The burgeoning field of generative artificial intelligence (AI), exemplified by tools like OpenAI’s ChatGPT, is bringing to light a critical environmental concern: the increasing water footprint of major technology companies.
What Happened: A study led by Shaolei Ren, a researcher at the University of California, Riverside, delved into the water consumption required to operate these advanced AI models.
Ren’s research discovered that ChatGPT consumes about 500 milliliters for every 10 to 50 user prompts, which varies based on the model’s deployment specifics.
This data highlights the significant water usage by AI technologies, considering the vast number of users these platforms attract. CNBC reports that, if not addressed, the escalating water footprint of AI could hinder the technology’s sustainable and ethical application.
Big Tech’s Water Usage
Technology giants such as Microsoft (NASDAQ: MSFT) and Alphabet-owned Google (NASDAQ: GOOG) have reported significant increases in water usage, primarily attributed to the demands of AI development. The necessity of water for cooling data centers, which are crucial for AI operations, is a primary factor in this surge.
For instance, Microsoft’s water consumption escalated by over a third from 2021 to 2022, amounting to nearly 1.7 billion gallons.
Google And Microsoft’s Environmental Goals
Google’s water usage at its data centers and offices reached 5.6 billion gallons in 2022, marking a 21% increase from the previous year. Both companies are actively working toward reducing their water footprints, aiming to achieve a “water positive” status by the decade’s end, where they replenish more water than they consume.
Also Read: GPT Builder Is Now Live For All ChatGPT Plus Subscribers: Here’s How To Create Your Own GPT
According to a Google spokesperson, research shows that, while AI computing demand has dramatically increased, the energy needed to power this technology is rising “at a much slower rate than many forecasts have predicted.”
“We are using tested practices to reduce the carbon footprint of workloads by large margins; together these principles can reduce the energy of training a model by up to 100x and emissions by up to 1000x,” the spokesperson said, according to CNBC.
The Challenge Of Sustainable AI
However, introducing AI-driven…
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