science

Matthias Scheutz, Karol Family Applied Technology Professor, compared this inefficiency to everyday AI tools. "These systems are just trying to predict the next word or action in a sequence, but that can be imperfect, and they can come up with inaccurate results or hallucinations. Their energy expense is often disproportionate to the task. For example, when you search on Google, the AI summary at the top of the page consumes up to 100 times more energy than the generation of the website listings."

As AI adoption accelerates across industries, demand for computing power continues to climb. Companies are building increasingly large data centers, some of which require hundreds of megawatts of electricity. That level of consumption can exceed the needs of entire small cities.