How CPUs will address the energy challenges of generative AI [Video]

The vast majority of company leaders (98%) recognize the strategic importance of AI, with nearly 65% planning increased investments. Global AI spending is expected to reach $300 billion by 2026. Also by 2026, AI’s electricity usage could increase tenfold, according to the International Energy Agency. Clearly, AI presents businesses with a dual challenge: maximizing AI’s capabilities while minimizing its environmental impact.

In the United States alone, power consumption by data centers is expected to double by 2030, reaching 35GW (gigawatts), primarily due to the growing demand for AI technologies. This increase is largely driven by the deployment of AI-ready racks, which consume an excessive 40kW to 60kW (kilowatts) each due to their GPU-intensive processes.

There are three main strategies available to address these looming energy challenges effectively:

1. Selecting the right computing resources for AI workloads, with a focus on distinguishing between training and inference needs.
2. Optimizing performance and energy efficiency within existing data center footprints.
3. Fostering sustainable …