Enterprise users are prioritizing AI performance over energy efficiency, according to a survey by Inference, CPU specialists. This is concerning, as AI systems are becoming increasingly power-hungry. In fact, training state-of-the-art AI models can cost upwards of $78 million, with some models like Google's Gemini Ultra costing $191 million.
The survey's findings suggest that companies are more focused on leveraging AI for business benefits than on reducing their environmental footprint. However, this approach may not be sustainable in the long run, as the energy consumption of AI systems continues to grow.
It's worth noting that the AI community is becoming more aware of the need for responsible AI development and deployment. Researchers are exploring ways to improve AI's environmental sustainability, such as developing more energy-efficient algorithms and hardware.
