ChatGPT Drinks Half a Liter Of Water For Every 20 Commands

ChatGPT drinks half a liter of water for every 20 commands

ChatGPT drinks half a liter of water for every 20 commands.

OpenAI’s groundbreaking AI chat robot, ChatGPT, may not be as innocent as it seems. According to a recent study, ChatGPT consumes a significant amount of water.

ChatGPT “drinks” half a liter of water for every 20 commands
Introduced into our lives in November and continuing to be present in many services, ChatGPT doesn’t seem very efficient when it comes to resource consumption.

According to a study, ChatGPT raises questions, especially regarding its water consumption.
ChatGPT’s unquenchable thirst
According to researcher Shaolei Ren from the University of California, ChatGPT and similar LLMs (Large Language Models) use up to 500 milliliters of water for every 20 to 50 prompts or questions users ask.

In a paper published on Arxiv, the researcher mentioned that 500 ml might not seem like much, but with ChatGPT being used globally by users collectively, the water usage becomes substantial. In August, ChatGPT had 180.5 million unique visitors, with a total visitor count of 1.43 billion. On the other hand, it had been previously reported that 700,000 liters of water were used in the training of the GPT-3 model.
ChatGPT continues to bleed resources
Microsoft, which is the largest investor in OpenAI, the creator of ChatGPT, actually confirms this research. Microsoft’s 2022 environmental report states that most of the increase in water usage is attributed to artificial intelligence. Microsoft’s water consumption increased by 34% in 2022, reaching 6.4 billion liters. Microsoft acknowledges this issue and says it’s exploring ways to measure energy consumption and carbon footprint. The software giant is also internally working on making large language models like ChatGPT (GPT-4, 3.5, etc.) less energy-intensive. Microsoft plans to achieve carbon-negative, water-positive, and zero-waste goals by 2030. Additionally, OpenAI acknowledges the water usage problem and is looking into making LLMs more energy-efficient. While the amount of water used to power these modern LLMs is surprising, it’s important to note that these models aren’t very old, so methods can be developed over time to reduce water and energy consumption.

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