However, the piece also stresses the significant environmental cost of this progress, particularly the enormous electricity consumption required to train and run large AI models, which can surpass the energy use of many homes or even small nations. The journal proposes that balancing AI's growth with sustainability is crucial, advocating for energy-efficient innovations and emphasizing ethical considerations as AI intelligence becomes intertwined with data, computation, energy, and ethics.