It is estimated that the energy consumption of artificial intelligence technology is equivalent to 1% of the global electricity demand. Moreover, due to the characteristics of artificial intelligence technology, its energy consumption is mainly concentrated in the two links of training models and inference. These links require high-power computing equipment, data centers and storage devices, and the energy consumption and carbon emissions of these devices have put tremendous pressure on the environment.
Energy-saving technologies: Researchers are exploring various energy-saving technologies, including model compression, network pruning, low-precision computing, model quantization, and other methods to reduce the computing resources and energy consumption required for model training and inference.
Environmentally friendly hardware: Researchers are exploring iceland mobile database more environmentally friendly hardware, including the use of renewable energy, low-power chips, superconducting computers, and other methods to reduce the impact of computing devices on the environment.
Interdisciplinary cooperation: Energy consumption and environmental issues are complex and systemic, requiring cooperation and joint efforts among various disciplines. Experts from multiple fields such as computer science, environmental science, and energy engineering need to think and study this issue together to find more effective and sustainable solutions.
Energy consumption and environmental issues are an important challenge facing the current development of artificial intelligence technology. Although some solutions have emerged, they still need to be promoted and improved at the technical, policy and social levels to achieve the sustainable development and application of artificial intelligence technology.