The artificial intelligence sector is grappling with escalating energy demands, prompting a race to find solutions. Tech companies are exploring multiple avenues to curb AI's power consumption, including advanced cooling technologies, more efficient chip designs, and optimised programming techniques.
One promising approach involves on-device AI processing, which can slash energy use by 100 to 1,000 times compared to cloud-based AI. Other strategies include model pruning, quantization, and the integration of renewable energy sources. Researchers are also developing AI training methods that are significantly faster and more energy-efficient. Practical changes, such as reducing the number of decimal places in AI models and shortening AI responses, could also substantially reduce energy consumption.
These efforts aim to mitigate the environmental impact and operational costs associated with AI, ensuring a more sustainable future for the technology. Startups are also pioneering energy-efficient AI technologies, and some are promoting the adoption of energy-efficient AI through energy credit trading systems.
