Sam Altman Reveals ChatGPT's Minimal Water Usage Per Query

In a recent blog post, OpenAI CEO Sam Altman revealed an intriguing statistic about the environmental impact of ChatGPT queries. According to Altman, each average query to ChatGPT uses approximately 0.000085 gallons of water, which he equates to roughly one fifteenth of a teaspoon. This figure sheds light on the surprisingly low water consumption associated with AI interactions.

Altman also addressed energy consumption, stating that a typical ChatGPT query uses about 0.34 watt-hours. To put this in perspective, this is roughly the amount of energy an oven uses in just over one second or what a high-efficiency lightbulb consumes in a couple of minutes. This comparison helps demystify the resource demands of AI technology for everyday users.

These insights come amid growing scrutiny of AI’s environmental footprint. Researchers have forecasted that AI could consume more power than Bitcoin mining by the end of the year, raising concerns about sustainability. However, Altman’s data suggests that the cost of intelligence, in terms of energy and water, may eventually approach the cost of electricity itself, signaling potential efficiency gains in AI development.

It’s important to note that OpenAI has not yet provided detailed sources for these figures, and water usage can vary significantly depending on the location of data centers. For example, data centers in water-scarce regions might have different environmental impacts compared to those in water-abundant areas.

Understanding the true environmental cost of AI is crucial as the technology becomes more integrated into daily life and business operations. Altman’s comparison of AI’s energy use to common household appliances offers a relatable way to grasp these impacts, but it also invites deeper investigation into how AI companies can innovate for sustainability.

As AI continues to evolve, balancing powerful capabilities with responsible resource use will be key. Altman’s optimistic view that intelligence costs could converge with electricity costs hints at a future where AI is not only smarter but also greener.