Generative AI's Dirty Secret

BITAN MISRA IS AN ASSISTANT PROFESSOR, NILANJAN DEY IS AN ASSOCIATE PROFESSOR, BOTH AT DEPT OF COMPUTER SCIENCE & ENGINEERING, TECHNO INTERNATIONAL NEW TOWN, KOLKATA

- BITAN MISRA & NILANJAN DEY

The swift expansion of artificial intelligence (AI), namely, generative AI and large-language models (LLMs), has caught many people off guard, but the effects on the environment continue to be a major concern. This surge has raised concerns about the strain on electrical systems due to the increasing electricity consumption of data centers. Large language models require tens of thousands of sophisticated high-performance computers to handle and analyze enormous volumes of data. Once trained, these models can make predictions about fresh data and answer questions. Specialized electrical circuits called graphics processing units (GPUs) are widely used because they can perform many calculations or processes simultaneously, but they use more energy than many other types of processors do.

One problem is that the carbon footprint of artificial intelligence has not received enough attention. While there are growing initiatives to incorporate renewable energy supplies, the majority of data centers currently function around the clock and are powered by conventional energy sources. Data centers are responsible for 2.5–3.7% of worldwide greenhouse gas emissions due to their energy consumption, which is greater than that of the aviation sector. Nearly one hundred million people were using ChatGPT a few weeks after it launched. Many individuals are keen to use AI for every purpose instead of using the current web searches that depend on simpler AI models; however, according to one tech professional, a single ChatGPT query could consume 100 times as much energy as a single Google search.